DETAILED ACTION
This office action is in response to communication filed on July 13, 2026.
Response to Amendment
Amendments filed on July 13, 2026 have been entered.
The specification has been amended.
Claims 1, 6, 9, 13, 15 and 19 have been amended.
Claims 1-20 have been examined.
Response to Arguments
Applicant’s arguments, see Remarks (p. 8), filed on 07/13/2026, with respect to the objections to the specification have been fully considered. In view of the amendments to the specification addressing the informalities raised in the previous office action, the objections to the specification have been withdrawn. However, upon further consideration, new objections to the specification are presented below to address additional informalities.
Applicant’s arguments, see Remarks (p. 8), filed on 07/13/2026, with respect to the objections to the claims have been fully considered. In view of the amendments to the claims addressing the informalities raised in the previous office action, the objections to the claims have been withdrawn. However, upon further consideration, a new objection to claim 15 is presented below to address additional informalities.
Applicant’s arguments, see Remarks (p. 8-19), filed on 07/13/2026, with respect to the rejection of claims 1-20 under 35 U.S.C. 101 have been fully considered but are not persuasive.
Applicant argues (p. 10) that The claims do not recite mathematical concepts as characterized by the MPEP. Rather than claiming a mathematical formula, equation, or calculation in the abstract, the claims recite a specific technical process for radiation consequence analysis. The claims require receiving input parameters “by a computing device” associated with “a rate of increase of a concentration of radioactivity,” a specific technical parameter tied to nuclear facility safety analysis. The claims further require sending sampled values “to a radiation dosage model configured to determine radiation dose consequences at one or more receptor locations” and determining dose values “by the radiation dosage model,” specific technical operations performed by a computational model, not abstract mathematical operations. Most significantly, the claims culminate in “generating [...] one or more design requirements associated with one or more features of a nuclear facility” and “causing the nuclear facility to operate within the one or more design requirements.” These limitations demonstrate that the claims are directed to a specific technical application in nuclear facility safety, not to mathematical concepts themselves. While the claims may involve or be based on mathematical concepts, the claims as a whole are not “directed to” mathematical concepts.
These arguments are not persuasive.
The examiner submits that, under the broadest reasonable interpretation in light of the specification, the claimed invention, when considered as a whole, recites data collection (i.e., receiving a plurality of input parameters associated with a rate of increase of a concentration of radioactivity, see also specification at [0026]-[0028]) and data manipulation using a series of mental processes and/or mathematical concepts (e.g., random sampling process, radiation dosage model, statistical analysis, see also specification at [0030], [0033], [0035]-[0036], [0039], [0042]-[0043], [0045]-[0047] and applicant’s arguments at p. 15 regarding the use of RADTRAD model) to determine additional information (i.e., a plurality of randomly samples values of the plurality of input parameters, radiation dose consequences at one or more receptor locations, a plurality of radiation dose values, an estimate of a radiation dose, a statistical uncertainty, one or more design requirements), while generally linking a field of use (e.g., radiation consequence analysis), adding extra-solution activities (e.g., mere data gathering, source/type of data, input data to a model), appending transformations recited at a high level of generality such that substantially all practical applications of the judicial exception(s) are covered (e.g., generating one or more design requirements associated with one or more features of a nuclear facility, wherein the one or more features are configured to reduce an accidental release of radioactivity; and causing the nuclear facility to operate within the one or more design requirements), and/or adding generic computer components used to facilitate the application of the judicial exception (i.e., a computing device), which under the current guidance is not patent eligible under 35 U.S.C. 101 (see rejection below).
Furthermore, the examiner submits that as indicated in the October 2019 Patent Eligibility Guidance Update:
“A claim that recites a mathematical calculation will be considered as falling within the “mathematical concepts” grouping. A mathematical calculation is a mathematical operation (such as multiplication) or an act of calculating using mathematical methods to determine a variable or number, e.g., performing an arithmetic operation such as exponentiation. There is no particular word or set of words that indicates a claim recites a mathematical calculation. That is, a claim does not have to recite the word “calculating” in order to be considered a mathematical calculation. For example, a step of “determining” a variable or number using mathematical methods or “performing” a mathematical operation may also be considered mathematical calculations when the broadest reasonable interpretation of the claim in light of the specification encompasses a mathematical calculation” (p. 4, section “iii. “Mathematical Calculations””, par. 1); and
“claims do recite a mental process when they contain limitations that can practically be performed in the human mind, including for example, observations, evaluations, judgments, and opinions” (p. 7-8).
Based on these guidelines, the examiner submits that the rejection indicated that the claimed invention recites limitations that fall under the “Mental Processes” and “Mathematical Concepts” groupings of Abstract Ideas (see rejection below).
Applicant also argues (p. 10-11) that The Examiner isolates individual limitations such as the “determining” steps, and by focusing on single elements in the claim, the Examiner fails to show how the claims as a whole could practically be performed in the mind … The claims require operations that are inseparable from computer-implemented data processing that exceed what a human could perform mentally, even with pen and paper … These limitations require specific technical operations performed by computing devices and radiation dosage models, and culminate in causing a nuclear facility to operate according to generated design requirements, operations that are fundamentally beyond human cognitive capabilities. The specification confirms that a computing device is necessary for these operations.
These arguments are not persuasive.
