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 .
DETAILED ACTION
1. The amendment filed 07/10/2026 has been received and considered. Claims 1-4, 6, and 9-20 are presented for examination.
Claim Objections
2. Claims 1, 12 and 15 are objected to because of the following informalities:
As per claim 1 and 15, they recite the limitation "wherein k and k+i are a time index" where which would be better as “wherein k and k+i are time indices” as two indices are recited with a singular noun.
As per claim 1, it recites the limitation “determining , based” in line 11 which would be better as “determining, based” as it stray space before the comma.
As per Claim 1 and 15, they recite the limitation “the (k+i)-th modification data indicate” (Claim 1) and “the (k+i)-th modification data indicates”. It is suggested to conform one to the other as the limitation shows inconsistent number.
As per Claim 15, it recites the limitation “the one or more physical detector system” in line 15 which would be better as “the one or more physical detector systems” to agree with “one or more physical detector systems” in line 8.
As per Claim 12, it recites the limitation “at least two different measurement systems” which has no clear relationship to the "one or more physical detector systems" of claim 1; thus, it would be better as “wherein the one or more physical detector systems comprise at least two different physical detector systems”.
Appropriate correction is required.
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
3. Claims 1-4, 6, and 9-20 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
As per Claim 1 and 15, they recite the step of “determining uncertainties of virtual measurement data based on measurement uncertainties of the measurement data of the physical object for the time step tk+i” which is unclear. It fails to show how essential step of determining the virtual measurement data whose uncertainties are recited in the second alternative of the claim. The virtual measurement data is not obtained, determined, or otherwise introduced by any prior step of the claim, and the claim does not recite what data the virtual measurement data is or how it relates to the recited measurement data of the physical object; the step of determining its uncertainties therefore has no nexus to any prior step.
uncertainties of the measurement data and the uncertainties of the virtual measurement data underlying the data assigned to the nodes of the finite element representation of the virtual object” where “determiningwhich omits an essential step of
As per Claim 3, it recites the limitation “determining a finite element representation of the experiment for the time step tk+i based on the measurement data of the physical object and the virtual measurement data for the time step tk+i;” which is unclear which features of the "experiment" are represented. In particular, it is unclear whether the “physical object” and the “virtual object” are part of “finite element representation” or not. Further it is unclear if “a finite element representation of the experiment” is part of simulation.
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.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
4. Claims 1 and 15-16 are rejected under 35 U.S.C. § 103 as being unpatentable over González et al. (“Model order reduction for real-time data assimilation through Extended Kalman Filters”), in view of Hallquist (LS-DYNA Keyword User’s Manual).
As per Claim 1 and 15-16, González et al. teaches a computer-implemented method/ apparatus/ non-transitory machine-readable medium for comparing a simulation of a physical object with measurement data of the physical object obtained in an experiment (pg. 679, Abstract “Data assimilation is the process by which experimental measurements are incorporated into the modeling process of a given system. …. real-time monitoring and control of structures or mixed/augmented reality”), …, the method comprising for one or more subsequent time steps tk+i of the simulation, wherein k and k+i are a time index, k is an integer equal to, or greater than, zero, and i is an integer greater than zero (pg. 682, Section 2, Corrector Phase):
(Claim 15) the apparatus comprising: one or more physical detector systems for obtaining measurement data of the physical object at time step tk+i, wherein k and k+i are a time index, k is an integer equal to, or greater than, zero, and i is an integer greater than zero (pg. 682, Section 2, Corrector Phase: experimental measurements are acquired and incorporated at each successive time step); an input interface coupled to the one or more physical detector system to receive the measurement data of the physical object; and a processing circuit configured to perform the following for one or more subsequent time steps tk+i of the simulation (Introduction “The ability to handle big data, along with the possibility of extracting relevant knowledge from raw data, once hidden correlations have been elucidated, has opened an unprecedented interest in the field of Dynamic Data Driven Application Systems [1]. Ubiquitous sensing and the generalization of the Internet of Things (IoT) in the framework of industry 4.0, is already providing us with large amounts of experimental data,” Inherency considered):
