DETAILED ACTION
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on 12/02/2025 has been entered.
Claims 12-14, 16, and 18-24 have been presented for examination based on the RCE filed on 12/02/2025.
Claims 12, 20, 21 are amended.
Claims 22-24 are new.
Claims 12-14, 16, and 18-24 are rejected under 35 U.S.C. 101.
Claims 12-14, 20, and 21-24 are rejected under 35 U.S.C. 103 as being unpatentable over Ao et al. “Dynamics Model Validation Using Time-Domain Metrics” (hereinafter “Ao”) in view of Rashidi et al. “Multi-objective Design and Optimization of Power Electronics Converters With Uncertainty Quantification—Part II: Model-Form Uncertainty” (hereinafter “Rashidi”), further in view Wang, Ning, et al. “A new interval area metric for model validation with limited experimental data.” (hereinafter “Wang”).
Claims 16 and 19 are rejected under 35 U.S.C. 103 as being unpatentable over Ao in view of Rashidi, in view of Wang, and in further view of Lenz et al. “Quantification and Evaluation of Parameter and Model Uncertainty for Passive and Active Vibration Isolation” (hereinafter “Lenz”).
Claim 18 is rejected under 35 U.S.C. 103 as being unpatentable over Ao in view of Rashidi, in view of Wang, and in further view of Zhu et al. “Real-time yaw rate prediction based on a non-linear model and feedback compensation for vehicle dynamics control” (hereinafter “Zhu”).
This action is made Non-Final.
Response to Arguments
(Argument 1) Applicant has argued in Remarks Pg.7-8:
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(Response 1) Applicant has pointed to specification [0002] are improvement in the technology. This is problem statement disembodied from any technology. This and the disclosure in general does not appear to disclose any specific technology that this abstract idea is applied to. Rashidi art and Wang are good counter examples where the abstract idea is applied to modeling power electronics and cantilever. Even if applied to specific technology, the methodology is a model evaluation method (remains an abstract idea) and not model a model design method (which may spur better designs as result of model evaluation), thereby improving a specific technological field. Not one technological field is claimed. The improvement in model assessment is not a technological field if it does not lead to improvement in the technology.
(Argument 2) Applicant has argued in Remarks Pg.:
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(Response 2) As per (1) and (2), these are abstract idea, an algorithm to determine better model (identified by simulated output of represented as first and second curve). Varying a parameter during simulation is a mental step to obtain different results from the simulation model. This is also considered a mental step. In alternate examiner has also updated rejection to show such varying and analysis is well known routine and conventional (WRC) (under MPEP 2106.05(d)) and is shown in both Rashidi and Wang prior arts (see specific mapping in prior art rejections below).
As per (3), it is unclear what is the practical application here. The argument would make if such an practical application connected to technological improvement would have been disclosed.
(Argument 3) Applicant has argued in Remarks Pg.10-11:
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(Response 3) Simulation model validation neither constructs the model nor improves on the model for any specific application/technological field. Simulation model validation as claimed is an abstract idea (mathematical concept involving mentals steps to vary the input parameters) which evaluates the model against the reference (or measured) values and determines fit of the model based on known1 mathematical/statistical technique (Modified Area Validation Metric (MAVM)). This is an improvement in statistical evaluation technique/an abstract idea not a specific technological field as per MPEP 2106.05(a) and use of such mathematical technique is building block as shown in Rashidi and Wang prior arts.
(Argument 4) Applicant has argued in Remarks Pg.11-13:
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(Response 4) Again rendering decision whether the model is a good simulation model or performing validation to determine a good simulation model is an evaluation/judgement/opinion (based on statistical method of MAVM) based on the observation (simulation model curves vs reference). See MPEP 2106.04(a)(2)(I) & (III). This neither constructs the nor improves the model itself.
Examiner has not only mapped this aspect to abstract idea as explained above, but also even if practical application to a specific technology is implied in the claim (which is not) such is now mapped under WRC with teachings of Wang & Rashidi. Examiner does not find applicant’s argument persuasive.
New grounds of rejection are presented for amended claims and new claims addressing applicants’ remarks.
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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 12-14, 16, and 18-24 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. Examiner has evaluated the claims under the framework provided in the 2019 Patent Eligibility Guidance published in the Federal Register 01/07/2019 and has provided such analysis below.
