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. 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and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114.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 08/22/2025 has been entered.
2. The amendment filed 05/22/2025 has been received and considered. Claims 1-17 are presented for examination.
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 1-17 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 13, they recite the limitation “estimate success or failure of the simulation” which is vague and indefinite since "success or failure " does not set a range.
As per Claim 1 and 13, they recite the limitation “termination condition is met” which is vague and indefinite since "termination condition" does not set a range.
As per Claim 6 and 17, it recites the limitation “until the estimated failure region satisfies the predetermined condition” which is vague and indefinite since it fails to define what the limitation “predefined condition” is therefore, the limitation “satisfies” does not set a range.
Allowable Subject Matter
4. Claim 1-17 are allowed.
5. The following is an examiner’s statement of reasons for allowance:
Wang et al. (US 20200327264 A1) discloses a calibration system/method for calibrating a model of dynamics of an industrial system (Fig. 3-5) that explains changes of a state of the industrial system in response to controlling the industrial system according to a sequence of control inputs to fit operational data indicative of measurements of an operation of the industrial system including values of the control inputs and corresponding values of the state of the industrial system ([0057] “the model can predict (e.g., via a neural network, or the like) a subset of parameters for model calibration and also predict/estimate optimal parameter values for the subset of parameters in association with a power system model that is being calibrated. According to the examples herein, the model may be used to capture both input-output function”, [0092]), the calibration system comprising: at least one processor (Fig. 14); and a memory having instructions stored thereon that, when executed by the at least one processor, cause the calibration system (Fig. 14) to:
simulate an operation of the industrial system multiple times, each simulation cycle includes execution of the model of the industrial system having different combinations of values of parameters selected within an admissible range of values of the parameters to estimate success or failure of the simulation ([0121] “V, f, P, and Q measurement data at a Point Of Interest (“POI”). At Step 410, a playback simulation may run load model benchmarking using default model parameters (e.g., associated with a Positive Sequence Load Flow (“PSLF”)”);
train a parameter-to-cost regressor for a probabilistic parameter-to-cost mapping between various combinations of different values of the parameters of the model of the industrial system and their corresponding calibration errors, wherein the parameter-to-cost regressor is trained ([0042], [0044], [0065], [0099] “Bayesian Optimization”) iteratively until a termination condition is met ([0042], [0044], [0065], [0080]-[0081], [0099], [0178]), and wherein to perform an iteration the at least one processor is configured to:
execute an acquisition function of a first two order moments of the calibration errors configured to identify a combination of parameters having maximum likelihood of minimizing the calibration errors according to the probabilistic parameter-to-cost mapping ([0042], [0044], [0065], [0080]-[0081], [0099], [0178] “acquisition function”);
update the identified combination of parameters with a … acquisition function adjusting the identified parameters …. to reduce the likelihood of the failure of the operation of the industrial system with the model having the updated parameters ([0178]);
simulate the operation of the industrial system controlled by the control inputs in the operational data with the model having the updated parameters to produce simulated states of the industrial system ([0165]); and
update the probabilistic parameter-to-cost mapping based on the updated parameters and calibration errors between the simulated states of the industrial system and corresponding states of the industrial system in the operational data ([0178]); and
calibrate, when the termination condition is met, the model of the industrial system with an optimal combination of the parameters having the largest likelihood of minimizing the calibration errors at the probabilistic parameter-to-cost mapping according to the acquisition function ([0042], [0044], [0065], [0080]-[0081], [0099], [0178]),
Wu et al. (“A Feature-Based Diagnosis Framework for Power Plant Model Validation” listed in IDS submitted on 11/29/2023) discloses a calibration method/system for calibrating a model of dynamics of an industrial system that explains changes of a state of the industrial system in response to controlling the industrial system according to a sequence of control inputs to fit operational data indicative of measurements of an operation of the industrial system including values of the control inputs and corresponding values of the state of the industrial system, the calibration method comprising: simulating an operation of the industrial system multiple times, each simulation cycle includes execution of the model of the industrial system having different combinations of values of parameters selected within an admissible range of values of the parameters to estimate success or failure of the simulation, training a failure classifier defining a likelihood of failure of the operation of the industrial system for the admissible range of values of parameters of the model using training data including the selected combinations of the values of the parameters labeled with the estimated success or failure of the simulation to determine the type of a power plant model problem, and
Want et al. (US 20200379424 A1) discloses a calibration system/method for calibrating a model of dynamics of an industrial system that explains changes of a state of the industrial system in response to controlling the industrial system according to a sequence of control inputs to fit operational data indicative of measurements of an operation of the industrial system including values of the control inputs and corresponding values of the state of the industrial system using Bayesian Optimization for parameter updating,
none of the prior art of record discloses a calibration system and method for calibrating an industrial system model using simulation failure including updating the identified combination of parameters with a failure-robust acquisition function adjusting the identified parameters according to the “failure classifier” to reduce the likelihood of the failure of the operation of the industrial system with the model having the updated parameters as disclosed in independent claims 1 and 13 of the instant application in combination with the remaining elements and features of the claimed invention.
In addition, neither reference uncovered that would have provided a basis of evidence for asserting a motivation, nor one of ordinary skilled in the art at the time the invention was made, knowing the teaching of the prior arts of record would have combined them to arrive at the present invention as recited in the context of independent claims 1 and 13 as a whole. Thus, independent claims 1 and 13 are allowed over the prior art of record.
Response to Arguments
6. Applicant's arguments filed 05/22/2025 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.
As per 112 rejection, applicants provided paragraphs in the specification for support with respect to the limitation “estimate success or failure of the simulation”, “termination condition is met” and "satisfies the predetermined condition" where the specification lists some examples. However, the claims fail to set/define specific ranges to ascertain the metes and bounds of the claimed invention. Thus 112 rejection maintains.
Conclusion
7. The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Ikonen et al. (“Calibration of physical models with process data using FIR filtering”) discloses an automatic calibration of physical plant models in the context of monitoring and control of industrial processes using estimated finite impulse response (FIR) filters with a data-driven mapping.
8. Any inquiry concerning this communication or earlier communications from the examiner should be directed to EUNHEE KIM whose telephone number is (571)272-2164. The examiner can normally be reached Monday-Friday 9am-5pm ET.
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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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EUNHEE KIM
Primary Examiner
Art Unit 2188
/EUNHEE KIM/Primary Examiner, Art Unit 2188