(Claim 16) when the program is executed on a processor or a programmable hardware (Introduction “The ability to handle big data, along with the possibility of extracting relevant knowledge from raw data, once hidden correlations have been elucidated, has opened an unprecedented interest in the field of Dynamic Data Driven Application Systems [1]. Ubiquitous sensing and the generalization of the Internet of Things (IoT) in the framework of industry 4.0, is already providing us with large amounts of experimental data,” Inherency considered);
obtaining, by using one or more physical detector systems, measurement data of the physical object at time step tₖ₊ᵢ (pg. 682, Section 2, Corrector Phase: experimental measurements are acquired and incorporated at each successive time step);
determining based on the measurement data of the physical object for the time step tk+i, (k+i)-th modification data for nodes of the finite element representation … in the time step tk+i-1, wherein the (k+i)-th modification data indicate modifications to data assigned to the nodes of the finite element representation …. from the time step tk+i-1 to the time step tk+i (section 2 on Pg 681-682, Corrector Phase: “Extended Kalman filters” correction phase computes at each time step a correction term “
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”: the Extended Kalman Filter computes at each time step the measurement-driven correction term
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);
determining the finite element representation of the physical object for the time step tk+i based on the finite element representation of the physical object for the time step tk+i-1, … (section 2-3 on Pg 681-682, equation (1): at each subsequent time step the updated state depends on the model prediction from the previous corrected state through the transfer function).
González et al. fails to teach explicitly wherein a finite element representation of a virtual object for interacting with a finite element representation of the physical object in order to restrain an evolution of the finite element representation of the physical object in the simulation is provided for a time step tk of the simulation,
the finite element representation of the virtual object for the time step tk+i-1 and the (k+i)-th modification data;
determining the finite element representation of the physical object for the time step...based on the finite element representation of the virtual object for the time step tk+i-1 and the (k+i)-th modification data.
outputting information about an interaction of the finite element representation of the virtual object with the finite element representation of the physical object,
wherein the virtual object is at least one surface enveloping at least part of the finite element representation of the physical object in the simulation, and the finite element representation of the physical object is restricted in the simulation to not penetrate the at least one surface, or
wherein the virtual object is a virtual replica of the experiment for the time step tk, and wherein nodes of the finite element representation of the virtual object are coupled to corresponding nodes of the finite element representation of the physical object via coupling elements, wherein the coupling elements exhibit coupling coefficients which vary based on the difference between the respective data assigned to coupled nodes, and the method further comprises: determining uncertainties of virtual measurement data based on measurement uncertainties of the measurement data of the physical object for the time step tk+i; and determining the coupling coefficients based on the measurement uncertainties of the measurement data and the uncertainties of the virtual measurement data underlying the data assigned to the nodes of the finite element representation of the virtual object.
Hallquist teaches wherein a finite element representation of a virtual object for interacting with a finite element representation of the physical object in order to restrain an evolution of the finite element representation of the physical object in the simulation is provided for a time step tk of the simulation (pg. 36-1, “*RIGIDWALL”, “The RIGIDWALL option provides a simple way of treating contact between a rigid surface and nodal points of a deformable body, called slave nodes.”; pg. 12-52, *CONTROL_CONTACT, RWPNAL “Scale factor for rigid wall penalties, which treat nodal points interacting with rigid walls, RWPNAL. The penalties are set so that an absolute value of unity should be optimal; however, this penalty value may be very problem dependent. If rigid/deformable materials switching is used, this option should be used if the switched materials are interacting with rigid walls”: “the rigidwall” corresponds to the claimed limitation “finite element representation of a virtual object”);