Regarding the argument about the examiner isolating individual limitations, the examiner submits that the claimed invention has been evaluated for patent eligibility under 35 U.S.C. 101 using the Office guidance which describes under Step 2A – Prong One: “A subject matter eligibility rejection should point to the specific claim limitation(s) that recites (i.e., sets forth or describes) the judicial exception” (see MPEP 2106.07(a), section I).
Regarding the argument about a computing device being necessary for the claimed operations, the examiner submits that as indicated in the MPEP:
“It is important to note that a general purpose computer that applies a judicial exception, such as an abstract idea, by use of conventional computer functions does not qualify as a particular machine … Merely adding a generic computer, generic computer components, or a programmed computer to perform generic computer functions does not automatically overcome an eligibility rejection” (see MPEP 2106.05(b)); and
“Use of a computer or other machinery in its ordinary capacity for economic or other tasks (e.g., to receive, store, or transmit data) or simply adding a general purpose computer or computer components after the fact to an abstract idea (e.g., a fundamental economic practice or mathematical equation) does not integrate a judicial exception into a practical application or provide significantly more … Similarly, “claiming the improved speed or efficiency inherent with applying the abstract idea on a computer” does not integrate a judicial exception into a practical application or provide an inventive concept” (see MPEP 2106.05(f), item 2).
Furthermore, applicant argues (p. 12-13) that the present claims integrate the alleged abstract idea into a practical application because the claims provide an improvement to technology and/or a technical field … A particular improvement is the reliable and accurate estimation of radiation dose consequences with quantified statistical uncertainty, enabling generation of more accurate design requirements for nuclear facility safety features.
These arguments are not persuasive.
The examiner submits that, as indicated above, the claimed invention seeks patent protection for a series of mental/mathematical steps used to manipulate data to obtain additional information, which according to the Office guidance: “For data, mere “manipulation of basic mathematical constructs [i.e.,] the paradigmatic ‘abstract idea,’” has not been deemed a transformation. CyberSource v. Retail Decisions, 654 F.3d 1366, 1372 n.2, 99 USPQ2d 1690, 1695 n.2 (Fed. Cir. 2011) (quoting In re Warmerdam, 33 F.3d 1354, 1355, 1360, 31 USPQ2d 1754, 1755, 1759 (Fed. Cir. 1994))” (see MPEP 2106.05(c)).
Additionally, the claimed invention appends steps/transformations at a high level of generality such that substantially all applications of the judicial exception are covered (e.g., generating one or more design requirements associated with one or more features of a nuclear facility, wherein the one or more features are configured to reduce an accidental release of radioactivity; and causing the nuclear facility to operate within the one or more design requirements), which according to the MPEP: “A transformation applied to a generically recited article or to any and all articles would likely not provide significantly more than the judicial exception” (see MPEP 2106.05(c)).
Applicant further argues (p. 14) that The claimed method takes a fundamentally different approach. Rather than deterministically selecting bounding values for all input parameters, the claims recite a specific combination of computational steps that provide more accurate dose estimates with quantified uncertainty, enabling generation of more accurate design requirements.
This argument is not persuasive.
The examiner submits that as described in the 2024 Guidance Update on Patent Subject Matter Eligibility, Including on Artificial Intelligence: “Even if the judicial exception is narrow (e.g., a particular mathematical formula or detailed mental process), the Court has held that a claim may not preempt that judicial exception” (see “III. Update on Certain Areas of the USPTO’s Patent Subject Matter Eligibility Guidance Applicable to AI Inventions”, section “A. Evaluation of Whether a Claim Is Directed to a Judicial Exception (Step 2A)”).
Also, the examiner submits that as explained in the October 2019 Update: Subject Matter Eligibility: “… in Parker v. Flook, the Court found that the claim recited a mathematical formula. This determination was not altered by the fact that the math was being used to solve an engineering problem (i.e., updating an alarm limit during catalytic conversion processes)” (see October 2019 Update: Subject Matter Eligibility, p. 3).
Applicant further argues (p. 15) that the claims recite “determining, based on the plurality of radiation dose values, an estimate of a radiation dose,” “determining a statistical uncertainty associated with the estimate of the radiation dose,” “generating, based on the estimate of the radiation dose and the statistical uncertainty, one or more design requirements associated with one or more features of a nuclear facility, wherein the one or more features are configured to reduce an accidental release of radioactivity,” and “causing the nuclear facility to operate within the one or more design requirements.” These limitations tie the computational output directly to a practical application: generating design requirements for nuclear facility safety features and causing the facility to operate within those requirements, and also argues (p. 16-17) that Amended claim 1 recites “generating, based on the estimate of the radiation dose and the statistical uncertainty, one or more design requirements associated with one or more features of a nuclear facility, wherein the one or more features are configured to reduce an accidental release of radioactivity” and “causing the nuclear facility to operate within the one or more design requirements.” The practical application is therefore expressly recited in the claim: the estimate and statistical uncertainty are used to generate design requirements for nuclear facility safety features, and the nuclear facility is caused to operate within those requirements. This is a concrete, real-world result that directly affects nuclear facility design and operation … Here, the present claims likewise recite an improved radiation consequence analysis method in which the combination of random sampling, radiation dosage model processing, statistical uncertainty determination, and generation of design requirements improves the functioning of the radiation consequence analysis system to provide more accurate dose estimates with quantified uncertainty, enabling more accurate design requirements for nuclear facility safety features.
