DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Status
Claims 1-20 are pending. Claims 1, 3, 8, 11, 13, and 18 are amended. No claims are cancelled.
Claims 1-20 are rejected under 35 USC 103.
Response to Amendment
The objection to claims 3 and 13 is withdrawn.
The rejection of claims 8 and 18 under 35 USC 112(b) is withdrawn. The amended claims 8 and 18 are understood to reference the model types as outlined in claims 1 and 11. Claims 8 and 18 narrow the scope of the independent claim by requiring one of each model type instead of “two or more” types as described in the independent claims.
Response to Arguments
Applicant’s arguments with respect to claim(s) 1-20 under 35 USC 103 have been considered but are moot because the new ground of rejection does not rely on any reference applied in the prior rejection of record for any teaching or matter specifically challenged in the argument.
Specification
The lengthy specification has not been checked to the extent necessary to determine the presence of all possible minor errors. Applicant’s cooperation is requested in correcting any errors of which applicant may become aware in the specification.
Applicant is reminded of the proper content of an abstract of the disclosure.
A patent abstract is a concise statement of the technical disclosure of the patent and should include that which is new in the art to which the invention pertains. The abstract should not refer to purported merits or speculative applications of the invention and should not compare the invention with the prior art.
If the patent is of a basic nature, the entire technical disclosure may be new in the art, and the abstract should be directed to the entire disclosure. If the patent is in the nature of an improvement in an old apparatus, process, product, or composition, the abstract should include the technical disclosure of the improvement. The abstract should also mention by way of example any preferred modifications or alternatives.
Where applicable, the abstract should include the following: (1) if a machine or apparatus, its organization and operation; (2) if an article, its method of making; (3) if a chemical compound, its identity and use; (4) if a mixture, its ingredients; (5) if a process, the steps.
Extensive mechanical and design details of an apparatus should not be included in the abstract. The abstract should be in narrative form and generally limited to a single paragraph within the range of 50 to 150 words in length.
See MPEP § 608.01(b) for guidelines for the preparation of patent abstracts.
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) 1-4, 6-14, and 16-20 are rejected under 35 U.S.C. 103 as being unpatentable over Cojocaru et al. (US 2020/0210542 A1) in view of Chaboche et al. “APPLICATION OF A KINEMATIC HARDENING VISCOPLASTICITY MODEL WITH THRESHOLDS TO THE RESIDUAL STRESS RELAXATION” International Journal of Plasticity, Vol. 13, 1998.
Regarding claim 1, Cojocaru discloses a non-transitory machine readable medium storing executable program instructions which when executed by a data processing system cause the data processing system to perform a method, the method comprising: ([0074] "As used herein, the terms "machine readable medium" "computer-readable medium" refers to any computer program product, apparatus and/or device (e.g., magnetic discs, optical disks, memory, Programmable Logic Devices (PLDs)) used to provide machine instructions and/or data to a programmable processor, including a machine-readable medium that receives machine instructions as a machine-readable signal. The "machine-readable medium" and "computer-readable medium," however, do not include transitory signals.")
storing material test data that has been collected from a set of one or more physical measurements of a material ([0030] "To prepare for calibration of the material model within the simulation software system 120, the user 102 gathers real-world test data.");
storing a set of optimization parameters ([0031] "Each material model includes one or more configurable parameters (e.g., typically coefficients of underlying equation variables) through which the response of the material model may be calibrated to alter the model response.") and storing a set of relationships between a set of material coefficients and the set of optimization parameters, ([0063] "The additional configuration may include, for example, allowing the user 102 to select which design parameters to use of those available for the selected material model, automatically populating initial values for the design parameters, allowing the user 102 to enter or alter those design parameters." The material coefficients are design parameters and are the initial values of the optimization parameters.) wherein values of the set of material coefficients can be calculated from the set of optimization parameters, ([0063] The optimization parameters are a subset of the material coefficients, the same subset as “at least a portion of the set”, so the values can be calculated by extracting them from the dataset. The relationship is “=”, assigning, or selection by the user.)