the finite element representation of the virtual object for the time step tk+i-1 and the (k+i)-th modification data (pg. 36-1, “*RIGIDWALL”, “The RIGIDWALL option provides a simple way of treating contact between a rigid surface and nodal points of a deformable body, called slave nodes.”; pg. 12-52, *CONTROL_CONTACT, RWPNAL “Scale factor for rigid wall penalties, which treat nodal points interacting with rigid walls, RWPNAL. The penalties are set so that an absolute value of unity should be optimal; however, this penalty value may be very problem dependent. If rigid/deformable materials switching is used, this option should be used if the switched materials are interacting with rigid walls”: “the rigidwall” corresponds to the claimed limitation “finite element representation of a virtual object”);
determining the finite element representation of the physical object for the time step... based on the finite element representation of the virtual object for the time step tk+i-1 and the (k+i)-th modification data (pg. 36-1, “*RIGIDWALL”; pg. 36-11, “*RIGIDWALL_GEOMETRIC”, Motion Card; pg. 12-52, “*CONTROL_CONTACT”, “RWPNAL”: the rigidwall contributes penalty forces or constraint corrections to the deformable body at each time step based on the current penetration state, establishing that the deformable body’s evolution at each time step depends on its own prior state (corresponding to the limitation “determining the finite element representation of the physical object”), the rigidwall (corresponding to the limitation “finite element representation of the virtual object”) configuration, and the measurement-derived modification data that updates the rigidwall’s prescribed motion);
outputting information about the interaction of the finite element representation of the virtual object with the finite element representation of the physical object (pg. 36-1& 36-2, “*RIGIDWALL” and “*RIGIDWALL_FORCE_TRANSDUCER”, “output of the transducer is written to the rwforc file.”: outputs rigidwall forces via the *RIGIDWALL_FORCE_TRANSDUCER keyword, which writes force data to the rwforc output file, and that energy dissipated due to rigidwalls is computed as stonewall energy: ...”),
wherein the virtual object is at least one surface enveloping at least part of the finite element representation of the physical object in the simulation, and the finite element representation of the physical object is restricted in the simulation to not penetrate the at least one surface (31-2, *RIGIDWALL_GEOMETRIC, providing geometric rigidwall shapes including a cylinder and a sphere; 31-10, *RIGIDWALL_GEOMETRIC_SPHERE example “prevents all nodes within a specified box from penetrating the sphere ... these nodes can slide on the sphere without friction”; 11-31, *CONTROL_CONTACT “Scale factor for rigid wall penalties, which treat nodal points interacting with rigid walls, RWPNAL.”: a geometric rigidwall of cylindrical or spherical shape is a surface enveloping part of the deformable body, and the RWPNAL penalty restricts the body from penetrating it), or
wherein the virtual object is a virtual replica of the experiment for the time step tk, and wherein nodes of the finite element representation of the virtual object are coupled to corresponding nodes of the finite element representation of the physical object via coupling elements (Hallquist: pg. 12-52, “*CONTROL_CONTACT, RWPNAL”; pg. 36-11 “Motion Card”, “*RIGIDWALL_GEOMETRIC_SHAPE_MOTION”: a rigidwall, the penetrated distance along the rigidwall normal is computed and resisted by applying a force proportional to the computed distance multiplied by a stiffness factor based on the material and element dimensions, which functions as coupling elements between the rigidwall and the physical object nodes.), wherein the coupling elements exhibit coupling coefficients which vary based on the difference between the respective data assigned to coupled nodes, and the method further comprises: determining uncertainties of virtual measurement data based on measurement uncertainties of the measurement data of the physical object for the time step tk+i; and determining the coupling coefficients based on the measurement uncertainties of the measurement data and the uncertainties of the virtual measurement data underlying the data assigned to the nodes of the finite element representation of the virtual object.
In particular, Hallquist teaches a rigidwall virtual object of geometric, enveloping shape that the deformable physical body is restrained from penetrating and whose prescribed motion is updated at each time step.
González et al. and Hallquist are analogous art because they are both related to a method for finite element simulation.
It would have obvious to one having ordinary skill in the art before the effective filling date of the claimed invention to combine the teachings of cited references. Thus, one of ordinary skill in the art before the effective filling date of the claimed invention would have been motivated to incorporate the teaching of Hallquist into González et al.’s to allow the simulation to be restrained to experimentally observed behavior while preserving the physical model’s constitutive relationships and internal consistency as LS-DYNA rigidwall contact is the standard mechanism for imposing boundary constraints in explicit finite element crash simulation (Hallquist: Pg 5-42; Pg 24-97).
