DETAILED ACTION
1. This office action is in responsive to the applicant’s arguments filed on 10/7/25.
2. The present application is being examined under the first inventor to file provisions of the AIA .
3. Claims 1-9, 11-20 are currently pending.
4. Claims 1, 12 and 20 are amended. Claims 10 and 21 are cancelled.
5. Claims 2-3, 7-9, 11, 13-15 and 19-20 are previously presented.
Response to Arguments
Response: 35 U.S.C. § 112
6. Examiner Response:
Applicant’s arguments, see page 11, filed 10/7/25, with respect to the 35 U.S.C. 112(a) rejections have been fully considered and are persuasive. The 35 U.S.C. 112(a) rejections of claims 12-20 has been withdrawn.
Response: 35 U.S.C. § 101
Applicants argue:
The applicant argues that the recent amendment to the training and updating limitations of claim 1, integrate the abstract idea into a practical application. The applicant points to the Diehr court case for support as to why the amended claims are eligible under 35 U.S.C. 101. (Remarks: pages 11-12)
8. Examiner Response:
The examiner notes that in the Diehr case, inputs of temperature measurements are constantly input into a computer and there's a calculation that is repeated at frequent intervals during each cure, where there's a repetitively comparison of the calculation of the total required cure time that is calculated with the Arrhenius equation and the elapsed time. Also, as stated in the previous office action dated 7/8/25, the computer system mentioned within the claim is functioning as a tool, where the computing system is applying the instruction, see MPEP 2106.05(f) (2) “Whether the claim invokes computers or other machinery merely as a tool to perform an existing process. Use of a computer or other machinery in its ordinary capacity for economic or other tasks (e.g., to receive, store, or transmit data) or simply adding a general purpose computer or computer components after the fact to an abstract idea (e.g., a fundamental economic practice or mathematical equation) does not integrate a judicial exception into a practical application or provide significantly more”.
Also, the recently amended limitation that states “training, using the computing system,
surrogate models representing a blend design space based on at least one aeromechanical quantity comprising the natural frequency, the modal force, or the Goodman scale factor of the plurality of simulated blended airfoil designs using an automated regression process” amounts to mere instructions to apply an exception, where it recites generic training, see MPEP 2106.05(f)(1) “(1) Whether the claim recites only the idea of a solution or outcome i.e., the claim fails to recite details of how a solution to a problem is accomplished. The recitation of claim limitations that attempt to cover any solution to an identified problem with no restriction on how the result is accomplished and no description of the mechanism for accomplishing the result, does not integrate a judicial exception into a practical application or provide significantly more because this type of recitation is equivalent to the words "apply it".”.
Also, the recently amended limitation that states “updating, using the computer system, at least one of the at least one aeromechanical constraint”. This limitation doesn’t distinguish itself from being able to be conducted in the human mind or with pencil and paper. Therefore, under the broadest reasonable interpretation, this limitation is a process step that covers performance in the human mind or with the aid of pencil and paper. As such, this limitation falls within the “Mental Process” grouping of abstract ideas.
Also, the recently amended limitation that states “iteratively updating, using the computer system, the blend design space visualization in real-time based on each update to the at least one aeromechanical constraint” amounts to mere instructions to apply an exception, where it recites an idea of a solution. The limitation doesn’t indicate how the updating is being conducted or how the aeromechanical constraint is associated with the blend design space visualization. See MPEP 2106.05(f)(1) “(1) Whether the claim recites only the idea of a solution or outcome i.e., the claim fails to recite details of how a solution to a problem is accomplished. The recitation of claim limitations that attempt to cover any solution to an identified problem with no restriction on how the result is accomplished and no description of the mechanism for accomplishing the result, does not integrate a judicial exception into a practical application or provide significantly more because this type of recitation is equivalent to the words "apply it".”.
Response: 35 U.S.C. § 103
The Applicant’s arguments, see pages 13-14, filed 10/7/25, with respect to the limitation
of claim 1 that states “training, using the computing system, surrogate models representing a blend design space based on at least one aeromechanical quantity comprising the natural frequency, the modal force, or the Goodman scale factor of the plurality of simulated blended airfoil designs using an automated regression process” have been fully considered and are persuasive. Therefore, the rejection has been withdrawn. However, upon further consideration, a new ground(s) of rejection is made in view of online reference Optimization of Airfoil Blend Limits with As-Manufactured Geometry Finite Element Models, written by Brown et al. (from IDS dates 5/15/22) in view of Morris et al. (U.S. PGPub 2014/0358500).
The examiner’s response regarding the applicant’s arguments to the newly added limitations are shown below.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-9 and 11-20 are rejected under 35 U.S.C. 101 because the claimed invention is
directed to an abstract idea without significantly more. Under the broadest reasonable interpretation, the claims cover performance of the limitation in the mind or by pencil and paper and as a mathematical concept.
Claims 1, 12 and 18
Regarding step 1, claims 1, 12 and 18 are directed towards a method, which has the claims fall within the eligible statutory categories of processes, machines, manufactures and composition of matter under 35 U.S.C. 101.
Claim 1
Regarding step 2A, prong 1, claim 1 recites “generating a plurality of simulated blended airfoil designs, each comprising one of a plurality of blend geometries”. Under the broadest reasonable interpretation, this limitation is a process step that covers performance in the human mind or with the aid of pencil and paper. As such, this limitation falls within the “Mental Process” grouping of abstract ideas.
Claim 1 recites “generating training data regarding a
natural frequency, a modal force, and a Goodman scale factor of the plurality of simulated blended airfoil designs”. Under the broadest reasonable interpretation, this limitation is a process step that covers performance in the human mind or with the aid of pencil and paper. As such, this limitation falls within the “Mental Process” grouping of abstract ideas.
Claim 1 recites “determining a likelihood of operational failure throughout the blend design space in response to one or more vibratory modes using the surrogate models”. Under the broadest reasonable interpretation, this limitation is a process step that covers performance in the human mind or with the aid of pencil and paper. As such, this limitation falls within the “Mental Process” grouping of abstract ideas.
Claim 1 recites “setting at least one aeromechanical constraint based on the likelihood of operational failure”. Under the broadest reasonable interpretation, this limitation is a process step that covers performance in the human mind or with the aid of pencil and paper. As such, this limitation falls within the “Mental Process” grouping of abstract ideas.
Claim 1 recites “determining one or more restricted
regions of the blend design space that violate the at least one aeromechanical constraint and one or more permitted regions of the blend design space that do not violate the at least one aeromechanical constraint”. Under the broadest reasonable interpretation, this limitation is a process step that covers performance in the human mind or with the aid of pencil and paper. As such, this limitation falls within the “Mental Process” grouping of abstract ideas.
Claim 1 recites “generating a blend design space
visualization of the blend design space including the one or more restricted regions of the blend design space and the one or more permitted regions of the blend design space”. This limitation doesn’t distinguish itself from being able to be conducted in the human mind or with pencil and paper. Therefore, under the broadest reasonable interpretation, this limitation is a process step that covers performance in the human mind or with the aid of pencil and paper. As such, this limitation falls within the “Mental Process” grouping of abstract ideas.
Claim 1 recites “updating at least one of the at least one aeromechanical constraint”. This limitation doesn’t distinguish itself from being able to be conducted in the human mind or with pencil and paper. Therefore, under the broadest reasonable interpretation, this limitation is a process step that covers performance in the human mind or with the aid of pencil and paper. As such, this limitation falls within the “Mental Process” grouping of abstract ideas.
Regarding step 2A, prong 2, the limitation of “training, using the computing system,
surrogate models representing a blend design space based on at least one aeromechanical quantity comprising the natural frequency, the modal force, or the Goodman scale factor of the plurality of simulated blended airfoil designs using an automated regression process” amounts to mere instructions to apply an exception, where it recites generic training, see MPEP 2106.05(f)(1) “(1) Whether the claim recites only the idea of a solution or outcome i.e., the claim fails to recite details of how a solution to a problem is accomplished. The recitation of claim limitations that attempt to cover any solution to an identified problem with no restriction on how the result is accomplished and no description of the mechanism for accomplishing the result, does not integrate a judicial exception into a practical application or provide significantly more because this type of recitation is equivalent to the words "apply it".”.
Also, the limitation of “iteratively updating, using the computer system, the blend design space visualization in real-time based on each update to the at least one aeromechanical constraint” amounts to mere instructions to apply an exception, where it recites an idea of a solution. The limitation doesn’t indicate how the updating is being conducted or how the aeromechanical constraint is associated with the blend design space visualization. See MPEP 2106.05(f)(1) “(1) Whether the claim recites only the idea of a solution or outcome i.e., the claim fails to recite details of how a solution to a problem is accomplished. The recitation of claim limitations that attempt to cover any solution to an identified problem with no restriction on how the result is accomplished and no description of the mechanism for accomplishing the result, does not integrate a judicial exception into a practical application or provide significantly more because this type of recitation is equivalent to the words "apply it".”.
Also, the limitation “outputting, by the computing system, the blend design space visualization to an external system for use in blending a damaged airfoil to form a blended airfoil” amounts insignificant extra-solution activity of receiving data i.e. pre-solution activity of gathering data for use in the claimed process, see MPEP 2106.05(g).
Also, the limitation of “capturing image data of the damaged airfoil with an image sensor of an imaging device in communication with the computer system to define a captured blend parameter of the damaged airfoil” amounts insignificant extra-solution activity of receiving data i.e. pre-solution activity of gathering data for use in the claimed process, see MPEP 2106.05(g).
Also, the limitation of “receiving, by the computer system, the captured blend parameter of the damaged airfoil from the imaging device” amounts insignificant extra-solution activity of receiving data i.e. pre-solution activity of gathering data for use in the claimed process, see MPEP 2106.05(g).
Also, the limitation of “outputting, by the computing system, the captured blend parameter to the external system” amounts insignificant extra-solution activity of receiving data i.e. pre-solution activity of gathering data for use in the claimed process, see MPEP 2106.05(g).
Also, the limitation of repairing, using the external system, a blended airfoil by blending the damaged airfoil based on the one or more permitted regions of the blend design space and the captured blend parameter amounts to mere instructions to apply an exception, see MPEP 2106.05(f)(3) “(3) The particularity or generality of the application of the judicial exception. A claim having broad applicability across many fields of endeavor may not provide meaningful limitations that integrate a judicial exception into a practical application or amount to significantly more. For instance, a claim that generically recites an effect of the judicial exception or claims every mode of accomplishing that effect, amounts to a claim that is merely adding the words "apply it" to the judicial exception.”.
Also, the claim(s) does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception. The additional element of the computing system that applies a judicial exception, such as an abstract idea, by use of conventional computer functions does not qualify as a particular machine, see MPEP 2106.05(b) 1. It is important to note that a general purpose computer that applies a judicial exception, such as an abstract idea, by use of conventional computer functions does not qualify as a particular machine. Ultramercial, Inc. v. Hulu, LLC, 772 F.3d 709, 716-17, 112 USPQ2d 1750, 1755-56 (Fed. Cir. 2014). See also TLI Communications LLC v. AV Automotive LLC, 823 F.3d 607, 613, 118 USPQ2d 1744, 1748 (Fed. Cir. 2016) (mere recitation of concrete or tangible components is not an inventive concept); Eon Corp. IP Holdings LLC v. AT&T Mobility LLC, 785 F.3d 616, 623, 114 USPQ2d 1711, 1715 (Fed. Cir. 2015) (noting that Alappat’s rationale that an otherwise ineligible algorithm or software could be made patent-eligible by merely adding a generic computer to the claim was superseded by the Supreme Court’s Bilski and Alice Corp. decisions).
Further, the claim recites the additional element of a computing system. The computing system is recited at a high level of generality such that it amounts no more than mere instructions to apply the exception using a computer and/or a generic computer component. Accordingly, this additional element does not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea.
Regarding Step 2B, the limitations of “capturing image data of the damaged airfoil with an image sensor of an imaging device in communication with the computer system to define a captured blend parameter of the damaged airfoil”, “receiving, by the computer system, the captured blend parameter of the damaged airfoil from the imaging device” and “outputting, by the computing system, the captured blend parameter to the external system” are also shown to reflect the court decisions of Versata Dev. Group, Inc. v. SAP Am., Inc. iv. Storing and retrieving information in memory, shown in MPEP 2106.05(d) (II).