These arguments are not persuasive.
The examiner submits that, as indicated above, the claimed invention when considered as a whole, seeks patent protection for a series of mental/mathematical steps used to manipulate data to obtain additional information, while appending steps/transformations at a high level of generality such that substantially all applications of the judicial exception are covered, however, based on the current guidance, such claims are not patent eligible under 35 U.S.C. 101.
In addition, applicant argues (p. 18) that The pending claims do not recite well-understood, routine, or conventional additional elements. For instance, the Examiner’s own prior art analysis acknowledges that the claimed features distinguish over the prior art of record.
This argument is not persuasive.
First, the examiner submits that the rejection did not rely on the well-understood, routine or conventional consideration.
Next, regarding the prior art analysis, the examiner submits that according to the current Office’s guidance: “The Supreme Court’s decisions make it clear that judicial exceptions need not be old or long-prevalent, and that even newly discovered or novel judicial exceptions are still exceptions. For example, the mathematical formula in Flook, the laws of nature in Mayo, and the isolated DNA in Myriad were all novel or newly discovered, but nonetheless were considered by the Supreme Court to be judicial exceptions because they were “‘basic tools of scientific and technological work’ that lie beyond the domain of patent protection.” Myriad, 569 U.S. 576, 589, 106 USPQ2d at 1976, 1978 (noting that Myriad discovered the BRCA1 and BRCA1 genes and quoting Mayo, 566 U.S. 71, 101 USPQ2d at 1965); Flook, 437 U.S. at 591-92, 198 USPQ2d at 198 (“the novelty of the mathematical algorithm is not a determining factor at all”); Mayo, 566 U.S. 73-74, 78, 101 USPQ2d 1966, 1968 (noting that the claims embody the researcher’s discoveries of laws of nature). The Supreme Court’s cited rationale for considering even “just discovered” judicial exceptions as exceptions stems from the concern that “without this exception, there would be considerable danger that the grant of patents would ‘tie up’ the use of such tools and thereby ‘inhibit future innovation premised upon them.’” Myriad, 569 U.S. at 589, 106 USPQ2d at 1978-79 (quoting Mayo, 566 U.S. at 86, 101 USPQ2d at 1971). See also Myriad, 569 U.S. at 591, 106 USPQ2d at 1979 (“Groundbreaking, innovative, or even brilliant discovery does not by itself satisfy the §101 inquiry.”). The Federal Circuit has also applied this principle, for example, when holding a concept of using advertising as an exchange or currency to be an abstract idea, despite the patentee’s arguments that the concept was “new”. Ultramercial, Inc. v. Hulu, LLC, 772 F.3d 709, 714-15, 112 USPQ2d 1750, 1753-54 (Fed. Cir. 2014). Cf. Synopsys, Inc. v. Mentor Graphics Corp., 839 F.3d 1138, 1151, 120 USPQ2d 1473, 1483 (Fed. Cir. 2016) (“a new abstract idea is still an abstract idea”) (emphasis in original)” (see MPEP 2106.04).
Specification
The disclosure is objected to because of the following informalities:
[0037]: Language “At step 208, the radiation does results may be evaluated …” should read “At step 208, the radiation dose results may be evaluated …” in order to correct minor informalities.
[0046]: Language “… For example, the estimate of the radiation does may be determined by the computing device 601…” should read “… For example, the estimate of the radiation dose may be determined by the computing device 601 …” in order to correct minor informalities.
Appropriate correction is required.
Claim Objections
Claim 15 is objected to because of the following informalities:
Claim language “determine, based on the plurality of radiation dose values an estimate of a radiation dose, wherein the estimate of the radiation dose is associated with a radiation release resulting from a postulated release of radioactivity” should read “determine, based on the plurality of radiation dose values, an estimate of a radiation dose, wherein the estimate of the radiation dose is associated with a radiation release resulting from a postulated release of radioactivity” in order to correct minor informalities (e.g., add comma).
Appropriate correction is required.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception without significantly more.
Regarding claim 1, the examiner submits that under Step 1 of the 2024 Guidance Update on Patent Subject Matter Eligibility, Including on Artificial Intelligence (see also 2019 Revised Patent Subject Matter Eligibility Guidance) for evaluating claims for eligibility under 35 U.S.C. 101, the claim is to a process, which is one of the statutory categories of invention.
Continuing with the analysis, under Step 2A - Prong One of the test (see italic text for abstract idea):
the limitation “determining, via a random sampling process, a plurality of randomly sampled values of the plurality of input parameters” is a process that, under its broadest reasonable interpretation in light of the specification, covers performance of the limitation using mathematical concepts to obtain data (i.e., a plurality of randomly sampled values of the plurality of input parameters, see specification at [0005]-[0006], [0029]-[0030], [0033]-[0035], [0039]-[0043], [0045]). The limitation in the context of the claim mainly refers to applying mathematical concepts to obtain data.
“sending the plurality of randomly sampled values to a radiation dosage model configured to determine radiation dose consequences at one or more receptor locations” is a process that, under its broadest reasonable interpretation in light of the specification, covers performance of the limitation using mathematical concepts to manipulate data and obtain additional information (i.e., radiation dose consequences at one or more receptor locations, see specification at [0006], [0025], [0030]-[0031], [0034]-[0036]). Except for the recitation of the extra-solution activities (e.g., inputting data into a model, source/type of data being evaluated) and/or the particular technological environment or field of use, the limitation in the context of the claim mainly refers to applying mathematical concepts to transform data.