5. Claims 2, 12, and 17 are rejected under 35 U.S.C. § 103 as being unpatentable over González et al. (“Model order reduction for real-time data assimilation through Extended Kalman Filters”), in view of Hallquist (LS-DYNA Keyword User’s Manual), and further in view of Yang et al. ("Investigating Grey-Box Modeling for Predictive Analytics in Smart Manufacturing”).
González et al as modified by Hallquist teaches most all the instant invention as applied to claims 1 and 15-16 above.
As per Claim 2 and 17, González et al as modified by Hallquist teaches wherein determining the (k+i)-th modification data comprises:
determining an estimate for the finite element representation of the physical object for the time step tk+i (González et al.: pg. 682, Predictor Phase);
allocating the measurement data of the physical object for the time step tk+i to nodes of the estimate (González et al.: pg. 682, section 2);
determining deviations between the measurement data of the physical object for the time step tk+i and data assigned to the allocated nodes of the estimate (González et al.: pg. 682, Corrector Phase).
González et al as modified by Hallquist fails to teach explicitly
determining distances between the nodes of the estimate;
determining virtual measurement data for the physical object for the time step tk+i by interpolating the deviations using the estimate and the distances between the nodes of the estimate; and
determining the (k+i)-th modification data based on the measurement data of the physical object and the virtual measurement data for the time step tk+i.
Yang et al. teaches determining distances between the nodes of the estimate (pg. 3 Section 2.2, Eqs. 3-4: the Kriging method estimates unknown point values based on spatial correlation between known sample points);
determining virtual measurement data for the physical object for the time step tk+i by interpolating the deviations using the estimate and the distances between the nodes of the estimate (pg. 3 Section 2.2, Eqs. 3-7: a grey-box approach where the residual between a white-box model prediction and experimental data is interpolated using Kriging, a spatial interpolation method that estimates unknown point values based on the positions of known sample points and distance-correlated weight values, thereby generating virtual complementary data by interpolating deviations across the model domain); and
determining the (k+i)-th modification data based on the measurement data of the physical object and the virtual measurement data for the time step tk+i (pg. 5 Section 4, Fig. 4: the final grey-box solution combines the basic solution from the white-box model with the estimated residual from the Kriging model).
González et al., Hallquist, and Yang et al. are analogous art because they are all related to a method for finite element simulation.
It would have obvious to one having ordinary skill in the art before the effective filling date of the claimed invention to combine the teachings of cited references. Thus, one of ordinary skill in the art before the effective filling date of the claimed invention would have been motivated to incorporate the teaching of Yang et al. into González et al. as modified by Hallquist’s to allow the simulation to be restrained to experimentally observed behavior while preserving the physical model’s constitutive relationships and internal consistency as LS-DYNA rigidwall contact is the standard mechanism for imposing boundary constraints in explicit finite element crash simulation (Hallquist: Pg 5-42; Pg 24-97). Further the motivation to combine the Yang et al. is to provide a high fidelity simulation or empirical data to build the foundation of the general model (Yang et al. Abstract) for employing Kriging interpolation to complement spatially incomplete measurement data across the FE mesh.
As per Claim 12, González et al as modified by Hallquist fails to teach explicitly wherein the measurement data of the physical object are generated by at least two different measurement systems.
Yang et al. teaches wherein the measurement data of the physical object are generated by at least two different measurement systems (pg. 8 Section 5.2 “metal PBF problems”).
6. Claims 3, 6, 18, and 20 are rejected under 35 U.S.C. § 103 as being unpatentable over González et al. (“Model order reduction for real-time data assimilation through Extended Kalman Filters”), in view of Hallquist (LS-DYNA Keyword User’s Manual) and Yang et al. ("Investigating Grey-Box Modeling for Predictive Analytics in Smart Manufacturing”), and further in view of Pierré et al. (“Finite Element Stereo Digital Image Correlation: Framework and Mechanical Regularization”).
González et al as modified by Hallquist teaches most all the instant invention as applied to claims 1 and 15-16 above.
González et al as modified by Hallquist and Yang et al. teaches most all the instant invention as applied to claims 2, 12 and 17 above.