Also, limitation of “training, using the computing system, surrogate models
representing a blend design space based on at least one aeromechanical quantity comprising the natural frequency, the modal force, or the Goodman scale factor of the plurality of simulated blended airfoil designs using an automated regression process” amounts to mere instructions to apply an exception, where it recites generic training, see MPEP 2106.05(f)(1) “(1) Whether the claim recites only the idea of a solution or outcome i.e., the claim fails to recite details of how a solution to a problem is accomplished. The recitation of claim limitations that attempt to cover any solution to an identified problem with no restriction on how the result is accomplished and no description of the mechanism for accomplishing the result, does not integrate a judicial exception into a practical application or provide significantly more because this type of recitation is equivalent to the words "apply it".”.
Also, the limitation of “iteratively updating, using the computer system, the blend design space visualization in real-time based on each update to the at least one aeromechanical constraint” amounts to mere instructions to apply an exception, where it recites an idea of a solution. The limitation doesn’t indicate how the updating is being conducted or how the aeromechanical constraint is associated with the blend design space visualization. See MPEP 2106.05(f)(1) “(1) Whether the claim recites only the idea of a solution or outcome i.e., the claim fails to recite details of how a solution to a problem is accomplished. The recitation of claim limitations that attempt to cover any solution to an identified problem with no restriction on how the result is accomplished and no description of the mechanism for accomplishing the result, does not integrate a judicial exception into a practical application or provide significantly more because this type of recitation is equivalent to the words "apply it".”.
Also, the limitation of repairing, using the external system, a blended airfoil by blending the damaged airfoil based on the one or more permitted regions of the blend design space and the captured blend parameter amounts to mere instructions to apply an exception, see MPEP 2106.05(f)(3) “(3) The particularity or generality of the application of the judicial exception. A claim having broad applicability across many fields of endeavor may not provide meaningful limitations that integrate a judicial exception into a practical application or amount to significantly more. For instance, a claim that generically recites an effect of the judicial exception or claims every mode of accomplishing that effect, amounts to a claim that is merely adding the words "apply it" to the judicial exception.”.
Further, the claim(s) does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception. The additional element of the computing system that applies a judicial exception, such as an abstract idea, by use of conventional computer functions does not qualify as a particular machine, see MPEP 2106.05(b) 1. It is important to note that a general purpose computer that applies a judicial exception, such as an abstract idea, by use of conventional computer functions does not qualify as a particular machine. Ultramercial, Inc. v. Hulu, LLC, 772 F.3d 709, 716-17, 112 USPQ2d 1750, 1755-56 (Fed. Cir. 2014). See also TLI Communications LLC v. AV Automotive LLC, 823 F.3d 607, 613, 118 USPQ2d 1744, 1748 (Fed. Cir. 2016) (mere recitation of concrete or tangible components is not an inventive concept); Eon Corp. IP Holdings LLC v. AT&T Mobility LLC, 785 F.3d 616, 623, 114 USPQ2d 1711, 1715 (Fed. Cir. 2015) (noting that Alappat’s rationale that an otherwise ineligible algorithm or software could be made patent-eligible by merely adding a generic computer to the claim was superseded by the Supreme Court’s Bilski and Alice Corp. decisions).
Claim 12
Regarding step 2A, prong 1, claim 12 recites “generating a plurality of simulated airfoil designs, each comprising one of a plurality of airfoil geometries”. Under the broadest reasonable interpretation, this limitation is a process step that covers performance in the human mind or with the aid of pencil and paper. As such, this limitation falls within the “Mental Process” grouping of abstract ideas.
Claim 12 recites “generating training data regarding a natural frequency, a modal force, and a Goodman scale factor of the plurality of simulated airfoil designs”. Under the broadest reasonable interpretation, this limitation is a process step that covers performance in the human mind or with the aid of pencil and paper. As such, this limitation falls within the “Mental Process” grouping of abstract ideas.
Claim 12 recites “generating a probabilistic distribution of an airfoil vibratory response of the airfoil design space using the surrogate models”. Under the broadest reasonable interpretation, this limitation is a process step that covers performance in the human mind or with the aid of pencil and paper. As such, this limitation falls within the “Mental Process” grouping of abstract ideas.
Claim 12 recites “generating a probabilistic distribution of a high cycle fatigue capability of a material of the airfoil”. Under the broadest reasonable interpretation, this limitation is a process step that covers performance in the human mind or with the aid of pencil and paper. As such, this limitation falls within the “Mental Process” grouping of abstract ideas.
Claim 12 recites “comparing the probabilistic distribution of the airfoil vibratory response and the probabilistic distribution of the high cycle fatigue capability of the material to generate a probabilistic distribution of a likelihood of high cycle fatigue failure of the airfoil design space in response to one or more vibratory modes”. Under the broadest reasonable interpretation, this limitation is a process step that covers performance in the human mind or with the aid of pencil and paper. As such, this limitation falls within the “Mental Process” grouping of abstract ideas.
Regarding step 2A, prong 2, the limitation of “training, using the computing system,
surrogate models representing a blend design space based on at least one aeromechanical quantity comprising the natural frequency, the modal force, or the Goodman scale factor of the plurality of simulated blended airfoil designs using an automated regression process” amounts to mere instructions to apply an exception, where it recites generic training, see MPEP 2106.05(f)(1) “(1) Whether the claim recites only the idea of a solution or outcome i.e., the claim fails to recite details of how a solution to a problem is accomplished. The recitation of claim limitations that attempt to cover any solution to an identified problem with no restriction on how the result is accomplished and no description of the mechanism for accomplishing the result, does not integrate a judicial exception into a practical application or provide significantly more because this type of recitation is equivalent to the words "apply it".”.
Also, the limitation of outputting, by the computing system, data corresponding to the likelihood of high cycle fatigue failure to an external device for the use in manufacturing the airfoil amounts insignificant extra-solution activity of receiving data i.e. pre-solution activity of gathering data for use in the claimed process, see MPEP 2106.05(g).
Also, the limitation of “capturing image data of the damaged airfoil with an image sensor of an imaging device in communication with the computer system to define a captured blend parameter of the example airfoil” amounts insignificant extra-solution activity of receiving data i.e. pre-solution activity of gathering data for use in the claimed process, see MPEP 2106.05(g).
Also, the limitation of “receiving, by the computer system, the captured blend parameter of the example airfoil from the imaging device” amounts insignificant extra-solution activity of receiving data i.e. pre-solution activity of gathering data for use in the claimed process, see MPEP 2106.05(g).
Also, the limitation of “outputting, by the computing system, the captured blend parameter of the example airfoil to the external device” amounts insignificant extra-solution activity of receiving data i.e. pre-solution activity of gathering data for use in the claimed process, see MPEP 2106.05(g).
Also, the limitation of manufacturing, by the external device, the airfoil based on the data corresponding to the likelihood of high cycle fatigue failure below a failure threshold and the captured blend parameter of the example airfoil amounts to merely indicating a field of use, see MPEP 2106.05(h) “Thus, limitations that amount to merely indicating a field of use or technological environment in which to apply a judicial exception do not amount to significantly more than the exception itself, and cannot integrate a judicial exception into a practical application”.
Also, the claim(s) does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception. The additional element of the computing system that applies a judicial exception, such as an abstract idea, by use of conventional computer functions does not qualify as a particular machine, see MPEP 2106.05(b) 1. It is important to note that a general purpose computer that applies a judicial exception, such as an abstract idea, by use of conventional computer functions does not qualify as a particular machine. Ultramercial, Inc. v. Hulu, LLC, 772 F.3d 709, 716-17, 112 USPQ2d 1750, 1755-56 (Fed. Cir. 2014). See also TLI Communications LLC v. AV Automotive LLC, 823 F.3d 607, 613, 118 USPQ2d 1744, 1748 (Fed. Cir. 2016) (mere recitation of concrete or tangible components is not an inventive concept); Eon Corp. IP Holdings LLC v. AT&T Mobility LLC, 785 F.3d 616, 623, 114 USPQ2d 1711, 1715 (Fed. Cir. 2015) (noting that Alappat’s rationale that an otherwise ineligible algorithm or software could be made patent-eligible by merely adding a generic computer to the claim was superseded by the Supreme Court’s Bilski and Alice Corp. decisions).
Further, the claim recites the additional element of a computing system. The computing system is recited at a high level of generality such that it amounts no more than mere instructions to apply the exception using a computer and/or a generic computer component. Accordingly, this additional element does not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea.
Regarding Step 2B, the limitations of “outputting, by the computing system, data corresponding to the likelihood of high cycle fatigue failure to an external device for the use in manufacturing the airfoil”, “capturing image data of the damaged airfoil with an image sensor of an imaging device in communication with the computer system to define a captured blend parameter of the example airfoil”, “receiving, by the computer system, the captured blend parameter of the example airfoil from the imaging device” and “outputting, by the computing system, the captured blend parameter of the example airfoil to the external device” are also shown to reflect the court decisions of Versata Dev. Group, Inc. v. SAP Am., Inc. iv. Storing and retrieving information in memory, shown in MPEP 2106.05(d) (II).
Also, the limitation of “training, using the computing system,
surrogate models representing a blend design space based on at least one aeromechanical quantity comprising the natural frequency, the modal force, or the Goodman scale factor of the plurality of simulated blended airfoil designs using an automated regression process” amounts to mere instructions to apply an exception, where it recites generic training, see MPEP 2106.05(f)(1) “(1) Whether the claim recites only the idea of a solution or outcome i.e., the claim fails to recite details of how a solution to a problem is accomplished. The recitation of claim limitations that attempt to cover any solution to an identified problem with no restriction on how the result is accomplished and no description of the mechanism for accomplishing the result, does not integrate a judicial exception into a practical application or provide significantly more because this type of recitation is equivalent to the words "apply it".”.
Also, the limitation of manufacturing, by the external device, the airfoil based on the data corresponding to the likelihood of high cycle fatigue failure below a failure threshold and the captured blend parameter of the example airfoil amounts to merely indicating a field of use, see MPEP 2106.05(h) “Thus, limitations that amount to merely indicating a field of use or technological environment in which to apply a judicial exception do not amount to significantly more than the exception itself, and cannot integrate a judicial exception into a practical application”.
Claim 18
Regarding step 2A, prong 1, claim 18 recites “generating a plurality of simulated airfoil designs, each comprising one of a plurality of airfoil geometries”. Under the broadest reasonable interpretation, this limitation is a process step that covers performance in the human mind or with the aid of pencil and paper. As such, this limitation falls within the “Mental Process” grouping of abstract ideas.
Claim 18 recites “generating training data regarding a natural frequency, a modal force, and a Goodman scale factor of the plurality of simulated airfoil designs”. Under the broadest reasonable interpretation, this limitation is a process step that covers performance in the human mind or with the aid of pencil and paper. As such, this limitation falls within the “Mental Process” grouping of abstract ideas.
Claim 18 recites “determining a likelihood of operational failure of each of the plurality of simulated airfoil designs in response to one or more vibratory modes”. Under the broadest reasonable interpretation, this limitation is a process step that covers performance in the human mind or with the aid of pencil and paper. As such, this limitation falls within the “Mental Process” grouping of abstract ideas.
Claim 18 recites “selecting a blend geometry from a plurality of blend geometries having a minimized likelihood of operational failure”. Under the broadest reasonable interpretation, this limitation is a process step that covers performance in the human mind or with the aid of pencil and paper. As such, this limitation falls within the “Mental Process” grouping of abstract ideas.
Regarding step 2A, prong 2, the limitation of “training, using the computing system,
surrogate models representing a blend design space based on at least one aeromechanical quantity comprising the natural frequency, the modal force, or the Goodman scale factor of the plurality of simulated blended airfoil designs using an automated regression process” amounts to mere instructions to apply an exception, where it recites generic training, see MPEP 2106.05(f)(1) “(1) Whether the claim recites only the idea of a solution or outcome i.e., the claim fails to recite details of how a solution to a problem is accomplished. The recitation of claim limitations that attempt to cover any solution to an identified problem with no restriction on how the result is accomplished and no description of the mechanism for accomplishing the result, does not integrate a judicial exception into a practical application or provide significantly more because this type of recitation is equivalent to the words "apply it".”.
Also, the limitation of outputting, by the computing system, data corresponding to the likelihood of high cycle fatigue failure to an external device for the use in manufacturing the airfoil amounts insignificant extra-solution activity of receiving data i.e. pre-solution activity of gathering data for use in the claimed process, see MPEP 2106.05(g).