“determining, by the radiation dosage model, based on the plurality of randomly sampled values, a plurality of radiation dose values” is a process that, under its broadest reasonable interpretation in light of the specification, covers performance of the limitation using mathematical concepts to manipulate data and obtain additional information (i.e., a plurality of radiation dose values, see specification at [0006], [0025], [0030]-[0031], [0034]-[0036]). Except for the recitation of the extra-solution activities (e.g., source/type of data being evaluated) and/or the particular technological environment or field of use, the limitation in the context of the claim mainly refers to applying mathematical concepts to transform data.
the limitation “determining, based on the plurality of radiation dose values, an estimate of a radiation dose, wherein the estimate of the radiation dose is associated with a radiation release resulting from a postulated release of radioactivity” is a process that, under its broadest reasonable interpretation in light of the specification, covers performance of the limitation using mental processes and/or mathematical concepts to manipulate data and obtain a result (i.e., an estimate of a radiation dose; see specification at [0006], [0025], [0031], [0035]-[0036], [0046]). Except for the recitation of the extra-solution activities (e.g., source/type of data being evaluated) and/or the particular technological environment or field of use, the limitation in the context of the claim mainly refers to performing a mental evaluation and/or applying mathematical concepts to manipulate data and obtain a result.
the limitation “determining a statistical uncertainty associated with the estimate of the radiation dose” is a process that, under its broadest reasonable interpretation in light of the specification, covers performance of the limitation using mental processes and/or mathematical concepts to manipulate data and obtain a result (i.e., a statistical uncertainty; see specification at [0025], [0036]-[0037], [0047]). Except for the recitation of the extra-solution activities (e.g., source/type of data being evaluated) and/or the particular technological environment or field of use, the limitation in the context of the claim mainly refers to performing a mental evaluation and/or applying mathematical concepts to manipulate data and obtain a result.
“generating, based on the estimate of the radiation dose and the statistical uncertainty, one or more design requirements associated with one or more features of a nuclear facility, wherein the one or more features are configured to reduce an accidental release of radioactivity” is a process that, under its broadest reasonable interpretation in light of the specification, covers performance of the limitation using mental processes and/or mathematical concepts to manipulate data and obtain additional information (i.e., one or more design requirements associated with one or more features; see specification at [0004], [0006], [0024]-[0025], [0028], [0031]-[0032], [0038]). Except for the recitation of the extra-solution activities (e.g., source/type of data being evaluated), steps recited at a high level of generality such that substantially all practical applications of the judicial exception(s) are covered (i.e., the one or more features are configured to reduce an accidental release of radioactivity), and/or the particular technological environment or field of use, the limitation in the context of the claim mainly refers to performing a mental evaluation and/or applying mathematical concepts to manipulate data and obtain additional information.
Therefore, the claim recites a judicial exception under Step 2A - Prong One of the test.
Furthermore, under Step 2A - Prong Two of the test, this judicial exception is not integrated into a practical application when considering the claim as a whole. In particular, the additional elements recited in the claim (see non-italic text for additional elements):
“receiving, by a computing device, a plurality of input parameters associated with a rate of increase of a concentration of radioactivity” adds extra-solution activities (e.g., mere data gathering, source/type of data to be manipulated; see specification at [0026]-[0028], [0044]) (see MPEP 2106.05(g)), generally links the use of the judicial exception to a particular technological environment or field of use (see MPEP 2106.05(h)); and adds the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea (see specification at [0004], [0021]-[0024], [0048]-[0051]) (see MPEP 2106.05(f));
“sending the plurality of randomly sampled values to a radiation dosage model configured to determine radiation dose consequences at one or more receptor locations” adds extra-solution activities (e.g., inputting data into a model, source/type of data being evaluated) (see MPEP 2106.05(g)) and generally links the use of the judicial exception to a particular technological environment or field of use (see MPEP 2106.05(h));
“generating, based on the estimate of the radiation dose and the statistical uncertainty, one or more design requirements associated with one or more features of a nuclear facility, wherein the one or more features are configured to reduce an accidental release of radioactivity” adds extra-solution activities (e.g., source/type of data being evaluated) (see MPEP 2106.05(g)), adds steps recited at a high level of generality such that substantially all practical applications of the judicial exception(s) are covered (see MPEP 2106.05(c)), and generally links the use of the judicial exception to a particular technological environment or field of use (see MPEP 2106.05(h)); and
“causing the nuclear facility to operate within the one or more design requirements” appends a transformation at a high level of generality such that substantially all practical applications of the judicial exception(s) are covered (see specification at [0004], [0006], [0024]-[0025], [0028], [0031]-[0032], [0038]; see also MPEP 2106.05(c)).
Accordingly, these additional elements, when considered individually and in combination, do not integrate the judicial exception into a practical application because they do not impose any meaningful limits on practicing the abstract idea when considering the claim as a whole. The claim is directed to a judicial exception under Step 2A of the test.