Step 1: Claims 12-14, 16, 18, and 19 are directed to methods and fall within the statutory category of processes; Claim 20 is directed to an apparatus and falls within the statutory category of machines; and Claim 21 is directed to a non-transitory machine-readable storage medium and fall within the statutory category of articles of manufacture. Therefore, claims 12-14, 16, and 18-21 are directed to patent eligible categories of invention.
Step 2A Prong 1: The limitations of the claims 12, 20, and 21 of “[determining or determine] multiple simulation values for the quantity using the simulation model;” and “[determining or determine] multiple associated reference values for the quantity;” as drafted, is a process that, but for the recitation of generic computing components, under its broadest reasonable interpretation, covers performance of the limitation in the mind. For example, a person can mentally determine multiple simulation values for the quantity using the simulation model and determine multiple associated reference values for the quantity. If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components, then it falls within the “Mental Processes” grouping of abstract ideas. Accordingly, the claims recite an abstract idea under Prong 1 step 2A.
The limitations of the claims 12, 20, and 21 of “[determining or determine], for each value of multiple values of the varying parameter, a model-form error as a deviation between the simulation value with respect to the value of the varying parameter, and the reference value with respect to the value of the varying parameter;” and “wherein each model-form error is determined using a modified area validation metric, in which the deviation between the simulation value and the reference value is determined individually for positive and negative deviations, wherein the simulation values correspond to a plurality of curves including at least a first boundary curve and a second boundary curve, wherein the positive deviation is between the first boundary curve and at least one of the multiple associated reference values, and wherein the negative deviation is between the second boundary curve and at least one other of the multiple associated reference values.”, as drafted, is a process that, under its broadest reasonable interpretation, covers mathematical operations but for the recitation of generic computer components. For example, a person can determine a model-form error by mathematically comparing the deviation between the simulation value with respect to the value of the varying parameter, and the reference value with respect to the value of the varying parameter, for each value of multiple values of the varying parameter. Further, a model-form error that is determined using the modified area validation metric requires areas d+ and d- to be calculated for the difference between simulation and reference values (See: Figure 1B and [0038]-[0039] of the instant specification). If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components, then it falls within the “Mathematical Operations” grouping of abstract ideas. Further defining the (first and second) curves from datum (like simulation) and identifying parts of curve as positive or negative deviation (as in Fig.1a of specification) is a mental step. Accordingly, the claims recite an abstract idea under Prong 1 step 2A.
The limitations of the claims 12, 20, and 21 of “[determining or determine], based on the model-form errors for the multiple values of the varying parameter, a function of the model-form error depending on the varying parameter”, as drafted, is a process that, but for the recitation of generic computing components, under its broadest reasonable interpretation, covers performance of the limitation in the mind. For example, a person can mentally determine, based on the model-form errors for the multiple values of the varying parameter, a function of the model-form error depending on the varying parameter. If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components, then it falls within the “Mental Processes” grouping of abstract ideas. Accordingly, the claims recite an abstract idea under Prong 1 step 2A.
Further under Step 2A Prong 1, gathering and analyzing data is considered as mental step. See MPEP 2106.04(a)(2)(III)(A).
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The specific methodology of analysis is an abstract idea (algorithm which are similar to the claimed steps), but in alternate may also be addressed as WRC below.
Step 2A Prong 2: This judicial exception is not integrated into a practical application. In particular, the claims 12, 20, and 21 recite additional elements such as “utilizing the determined function for the assessment and/or validation, of the simulation model” which are merely instructions to apply the judicial exception (See MPEP § 2106.05(f)) which does not integrate a judicial exception into practical application. Therefore, this additional element does not integrate the abstract idea into a practical application and it does not impose any meaningful limits on practicing the abstract idea. The claims are directed to an abstract idea under Steps 2A Prong 1 and 2.
Step 2B: The claims 12, 20, and 21 do not include additional elements, alone or in combination, that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application, the additional elements amount to no more than merely instructions to apply the judicial exception.
Therefore, these additional elements, alone or in combination, do not amount to significantly more than the judicial exception. Having concluded analysis within the provided framework, claims 12, 20, and 21 do not recite patent eligible subject matter under 35 U.S.C. § 101.
Further in view of claim as a whole the claim does not improve on any technology (as per MPEP 2106.05(a)2) as no field of use is claimed (see respective preambles and the steps which are not tied to any specific technology). A good counter example would be disclosure in Rashidi (Optimization of Power Electronics Converters) or Wang (Fig.12 The cantilever beam example for satellite support).
The data gathering and analysis as is also considered as conventional in view of Rashidi (2021) prior art NPL and Wang (2018), under MPEP 2106.05(d) in view of gathering and analyzing data is considered a mental process.