Also, the limitation of “capturing image data of the damaged airfoil with an image sensor of an imaging device in communication with the computer system to define a captured blend parameter of the example airfoil” amounts insignificant extra-solution activity of receiving data i.e. pre-solution activity of gathering data for use in the claimed process, see MPEP 2106.05(g).
Also, the limitation of “receiving, by the computer system, the captured blend parameter of the example airfoil from the imaging device” amounts insignificant extra-solution activity of receiving data i.e. pre-solution activity of gathering data for use in the claimed process, see MPEP 2106.05(g).
Also, the limitation of “outputting, by the computing system, the captured blend parameter of the example airfoil to the external device” amounts insignificant extra-solution activity of receiving data i.e. pre-solution activity of gathering data for use in the claimed process, see MPEP 2106.05(g).
Also, the limitation of manufacturing or repairing, by the external device, the airfoil based on the data corresponding to the minimized likelihood of operational failure and the captured blend parameter of the example airfoil amounts to merely indicating a field of use, see MPEP 2106.05(h) “Thus, limitations that amount to merely indicating a field of use or technological environment in which to apply a judicial exception do not amount to significantly more than the exception itself, and cannot integrate a judicial exception into a practical application”.
Further, the claim(s) does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception. The additional element of the computing system that applies a judicial exception, such as an abstract idea, by use of conventional computer functions does not qualify as a particular machine, see MPEP 2106.05(b) 1. It is important to note that a general purpose computer that applies a judicial exception, such as an abstract idea, by use of conventional computer functions does not qualify as a particular machine. Ultramercial, Inc. v. Hulu, LLC, 772 F.3d 709, 716-17, 112 USPQ2d 1750, 1755-56 (Fed. Cir. 2014). See also TLI Communications LLC v. AV Automotive LLC, 823 F.3d 607, 613, 118 USPQ2d 1744, 1748 (Fed. Cir. 2016) (mere recitation of concrete or tangible components is not an inventive concept); Eon Corp. IP Holdings LLC v. AT&T Mobility LLC, 785 F.3d 616, 623, 114 USPQ2d 1711, 1715 (Fed. Cir. 2015) (noting that Alappat’s rationale that an otherwise ineligible algorithm or software could be made patent-eligible by merely adding a generic computer to the claim was superseded by the Supreme Court’s Bilski and Alice Corp. decisions).
Regarding Step 2B, the limitations of “outputting, by the computing system, data corresponding to the likelihood of high cycle fatigue failure to an external device for the use in manufacturing the airfoil”, “capturing image data of the damaged airfoil with an image sensor of an imaging device in communication with the computer system to define a captured blend parameter of the example airfoil”, “capturing image data of the damaged airfoil with an image sensor of an imaging device in communication with the computer system to define a captured blend parameter of the example airfoil”, “receiving, by the computer system, the captured blend parameter of the example airfoil from the imaging device”, “outputting, by the computing system, the captured blend parameter of the example airfoil to the external device” are also shown to reflect the court decisions of Versata Dev. Group, Inc. v. SAP Am., Inc. iv. Storing and retrieving information in memory, shown in MPEP 2106.05(d) (II).
Also, limitation of “training, using the computing system, surrogate models
representing a blend design space based on at least one aeromechanical quantity comprising the natural frequency, the modal force, or the Goodman scale factor of the plurality of simulated blended airfoil designs using an automated regression process” amounts to mere instructions to apply an exception, where it recites generic training, see MPEP 2106.05(f)(1) “(1) Whether the claim recites only the idea of a solution or outcome i.e., the claim fails to recite details of how a solution to a problem is accomplished. The recitation of claim limitations that attempt to cover any solution to an identified problem with no restriction on how the result is accomplished and no description of the mechanism for accomplishing the result, does not integrate a judicial exception into a practical application or provide significantly more because this type of recitation is equivalent to the words "apply it".”.
Also, the limitation of manufacturing or repairing, by the external device, the airfoil based on the data corresponding to the minimized likelihood of operational failure and the captured blend parameter of the example airfoil amounts to merely indicating a field of use, see MPEP 2106.05(h) “Thus, limitations that amount to merely indicating a field of use or technological environment in which to apply a judicial exception do not amount to significantly more than the exception itself, and cannot integrate a judicial exception into a practical application”.
Further, the claim(s) does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception. The additional element of the computing system that applies a judicial exception, such as an abstract idea, by use of conventional computer functions does not qualify as a particular machine, see MPEP 2106.05(b) 1. It is important to note that a general purpose computer that applies a judicial exception, such as an abstract idea, by use of conventional computer functions does not qualify as a particular machine. Ultramercial, Inc. v. Hulu, LLC, 772 F.3d 709, 716-17, 112 USPQ2d 1750, 1755-56 (Fed. Cir. 2014). See also TLI Communications LLC v. AV Automotive LLC, 823 F.3d 607, 613, 118 USPQ2d 1744, 1748 (Fed. Cir. 2016) (mere recitation of concrete or tangible components is not an inventive concept); Eon Corp. IP Holdings LLC v. AT&T Mobility LLC, 785 F.3d 616, 623, 114 USPQ2d 1711, 1715 (Fed. Cir. 2015) (noting that Alappat’s rationale that an otherwise ineligible algorithm or software could be made patent-eligible by merely adding a generic computer to the claim was superseded by the Supreme Court’s Bilski and Alice Corp. decisions).
Claim 2
Dependent claim 2 recites “wherein the blend design space visualization comprises the one or more restricted regions indicating one or more blended airfoil designs where the at least one aeromechanical constraint is violated and the one or more permitted regions indicating one or more blended airfoil designs where no aeromechanical constraints are violated.”. Under the broadest reasonable interpretation, this limitation is a process step that covers performance in the human mind or with the aid of pencil and paper. As such, this limitation falls within the “Mental Process” grouping of abstract ideas.
Claim 3
Dependent claim 3 recites “blending the damaged airfoil based on a simulated blended airfoil design outside of the one or more restricted regions of the blend design space that violate the at least one aeromechanical constraint to form the blended airfoil”. Under the broadest reasonable interpretation, this limitation is a process step that covers performance in the human mind or with the aid of pencil and paper. As such, this limitation falls within the “Mental Process” grouping of abstract ideas.
Claim 4
Dependent claim 4 recites “wherein the blend design space comprises at least two blend parameters”. Under the broadest reasonable interpretation, this limitation is a process step that covers performance in the human mind or with the aid of pencil and paper. As such, this limitation falls within the “Mental Process” grouping of abstract ideas.
Claim 5
Dependent claim 5 recites “wherein a first blend parameter comprises a radial location of a blended region between a tip end and a hub end of the blended airfoil and a second blend parameter comprises a depth of the blended region”. Under the broadest reasonable interpretation, this limitation is a process step that covers performance in the human mind or with the aid of pencil and paper. As such, this limitation falls within the “Mental Process” grouping of abstract ideas.
Claim 6
Dependent claim 6 recites “wherein the blend design space visualization is interactive such that the at least one aeromechanical constraint and the at least two blend parameters are adjustable”. Under the broadest reasonable interpretation, this limitation is a process step that covers performance in the human mind or with the aid of pencil and paper. As such, this limitation falls within the “Mental Process” grouping of abstract ideas.
Claim 7
Dependent claim 7 recites “wherein determining the one or more restricted regions of the blend design space that violate the at least one aeromechanical constraint is a probabilistic determination and the blend design space visualization is a probabilistic blend design space comprising a contour plot depicting a probability of violation of the at least one aeromechanical constraint”. Under the broadest reasonable interpretation, this limitation is a process step that covers performance in the human mind or with the aid of pencil and paper. As such, this limitation falls within the “Mental Process” grouping of abstract ideas.
Claim 8
Dependent claim 8 recites “determining a vibratory response as a percentage of material capability throughout the blend design space in response to the one or more vibratory modes by generating statistical distributions on a damping parameter (Q), a mistuning amplification parameter (k,,), a non-uniform vane spacing factor parameter (Ky >), and an aero- scaling factor parameter (P;), such that the vibratory response as a percentage of material capability is
calculated by performing a Monte Carlo analysis using equation
PNG
media_image1.png
90
176
media_image1.png
Greyscale
where Fmodal is the modal force, f is the natural frequency, and GSF is the Goodman scale factor. Under the broadest reasonable interpretation, this limitation is a process step that covers performance in the human mind or with the aid of pencil and paper. As such, this limitation falls within the “Mental Process” grouping of abstract ideas.
Also, this limitation is determining a vibratory response as a percentage of material capability throughout the blend design space in response to the one or more vibratory modes by generating statistical distributions on a damping parameter (Q), a mistuning amplification parameter (k,,), a non-uniform vane spacing factor parameter (Ky >), and an aero- scaling factor parameter (P;), such that the vibratory response as a percentage of material capability is
calculated by performing a Monte Carlo analysis using equation
PNG
media_image1.png
90
176
media_image1.png
Greyscale
. Therefore, under MPEP 2106.04(a)(2), this limitation covers a mathematical concept, which falls in the “Mathematical Concept” grouping of abstract ideas.
Claim 9
Dependent claim 9 recites “wherein the blend design space visualization visualizes the blend design space for the one or more vibratory modes”. Under the broadest reasonable interpretation, this limitation is a process step that covers performance in the human mind or with the aid of pencil and paper. As such, this limitation falls within the “Mental Process” grouping of abstract ideas.
Claim 11
Dependent claim 11 recites “wherein the at least one aeromechanical constraint is based on a change in a natural frequency from an original airfoil design, an endurance limit, and a change in the endurance limit from the original airfoil design”. Under the broadest reasonable interpretation, this limitation is a process step that covers performance in the human mind or with the aid of pencil and paper. As such, this limitation falls within the “Mental Process” grouping of abstract ideas.
Claim 13
Dependent claim 13 recites “wherein the failure threshold being based on a threshold endurance limit of the airfoil geometry”. Under the broadest reasonable interpretation, this limitation is a process step that covers performance in the human mind or with the aid of pencil and paper. As such, this limitation falls within the “Mental Process” grouping of abstract ideas.
Claim 14
Dependent claim 14 recites “wherein generating a probabilistic distribution of the airfoil vibratory response of the airfoil design space further comprises generating statistical distributions on a damping parameter (Q), a mistuning amplification parameter (k,,), a non-uniform vane spacing factor parameter (Ky >), and an aero- scaling factor parameter (P;), such that the vibratory response as a percentage of material capability is calculated by performing a Monte Carlo analysis using equation
PNG
media_image1.png
90
176
media_image1.png
Greyscale
where Fmodal is the modal force, f is the natural frequency, and GSF is the Goodman scale factor.”. Under the broadest reasonable interpretation, this limitation is a process step that covers performance in the human mind or with the aid of pencil and paper. As such, this limitation falls within the “Mental Process” grouping of abstract ideas.
Also, this limitation is generating statistical distributions on a damping parameter (Q), a mistuning amplification parameter (k,,), a non-uniform vane spacing factor parameter (Ky >), and an aero- scaling factor parameter (P;), such that the vibratory response as a percentage of material capability is calculated by performing a Monte Carlo analysis using equation. Therefore, under MPEP 2106.04(a)(2), this limitation covers a mathematical concept, which falls in the “Mathematical Concept” grouping of abstract ideas.
Claim 15
Dependent claim 15 recites “calibrating the damping parameter (Q), mistuning amplification parameter (kv), the non-uniform vane spacing factor parameter (Knuvs), and the aero-scaling factor parameter (Ps) using Bayesian probabilistic tuning”. This limitation is calibrating the damping parameter (Q), the mistuning amplification parameter (kv), the non-uniform vane spacing factor parameter (Knuvs), and the aero-scaling factor parameter (Ps) using Bayesian probabilistic tuning. Therefore, under MPEP 2106.04(a)(2), this limitation covers a mathematical concept, which falls in the “Mathematical Concept” grouping of abstract ideas.
Claim 16
Dependent claim 16 recites “determining, using the computing system, a relative impact of each of a plurality of geometrical parameters of the plurality of simulated airfoil designs and a plurality of systemic variables on the likelihood of high cycle fatigue failure of the plurality of simulated airfoil designs”. Under the broadest reasonable interpretation, this limitation is a process step that covers performance in the human mind or with the aid of pencil and paper. As such, this limitation falls within the “Mental Process” grouping of abstract ideas.