Additionally, under Step 2B of the test, the claim, when considered as a whole, does not include additional elements that, when considered individually and in combination, are sufficient to amount to significantly more than the judicial exception because the additional elements:
generally link the use of the judicial exception to a particular technological environment or field of use (e.g., radiation consequence analysis), which as indicated in the MPEP: “As explained by the Supreme Court, a claim directed to a judicial exception cannot be made eligible “simply by having the applicant acquiesce to limiting the reach of the patent for the formula to a particular technological use.” Diamond v. Diehr, 450 U.S. 175, 192 n.14, 209 USPQ 1, 10 n. 14 (1981). Thus, limitations that amount to merely indicating a field of use or technological environment in which to apply a judicial exception do not amount to significantly more than the exception itself, and cannot integrate a judicial exception into a practical application” (see MPEP 2106.05(h));
recite extra-solution activities (i.e., mere data gathering by selecting a particular data source/type to be manipulated, inputting data to a model), which as indicated in the MPEP: “Another consideration when determining whether a claim integrates the judicial exception into a practical application in Step 2A Prong Two or recites significantly more in Step 2B is whether the additional elements add more than insignificant extra-solution activity to the judicial exception. The term “extra-solution activity” can be understood as activities incidental to the primary process or product that are merely a nominal or tangential addition to the claim. Extra-solution activity includes both pre-solution and post-solution activity. An example of pre-solution activity is a step of gathering data for use in a claimed process” (see MPEP 2106.05(g));
append generic computer components (i.e., computing device) used to facilitate the application of the abstract idea (i.e., mere computer implementation), which as indicated in the MPEP: “Use of a computer or other machinery in its ordinary capacity for economic or other tasks (e.g., to receive, store, or transmit data) or simply adding a general purpose computer or computer components after the fact to an abstract idea (e.g., a fundamental economic practice or mathematical equation) does not provide significantly more” (see MPEP 2106.05(f));
append steps at a high level of generality such that substantially all practical applications of the judicial exception(s) are covered (i.e., causing the nuclear facility to operate within the one or more design requirements), which as indicated in the MPEP: “A transformation applied to a generically recited article or to any and all articles would likely not provide significantly more than the judicial exception” (see MPEP 2106.05(c)).
The claim, when considered as a whole, does not provide significantly more under Step 2B of the test.
Based on the analysis, the claim is not patent eligible.
Similarly, independent claims 9 and 15 are directed to a judicial exception (abstract idea) without significantly more as explained above with regards to claim 1 (see also MPEP 2106.05(f) regarding claims 9 and 15 reciting generic computer components used to facilitate the application of the judicial exception and therefore do not integrating the judicial exception into a practical application (Step 2A – Prong Two) and/or do not providing significantly more (Step 2B) when considering the claimed invention as a whole).
With regards to the dependent claims they are also directed to the non-statutory subject matter because:
they just extend the abstract idea of the independent claims by additional limitations (Claims 3-7, 11-13 and 17-19), that under the broadest reasonable interpretation in light of the specification, cover performance of the limitations using mental processes and/or mathematical concepts, and
the additional elements recited in the dependent claims, when considered individually and in combination, refer to extra-solution activities (e.g., mere data gathering using a data type or source), generic computer components and/or field of use (Claims 2, 8, 10, 14, 16 and 20), which as indicated in the Office’s guidance does not integrate the judicial exception into a practical application (Step 2A – Prong Two) and/or does not provide significantly more (Step 2B) when considering the claimed invention as a whole.
Subject Matter Not Rejected Over Prior Art
Claims 1-20 are distinguished over the prior art of record for the following reasons:
Regarding claim 1.
Yilmaz (US 20210149383 A1) discloses/teaches:
A method ([0005]-[0006], [0058]: a method for ascertaining catastrophic anomalies in a nuclear power plant based on scenario test data and using a neural network is presented (see also [0036])) comprising:
receiving, by a computing device (Fig. 1, item 102; [0039]: a computer is used for data processing), a plurality of input parameters associated with a rate of increase of a concentration of radioactivity ([0040], [0042], [0044]-[0045], [0058]: scenario data characterized by a set of observable parameters (plurality of input parameters) associated with offsite release of radionuclides (see [0037]; associated with a rate of increase of a concentration of radioactivity) is received);
determining a plurality of sampled values of the plurality of input parameters ([0041]-[0043]: part of the scenario data is generated using ADAPT system and MELCOR/RASCAL codes in order to obtain a wide range of scenarios (see also [0038], [0044])); and
determining an estimate of a radiation dose, wherein the estimate of the radiation dose is associated with a radiation release resulting from a postulated release of radioactivity ([0043]-[0045]: scenario data is analyzed in order to determine radiation dosage for each scenario (resulting from a postulated release of radioactivity) (see also [0054])).
Yilmaz (US 20210149383 A1) also discloses:
“An event tree (ET)/fault tree (FT) methodology may be traditionally used for PRA to account for uncertainties in accident progression. The ET may be used to model
the sequence of events to possible end states. When there is uncertainty in the occurrence of an event, the ET branches into two (or more) ETs where each ET follows the consequences associated with the uncertain event. For example, if a valve is designed to open when the pressure in the reactor vessel exceeds a pre-specified set point, the ET may need to follow the consequences of the valve opening or failing to open. The uncertainties associated with the events occurring or not occurring are estimated using FTs” ([0034]: event tree methodology is used by probabilistic risk assessment (PRA) to account for uncertainties by generating additional consequential branches).