calculating optimum values of the set of optimization parameters to yield a fit of the plurality of material models to the material test data, ([0045] "In the example embodiment, the calibration computation module 220 performs an iterative minimization process that uses a user-selected numerical minimization algorithm to calibrate the material model, starting with the initial parameter values.") the fit based on the values of the set of optimum material coefficients calculated from the calculated optimum values of the set of optimization parameters ([0063] "The additional configuration may include, for example, allowing the user 102 to select which design parameters to use of those available for the selected material model, automatically populating initial values for the design parameters, allowing the user 102 to enter or alter those design parameters." The material coefficients are design parameters and are the initial values of the optimization parameters. After the calibration/optimization is completed, the optimum fit is described by the optimum material coefficients which are equal to the calculated optimum values of the optimization parameters.);
performing a simulation of a physical object that contains the material using one or more material models to determine behavior of the material in the simulation of the physical object ([0005] “The optimization process generates a calibrated material model. The instructions also cause the processor to assign the calibrated material model to a component of a simulation model based on input from the user. A real-world equivalent of the component is made of the physical material. The instructions further cause the processor to perform a simulation that includes the component. The simulation uses the stable material model and stable set of parameters to simulate response of the real-world equivalent during the simulation.”); and
generating one or more results based on the simulation, the one or more results indicating a performance of a design of the physical object ([0005] “The optimization process generates a calibrated material model. The instructions also cause the processor to assign the calibrated material model to a component of a simulation model based on input from the user. A real-world equivalent of the component is made of the physical material. The instructions further cause the processor to perform a simulation that includes the component. The simulation uses the stable material model and stable set of parameters to simulate response of the real-world equivalent during the simulation.”).
Cojocaru does not explicitly teach the set of material coefficients used in a plurality of material models of different model types including two or more of a Chaboche Kinematic Hardening model; a Kinematic Static Recovery model; or an Exponential Visco Hardening (Viscoplasticity) model.
Chaboche teaches the plurality of material models of different model types including two or more of (Under the broadest reasonable interpretation, only two of the listed alternatives must be taught. More than one may be mapped for the sake of compact prosecution. ) a Chaboche Kinematic Hardening model (pg. 792 “In that case, the kinematic hardening model (18) writes:” and Eq. (32)); a Kinematic Static Recovery model (pg. 787 “a static recovery potential” and Eq. (6)); and a Exponential Visco Hardening (Viscoplasticity) model (pg. 786 “II. THERMOVISCOPLASTICITY WITH MULTI-KINEMATIC HARDENING” and Eq. 11. In Eq. 11, m is a material coefficient in the viscoplasticity model.).
Cojocaru and Chaboche are analogous because they are from the “same field of endeavor” material modelling.
Before the effective filing date of the claimed invention, it would have been obvious to one of the ordinary skill in the art, having the teachings of Cojocaru and Chaboche before him or her, to modify Cojocaru to include material model types as taught by Chaboche.
The suggestion/motivation for doing so would have been Chaboche Conclusion ¶ 2 “The extended thermodynamic framework, with several independent dissipation pseudo-potentials and several Lagrange multipliers, seems to be a good compromise to introduce the constitutive models in a potential form but within a slightly less restrictive format than usual. This modifcation is especially useful when incorporating both the dynamic recovery and static recovery terms in a viscoplasticity theory.”
Regarding claim 2, Cojocaru in view of Chaboche teaches the medium as in claim 1 and Cojocaru discloses wherein the set of material coefficients comprises a first subset of material coefficients and a second subset of material coefficients ([0066] “In this example, Ogden includes design parameters mu1, alpha1, mu2, alpha2, mu3, alpha3, D1, D2, and D3, and the user 102 has elected to use all design parameters except D1, D2, and D3.” The subsets are selected parameters and unselected parameters.), and the second subset of material coefficients is the portion of the set of material coefficients that is calculated from the set of optimization parameters([0063] The optimization parameters are a subset of the material coefficients, the same subset as “at least a portion of the set”, so the values can be calculated by extracting them from the dataset.); and wherein the method further comprises: calculating the first subset of material coefficients from the stored material test data before calculating the optimum values (Fig. 6 and [0067] The stress and strain parameters are calculated and plotted before calibration).