Regarding claim 13, it recites additional element recitations of “wherein the varying parameter is a time, so that the quantity is a time characteristic of the fixed parameter” which is merely a recitation of a field of use/technological environment (see MPEP § 2106.05(h)) which does not integrate a judicial exception into practical application. Further, the claim does not recite any further additional elements and for the same reasons as above with regard to integration into practical application and whether additional elements amount to significantly more, the claim also fails both Step 2A prong 2, thus the claim is directed to the judicial exception as it has not been integrated into practical application, and fails Step 2B as not amounting to significantly more. Therefore, claim 13 does not recite patent eligible subject matter under 35 U.S.C. §101.
Regarding claim 14, it recites additional element recitations of “wherein the fixed parameter is predetermined by a signal, so that the quantity is a time characteristic of the signal” which is merely a recitation of a field of use/technological environment (see MPEP § 2106.05(h)) which does not integrate a judicial exception into practical application. Further, the claim does not recite any further additional elements and for the same reasons as above with regard to integration into practical application and whether additional elements amount to significantly more, the claim also fails both Step 2A prong 2, thus the claim is directed to the judicial exception as it has not been integrated into practical application, and fails Step 2B as not amounting to significantly more. Therefore, claim 14 does not recite patent eligible subject matter under 35 U.S.C. §101.
Regarding claim 16, it recites additional element recitations of “wherein the simulation model has at least one fixed and at least one varying model parameter, and the simulation values have an uncertainty in the form of a probability distribution which reflects the varying model parameters, and the reference values have an uncertainty in the form of a frequency distribution” which is merely a recitation of a field of use/technological environment (see MPEP § 2106.05(h)) which does not integrate a judicial exception into practical application. Further, the claim does not recite any further additional elements and for the same reasons as above with regard to integration into practical application and whether additional elements amount to significantly more, the claim also fails both Step 2A prong 2, thus the claim is directed to the judicial exception as it has not been integrated into practical application, and fails Step 2B as not amounting to significantly more. Therefore, claim 16 does not recite patent eligible subject matter under 35 U.S.C. §101.
Regarding claim 18, it recites additional element recitations of “wherein the quantity includes a time characteristic of a vehicle yaw rate, or a variation of an impact energy of a drill hammer, or a drying time of dishes in a dishwasher, or a variation of a no-load breakaway torque of a steering system, or a measured variable of a radar sensor” which is merely a recitation of a field of use/technological environment (see MPEP § 2106.05(h)) which does not integrate a judicial exception into practical application. Further, the claim does not recite any further additional elements and for the same reasons as above with regard to integration into practical application and whether additional elements amount to significantly more, the claim also fails both Step 2A prong 2, thus the claim is directed to the judicial exception as it has not been integrated into practical application, and fails Step 2B as not amounting to significantly more. Therefore, claim 18 does not recite patent eligible subject matter under 35 U.S.C. §101.
Regarding claim 19, it recites additional element recitations of “wherein a software product or a controller is virtualized or released using the assessed and/or validated, simulation model” which is merely a recitation of a field of use/technological environment (see MPEP § 2106.05(h)) which does not integrate a judicial exception into practical application. Further, the claim does not recite any further additional elements and for the same reasons as above with regard to integration into practical application and whether additional elements amount to significantly more, the claim also fails both Step 2A prong 2, thus the claim is directed to the judicial exception as it has not been integrated into practical application, and fails Step 2B as not amounting to significantly more. Therefore, claim 19 does not recite patent eligible subject matter under 35 U.S.C. §101.
Dependent claims 13, 14, 16, 18, and 19 are also similarly rejected under same rationale as cited above wherein these claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception. These claims are merely further elaborating the judicial exception itself or providing additional definition of process which does not impose any meaningful limits on practicing the abstract idea. Claims 13, 14, 16, 18, and 19 are also rejected for incorporating the deficiency of their independent claim 12.
Regarding claims 22-24 (New), they recites “wherein an interval-characterized epistemic input uncertainty determines a horizontal distance of the first boundary curve and the second boundary curve.” which merely are considered as a mental step performed with pencil and paper to further annotate the regions (intervals) based on observation (of the two curves) on a graph (see Fig.1a of specification). See MPEP 2104.04(a)(2)(III). If any uncertainty determination is implied it is but a mathematical concept at best. See MPEP 2104.04(a)(2)(I). The claims do not recite any additional elements that integrate the claims into practical application (Step 2A Prong2) or add significantly more (Step 2B).