Martin (US 20170177756 A1) discloses:
“In some example embodiments, the computing device may determine SSC parameters and uncertainties for construction design based on the assessment judgment 306, design envelope 310, and limiting scenario 318. In that regard, for example, a design envelope may have nominal values and uncertainties associated with the SSCs which have undergone the analysis above with an assessment judgment of excellent or reasonable, and SSC parameter values with nominal variance less than or equal to the
uncertainty may be determined for a construction design” ([0098]: a computing device may determine structure, system or component (SSC) parameters and uncertainties for construction design of a nuclear plant (see [0032]; see also [0008]; see further [0018] and [0034] regarding using limited scenarios for reducing computational load and faster processing instead of random sampling, and [0093] regarding using Monte-Carlo sampling approach for a particular random sample)).
Liu (US 20190369273 A1, IDS reference) discloses:
“In accordance with one broad aspect of the teachings disclosed herein, a system for monitoring ionizing radiation in a target area may include a first plurality of consumable nodes deployable within the target area to be exposed to the ionizing radiation. Each consumable node may be progressively damageable over a monitoring time as a result of exposure to the ionizing radiation. A plurality of resilient nodes may be deployable within the target area amongst the consumable nodes to be exposed to the ionizing radiation. Each resilient node may be progressively damageable over the monitoring time as a result of exposure to the ionizing radiation at a slower rate than the consumable nodes. A base station may be communicably linked to the consumable nodes and may be operable to detect an amount of radiation damage sustained by the consumable nodes and to determine a dosage of ionizing radiation received by any
one of the consumable nodes based on a pre-determined correlation between the dosage of ionizing radiation and the amount of radiation damage sustained by the consumable
node” ([0006]: ionizing radiation amount is monitored using consumable nodes and resilient nodes randomly placed in a target area by detecting amount of radiation damage sustained by consumable nodes and using a pre-determined correlation (see also [0127], [0138]-[0139])).
Kim (KR 20200086862 A, see translation) discloses:
“The present invention relates to a method for predicting a radiation exposure dose using gate simulation, which comprises the following steps of: measuring an initial exposure dose from an input original image; receiving condition information input from a user terminal; predicting an experimental value using the gate simulation based on the received condition information; and comparing the predicted experimental value with the initial exposure dose to extract error information” (Abstract: radiation exposure prediction of a patient is achieved by measuring initial exposure dose from original image and receiving condition information for performing a gate simulation (see p. 4, par. 6 regarding gate simulation being used in medical imaging and radiation therapy for random sampling) in order to predict an experimental value for comparison with the initial exposure dose to extract error information).
The closest prior art of record, taken individually or in combination, fail to teach or suggest (see italic text):
“determining, via a random sampling process, a plurality of randomly sampled values of the plurality of input parameters;
sending the plurality of randomly sampled values to a radiation dosage model configured to determine radiation dose consequences at one or more receptor locations;
determining, by the radiation dosage model, based on the plurality of randomly sampled values, a plurality of radiation dose values;
determining, based on the plurality of radiation dose values, an estimate of a radiation dose
determining a statistical uncertainty associated with the estimate of the radiation dose;
generating, based on the estimate of the radiation dose and the statistical uncertainty, one or more design requirements associated with one or more features of a nuclear facility, wherein the one or more features are configured to reduce an accidental release of radioactivity; and
causing the nuclear facility to operate within the one or more design requirements” (examiner notes that the prior art of record in general estimates an amount of radiation exposure based on measured/simulated data, without determining statistical uncertainties associated with the estimate and without using random sampling process for determining randomly sampled values of input parameters)
in combination with all other limitations within the claim, as claimed and defined by the applicant.
Regarding claim 9.
Yilmaz (US 20210149383 A1) discloses/teaches:
An apparatus (Fig. 1, item 102 – ‘tool’; [0005]-[0006], [0039], [0058]: a tool is used to implement a method for ascertaining catastrophic anomalies in a nuclear power plant based on scenario test data and using a neural network is presented (see also [0036])) comprising:
one or more processors (Fig. 1, item 106 – “processing unit”; [0040]: a computer tool includes a processing unit); and
a memory (Fig. 1, item 104 – ‘memory’) storing processor-executable instructions that, when executed by the one or more processors ([0039]: the computer includes memory storing data and machine-readable instructions), cause the apparatus to:
receive a plurality of input parameters associated with a rate of increase of a concentration of radioactivity ([0040], [0042], [0044]-[0045], [0058]: scenario data characterized by a set of observable parameters (plurality of input parameters) associated with offsite release of radionuclides (see [0037]; associated with a rate of increase of a concentration of radioactivity) is received);
determine a plurality of sampled values of the plurality of input parameters ([0041]-[0043]: part of the scenario data is generated using ADAPT system and MELCOR/RASCAL codes in order to obtain a wide range of scenarios (see also [0038], [0044])); and
determine an estimate of a radiation dose, wherein the estimate of the radiation dose is associated with a radiation release resulting from the postulated release of radioactivity ([0043]-[0045]: scenario data is analyzed in order to determine radiation dosage for each scenario (resulting from a postulated release of radioactivity) (see also [0054])).