As per Claim 3 and 18, González et al as modified by Hallquist and Yang et al. fails to teach explicitly wherein determining the (k+i)-th modification data based on the measurement data of the physical object and the virtual measurement data for the time step tk+i comprises: determining a finite element representation of the experiment for the time step tk+i based on the measurement data of the physical object and the virtual measurement data for the time step tk+i;
determining normal vectors for the nodes of the finite element representation of the experiment for the time step tk+i; and
determining the (k+i)-th modification data based on the finite element representation of the experiment and the normal vectors for the nodes of the finite element representation of the experiment for the time step tk+i.
Pierré et al. teaches determining a finite element representation of the experiment for the time step tk+i based on the measurement data of the physical object and the virtual measurement data for the time step tk+i (Pg 446 “Shape measurement with an FE mesh”, Equation (3));
determining normal vectors for the nodes of the finite element representation of the experiment for the time step tk+i (pg. 446-447 "Shape measurement with an FE mesh," "Regularization", "the surface normal is estimated at each node (average of the neighbouring element normals) in the initial shape of the mesh"); and
determining the (k+i)-th modification data based on the finite element representation of the experiment and the normal vectors for the nodes of the finite element representation of the experiment for the time step tk+i (Pg 446-447 “Shape measurement with an FE mesh”, Equation (3)-(4)). In particular, Pierré teaches an FE-SDIC framework that constructs a finite element representation of the experimentally observed surface by performing shape measurement directly on the FE mesh in the world coordinate system, where the 3D positions of mesh nodes are optimized to match the experimental stereo image data by minimizing grey-level conservation residuals and that the shape correction displacement field is determined along the surface normals based on the discrepancy between the projected FE mesh positions and the stereo image data, where the normal-direction correction at each node constitutes the modification data derived from the comparison of the FE representation with the experimental observations.
González et al. as modified by Hallquist, and Yang et al. and Pierré et al. are analogous art because they are all related to a method for finite element simulation.
It would have obvious to one having ordinary skill in the art before the effective filling date of the claimed invention to combine the teachings of cited references. Thus, one of ordinary skill in the art before the effective filling date of the claimed invention would have been motivated to incorporate the teaching of Pierré et al. into González et al. as modified by Hallquist and Yang et al.’s to allow the simulation to be restrained to experimentally observed behavior while preserving the physical model’s constitutive relationships and internal consistency as LS-DYNA rigidwall contact is the standard mechanism for imposing boundary constraints in explicit finite element crash simulation (Hallquist: Pg 5-42; Pg 24-97) and to provide a high fidelity simulation or empirical data to build the foundation of the general model (Yang et al. Abstract) for employing Kriging interpolation to complement spatially incomplete measurement data across the FE mesh. Further to combine the teaching of Pierré et al. is to enable quantitative comparison of experimental and simulated deformation fields for both experimental shape measurement and simulationusing the same finite element mesh (Conclusion).
As per Claim 6 and 20, González et al as modified by Hallquist and Yang et al. fails to teach explicitly wherein determining the (k+i)-th modification data based on the measurement data of the physical object and the virtual measurement data for the time step tk+i comprises:
determining a finite element representation of the experiment for the time step tk+i based on the measurement data of the physical object and the virtual measurement data for the time step tk+i; and
determining the (k+i)-th modification data based on a comparison of the finite element representation of the experiment for the time step tk+i and the finite element representation of the virtual object for the time step tk+i-1.
Pierré et al. teaches determining a finite element representation of the experiment for the time step tk+i based on the measurement data of the physical object and the virtual measurement data for the time step tk+i Pg 446 “Shape measurement with an FE mesh”, Equation (3)); and
determining the (k+i)-th modification data based on a comparison of the finite element representation of the experiment for the time step tk+i and the finite element representation of the virtual object for the time step tk+i-1 (pg. 444 “Introduction”; pg. 452-454, "Real test case").
As per Claim 7, González et al as modified by Hallquist and Yang et al. teaches wherein the virtual object is a virtual replica of the experiment for the time step tk, and wherein nodes of the finite element representation of the virtual object are coupled to corresponding nodes of the finite element representation of the physical object via coupling elements (Hallquist: pg. 12-52, “*CONTROL_CONTACT, RWPNAL”; pg. 36-11 “Motion Card”, “*RIGIDWALL_GEOMETRIC_SHAPE_MOTION”: a rigidwall, the penetrated distance along the rigidwall normal is computed and resisted by applying a force proportional to the computed distance multiplied by a stiffness factor based on the material and element dimensions, which functions as coupling elements between the rigidwall and the physical object nodes.).