Also, the claim recites the additional element of a computing system. The computing system is recited at a high level of generality such that it amounts no more than mere instructions to apply the exception using a computer and/or a generic computer component. Accordingly, this additional element does not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea.
Claim 17
Dependent claim 17 recites “wherein the plurality of systemic variables comprise axial gap and tip clearance.”. Under the broadest reasonable interpretation, this limitation is a process step that covers performance in the human mind or with the aid of pencil and paper. As such, this limitation falls within the “Mental Process” grouping of abstract ideas.
Claim 19
Dependent claim 19 recites “wherein: the plurality of simulated airfoil designs comprise a plurality of simulated blended airfoil designs each comprising one of the plurality of blend geometries”. Under the broadest reasonable interpretation, this limitation is a process step that covers performance in the human mind or with the aid of pencil and paper. As such, this limitation falls within the “Mental Process” grouping of abstract ideas.
Dependent claim 19 recites “and the data corresponding to the likelihood of operational failure is provided to the external device for use in blending a damaged airfoil”. Under the broadest reasonable interpretation, this limitation is a process step that covers performance in the human mind or with the aid of pencil and paper. As such, this limitation falls within the “Mental Process” grouping of abstract ideas.
Claim 20
Dependent claim 20 recites “wherein: the likelihood of operational failure is determined by comparing, using the computing system, a probabilistic distribution of airfoil vibratory response of an airfoil design space with a probabilistic distribution of a high cycle fatigue capability of a material of the airfoil to generate a probabilistic distribution of a likelihood of high cycle fatigue failure of the airfoil design space in response to the one or more vibratory modes”. Under the broadest reasonable interpretation, this limitation is a process step that covers performance in the human mind or with the aid of pencil and paper. As such, this limitation falls within the “Mental Process” grouping of abstract ideas.
Also, the claim recites the additional element of a computing system. The computing system is recited at a high level of generality such that it amounts no more than mere instructions to apply the exception using a computer and/or a generic computer component. Accordingly, this additional element does not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea.
Dependent claim 20 recites “and the data corresponding to the likelihood of operational failure is provided to the external device for use in manufacturing the airfoil.”. Under the broadest reasonable interpretation, this limitation is a process step that covers performance in the human mind or with the aid of pencil and paper. As such, this limitation falls within the “Mental Process” grouping of abstract ideas.
Claims 1-9 and 11-20 are therefore not drawn to eligible subject matter as they are directed to an abstract idea without significantly more.
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness
rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
The factual inquiries for establishing a background for determining obviousness under 35
U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claim(s) 1-2, 4-6, 9, 11-12, 16, 18-20 is/are rejected under 35 U.S.C. 103 as being
unpatentable over online reference Optimization of Airfoil Blend Limits with As-Manufactured Geometry Finite Element Models, written by Brown et al. (from IDS dates 5/15/22) in view of Morris et al. (U.S. PGPub 2014/0358500) in further view of Ruggiero (U.S. PGPub 2019/0049392) in further view of Hudson et al. (U.S. PGPub 2018/0099362).
With respect to claim 1, Brown discloses “A method of repairing a damaged airfoil based on a blend design space visualization” as [Brown et al. (Pg. 2, right col., last paragraph “The as-manufactured geometry surfaces of the PBS rotor are, etc.”)];
“generating, using a computing system, a plurality of simulated blended airfoil designs, each comprising one of a plurality of blend geometries” as [Brown et al. (Pg. 2, right col., Blended Airfoil Modeling Process, 1st – 2nd paragraph, “The approach is demonstrated on an high through flow compressor stage that has been frequently studied in the literature [27, 28]. It is referred to as the PBS rotor, the acronym for the parametric blade study project that it was originally associated with. The stage is comprised of twenty low aspect ratio airfoils trailed by 31 stator airfoils in the experimental rig”)];
“generating, using the computing system, training data regarding a natural frequency, a modal force, and a Goodman scale factor of the plurality of simulated blended airfoil designs” as [Brown et al. (Pg. 5, left col., Structural Integrity Effects of Large Blends, 1st – 2nd paragraph, “This section uses a 0.25 inch and 0.5 inch blend on each as-manufactured airfoil FEM to show the effect of blends on frequency, mode shape, and Goodman limits”, Figs. 6-8)];
“determining, using the computing system, a likelihood of operational failure throughout the blend design space in response to one or more vibratory modes using the surrogate models” as [Brown et al. (Pg. 10, left col., 2nd paragraph, “Because the ninth vibration mode played such a prominent role in constraining blend limits and results through this work indicate frequency veering, this behavior is explored as a final aspect of blend effects on as-manufactured airfoils. Fig. 16 shows a plot of the frequency change with respect to blend depth for the first airfoil. The x-axis is marked with the blend depth and the y-axis is a normalized frequency value for the ninth and tenth modes.”, Fig. 16)];
“setting, by the computing system, at least one aeromechanical constraint based on the likelihood of operational failure” as [Brown et al. (Pg. 7, right col., 1st – 2nd paragraph “Setting the constraint limits are a key aspect of practical blend limit extension efforts and will require organizations, etc.”, Brown et al. Pg. 8 Case 1: Depth Optimization Results, 1st – 2nd paragraph, “This section reviews the results of the first optimization case where depth is optimized with a fixed 4.0 aspect ratio. Fig. 11 shows the progression of constraint values during the optimization of the first airfoil., etc.”)];
“determining, using the computing system, one or more restricted regions of the blend design space that violate the at least one aeromechanical constraint” as [Brown et al. (Pg. 8, Case 1: Depth Optimization Results, 1st paragraph, “This section reviews the results of the first optimization case where depth is optimized with a fixed 4.0 aspect ratio, etc.,”, Fig. 11, The examiner considers the lines of Fig. 11 that are shaded light grey as being the restricted region, since the lines that are shaded black indicates that the constraints are satisfied)];
“and one or more permitted regions of the blend design space which do not violate the at least one aeromechanical constraint” as [Brown et al. (Pg. 8, Case 1: Depth Optimization Results, 1st paragraph, “This section reviews the results of the first optimization case where depth is optimized with a fixed 4.0 aspect ratio, etc.,”, Fig. 11, The examiner considers the lines of Fig. 11 that are shaded black to be the permitted region, since the shaded black lines indicate that the constraints are satisfied)];
“generating, using the computing system, a blend design space visualization of the blend design space including the one or more restricted regions of the blend design space and the one or more permitted regions of the blend design space” as [Brown et al. (Pgs. 8-9, Figs. 11-13, Figs. 11-13 of the Brown et al. reference show charts of the modal constraint iterations and the Goodman constraint iterations. The examiner considers the charts of the Brown reference to be the blend design space visualization, since the blend design space visualization can be a chart, see paragraph [0033] of the specification. Also, the examiner considers the lines of Fig. 11 that are shaded light grey as being the restricted region, since the lines that are shaded black indicates that the constraints are satisfied)];
“updating, using the computer system, at least one of the at least one aeromechanical constraint”. as [Brown et al. (Pg. 6, left col., 1st paragraph, “Fig. 8 shows the two blend effects on the maximum Goodman percentage across each airfoil. The modes shown demonstrate that there can be either a consistent or variable shift in Goodman percentage. The first mode subplot shows a consistent shift in limit for each blend depth, indicating that the response variation caused by the as-manufactured geometry variations are not interacting with blend depth changes.”, The examiner considers the blend depth changes to be the updating of the at least one aeromechanical constraint, since a blend parameter constraint can be a depth constraint)];
“iteratively updating, using the computer system, the blend design space visualization in real-time based on each update to the at least one aeromechanical constraint” as [Brown et al. (Pg. 6, 2nd paragraph “The effect of blends on Goodman behavior is further observed with the blend effects on the leading edge criteria shown in Fig. 9. Here the first mode shows a reduction in Goodman percentage from both blend sizes. While the blade-to-blade variation of the 0.25 inch blended blades follows the same trend as the as-manufactured variation, it is clear with the 0.50 inch blend the pattern has changed. This change in shape is not seen in the MAC effects, indicating that the change is either from a steady stress change or a modal stress change not captured by the MAC criteria.”, The examiner considers the pattern changes to be the updating the blend design space, since the pattern change, changes the shape of blade, which results in the design of the blade being different)];
“and outputting, by the computing system, the blend design space visualization to an external system for use in blending a damaged airfoil to form a blended airfoil.” as [Brown et al. (Pg. 2, right col., Blended Airfoil Modeling Process, 2nd paragraph, “The as-manufactured geometry surfaces of the PBS, etc.”, By having the airfoil data stored as a standard tessellated surface (STL), demonstrates that there’s a computer, since a STL file is stored on a computer, see Non-Patent literature of the definition of a standard tessellated language in the file wrapper dated 5/24/24)];
While Brown et al. teaches generating training data regarding a natural frequency, a
modal force, and a Goodman scale factor of the plurality of simulated blended airfoil designs, Brown does not explicitly disclose “training, using the computing system, surrogate models
representing a blend design space based on at least one aeromechanical quantity comprising the natural frequency, the modal force, or the Goodman scale factor of the plurality of simulated blended airfoil designs using an automated regression process”
Morris et al. discloses “training, using the computing system, surrogate models
representing a blend design space based on at least one aeromechanical quantity comprising the natural frequency, the modal force, or the Goodman scale factor of the plurality of simulated blended airfoil designs using an automated regression process” as [Morris et al. (paragraph [0045] “As part of this, statistical surrogate models are developed and utilized to determine optimal blend geometries on a case by case basis. The statistical surrogate models are developed from analytical engineering analyses and/or a library of acceptable conditions to repair and center on the parameters D, S and L as shown in FIG. 1C. The use of statistical surrogate models enables a system to rapidly customize a blend solution for the engine that allows the engine to be returned to service quickly and safely.”, Morris et al. paragraph [0071] “This disclosure could be summarized as a method of suggesting appropriate blends to an airfoil, wherein the suggested blend is considered for structural adequacy based on at least one of system frequencies, mode shapes, mistuning characteristics, vibratory stresses, or material capability from a variety of engine conditions.”, The examiner considers the frequencies to be the natural frequency, since the blend of the airfoil can be based on the system frequencies)];
Brown et al. and Morris et al. are analogous art because they are from the same field
endeavor of analyzing the design airfoils.
Before the effective filing date of the invention, it would have been obvious to a person
of ordinary skill in the art to modify the teachings of Brown et al. of generating training data regarding a natural frequency, a modal force, and a Goodman scale factor of the plurality of simulated blended airfoil designs by incorporating training, using the computing system, surrogate models representing a blend design space based on at least one aeromechanical quantity comprising the natural frequency, the modal force, or the Goodman scale factor of the plurality of simulated blended airfoil designs using an automated regression process as taught by Morris et al. for the purpose of analyzing high cycle fatigue (HCF) in a design of a gas turbine engine.
Brown et al. in view of Morris et al. teaches training, using the computing system,
surrogate models representing a blend design space based on at least one aeromechanical quantity comprising the natural frequency, the modal force, or the Goodman scale factor of the plurality of simulated blended airfoil designs using an automated regression process.
The motivation for doing so would have been because Morris et al. teaches that by analyzing high cycle fatigue (HCF) in a design of a gas turbine engine, the ability to capture the inherent blade-to-blade and engine-to-engine variability in HCF behavior can be accomplished in order to recognize the inherent variability in manufactured components (Morris et al. (paragraph [0005] – [0006])).