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
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.
Claims 12-14, 20, and 21-24 are rejected under 35 U.S.C. 103 as being unpatentable over Ao et al. “Dynamics Model Validation Using Time-Domain Metrics” (hereinafter “Ao”) in view of Rashidi et al. “Multi-objective Design and Optimization of Power Electronics Converters With Uncertainty Quantification—Part II: Model-Form Uncertainty” (hereinafter “Rashidi”), further in view Wang, Ning, et al. “A new interval area metric for model validation with limited experimental data.” (hereinafter “Wang”).
Regarding Claim 12
Regarding Claim 12, Ao teaches a method for automated assessment and/or validation of a simulation model (Page 14, Sect. 5 Conclusion, “The methodology developed in this paper helps risk-informed decision making by providing quantitative information about the model reliability”; (Page 1, Sect. 1 Introduction) Model validation can be used for simulation models prior to implementation in practice to validate that the simulation model represents the physical system accurately), which is used to simulate measured values of a quantity that is defined by a fixed parameter and a varying parameter (Page 9, Sect. 4.1 Beam Under Stochastic Time-Varying Loads, Fig. 5 includes a simulation where deflection is the fixed parameter (Y-axis) and time is the varying parameter (X-axis)), the method comprising the following steps: determining multiple simulation values for the quantity using the simulation model (Page 9, Sect. 4.1.2 Results and Discussion, Fig. 5 gives several realizations of the simulation output, where these realizations are multiple simulation values for the quantity using the model in Eq. 29); determining multiple associated reference values for the quantity (Page 9, Sect. 4.1.2 Results and Discussion, "Figure 5 gives the time-dependent experimental output (bolded lines)" where the experimental output is the reference values for the quantity); determining, for each value of multiple values of the varying parameter, a model-form error (Page 3, Sect. 3.1 Model Reliability Metric, The model reliability metric quantifies the difference between model output and experimental data using a prediction error threshold decided by the decision maker; (Page 9, Sect. 4.1.2 Results and Discussion) Fig. 6 includes a reliability metric for each value of multiple values of time) as a deviation between the simulation value with respect to the value of the varying parameter, and the reference value with respect to the value of the varying parameter (Page 1, Abstract, The three reliability metrics "provide quantitative assessment regarding the agreement between the simulation model and experiment over time"; (Page 3, Sect. 3.1 Model Reliability Metric) The model reliability metric quantifies the difference between model output and experimental data); and determining, based on the model-form errors for the multiple values of the varying parameter, a function of the model-form error depending on the varying parameter (Page 4-5, Sect. 3.2.1 Instantaneous Reliability Metric, Eq. 6 is a function of one of the reliability metrics depending on time), and utilizing the determined function for the assessment and/or validation, of the simulation model, [[wherein each model-form error is determined using a modified area validation metric, in which the deviation between the simulation value and the reference value is determined individually for positive and negative deviations]] (Page 14, Sect. 5 Conclusion, “The methodology developed in this paper helps risk-informed decision making by providing quantitative information about the model reliability”; and (Page 1, Abstract) “This paper investigates quantitative approaches for the validation of dynamics models”).
Ao does not specifically teach, however Rashidi teaches [[determining, based on the model-form errors for the multiple values of the varying parameter, a function of the model-form error depending on the varying parameter, and utilizing the determined function for the assessment and/or validation, of the simulation model,]] wherein each model-form error is determined using a modified area validation metric, in which the deviation between the simulation value and the reference value is determined individually for positive and negative deviations, (Page 1447, Section III Case Study: Design Optimization of a Vienna-Type Rectifier, Table III shows the model-form error of total converter loss (εMF(W)) of simulations and experiments under several design configurations and Figures 10 and 11 graphically display the model-form error (red points and blue planes) under different, switching frequencies, inductances, and core sizes, (Page 1446, Section III Case Study: Design Optimization of a Vienna-Type Rectifier) where the model-form error is calculated using individually determined positive and negative deviations with the modified area validation metric as shown by Equation 6 and Figure 9).
Ao and Rashidi do not explicitly teach wherein the simulation values correspond to a plurality of curves including at least a first boundary curve and a second boundary curve, wherein the positive deviation is between the first boundary curve and at least one of the multiple associated reference values, andwherein the negative deviation is between the second boundary curve and at least one other of the multiple associated reference values.