Yilmaz (US 20210149383 A1) also discloses:
“An event tree (ET)/fault tree (FT) methodology may be traditionally used for PRA to account for uncertainties in accident progression. The ET may be used to model
the sequence of events to possible end states. When there is uncertainty in the occurrence of an event, the ET branches into two (or more) ETs where each ET follows the consequences associated with the uncertain event. For example, if a valve is designed to open when the pressure in the reactor vessel exceeds a pre-specified set point, the ET may need to follow the consequences of the valve opening or failing to open. The uncertainties associated with the events occurring or not occurring are estimated using FTs” ([0034]: event tree methodology is used by probabilistic risk assessment (PRA) to account for uncertainties by generating additional consequential branches).
Martin (US 20170177756 A1) discloses:
“In some example embodiments, the computing device may determine SSC parameters and uncertainties for construction design based on the assessment judgment 306, design envelope 310, and limiting scenario 318. In that regard, for example, a design envelope may have nominal values and uncertainties associated with the SSCs which have undergone the analysis above with an assessment judgment of excellent or reasonable, and SSC parameter values with nominal variance less than or equal to the
uncertainty may be determined for a construction design” ([0098]: a computing device may determine structure, system or component (SSC) parameters and uncertainties for construction design of a nuclear plant (see [0032]; see also [0008]; see further [0018] and [0034] regarding using limited scenarios for reducing computational load and faster processing instead of random sampling, and [0093] regarding using Monte-Carlo sampling approach for a particular random sample)).
Liu (US 20190369273 A1, IDS reference) discloses:
“In accordance with one broad aspect of the teachings disclosed herein, a system for monitoring ionizing radiation in a target area may include a first plurality of consumable nodes deployable within the target area to be exposed to the ionizing radiation. Each consumable node may be progressively damageable over a monitoring time as a result of exposure to the ionizing radiation. A plurality of resilient nodes may be deployable within the target area amongst the consumable nodes to be exposed to the ionizing radiation. Each resilient node may be progressively damageable over the monitoring time as a result of exposure to the ionizing radiation at a slower rate than the consumable nodes. A base station may be communicably linked to the consumable nodes and may be operable to detect an amount of radiation damage sustained by the consumable nodes and to determine a dosage of ionizing radiation received by any
one of the consumable nodes based on a pre-determined correlation between the dosage of ionizing radiation and the amount of radiation damage sustained by the consumable
node” ([0006]: ionizing radiation amount is monitored using consumable nodes and resilient nodes randomly placed in a target area by detecting amount of radiation damage sustained by consumable nodes and using a pre-determined correlation (see also [0127], [0138]-[0139])).
Kim (KR 20200086862 A, see translation) discloses:
“The present invention relates to a method for predicting a radiation exposure dose using gate simulation, which comprises the following steps of: measuring an initial exposure dose from an input original image; receiving condition information input from a user terminal; predicting an experimental value using the gate simulation based on the received condition information; and comparing the predicted experimental value with the initial exposure dose to extract error information” (Abstract: radiation exposure prediction of a patient is achieved by measuring initial exposure dose from original image and receiving condition information for performing a gate simulation (see p. 4, par. 6 regarding gate simulation being used in medical imaging and radiation therapy for random sampling) in order to predict an experimental value for comparison with the initial exposure dose to extract error information).
The closest prior art of record, taken individually or in combination, fail to teach or suggest (see italic text):
“determine, via a random sampling process, a plurality of randomly sampled values of the plurality of input parameters; and
send the plurality of randomly sampled values to a radiation dosage model configured to determine radiation dose consequences at one or more receptor locations;
determine, by the radiation dosage model, based on the plurality of randomly sampled values, a plurality of radiation dose values;
determine, based on the plurality of radiation dose values, an estimate of a radiation dose;
determine a statistical uncertainty associated with the estimate of the radiation dose;
generate, based on the estimate of the radiation dose and the statistical uncertainty, one or more design requirements associated with one or more features of a nuclear facility, wherein the one or more features are configured to reduce an accidental release of radioactivity; and
cause the nuclear facility to operate within the one or more design requirements” (examiner notes that the prior art of record in general estimates an amount of radiation exposure based on measured/simulated data, without determining statistical uncertainties associated with the estimate and without using random sampling process for determining randomly sampled values of input parameters)
in combination with all other limitations within the claim, as claimed and defined by the applicant.
Regarding claim 15.
Yilmaz (US 20210149383 A1) discloses/teaches:
A non-transitory computer-readable medium (Fig. 1, item 104 – ‘memory’) storing processor-executable instructions ([0039]: a computer tool (see Fig. 1, item 102) includes memory storing data and machine-readable instructions to implement a method for ascertaining catastrophic anomalies in a nuclear power plant based on scenario test data and using a neural network is presented (see [0005]-[0006], [0036], [0058])) that, when executed by at least one processor (Fig. 1, item 106 – “processing unit”; [0040]: computer tool includes a processing unit), cause the at least one processor to:
receive, by a computing device (Fig. 1, item 102; [0039]: a computer is used for data processing), a plurality of input parameters associated with a source term of a postulated release of radioactivity ([0040], [0042], [0044]-[0045], [0058]: scenario data characterized by a set of observable parameters (plurality of input parameters) associated with offsite release of radionuclides (see [0037]; associated with a rate of increase of a concentration of radioactivity) is received);
determine, via a random sampling process, a plurality of randomly sampled values of the plurality of input parameters ([0041]-[0043]: part of the scenario data is generated using ADAPT system and MELCOR/RASCAL codes in order to obtain a wide range of scenarios (see also [0038], [0044])); and
determine an estimate of a radiation dose, wherein the estimate of the radiation dose is associated with a radiation release resulting from a postulated release of radioactivity ([0043]-[0045]: scenario data is analyzed in order to determine radiation dosage for each scenario (resulting from a postulated release of radioactivity) (see also [0054])).