Regarding claim 3, Cojocaru in view of Chaboche teaches the medium as in claim 2 and Cojocaru discloses wherein the fit is based on a desired error level ( [0064] “The material calibration module 130 then evaluates the model results for that iteration against the objective function with the penalty function to determine whether the model results have produced an error below a pre-determined convergence value.”).
Regarding claim 4, Cojocaru in view of Chaboche teaches the medium as in claim 2 and Cojocaru discloses wherein the set of material coefficients calculated from the set of optimization parameters ([0063] "The additional configuration may include, for example, allowing the user 102 to select which design parameters to use of those available for the selected material model, automatically populating initial values for the design parameters, allowing the user 102 to enter or alter those design parameters." The material coefficients are design parameters and are the initial values of the optimization parameters. After the calibration/optimization is completed, the optimum fit is described by the optimum material coefficients which are equal to the calculated optimum values of the optimization parameters.) are used in the simulation to determine the behavior of the material in the simulation of the physical object ([0005] “The simulation uses the stable material model and stable set of parameters to simulate response of the real-world equivalent during the simulation.”).
Regarding claim 6, Cojocaru in view of Chaboche teaches the medium as in claim 2 and Cojocaru discloses wherein the method uses specified ranges of possible values for each of the optimization parameters in the set of optimization parameters to allow the set of optimization parameters to work for a variety of different materials ([0042] “Further, in the example embodiment, the stability configuration module 218 allows the user 102 to identify one or more strain ranges of interest for this calibration. For example, the user 102 may wish to have the material model stable across one or more ranges of strains, and optionally or one or more modes of deformation. As such, the stability configuration module 218 allows the user 102 to enter strain ranges such as, for example, a range of strain in the loading direction and lateral direction, a volume ratio, and a shear strain.”).
Regarding claim 7, Cojocaru in view of Chaboche teaches the medium as in claim 2 and Cojocaru discloses wherein the optimum values are calculated iteratively in a solver ([0005] “The instructions also cause the processor to perform an iterative optimization process to calibrate the material model.”) that determines whether a fit is within a threshold value of a desired error level ([0064] “The material calibration module 130 then evaluates the model results for that iteration against the objective function with the penalty function to determine whether the model results have produced an error below a pre-determined convergence value.”).
Regarding claim 8, Cojocaru in view of Chaboche teaches the medium as in claim 2 and Cojocaru discloses wherein the material test data comprises one or more of: uniaxial test data (Under the broadest reasonable interpretation, only one of the listed alternatives must be taught. [0030] “A real material (also referred to herein as the “subject material”) may be tested in a laboratory under specific loading conditions, during which a specimen made of the real material is subjected to one or more deformation modes (e.g., tensile and compressive uniaxial loading, tensile and compressive biaxial loading, tensile and compressive planar loading (also known as pure shear loading), volumetric loading, and simple shear loading).” Under broadest reasonable interpretation, only one of the listed alternatives must be taught.); but Cojocaru does not explicitly teach wherein the plurality of material models comprise each of: the Chaboche Kinematic Hardening model; the Kinematic Static Recovery model; and the Exponential Visco Hardening (Viscoplasticity) model.
Chaboche teaches wherein the plurality of material models comprise each of: the Chaboche Kinematic Hardening model (pg. 792 “In that case, the kinematic hardening model (18) writes:” and Eq. (32)); the Kinematic Static Recovery model (pg. 787 “a static recovery potential” and Eq. (6)); and the Exponential Visco Hardening (Viscoplasticity) model (pg. 786 “II. THERMOVISCOPLASTICITY WITH MULTI-KINEMATIC HARDENING” and Eq. 11. In Eq. 11, m is a material coefficient in the viscoplasticity model.).
Cojocaru and Chaboche are analogous because they are from the “same field of endeavor” material modelling.
Before the effective filing date of the claimed invention, it would have been obvious to one of the ordinary skill in the art, having the teachings of Cojocaru and Chaboche before him or her, to modify Cojocaru to include material model types as taught by Chaboche.