While the combination of the Brown et al. and Morris et al. teaches outputting the blend design space visualization to an external system for use in blending a damaged airfoil to form a blended airfoil, Brown et al., Morris et al. do not explicitly disclose “capturing image data of the damaged airfoil with an image sensor of an imaging device in communication with the computer system to define a captured blend parameter of the damaged airfoil: receiving, by the computer system, the captured blend parameter of the damaged airfoil from the imaging device; outputting, by the computing system, the captured blend parameter to the external system”
Ruggiero discloses “capturing image data of the damaged airfoil with an image sensor of an imaging device in communication with the computer system to define a captured blend parameter of the damaged airfoil” as [Ruggiero (paragraph [0035] “The borescope 100 can also include an imaging device 114 as well as a memory 116. The imaging device 114 can include an imaging sensor 118 and a processor 120 capable of converting light incident on the sensor 118 into an electronic signal. The imaging sensor 118 is illustrated herein as a CCD sensor, and it will be understood that other sensors such as a CMOS sensor can also be used. The imaging device 114 can be connected in data communication to the microlens array 104, such as via a set of fiber optic cables 122.”, Ruggiero paragraph [0044] “A first region 411, a second region 412, and a third region 413 are visible on the airfoil 304, and these regions may indicate damage to the airfoil 304. In this first exemplary view, the first region 411 is in focus and damage to the airfoil 304 (such as a crack) is visible to an observer.”, Ruggiero paragraph [0045] “The computer system 400 can process the composite image 150 to shift the observed focal plane and bring the second region 412 into focus while the first and third regions 401, 403 become out of focus. In this view, it can be seen that the second region 412 includes damage to the airfoil 304.”, Ruggiero paragraph [0049] “It should be appreciated that other optical factors such as aperture size or lens focal length can determine the depth of field and how much of the airfoil 304 is in focus at a given time. While the examples of FIGS. 6-9 illustrate one selected region being in focus with other regions out of focus, it is contemplated that the borescope 100 can have a sufficiently large depth of field to bring multiple regions into focus simultaneously.”, The examiner considers the depth of field to be the blend parameter, since a blend parameters can be the depth of an airfoil, see paragraph [0027] of the specification)];
“receiving, by the computer system, the captured blend parameter of the damaged airfoil from the imaging device” as [Ruggiero (paragraph [0018] “The resulting image data can contain spatial information about the object; software post-processing of the image data can provide for manipulation of the image data to selectively change the focal plane/depth of view (for example, focusing on a portion in the foreground or background) or the viewing perspective (for example, tilting the field of view upward or panning to the right)”, The examiner considers the spatial information about the object to be the captured blend parameter, since the a blend parameter can be the depth of an airfoil, see paragraph [0027] of the specification)];
“outputting, by the computing system, the captured blend parameter to the external system” as [Ruggiero (paragraph [0018] “Light rays from an object can be focused by the microlens array to form multiple optical images which may be captured by a light-sensitive device such as a CCD or CMOS sensor and stored in an electronic storage medium. The resulting image data can contain spatial information about the object; software post-processing of the image data can provide for manipulation of the image data to selectively change the focal plane/depth of view (for example, focusing on a portion in the foreground or background) or the viewing perspective (for example, tilting the field of view upward or panning to the right).”
Brown et al., Morris et al. and Ruggiero are analogous art because they are
from the same field endeavor of analyzing the design of blended airfoils.
Before the effective filing date of the invention, it would have been obvious to a person
of ordinary skill in the art to modify the teachings of Brown et al. and Morris et al. of outputting the blend design space visualization to an external system for use in blending a damaged airfoil to form a blended airfoil by incorporating capturing image data of the damaged airfoil with an image sensor of an imaging device in communication with the computer system to define a captured blend parameter of the damaged airfoil: receiving, by the computer system, the captured blend parameter of the damaged airfoil from the imaging device; outputting, by the computing system, the captured blend parameter to the external system as taught by Ruggiero for the purpose of having a borescope for generating a composite image within an unlit.
Brown et al. in view of Morris et al. in further view of Ruggiero teaches capturing image data of the damaged airfoil with an image sensor of an imaging device in communication with the computer system to define a captured blend parameter of the damaged airfoil; receiving, by the computer system, the captured blend parameter of the damaged airfoil from the imaging device; outputting, by the computing system, the captured blend parameter to the external system.
The motivation for doing so would have been because Ruggiero teaches that by having a borescope for generating a composite image within an unlit, the ability to gather as much data as possible during inspection of a turbine engine component can be accomplished in order to maximize safety and efficiency (Ruggiero paragraphs [0002] – [0003]).
While the combination of Brown et al., Morris et al. and Ruggiero teaches generating a plurality of simulated blended airfoil designs, each comprising one of a plurality of blend geometries, Brown et al., Morris et al. and Ruggiero do not explicitly disclose “repairing, using the external system, a blended airfoil by blending the damaged airfoil based on the one or more permitted regions of the blend design space and the captured blend parameter”
Hudson et al. discloses “repairing, using the external system, a blended airfoil by blending the damaged airfoil based on the one or more permitted regions of the blend design space and the captured blend parameter” as [Hudson et al. (paragraph [0011] “Further, the method includes removing material from a second surface, opposite the first surface, of the one of the leading edge portion and the trailing edge portion of the airfoil to reduce a dimension of the one of the leading edge portion and the trailing edge portion of the airfoil and to blend a transition from one of the pressure side and the suction side of the airfoil to the second surface”)];
Brown et al., Morris et al., Ruggiero and Hudson et al. are analogous art
because they are from the same field endeavor of analyzing the design of blended airfoils.
Before the effective filing date of the invention, it would have been obvious to a person
of ordinary skill in the art to modify the teachings of Brown et al., Morris et al. and Ruggiero of generating a plurality of simulated blended airfoil designs, each comprising one of a plurality of blend geometries by incorporating repairing, using the external system, a blended airfoil by blending the damaged airfoil based on the one or more permitted regions of the blend design space and the captured blend parameter as taught by Hudson et al. for the purpose of manufacturing an airfoil of a gas turbine engine.
Brown et al. in view of Morris et al. in further view of Ruggiero in further view of Hudson et al. teaches repairing, using the external system, a blended airfoil by blending the damaged airfoil based on the one or more permitted regions of the blend design space and the captured blend parameter.
The motivation for doing so would have been because Hudson et al. teaches that by removing material from the second surface of the at least one of the leading-edge portions and the trailing edge portion of the airfoil that includes blending a transition from a pressure side of the airfoil to the second surface, the gas turbine engine is overall more efficient, because the trailing edge isn’t as thick (Hudson et al. (paragraph [0003], paragraph [0008])).
With respect to claim 2, the combination of Brown et al., Morris et al., Ruggiero and Hudson et al. discloses the method of claim 1 above, and Brown et al. discloses “wherein the blend design space visualization comprises the one or more restricted regions indicating one or more blended airfoil designs where the at least one aeromechanical constraint is violated and one or more permitted regions indicating one or more blended airfoil designs where no aeromechanical constraints are violated” as [Brown et al. (Pg.8, Case 1: Depth Optimization Results, 1st paragraph, “This section reviews the results of the first optimization case where depth is optimized with a fixed 4.0 aspect ratio, etc,”, Fig. 11)];
With respect to claim 4, the combination of Brown et al., Morris et al., Ruggiero and Hudson et al. discloses the method of claim 1 above, and Brown et al. discloses “wherein the blend design space comprises at least two blend parameters.” as [Brown et al. (Pg. 3, left col., 3rd paragraph, “In this study, a relatively simple blend geometry is considered for demonstration purposes. The blend is defined by leading edge radial height, depth, and length. Together these define an elliptical cut along the airfoil leading edge. For the optimization development, both the depth and length are active design parameters while the radial location is fixed and assumed to be depended on FOD damage location. The model in Fig 1 shows the case with a 0.5 inch blend depth with a 4.0 aspect ratio”)];
With respect to claim 5, the combination of Brown et al., Morris et al., Ruggiero and Hudson et al. discloses the method of claim 4 above, and Brown et al. discloses “wherein a first blend parameter comprises a radial location of a blended region between a tip end and a hub end of the blended airfoil and a second blend parameter comprises a depth of the blended region” as [Brown et al. (Pg. 3, left col., 3rd paragraph, “In this study, a relatively simple blend geometry is considered for demonstration purposes. The blend is defined by leading edge radial height, depth, and length. Together these define an elliptical cut along the airfoil leading edge. For the optimization development, both the depth and length are active design parameters while the radial location is fixed and assumed to be depended on FOD damage location. The model in Fig 1 shows the case with a 0.5 inch blend depth with a 4.0 aspect ratio”)];
With respect to claim 6, the combination of Brown et al., Morris et al., Ruggiero and Hudson et al. discloses the method of claim 4 above, and Brown et al. discloses “wherein the blend design space visualization is interactive such that the at least one aeromechanical constraint and the at least two blend parameters are adjustable” as [Brown et al. (Pg.8, Case 1: Depth Optimization Results, 1st – 2nd paragraph, “This section reviews the results of the first optimization case where depth is optimized with a fixed 4.0 aspect ratio, etc.,”, Brown et al. (Pg. 10, Case 2: Depoth, Aspect Ratio Optimization, 1st paragraph, “The optimization next considers both the depth and aspect ratio as design parameters. Fig. 17 shows that inclusion of this second parameter increases the optimal blend depth in most cases. The one-variable, depth only optimization with fixed aspect ratio results are shown as the dark gray bars while the light gray bars are those from both depth and aspect ratio. The results of case 2 for blades four, thirteen, and fourteen are nearly identical to case 1. The secondary y-axis on the right is for the optimal blend aspect ratio values which are annotated with ’x’ markers.”, Fig. 17, The aspect ratio and depth has different values as shown in Fig. 17, which demonstrates that these blend parameters are adjustable)];
With respect to claim 9, the combination of Brown et al., Morris et al., Ruggiero and Hudson et al. discloses the method of claim 1 above, and Brown et al. discloses “wherein the blend design space visualization visualizes the blend design space for the one or more vibratory mode.” as [Brown et al. (Pg. 4, left col., 2nd paragraph, “The Goodman limit variation for the first ten modes is shown in Fig. 4. The x-axis shows the result for each blade, where each x location has a data point for each of the ten vibration modes. A number annotates each data point with the mode number and a line connects the mode’s result across all twenty airfoils to show the blade-to-blade variation”, Fig. 4)];
With respect to claim 11, the combination of Brown et al., Morris et al., Ruggiero and Hudson et al. discloses the method of claim 1 above, and Brown et al. discloses “wherein the at least one aeromechanical constraint is based on a change in a natural frequency from an original airfoil design, an endurance limit, and a change in the endurance limit from the original airfoil design.” as [Brown et al. (Pg.8, Case 1: Depth Optimization Results, 1st – 2nd paragraph, “This section reviews the results of the first optimization case where depth is optimized with a fixed 4.0 aspect ratio, etc,”, Figs. 11-13)];
With respect to claim 12, Brown et al. discloses “generating, using a computing system, a plurality of simulated airfoil designs, each comprising one of a plurality of airfoil geometries” as [Brown et al. (Pg. 2, right col., Blended Airfoil Modeling Process, 1st – 2nd paragraph, “The approach is demonstrated on an high through flow compressor stage that has been frequently studied in the literature [27, 28]. It is referred to as the PBS rotor, the acronym for the parametric blade study project that it was originally associated with. The stage is comprised of twenty low aspect ratio airfoils trailed by 31 stator airfoils in the experimental rig”)];
“generating, using the computing system, training data regarding a natural frequency, a modal force, and a Goodman scale factor of the plurality of simulated airfoil designs” as [Brown et al. (Pg. 5, left col., Structural Integrity Effects of Large Blends, 1st – 2nd paragraph, “This section uses a 0.25 inch and 0.5 inch blend on each as-manufactured airfoil FEM to show the effect of blends on frequency, mode shape, and Goodman limits”, Figs. 6-8)];
“generating, using the computing system, a probabilistic distribution of an airfoil vibratory response of the airfoil design space using the surrogate models” as [Brown et al. (Pg. 10, left col., 2nd paragraph, “Because the ninth vibration mode played such a prominent role in constraining blend limits and results through this work indicate frequency veering, this behavior is explored as a final aspect of blend effects on as-manufactured airfoils. Fig. 16 shows a plot of the frequency change with respect to blend depth for the first airfoil. The x-axis is marked with the blend depth and the y-axis is a normalized frequency value for the ninth and tenth modes.”, Fig. 16)];
“generating, using the computing system, a probabilistic distribution of a high cycle fatigue capability of a material of the airfoil” as [Brown et al. (Abstract “The numerical optimization maximizes blend depth values within frequency, mode shape, and high cycle fatigue (HCF) constraint boundaries”, Brown et al. Pg. 2, right col., 1st paragraph, “This work extends the knowledge of blend effects on airfoil structural response and the ability to use computational methods to use optimization methods to create part-specific limits for as-manufactured geometry FEM. Blend size effects on frequency, mode shape, and structural fatigue limits are considered in the presence of small geometric mistuning from manufacturing.”)];
“comparing, using the computing system, the probabilistic distribution of the airfoil vibratory response and the probabilistic distribution of the high cycle fatigue capability of the material to generate a probabilistic distribution of a likelihood of high cycle fatigue failure of the airfoil design space in response to one or more vibratory modes” as [Brown et al. (Pg. 4, left col., 1st – 3rd paragraph, “The influence of both steady and modal stress variations are accounted for with a Goodman fatigue damage model. The Goodman limit is an infinite life criteria determined through quasi-static or vibration based specimen testing and is a function of both steady and vibratory stress. The steady load of the PBS rotor is calculated at the maximum design RPM and both steady aerodynamic and thermal loading are omitted. These later effects are small relative to the rotational loads and their absence does not change the demonstration of the blend optimization. The airfoil vibratory stress was computed using an assumed maximum vibratory stress amplitude based on airfoil design practice and then applied as a scale factor to the mass normalized modal stress prediction for each airfoil. Goodman material capability for Ti 6-4 was the final component for the Goodman result calculation, etc.”)];
“and outputting, by the computing system, data corresponding to the likelihood of high cycle fatigue failure to an external device for the use in manufacturing the airfoil.” as [Brown et al. (Pg. 2, right col., Blended Airfoil Modeling Process, 2nd paragraph, “The as-manufactured geometry surfaces of the PBS, etc.”, By having the airfoil data stored as a standard tessellated surface (STL), demonstrates that there’s a computer, since a STL file is stored on a computer, see attachment of the definition of a standard tessellated language)];
While Brown et al. teaches generating, using the computing system, training data
regarding a natural frequency, a modal force, and a Goodman scale factor of the plurality of simulated airfoil designs, Brown et al. doesn’t explicitly disclose “training, using the computing system, surrogate models representing an airfoil design space based on at least one aeromechanical quantity comprising the natural frequency, the modal force, or the Goodman scale factor of the plurality of simulated blended airfoil designs using an automated regression process”
Morris et al. discloses “training, using the computing system, surrogate models representing an airfoil design space based on at least one aeromechanical quantity comprising the natural frequency, the modal force, or the Goodman scale factor of the plurality of simulated blended airfoil designs using an automated regression process” as [Morris et al. (paragraph [0045] “As part of this, statistical surrogate models are developed and utilized to determine optimal blend geometries on a case by case basis. The statistical surrogate models are developed from analytical engineering analyses and/or a library of acceptable conditions to repair and center on the parameters D, S and L as shown in FIG. 1C. The use of statistical surrogate models enables a system to rapidly customize a blend solution for the engine that allows the engine to be returned to service quickly and safely.”, Morris et al. paragraph [0071] “This disclosure could be summarized as a method of suggesting appropriate blends to an airfoil, wherein the suggested blend is considered for structural adequacy based on at least one of system frequencies, mode shapes, mistuning characteristics, vibratory stresses, or material capability from a variety of engine conditions.”, The examiner considers the frequencies to be the natural frequency, since the blend of the airfoil can be based on the system frequencies)];
Brown et al. and Morris et al. are analogous art because they are from the same field
endeavor of analyzing the design airfoils.