Wang teaches wherein the simulation values correspond to a plurality of curves including at least a first boundary curve (Wang : Pg.061403-10 Col.1 & Fig.14 showing first boundary curve as model 1 (Fm1(y)) and a second boundary curve (Wang : Pg.061403-10 Col.1 & Fig.14 showing second boundary curve as model 2 (Fm2(y)), wherein the positive deviation is between the first boundary curve and at least one of the multiple associated reference values, and wherein the negative deviation is between the second boundary curve and at least one other of the multiple associated reference values (Wang: Positive deviation d+ and negative d-measured as in Fig.1(c); w.r.t to two model See Pg. 061403-4 Col.1- 061403-5 Col.1 stating "... For examples, two models, model 1 and 2, are available and their area difference intervals are calculated to be [d1L ; d1U] and [d2L; d2U, respectively...." which can be applied to Fig.14 with two curves as annotated below
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Compare this with Fig.1a of specification which maps to the claimed limitations)
Therefore, it would have been obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to add that model-form errors are determined using a modified area validation metric, as conceptually seen from the teaching of Rashidi, into that of Ao. Motivation to do so would have been to use the determined model-form errors to identify improvements needed in the system model that can reduce uncertainty (Rashidi, Page 1449, Section V Conclusion).
Therefore, it would have been obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to add that model-form errors are determined using plurality of simulated model curves compared to the measured (reference) values to form a modified area validation metric, as conceptually seen from the teaching of Wang applied to Rashidi, & Ao. Motivation to do so would have been to use the determined model-form errors to identify improvements needed in the system model that can reduce uncertainty (Wang: See Pg. 061403-4 Col.1- 061403-5 Col.1
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;Rashidi, Page 1449, Section V Conclusion).
Regarding Claim 13
Ao teaches the method as recited in claim 12, wherein the varying parameter is a time, so that the quantity is a time characteristic of the fixed parameter (Page 9, Sect. 4.1 Beam Under Stochastic Time-Varying Loads, The varying parameter in Fig. 5 is time, so that the output is a time characteristic of deflection).
Regarding Claim 14
Ao teaches the method as recited in claim 13, wherein the fixed parameter is predetermined by a signal, so that the quantity is a time characteristic of the signal (Page 9, Sect. 4.1 Beam Under Stochastic Time-Varying Loads, Fig. 5 shows the experimental and simulation output such that the deflection is predetermined by a signal and the output is a time characteristic of the deflection).
Regarding Claim 20
Regarding Claim 20, it is the system claim, having similar limitations of claim 12. Thus, claim 20 is also rejected under the similar rationale as cited in the rejection of claim 12.
Regarding Claim 21
Regarding Claim 21, it is the product claim, having similar limitations of claim 12. Thus, claim 21 is also rejected under the similar rationale as cited in the rejection of claim 12
Regarding Claim 22-243 (New)
Wang teaches wherein an interval-characterized epistemic input uncertainty determines a horizontal distance of the first boundary curve and the second boundary curve (Wang: In reference to Fig.14 Pg.061403-10 states:
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here the horizontal distance would be interval on x axis (y parameter) between the two model curves) .
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Claims 16 and 19 are rejected under 35 U.S.C. 103 as being unpatentable over Ao in view of Rashidi, in view of Wang, and in further view of Lenz et al. “Quantification and Evaluation of Parameter and Model Uncertainty for Passive and Active Vibration Isolation” (hereinafter “Lenz”).
Regarding Claim 16
Ao teaches the method as recited in claim 12, wherein the simulation model has at least one fixed and at least one varying model parameter, and (Page 9, Sect. 4.1 Beam Under Stochastic Time-Varying Loads, Table 1 shows for example a fixed model parameter of the length of the beam (L) and a varying parameter of a dimension of the beam cross section (a0)). Neither Ao nor Rashidi specifically teach, however Lenz teaches the simulation values have an uncertainty in the form of a probability distribution which reflects the varying model parameters (Page 142, Sect. 14.3.1 Quantification of Uncertainty with the Area Validation Metric, Fig 14.4(b) for example includes a probability distribution in the form of a CDF (solid blue line) where (Page 139, Sect. 14.2.3 Variation of the Input Parameters) “the parameter uncertainty results in the variation of the model’s output, the numerically simulated amplitude and the phase, (14.4) and (14.5), and in the variation of the experimentally measured output data from the test rig due to the varying parameters mass m, stiffness k, damping coefficient b and gain g according to Table 14.2”), and the reference values have an uncertainty in the form of a frequency distribution (Page 142, Sect. 14.3.1 Quantification of Uncertainty with the Area Validation Metric, The measured values have uncertainty reflected in Fig 14.4(b) for example shown by a cumulative frequency distribution (red solid line)).