Yilmaz (US 20210149383 A1) also discloses:
“An event tree (ET)/fault tree (FT) methodology may be traditionally used for PRA to account for uncertainties in accident progression. The ET may be used to model
the sequence of events to possible end states. When there is uncertainty in the occurrence of an event, the ET branches into two (or more) ETs where each ET follows the consequences associated with the uncertain event. For example, if a valve is designed to open when the pressure in the reactor vessel exceeds a pre-specified set point, the ET may need to follow the consequences of the valve opening or failing to open. The uncertainties associated with the events occurring or not occurring are estimated using FTs” ([0034]: event tree methodology is used by probabilistic risk assessment (PRA) to account for uncertainties by generating additional consequential branches).
Martin (US 20170177756 A1) discloses:
“In some example embodiments, the computing device may determine SSC parameters and uncertainties for construction design based on the assessment judgment 306, design envelope 310, and limiting scenario 318. In that regard, for example, a design envelope may have nominal values and uncertainties associated with the SSCs which have undergone the analysis above with an assessment judgment of excellent or reasonable, and SSC parameter values with nominal variance less than or equal to the
uncertainty may be determined for a construction design” ([0098]: a computing device may determine structure, system or component (SSC) parameters and uncertainties for construction design of a nuclear plant (see [0032]; see also [0008]; see further [0018] and [0034] regarding using limited scenarios for reducing computational load and faster processing instead of random sampling, and [0093] regarding using Monte-Carlo sampling approach for a particular random sample)).
Liu (US 20190369273 A1, IDS reference) discloses:
“In accordance with one broad aspect of the teachings disclosed herein, a system for monitoring ionizing radiation in a target area may include a first plurality of consumable nodes deployable within the target area to be exposed to the ionizing radiation. Each consumable node may be progressively damageable over a monitoring time as a result of exposure to the ionizing radiation. A plurality of resilient nodes may be deployable within the target area amongst the consumable nodes to be exposed to the ionizing radiation. Each resilient node may be progressively damageable over the monitoring time as a result of exposure to the ionizing radiation at a slower rate than the consumable nodes. A base station may be communicably linked to the consumable nodes and may be operable to detect an amount of radiation damage sustained by the consumable nodes and to determine a dosage of ionizing radiation received by any
one of the consumable nodes based on a pre-determined correlation between the dosage of ionizing radiation and the amount of radiation damage sustained by the consumable
node” ([0006]: ionizing radiation amount is monitored using consumable nodes and resilient nodes randomly placed in a target area by detecting amount of radiation damage sustained by consumable nodes and using a pre-determined correlation (see also [0127], [0138]-[0139])).
Kim (KR 20200086862 A, see translation) discloses:
“The present invention relates to a method for predicting a radiation exposure dose using gate simulation, which comprises the following steps of: measuring an initial exposure dose from an input original image; receiving condition information input from a user terminal; predicting an experimental value using the gate simulation based on the received condition information; and comparing the predicted experimental value with the initial exposure dose to extract error information” (Abstract: radiation exposure prediction of a patient is achieved by measuring initial exposure dose from original image and receiving condition information for performing a gate simulation (see p. 4, par. 6 regarding gate simulation being used in medical imaging and radiation therapy for random sampling) in order to predict an experimental value for comparison with the initial exposure dose to extract error information).
The closest prior art of record, taken individually or in combination, fail to teach or suggest (see italic text):
“determine, via a random sampling process, a plurality of randomly sampled values of the plurality of input parameters;
send the plurality of randomly sampled values to a radiation dosage model configured to determine radiation dose consequences at one or more receptor locations;
determine, by the radiation dosage model, based on the plurality of randomly sampled values, a plurality of radiation dose values;
determine, based on the plurality of radiation dose values, an estimate of a radiation dose;
determine a statistical uncertainty associated with the estimate of the radiation dose;
generate, based on the estimate of the radiation dose and the statistical uncertainty, one or more design requirements associated with one or more features of a nuclear facility, wherein the one or more features are configured to reduce an accidental release of radioactivity; and
cause the nuclear facility to operate within the one or more design requirements” (examiner notes that the prior art of record in general estimates an amount of radiation exposure based on measured/simulated data, without determining statistical uncertainties associated with the estimate and without using random sampling process for determining randomly sampled values of input parameters)
in combination with all other limitations within the claim, as claimed and defined by the applicant.
Regarding claims 2-8, 10-14 and 16-20.
They are also distinguished over the prior art of record due to their dependency.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Helton, Jon C., and A. W. Shiver. “A Monte Carlo procedure for the construction of complementary cumulative distribution functions for comparison with the EPA release limits for radioactive waste disposal.” Risk Analysis 16.1 (1996): 43-55.
Reference discloses use of Monte-Carlo analysis for determining cumulative distribution functions for comparison to EPA release limits for radioactive waste disposal.
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.
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/LINA CORDERO/Primary Examiner, Art Unit 2857
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