Before the effective filing date of the invention, it would have been obvious to a person
of ordinary skill in the art to modify the teachings of Brown et al. of generating training data regarding a natural frequency, a modal force, and a Goodman scale factor of the plurality of simulated blended airfoil designs by incorporating training, using the computing system, surrogate models representing an airfoil design space based on at least one aeromechanical quantity comprising the natural frequency, the modal force, or the Goodman scale factor of the plurality of simulated blended airfoil designs using an automated regression process as taught by Morris et al. for the purpose of analyzing high cycle fatigue (HCF) in a design of a gas turbine engine.
Brown et al. in view of Morris et al. teaches training, using the computing system, surrogate models representing an airfoil design space based on at least one aeromechanical quantity comprising the natural frequency, the modal force, or the Goodman scale factor of the plurality of simulated blended airfoil designs using an automated regression process.
The motivation for doing so would have been because Morris et al. teaches that by analyzing high cycle fatigue (HCF) in a design of a gas turbine engine, the ability to capture the inherent blade-to-blade and engine-to-engine variability in HCF behavior can be accomplished in order to recognize the inherent variability in manufactured components (Morris et al. (paragraph [0005] – [0006])).
While the combination of the Brown et al. and Morris et al. teaches outputting the blend design space visualization to an external system for use in blending a damaged airfoil to form a blended airfoil, Brown et al., Morris et al. do not explicitly disclose “capturing image data of an example airfoil with an image sensor of an imaging device in communication with the computing system to define a captured blend parameter of the example airfoil; receiving, by the computing system, the captured blend parameter of the example airfoil from the imaging device; outputting, by the computer system, the captured blend parameter of the example airfoil to the external device”
Ruggiero discloses “capturing image data of an example airfoil with an image sensor of an imaging device in communication with the computing system to define a captured blend parameter of the example airfoil” as [Ruggiero (paragraph [0035] “The borescope 100 can also include an imaging device 114 as well as a memory 116. The imaging device 114 can include an imaging sensor 118 and a processor 120 capable of converting light incident on the sensor 118 into an electronic signal. The imaging sensor 118 is illustrated herein as a CCD sensor, and it will be understood that other sensors such as a CMOS sensor can also be used. The imaging device 114 can be connected in data communication to the microlens array 104, such as via a set of fiber optic cables 122.”, Ruggiero paragraph [0044] “A first region 411, a second region 412, and a third region 413 are visible on the airfoil 304, and these regions may indicate damage to the airfoil 304. In this first exemplary view, the first region 411 is in focus and damage to the airfoil 304 (such as a crack) is visible to an observer.”, Ruggiero paragraph [0045] “The computer system 400 can process the composite image 150 to shift the observed focal plane and bring the second region 412 into focus while the first and third regions 401, 403 become out of focus. In this view, it can be seen that the second region 412 includes damage to the airfoil 304.”, Ruggiero paragraph [0049] “It should be appreciated that other optical factors such as aperture size or lens focal length can determine the depth of field and how much of the airfoil 304 is in focus at a given time. While the examples of FIGS. 6-9 illustrate one selected region being in focus with other regions out of focus, it is contemplated that the borescope 100 can have a sufficiently large depth of field to bring multiple regions into focus simultaneously.”, The examiner considers the depth of field to be the blend parameter, since a blend parameters can be the depth of an airfoil, see paragraph [0027] of the specification)];
“receiving, by the computing system, the captured blend parameter of the example airfoil from the imaging device” as [Ruggiero (paragraph [0018] “The resulting image data can contain spatial information about the object; software post-processing of the image data can provide for manipulation of the image data to selectively change the focal plane/depth of view (for example, focusing on a portion in the foreground or background) or the viewing perspective (for example, tilting the field of view upward or panning to the right)”, The examiner considers the spatial information about the object to be the captured blend parameter, since the a blend parameter can be the depth of an airfoil, see paragraph [0027] of the specification)];
“outputting, by the computer system, the captured blend parameter of the example airfoil to the external device” as [Ruggiero (paragraph [0018] “Light rays from an object can be focused by the microlens array to form multiple optical images which may be captured by a light-sensitive device such as a CCD or CMOS sensor and stored in an electronic storage medium. The resulting image data can contain spatial information about the object; software post-processing of the image data can provide for manipulation of the image data to selectively change the focal plane/depth of view (for example, focusing on a portion in the foreground or background) or the viewing perspective (for example, tilting the field of view upward or panning to the right).”
Brown et al., Morris et al. and Ruggiero are analogous art because they are
from the same field endeavor of analyzing the design of blended airfoils.
Before the effective filing date of the invention, it would have been obvious to a person
of ordinary skill in the art to modify the teachings of Brown et al. and Morris et al. of outputting the blend design space visualization to an external system for use in blending a damaged airfoil to form a blended airfoil by incorporating capturing image data of an example airfoil with an image sensor of an imaging device in communication with the computing system to define a captured blend parameter of the example airfoil; receiving, by the computing system, the captured blend parameter of the example airfoil from the imaging device; outputting, by the computer system, the captured blend parameter of the example airfoil to the external device as taught by Ruggiero for the purpose of having a borescope for generating a composite image within an unlit.
Brown et al. in view of Morris et al. in further view of Ruggiero teaches capturing image data of an example airfoil with an image sensor of an imaging device in communication with the computing system to define a captured blend parameter of the example airfoil; receiving, by the computing system, the captured blend parameter of the example airfoil from the imaging device; outputting, by the computer system, the captured blend parameter of the example airfoil to the external device.
The motivation for doing so would have been because Ruggiero teaches that by having a borescope for generating a composite image within an unlit, the ability to gather as much data as possible during inspection of a turbine engine component can be accomplished in order to maximize safety and efficiency (Ruggiero paragraphs [0002] – [0003]).
While the combination of Brown et al., Morris et al. and Ruggiero teaches generating a plurality of simulated blended airfoil designs, each comprising one of a plurality of blend geometries, Brown et al., Morris et al. and Ruggiero do not explicitly disclose “A method manufacturing an airfoil based on a probabilistic distribution of a likelihood of high cycle fatigue failure; manufacturing, by the external device, the airfoil based on the data corresponding to the likelihood of high cycle fatigue failure below a failure threshold and the captured blend parameter of the example airfoil”
Hudson et al. discloses “A method manufacturing an airfoil based on a probabilistic distribution of a likelihood of high cycle fatigue failure” as [Hudson et al. (paragraph [0011] “Also disclosed herein, according to various embodiments, is another method of manufacturing an airfoil of a gas turbine engine. The method includes fixing the airfoil in a workpiece space, the airfoil having a leading edge, a leading edge portion, a trailing edge, a trailing edge portion, a suction side, and a pressure side. The method also includes detecting a position of the airfoil in the workpiece space by moving a force-sensing element across a first surface of one of the leading edge portion and the trailing edge portion of the airfoil. Further, the method includes removing material from a second surface, opposite the first surface, of the one of the leading edge portion and the trailing edge portion of the airfoil to reduce a dimension of the one of the leading edge portion and the trailing edge portion of the airfoil and to blend a transition from one of the pressure side and the suction side of the airfoil to the second surface.”)];
“manufacturing, by the external device, the airfoil based on the data corresponding to the likelihood of high cycle fatigue failure below a failure threshold and the captured blend parameter of the example airfoil” as [Hudson et al. (paragraph [0011] “Also disclosed herein, according to various embodiments, is another method of manufacturing an airfoil of a gas turbine engine. The method includes fixing the airfoil in a workpiece space, the airfoil having a leading edge, a leading edge portion, a trailing edge, a trailing edge portion, a suction side, and a pressure side. The method also includes detecting a position of the airfoil in the workpiece space by moving a force-sensing element across a first surface of one of the leading edge portion and the trailing edge portion of the airfoil. Further, the method includes removing material from a second surface, opposite the first surface, of the one of the leading edge portion and the trailing edge portion of the airfoil to reduce a dimension of the one of the leading edge portion and the trailing edge portion of the airfoil and to blend a transition from one of the pressure side and the suction side of the airfoil to the second surface.”, The examiner notes that as mentioned in section 6 of the current office action, there is any written description for the phrase “geometrical parameter”. The examiner considers the image data of the damaged airfoil that is captured and communicated with a computing system to define a captured blend parameter of the damaged airfoil, since there’s support for this within the specification)];
Brown et al., Morris et al., Ruggiero and Hudson et al. are analogous art
because they are from the same field endeavor of analyzing the design of blended airfoils.
Before the effective filing date of the invention, it would have been obvious to a person
of ordinary skill in the art to modify the teachings of Brown et al., Morris et al. and Ruggiero of generating a plurality of simulated blended airfoil designs, each comprising one of a plurality of blend geometries by incorporating a method manufacturing an airfoil based on a probabilistic distribution of a likelihood of high cycle fatigue failure; manufacturing, by the external device, the airfoil based on the data corresponding to the likelihood of high cycle fatigue failure below a failure threshold and the captured blend parameter of the example airfoil as taught by Hudson et al. for the purpose of manufacturing an airfoil of a gas turbine engine.
Brown et al. in view of Morris et al. in further view of Ruggiero in further view of Hudson et al. teaches a method manufacturing an airfoil based on a probabilistic distribution of a likelihood of high cycle fatigue failure; manufacturing, by the external device, the airfoil based on the data corresponding to the likelihood of high cycle fatigue failure below a failure threshold and the captured blend parameter of the example airfoil.
The motivation for doing so would have been because Hudson et al. teaches that by removing material from the second surface of the at least one of the leading-edge portions and the trailing edge portion of the airfoil that includes blending a transition from a pressure side of the airfoil to the second surface, the gas turbine engine is overall more efficient, because the trailing edge isn’t as thick (Hudson et al. (paragraph [0003], paragraph [0008])).