7. Claims 11 and 13 are rejected under 35 U.S.C. § 103 as being unpatentable over González et al. (“Model order reduction for real-time data assimilation through Extended Kalman Filters”), in view of Hallquist (LS-DYNA Keyword User’s Manual), and further in view of Pierré et al. (“Finite Element Stereo Digital Image Correlation: Framework and Mechanical Regularization”).
González et al as modified by Hallquist teaches most all the instant invention as applied to claims 1 and 15-16 above.
As per Claim 11, González et al. as modified by Hallquist fails to teach explicitly wherein the measurement data of the physical object is position data indicating measured positions of the physical object, and wherein the data assigned to the nodes of the finite element representation of the virtual object is position data.
Pierré et al. teaches wherein the measurement data of the physical object is position data indicating measured positions of the physical object, and wherein the data assigned to the nodes of the finite element representation of the virtual object is position data. (Pg 446-447 “Shape measurement”).
González et al. as modified by Hallquist, and Pierré et al. are analogous art because they are all related to a method for finite element simulation.
It would have obvious to one having ordinary skill in the art before the effective filling date of the claimed invention to combine the teachings of cited references. Thus, one of ordinary skill in the art before the effective filling date of the claimed invention would have been motivated to incorporate the teaching of Pierré et al. into González et al. as modified by Hallquist’s to allow the simulation to be restrained to experimentally observed behavior while preserving the physical model’s constitutive relationships and internal consistency as LS-DYNA rigidwall contact is the standard mechanism for imposing boundary constraints in explicit finite element crash simulation (Hallquist: Pg 5-42; Pg 24-97). Further to combine the teaching of Pierré et al. is to enable quantitative comparison of experimental and simulated deformation fields for both experimental shape measurement and simulationusing the same finite element mesh (Conclusion).
As per Claim 13, González et al. as modified by Hallquist fails to teach explicitly wherein outputting information about the interaction comprises: coloring one of the finite element representation of the virtual object and the finite element representation of the physical object according to a color code indicating two or more levels of interaction of the finite element representation of the virtual object with the finite element representation of the physical object; and/or determining a scalar parameter indicating a type and/or the level of interaction of the finite element representation of the virtual object with the finite element representation of the physical object.
Pierré et al. teaches coloring one of the finite element representation of the virtual object and the finite element representation of the physical object according to a color code indicating two or more levels of interaction of the finite element representation of the virtual object with the finite element representation of the physical object (Pg 452-454 Figs 12-14); and/or determining a scalar parameter indicating a type and/or the level of interaction of the finite element representation of the virtual object with the finite element representation of the physical object.
8. Claim 14 is rejected under 35 U.S.C. § 103 as being unpatentable over González et al. (“Model order reduction for real-time data assimilation through Extended Kalman Filters”), in view of Hallquist (LS-DYNA Keyword User’s Manual) and Pierré et al. (“Finite Element Stereo Digital Image Correlation: Framework and Mechanical Regularization”), and further in view of Corigliano et al. (“Parameter identification in explicit structural dynamics: performance of the extended Kalman filter”).
González et al as modified by Hallquist teaches most all the instant invention as applied to claims 1 and 15-16 above.
González et al as modified by Hallquist and Pierré et al. teaches most all the instant invention as applied to claims 11 and 13 above.
As per Claim 14, González et al as modified by Hallquist and Pierré et al. fails to teach explicitly wherein the simulation of the physical object is one of a plurality of simulations of the physical object, and wherein the method further comprises: comparing the information about the interaction of the finite element representation of the virtual object with the finite element representation of the physical object determined for the simulation with information about the interaction of the finite element representation of the virtual object with the finite element representation of the physical object determined for other simulations of the plurality of simulations in order to obtain a comparison result; and
determining the simulation among the plurality of simulations that matches the measurement data of the physical object best based on the comparison result.