The suggestion/motivation for doing so would have been Chaboche Conclusion ¶ 2 “The extended thermodynamic framework, with several independent dissipation pseudo-potentials and several Lagrange multipliers, seems to be a good compromise to introduce the constitutive models in a potential form but within a slightly less restrictive format than usual. This modifcation is especially useful when incorporating both the dynamic recovery and static recovery terms in a viscoplasticity theory.”
Regarding claim 9, Cojocaru in view of Chaboche teaches the medium as in claim 2 and Cojocaru discloses wherein the optimum fit is based on errors computed at only selected points of the material test data (Fig. 4 #430 There are a limited number of selected measured data points on the stress/strain plot. The continuous optimized curve is compared to the non-continuous test data to calculate the error. The loaded test points are selected points of the material test data.).
Regarding claim 10, Cojocaru in view of Chaboche teaches the medium as in claim 2 and Cojocaru discloses wherein the method further comprises: modifying some values in the second subset to apply a second material model in calculating the optimum values ([0066] “In the example embodiment, the graphical user interface includes a material model panel 410 within which the user 102 has selected a hyperelastic Ogden material model for calibration. The material model panel 410 includes a list of design parameters 412 provided by the model, check boxes indicating which design parameters 412 the user 102 has elected to use during this calibration, as well as display boxes for associated parameter values 414. In this example, Ogden includes design parameters mu1, alpha1, mu2, alpha2, mu3, alpha3, D1, D2, and D3, and the user 102 has elected to use all design parameters except D1, D2, and D3.” The user has the ability to select from a list of material models. The user can also modify the second subset by selecting or excluding parameters from the optimization.).
Regarding claim 11, Cojocaru teaches a machine implemented method, the method comprising: ([0001] “This disclosure relates generally to simulation systems and, more particularly, to systems and methods for stability-based constrained numerical calibration of material models in computer simulations.”). The remainder of claim 11 is rejected in substantially the same way as claim 1.
Claims 12-14 and 16-20 are rejected in substantially the same way as claims 2-4 and 6-10 respectively.
Claim(s) 5 and 15 are rejected under 35 U.S.C. 103 as being unpatentable over Cojocaru et al. (US 2020/0210542 A1) in view of Chaboche et al. “APPLICATION OF A KINEMATIC HARDENING VISCOPLASTICITY MODEL WITH THRESHOLDS TO THE RESIDUAL STRESS RELAXATION” International Journal of Plasticity, Vol. 13, 1998 in view of Ayyagari et al. (US 2021/0240896 A1).
Regarding claim 5, Cojocaru in view of Chaboche teaches the medium as in claim 4, and Cojocaru discloses wherein the simulation provides one or more results that indicate one or more of: a performance of the physical object (Abstract “simulate response of the real-world equivalent during the simulation.” Simulating the response is simulating the performance. Under broadest reasonable interpretation, only one of the listed alternatives must be taught.)
Cojocaru and Chaboche do not explicitly teach wherein the method further comprises: revising the design of the physical object based on the one or more results.
Ayyagari does teach wherein the method further comprises: revising the design of the physical object based on the one or more results (Abstract “evaluating a performance of a software algorithm on the digital system to determine an effect of the material or process change for the semiconductor manufacturing process.”).
Cojocaru, Chaboche, and Ayyagari are analogous because they are from the “same field of endeavor” material simulation.
Before the effective filing date of the claimed invention, it would have been obvious to one of the ordinary skill in the art, having the teachings of Cojocaru, Chaboche, and Ayyagari before him or her, to modify Cojocaru and Chaboche to include design revision as taught by Ayyagari.
The suggestion/motivation for doing so would have been Ayyagari [0017] “Finally, the embodiments described herein dramatically reduce the time it takes to evaluate a material/process change by aggregating each stage of the process—from materials to full systems—into a single software workflow. This combination of advantages provided by these embodiments reduces the previous multi-year process for evaluating material/process changes at the equipment manufacturer down to days or weeks at most.”
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 TROY A MAUST whose telephone number is (571)272-1931. The examiner can normally be reached on Monday-Friday from 8AM to 4PM.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Rehana Perveen, can be reached at telephone number (571) 272-3676. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/T.A.M./Examiner, Art Unit 2189
/REHANA PERVEEN/Supervisory Patent Examiner, Art Unit 2189