With respect to claim 16, the combination of Brown et al., Morris et al., Ruggiero and Hudson et al. discloses the method of claim 12 above, and Brown et al. discloses “determining, using the computing system, a relative impact of each of a plurality of geometrical parameters of the plurality of simulated airfoil designs” as [Brown et al. (Pg. 3, left col. 2nd paragraph “In this study, a relatively simple blend geometry is considered for demonstration purposes. The blend is defined by leading edge radial height, depth, and length. Together these define an elliptical cut along the airfoil leading edge. For the optimization development, both the depth and length are active design parameters while the radial location is fixed and assumed to be depended on FOD damage location. The model in Fig 1 shows the case with a 0.5 inch blend depth with a 4.0 aspect ratio. This represents the upper bound of the blend depth optimization. These processes are employed in the following sections to first quantify the blade-to-blade variations in structural integrity quantities for the PBS rotor, predict the effect of large blends on structural criteria, and conduct the optimization process that predicts part specific blend limits.”)];
“and a plurality of systemic variables on the likelihood of high cycle fatigue failure of the plurality of simulated airfoil designs.” as [Brown et al. (Pg. 2, right col. 1st paragraph “This work extends the knowledge of blend effects on airfoil structural response and the ability to use computational methods to use optimization methods to create part-specific limits for as-manufactured geometry FEM. Blend size effects on frequency, mode shape, and structural fatigue limits are considered in the presence of small geometric mistuning from manufacturing.”, Brown et al. Pg. 4, left col., 1st paragraph ““The influence of both steady and modal stress variations are accounted for with a Goodman fatigue damage model. The Goodman limit is an infinite life criteria determined through quasi-static or vibration based specimen testing and is a function of both steady and vibratory stress. The steady load of the PBS rotor is calculated at the maximum design RPM and both steady aerodynamic and thermal loading are omitted. These later effects are small relative to the rotational loads and their absence does not change the demonstration of the blend optimization. The airfoil vibratory stress was computed using an assumed maximum vibratory stress amplitude based on airfoil design practice and then applied as a scale factor to the mass normalized modal stress prediction for each airfoil.)];
With respect to claim 18, Brown et al. discloses “selecting a blend geometry from a plurality of blend geometries having a minimized likelihood of operational failure” as [Brown et al. (Pg. 3 left col., 3rd paragraph “In this study, a relatively simple blend geometry is considered for demonstration purposes. The blend is defined by leading edge radial height, depth, and length. Together these define an elliptical cut along the airfoil leading edge. For the optimization development, both the depth and length are active design parameters while the radial location is fixed and assumed to be depended on FOD damage location. The model in Fig 1 shows the case with a 0.5 inch blend depth with a 4.0 aspect ratio. This represents the upper bound of the blend depth optimization. These processes are employed in the following sections to first quantify the blade-to-blade variations in structural integrity quantities for the PBS rotor, predict the effect of large blends on structural criteria, and conduct the optimization process that predicts part specific blend limits.”)];
Hudson et al. discloses “A method of manufacturing or repairing an airfoil based on a likelihood of operational failure” as [Hudson et al. (paragraph [0011] “Also disclosed herein, according to various embodiments, is another method of manufacturing an airfoil of a gas turbine engine. The method includes fixing the airfoil in a workpiece space, the airfoil having a leading edge, a leading edge portion, a trailing edge, a trailing edge portion, a suction side, and a pressure side. The method also includes detecting a position of the airfoil in the workpiece space by moving a force-sensing element across a first surface of one of the leading edge portion and the trailing edge portion of the airfoil. Further, the method includes removing material from a second surface, opposite the first surface, of the one of the leading edge portion and the trailing edge portion of the airfoil to reduce a dimension of the one of the leading edge portion and the trailing edge portion of the airfoil and to blend a transition from one of the pressure side and the suction side of the airfoil to the second surface.”)];
“manufacturing or repairing, by the external device an airfoil based on the data corresponding to the minimized likelihood of operational failure and the geometrical parameter of the example airfoil” as [Hudson et al. (paragraph [0011] “Also disclosed herein, according to various embodiments, is another method of manufacturing an airfoil of a gas turbine engine. The method includes fixing the airfoil in a workpiece space, the airfoil having a leading edge, a leading edge portion, a trailing edge, a trailing edge portion, a suction side, and a pressure side. The method also includes detecting a position of the airfoil in the workpiece space by moving a force-sensing element across a first surface of one of the leading edge portion and the trailing edge portion of the airfoil. Further, the method includes removing material from a second surface, opposite the first surface, of the one of the leading edge portion and the trailing edge portion of the airfoil to reduce a dimension of the one of the leading edge portion and the trailing edge portion of the airfoil and to blend a transition from one of the pressure side and the suction side of the airfoil to the second surface.”, The examiner notes that as mentioned in section 9 of the current office action, there is any written description for the phrase “geometrical parameter”. The examiner considers the image data of the damaged airfoil that is captured and communicated with a computing system to define a captured blend parameter of the damaged airfoil, since there’s support for this within the specification)];
Brown et al., Morris et al., Ruggiero and Hudson et al. are analogous art because they are from the same field endeavor of analyzing the design of blended airfoils.
Before the effective filing date of the invention, it would have been obvious to a person
of ordinary skill in the art to modify the teachings of Brown et al., Morris et al. and Ruggiero of generating a plurality of simulated blended airfoil designs, each comprising one of a plurality of blend geometries by incorporating a method of manufacturing or repairing an airfoil based on a likelihood of operational failure; manufacturing or repairing, by the external device an airfoil based on the data corresponding to the minimized likelihood of operational failure and the geometrical parameter of the example airfoil as taught by Hudson et al. for the purpose of manufacturing an airfoil of a gas turbine engine.
Brown et al. in view of Morris et al. in further view of Ruggiero in further view of Hudson et al. teaches a method of manufacturing or repairing an airfoil based on a likelihood of operational failure; manufacturing or repairing, by the external device an airfoil based on the data corresponding to the minimized likelihood of operational failure and the geometrical parameter of the example airfoil.
The motivation for doing so would have been because Hudson et al. teaches that by removing material from the second surface of the at least one of the leading-edge portions and the trailing edge portion of the airfoil that includes blending a transition from a pressure side of the airfoil to the second surface, the gas turbine engine is overall more efficient, because the trailing edge isn’t as thick (Hudson et al. (paragraph [0003], paragraph [0008])).
The other limitations of the claim recite the same substantive limitations as claims 1 and 12 above, and are rejected using the same teaching.
With respect to claim 19, the claim recites the same substantive limitations as claims 1 and 12 above, and are rejected using the same teaching.
With respect to claim 20, the claim recites the same substantive limitations as claims 1 and 12 above, and are rejected using the same teaching.
Claim(s) 13 and 17 is/are rejected under 35 U.S.C. 103 as being unpatentable over Brown
et al. in view of Morris et al. in further view of Ruggiero in further view of Hudson et al. in further view of online reference Combined Airfoil and Snubber Design Optimization of Turbine Blades with Respect to Friction Damping, written by Huls et al.
With respect to claim 13, the combination of Brown et al., Morris et al., Ruggiero and Hudson et al. discloses the method of claim 12 above.
While the combination of Brown et al., Morris et al., Ruggiero and Hudson et al. teaches generating, using the computing system, a probabilistic distribution of an airfoil vibratory response of the airfoil design space using the surrogate models, Brown et al., Morris et al., Ruggiero and Hudson et al. do not explicitly disclose “wherein the failure threshold is based on a threshold endurance limit of the airfoil”
Huls et al. discloses “wherein the failure threshold is based on a threshold endurance limit of the airfoil” as [Huls et al. (Pg. 3, sec. 3.2 Closing Speed Approximation, 1st paragraph “These values are in fact a function of the blade geometry and thus of the defined geometric parameters. Arkhipov et al. [14] presented real engine data which shows a significant transition zone between first and full stage coupling due to individual manufacturing and assembly tolerances for the standstill shroud gap. In order to avoid pitting issues in the contact interface caused by high-frequent impact during vibration, full coupling is required under full engine speed N.”)];
Brown et al., Morris et al., Ruggiero, Hudson et al. and Huls et al. are analogous art
because they are from the same field endeavor of analyzing the design of blended airfoils.
Before the effective filing date of the invention, it would have been obvious to a person
of ordinary skill in the art to modify the teachings of Brown et al., Morris et al., Ruggiero and Hudson et al. of generating, using the computing system, a probabilistic distribution of an airfoil vibratory response of the airfoil design space using the surrogate models by incorporating wherein the failure threshold is based on a threshold endurance limit of the airfoil as taught by Huls et al. for the purpose of creating geometric blade design parameters onto a damped system response.
Brown et al. in view of Morris et al. in further view of Ruggiero in further view of Hudson et al. in view of Huls et al. teaches wherein the failure threshold is based on a threshold endurance limit of the airfoil.
The motivation for doing so would have been because Huls et al. teaches that by creating geometric blade design parameters onto a damped system response, the ability to predict the effect of the geometric design parameters onto vibrational characteristics can be accomplished to determine optimal design parameters subjected to dynamic constraints (Huls et al. (Abstract, Conclusions, 1st – 4th paragraph, “At the beginning of this paper, a combined parametrization of a snubber friction, etc.”)).
With respect to claim 17, the combination of Brown et al., Huls et al., Hudson et al. and Ruggiero discloses the method of claim 16 above, and Brown et al. discloses “wherein the plurality of systemic variables comprise tip clearance.” as [Brown et al. (Pg. 10, left col., 2nd paragraph, “Because the ninth vibration mode played such a prominent role in constraining blend limits and results through this work indicate frequency veering, etc…..It is seen that at the 0.10 inch blend that the tenth mode is characterized by modal deflections on the leading edge, tip, and trailing edge while the ninth mode is dominated by leading edge activity.”)];
While the combination of Brown et al., Morris et al., Ruggiero and Hudson et al. teaches generating, using the computing system, a probabilistic distribution of an airfoil vibratory response of the airfoil design space using the surrogate models, Brown et al., Morris et al., Ruggiero and Hudson et al. do not explicitly disclose “axial gap”
Huls et al. discloses “axial gap” as [Huls et al. (Pg. 2, sec. 2 Parametrization, 1st paragraph, “In order to investigate the physical relations between design variables and the dynamic system response under friction damping and examine the stated research questions, a parametric, generic high-aspect ratio turbine blade has to be developed as a reasonable test case.”)];
Brown et al., Morris et al., Ruggiero, Hudson et al. and Huls et al. are analogous art
because they are from the same field endeavor of analyzing the design of blended airfoils.
Before the effective filing date of the invention, it would have been obvious to a person
of ordinary skill in the art to modify the teachings of Brown et al., Morris et al., Ruggiero and Hudson et al. of generating, using the computing system, a probabilistic distribution of an airfoil vibratory response of the airfoil design space using the surrogate models by incorporating axial gap as taught by Huls et al. for the purpose of creating geometric blade design parameters onto a damped system response.
Brown et al. in view of Morris et al. in further view of Ruggiero in further view of Hudson et al. in view of Huls et al. teaches an axial gap.
The motivation for doing so would have been because Huls et al. teaches that by creating geometric blade design parameters onto a damped system response, the ability to predict the effect of the geometric design parameters onto vibrational characteristics can be accomplished to determine optimal design parameters subjected to dynamic constraints (Huls et al. (Abstract, Conclusions, 1st – 4th paragraph, “At the beginning of this paper, a combined parametrization of a snubber friction, etc.”)).
Claim(s) 3 and 7 is/are rejected under 35 U.S.C. 103 as being unpatentable over Brown et
al. in view of Morris et al. in further view of Ruggiero in further view of Hudson et al. in further view of online reference Probabilistic Study of Integrity Bladed Rotot Blends using Geometric Mistuning Models, written by Beck et al.
With respect to claim 3, the combination of Brown et al., Morris et al., Ruggiero and Hudson et al. discloses the method of claim 1 above.
While the combination of Brown et al., Morris et al., Ruggiero and Hudson et al. teaches generating, using a computing system, a plurality of simulated blended airfoil designs, each comprising one of a plurality of blend geometries, Brown et al., Morris et al., Ruggiero and Hudson et al. do not explicitly disclose “blending the damaged airfoil based on a simulated blended airfoil design outside of the one or more restricted regions of the blend design space that violate the at least one aeromechanical constraint to form the blended airfoil.”