Corigliano et al. teaches comparing the information about the interaction of the finite element representation of the virtual object with the finite element representation of the physical object determined for the simulation with information about the interaction of the finite element representation of the virtual object with the finite element representation of the physical object determined for other simulations of the plurality of simulations in order to obtain a comparison result (Pg 3813-3812 section 4.1-4.3 Fig.3 & 5-10); and
determining the simulation among the plurality of simulations that matches the measurement data of the physical object best based on the comparison result (Pg 3813-3812 section 4.1-4.3 Fig.3 & 5-10). In particular, Corigliano teaches that the EKF was applied to multiple constitutive models with varying parameter sets and that the filter performance was evaluated across different initialization conditions, noise levels, and time step amplitudes, thereby comparing multiple simulation configurations against pseudo-experimental measurements to assess which parameter set and model best tracks the physical system’s behavior.
González et al. as modified by Hallquist, and Pierré et al., and Corigliano et al. are analogous art because they are all related to a method for finite element simulation.
It would have obvious to one having ordinary skill in the art before the effective filling date of the claimed invention to combine the teachings of cited references. Thus, one of ordinary skill in the art before the effective filling date of the claimed invention would have been motivated to incorporate the teaching of Corigliano et al. into González et al. as modified by Hallquist and Pierré et al.’s to allow the simulation to be restrained to experimentally observed behavior while preserving the physical model’s constitutive relationships and internal consistency as LS-DYNA rigidwall contact is the standard mechanism for imposing boundary constraints in explicit finite element crash simulation (Hallquist: Pg 5-42; Pg 24-97) and to enable quantitative comparison of experimental and simulated deformation fields for both experimental shape measurement and simulation using the same finite element mesh (Pierré et al.: Conclusion), and to provide a system with a high level of accuracy (Corigliano et al.: Abstract).
Allowable Subject Matter
9. Claims 4, 9, 10 and 19 are objected to as being dependent upon a rejected base claim, but would be allowable if rewritten in independent form including all of the limitations of the base claim and any intervening claims.
(Claim 4 and 19) “determining uncertainties of the virtual measurement data based on measurement uncertainties of the measurement data of the physical object for the time step tk+i;
determining an auxiliary finite element representation of the virtual object for the time step tk+i based on the finite element representation of the experiment and the normal vectors for the nodes of the finite element representation of the experiment for the time step tk+i using a predetermined metric for converting the uncertainties of the virtual measurement data and the measurement uncertainties of the measurement data of the physical object for the time step tk+i to scalar values of the same type as the measurement data of the physical object; and
determining the (k+i)-th modification data based on a comparison of the auxiliary finite element representation of the virtual object for the time step tk+i and the finite element representation of the virtual object for the time step tk+i-1.”
(Claim 9-10) “combining the finite element representation of the experiment for the time step tk+i-1 with (k+i)-th auxiliary modification data, wherein the (k+i)-th auxiliary modification data indicate modifications of data assigned to the nodes of the finite element representation of the physical object from the time step tk+i-1 to the time step tk+i in the simulation when the finite element representation of the virtual object is omitted.
Response to Arguments
10. Applicant's arguments filed 07/10/2026 have been fully considered but they are not persuasive.
Examiner respectfully withdraws Claim Rejections - 35 USC § 101 in view of the amendment and/or applicant’s arguments.
Withdrawal of Indication of Allowable Subject Matter: The indication in the prior Office Action that the subject matter of former claim 5 would be allowable is withdrawn. That subject matter which now recited as the first (enveloping, non-penetration) alternative of independent claims 1 and 15 is taught by Hallquist *RIGIDWALL_GEOMETRIC, which was already of record: a geometric rigidwall of cylindrical or spherical shape (31-2) is a surface enveloping at least part of the deformable body that the body is restricted from penetrating (31-10; RWPNAL, 11-31). The prior indication did not account for the geometric (enclosing) rigidwall shapes of the same reference relied upon for the base rejection.
Conclusion
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EUNHEE KIM
Primary Examiner
Art Unit 2188
/EUNHEE KIM/ Primary Examiner, Art Unit 2188
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