Therefore, it’s obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to add a probability distribution of the simulation values that reflects the varying model parameters and add a frequency distribution of the reference values, as conceptually seen from the teaching of Lenz, into that of Ao because this modification allows for a comparison of parameter uncertainty between simulation and reference values, which can further validate that the simulation model is representative of the actual system (Lenz, Page 142, Sect. 14.3.1 Quantification of Uncertainty with the Area Validation Metric).
Regarding Claim 19
Ao teaches the method as recited in claim 12. Neither Ao nor Rashidi specifically teach, however Lenz teaches wherein a software product or a controller is virtualized or released using the assessed and/or validated, simulation model (Page 137, Sect. 14.2.2 Realization of the Test Rig, DSPACE and MATLAB/SIMULINK are used to realize the test rig that is used to validate the model introduced in Sect. 14.2.1).
Therefore, it’s obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to add that a software product or a controller is virtualized or released using the assessed and/or validated, simulation model as conceptually seen from the teaching of Lenz, into that of Ao because this modification of adding the use of MATLAB/SIMULINK for example, allows for the quick generation of several simulations where a wide range of varying model parameters, such as the beam cross dimensions in Ao, can be used, which allows for the validation of the model under uncertain conditions.
Claim 18 is rejected under 35 U.S.C. 103 as being unpatentable over Ao in view of Rashidi, in view of Wang, and in further view of Zhu et al. “Real-time yaw rate prediction based on a non-linear model and feedback compensation for vehicle dynamics control” (hereinafter “Zhu”).
Regarding Claim 18
Ao teaches the method as recited in claim 12. Neither XX nor XX specifically teach, however Zhu teaches wherein the quantity includes a time characteristic of a vehicle yaw rate (Page 1438, Verification test, Fig. 7(c) depicts model and measurement output where a vehicle yaw rate is represented as a characteristic of time), or a variation of an impact energy of a drill hammer, or a drying time of dishes in a dishwasher, or a variation of a no-load breakaway torque of a steering system, or a measured variable of a radar sensor.
Therefore, it’s obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to add wherein the quantity includes a time characteristic of a vehicle yaw rate as conceptually seen from the teaching of Zhu, into that of Ao because this modification further indicates the usefulness of time-domain model validation using the reliability metric by providing an additional example where the reliability metric can be used to validate the models contained in Zhu.
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Relevant Prior Art of Record (Previously cited)
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure:
Rashidi et al “On the Modeling and Design of Modular Multilevel Converters With Parametric and Model-Form Uncertainty Quantification” also teaches using the modified area validation metric to determine positive and negative deviations from simulation and experimental values for the peak dc-bus voltage under different conditions such as variable input voltage and load current.
Choudhary, Aniruddha, et al. "Probability bounds analysis applied to the Sandia verification and validation challenge problem." Journal of Verification, Validation and Uncertainty Quantification 1.1 (2016): 011003. Teaches MAVM technique applied to model validation. See Fig.2 and Fig.9.
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Communication
Any inquiry concerning this communication or earlier communications from the examiner should be directed to AKASH SAXENA whose telephone number is (571)272-8351. The examiner can normally be reached Mon-Fri, 7AM-3:30PM.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, RYAN 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.
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AKASH SAXENA
Primary Examiner
Art Unit 2188
/AKASH SAXENA/
Primary Examiner, Art Unit 2188
Tuesday, December 23, 2025
1 Choudhary, Aniruddha, et al. "Probability bounds analysis applied to the Sandia verification and validation challenge problem." Journal of Verification, Validation and Uncertainty Quantification 1.1 (2016): 011003.
Also see Rashidi and Wang prior arts as used in rejection for using the tool in specific practical applications as mathematical tool to assess models.
2 This is to address remarks Pg.7 about technological improvement. There are no computer components that are improved cited in the claim.
3 Choudhary, Aniruddha, et al. "Probability bounds analysis applied to the Sandia verification and validation challenge problem." Journal of Verification, Validation and Uncertainty Quantification 1.1 (2016): 011003. Fig.2 also shows An example of probability box (p-box) for a parameter (x) that is a mixture of both aleatory (random) and epistemic (lack of knowledge) uncertainty, and can be used in future rejections as alternate.