Beck et al. discloses “blending the damaged airfoil based on a simulated blended airfoil design outside of the one or more restricted regions of the blend design space that violate the at least one aeromechanical constraint to form the blended airfoil.” as [Beck et al. (Pg. 8, 1st – 2nd paragraph, “Of all 1600IBRS in this population set, etc.”)];
Brown et al., Morris et al., Ruggiero, Hudson et al. and Beck et al. are analogous art
because they are from the same field endeavor of analyzing the design of blended airfoils.
Before the effective filing date of the invention, it would have been obvious to a person
of ordinary skill in the art to modify the teachings of Brown et al., Morris et al., Ruggiero and Hudson et al. of generating, using a computing system, a plurality of simulated blended airfoil designs, each comprising one of a plurality of blend geometries by incorporating blending the damaged airfoil based on a simulated blended airfoil design outside of the one or more restricted regions of the blend design space that violate the at least one aeromechanical constraint to form the blended airfoil as taught by Beck et al. for the purpose of blending airfoil geometries and predicting the mistuned response.
Brown et al. in view of Morris et al. in further view of Ruggiero in further view of Hudson et al. in further view of Beck et al. teaches blending the damaged airfoil based on a simulated blended airfoil design outside of the one or more restricted regions of the blend design space that violate the at least one aeromechanical constraint to form the blended airfoil.
The motivation for doing so would have been because Beck et al. teaches that by blending airfoil geometries and predicting the mistuned response, the ability to determine if blends provide larger risk of mistuned response amplification and if there are best/worst airfoils
to blend to increase/decrease forced response in order to determine the impact of Integrally Bladed Rotor (IBR) blend repair (Beck et al. (Abstract, Conclusion 1st paragraph, “Forces response results of four IBR populations, etc.”)).
With respect to claim 7, the combination of Brown et al., Morris et al., Ruggiero and Hudson et al. discloses the method of claim 1 above, and Brown et al. discloses “wherein determining the one or more restricted regions of the blend design space that violate the at least one aeromechanical constraint is a probabilistic determination” as [Brown et al. (Pg.8, Case 1: Depth Optimization Results, 1st paragraph, “This section reviews the results of the first optimization case where depth is optimized with a fixed 4.0 aspect ratio, etc,”, Fig. 11)];
While the combination of Brown et al., Morris et al., Ruggiero and Hudson et al. teaches determining the one or more regions of the blend design space that violate the at least one aeromechanical constraint is a probabilistic determination, Brown et al., Huls et al., Hudson et al. and Ruggiero do not explicitly disclose “and the blend design space visualization is a probabilistic blend design space comprising a contour plot depicting a probability of violation of the at least one aeromechanical constraint”
Beck et al. discloses “and the blend design space visualization is a probabilistic blend design space comprising a contour plot depicting a probability of violation of the at least one aeromechanical constraint.” as [Beck et al. (Pg. 2, sec. 2 Parametric Blended Airfoil model, 1st paragraph, “A probabilistic work-flow requires a Parametric Blended Airfoil Model(P-BAM), etc.”, Fig. 1)];
Brown et al., Morris et al., Ruggiero, Hudson et al. and Beck et al. are analogous art
because they are from the same field endeavor of analyzing the design of blended airfoils.
Before the effective filing date of the invention, it would have been obvious to a person
of ordinary skill in the art to modify the teachings of Brown et al., Morris et al., Ruggiero and Hudson et al. of determining the one or more regions of the blend design space that violate the at least one aeromechanical constraint is a probabilistic determination by incorporating and the blend design space visualization is a probabilistic blend design space comprising a contour plot depicting a probability of violation of the at least one aeromechanical constraint as taught by Beck et al. for the purpose of blending airfoil geometries and predicting the mistuned response.
Brown et al. in view of Morris et al. in further view of Ruggiero in further view of Hudson et al. in further view of Beck et al. teaches and the blend design space visualization is a probabilistic blend design space comprising a contour plot depicting a probability of violation of the at least one aeromechanical constraint.
The motivation for doing so would have been because Beck et al. teaches that by blending airfoil geometries and predicting the mistuned response, the ability to determine if blends provide larger risk of mistuned response amplification and if there are best/worst airfoils
to blend to increase/decrease forced response in order to determine the impact of Integrally Bladed Rotor (IBR) blend repair (Beck et al. (Abstract, Conclusion 1st paragraph, “Forces response results of four IBR populations, etc.”)).
Claim(s) 8 and 14-15 is/are rejected under 35 U.S.C. 103 as being unpatentable over
Brown et al. in view of Morris et al. in further view of Ruggiero in further view of Hudson et al. in further view of online reference Combined Airfoil and Snubber Design Optimization of Turbine Blades with Respect to Friction Damping, written by Huls et al. in further view of
online reference NASA Aeroelasticity Handbook Vol. 2: Design Guides Part 2, written by Ramsey.
With respect to claim 8, the combination of Brown et al., Huls et al., Hudson et al. and Ruggiero discloses the method of claim 1 above, and Brown et al. further discloses “and an aero- scaling factor parameter (Ps)” as [Brown et al. (Pg. 3, left col. 3rd paragraph “In this study, a relatively simple blend geometry is considered for demonstration purposes. The blend is defined by leading edge radial height, depth, and length.”, The examiner considers length to be the aero-scaling factor parameter, since length is one of the four principal scale factors for aeroelastic scaling, see attachment of Non-Patent Literature titled Wind Tunnel to Atmospheric Mapping for Static Aeroelastic Scaling)];
Morris et al. discloses “a mistuning amplification parameter (kv)” as [Morris et al. (paragraph [0049] “As an example, the advisability of an additional blend may be evaluated based upon stability, aerodynamic performance, vibratory stress and mistuning assessments.”, Morris et al. paragraph [0071] “This disclosure could be summarized as a method of suggesting appropriate blends to an airfoil, wherein the suggested blend is considered for structural adequacy based on at least one of system frequencies, mode shapes, mistuning characteristics, vibratory stresses, or material capability from a variety of engine conditions.”)];
Ruggiero discloses “a non-uniform vane spacing factor parameter (Knuvs)” as [Ruggiero (paragraph [0029] “Complementary to the rotor portion, the stationary portions of the engine 10, such as the static vanes 60, 62, 72, 74 among the compressor and turbine section 22, 32 are also referred to individually or collectively as a stator 63. As such, the stator 63 can refer to the combination of non-rotating elements throughout the engine 10.”)];
While the combination of Brown et al., Morris et al., Ruggiero, Hudson et al. teaches determining, using the computing system, a likelihood of operational failure throughout the blend design space in response to one or more vibratory modes using the surrogate models, Brown et al., Morris et al., Ruggiero, Hudson et al. do not explicitly disclose “determining a vibratory response as a percentage of material capability throughout the blend design space in response to the one or more vibratory modes by generating statistical distributions on a damping parameter (Q)”
Huls et al. discloses “determining a vibratory response as a percentage of material capability throughout the blend design space in response to the one or more vibratory modes by generating statistical distributions on a damping parameter (Q)” as [Huls (Pg. 3, left col. 1st paragraph, “This approach is considered a reasonable approximation as long as lift-off in the contact interface is avoided, as shown by Jareland [23]. A modal reduction is applied given the transformation µ = U ^q, with the complex modal matrix ^U containing a sufficient number of the blade rows mass normalized, uncoupled mode shapes. Furthermore, small modal damping ratios of D, etc.”)];
Brown et al., Morris et al., Ruggiero, Hudson et al. and Huls et al. are analogous art
because they are from the same field endeavor of analyzing the design of blended airfoils.
Before the effective filing date of the invention, it would have been obvious to a person
of ordinary skill in the art to modify the teachings of Brown et al., Morris et al., Ruggiero and Hudson et al. of determining, using the computing system, a likelihood of operational failure throughout the blend design space in response to one or more vibratory modes using the surrogate models by incorporating determining a vibratory response as a percentage of material capability throughout the blend design space in response to the one or more vibratory modes by generating statistical distributions on a damping parameter (Q) as taught by Huls et al. for the purpose of creating geometric blade design parameters onto a damped system response.
Brown et al. in view of Morris et al. in further view of Ruggiero in further view of Hudson et al. in view of Huls et al. teaches determining a vibratory response as a percentage of material capability throughout the blend design space in response to the one or more vibratory modes by generating statistical distributions on a damping parameter (Q).
The motivation for doing so would have been because Huls et al. teaches that by creating geometric blade design parameters onto a damped system response, the ability to predict the effect of the geometric design parameters onto vibrational characteristics can be accomplished to determine optimal design parameters subjected to dynamic constraints (Huls et al. (Abstract, Conclusions, 1st – 4th paragraph, “At the beginning of this paper, a combined parametrization of a snubber friction, etc.”)).
While the combination of Brown et al., Morris et al., Ruggiero, Hudson et al. and Huls et al. teaches modeling Goodman material, Brown et al., Morris et al., Ruggiero, Hudson et al. and Huls et al. do not explicitly disclose “
such that the vibratory response as a percentage of material capability is calculated by performing a Monte Carlo analysis using equation
PNG
media_image1.png
90
176
media_image1.png
Greyscale
where Fmodal is the modal force, f is the natural frequency, and GSF is the Goodman scale factor.”
Ramsey discloses “such that the vibratory response as a percentage of material capability is calculated by performing a Monte Carlo analysis using equation
PNG
media_image1.png
90
176
media_image1.png
Greyscale
where Fmodal is the modal force, f is the natural frequency, and GSF is the Goodman scale factor.” As [Ramsey (Pg. 9-29, 2nd paragraph, “Figures 4-13 and 4-14 give an example of an application of this probabilistic assessment approach, etc.”, Fig. 4-13)];
Brown et al., Morris et al., Ruggiero, Hudson et al., Huls et al. and Ramsey
are analogous art because they are from the same field endeavor of analyzing the design airfoils.
Before the effective filing date of the invention, it would have been obvious to a person
of ordinary skill in the art to modify the teachings of Brown et al., Morris et al., Ruggiero, Hudson et al. and Huls et al. of modeling Goodman material by incorporating such that the vibratory response as a percentage of material capability is calculated by performing a Monte Carlo analysis using equation
PNG
media_image1.png
90
176
media_image1.png
Greyscale
where Fmodal is the modal force, f is the natural frequency, and GSF is the Goodman scale factor as taught by Ramsey for the purpose of evaluating aeroelastic behavior.
Brown et al. in view of Morris et al. in further view of Ruggiero in further view of Hudson et al. in view of Huls et al. in further view of Ramsey teaches such that the vibratory response as a percentage of material capability is calculated by performing a Monte Carlo analysis using the equation
PNG
media_image1.png
90
176
media_image1.png
Greyscale
where Fmodal is the modal force, f is the natural frequency, and GSF is the Goodman scale factor.
The motivation for doing so would have been because Ramsey teaches that by evaluating aeroelastic behavior, the ability to design turbomachinery blading with an emphasis on full scale engine testing can be accomplished, which can prevent blade separation (Ramsey (Pg. 9-1, Introduction, Pg. 9-2, 4th paragraph “As mentioned above an aeroelastic, etc.”)).
With respect to claim 14, the claim recites the same substantive limitations as claim 8 above, and is rejected using the same teaching.
With respect to claim 15, the combination of Brown et al., Morris et al., Ruggiero,
Hudson et al., Huls et al. and Ramsey discloses the method of claim 14 above, and Morris further discloses “calibrating the damping parameter (Q), mistuning amplification parameter (k_v), the non-uniform vane spacing factor parameter (K_nuvs), and the aero-scaling factor parameter (P_s) using Bayesian probabilistic tuning.” as [Morris et al. (paragraph [0038] “Reduced order modeling approaches to create the emulators may include, but not be limited to, the use of mathematical analysis techniques, principal component analysis, proper orthogonal decomposition, Gaussian stochastic processes, response surface techniques, and Bayesian calibration methods.”)];
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to BERNARD E COTHRAN whose telephone number is (571)270-5594. The examiner can normally be reached 9AM -5:30PM EST M-F.
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Ryan F Pitaro can be reached at (571)272-4071. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000.
/BERNARD E COTHRAN/Examiner, Art Unit 2188
/RYAN F PITARO/Supervisory Patent Examiner, Art Unit 2188