Assessment method, assessment device, and program

Abstract

To provide a method of performing a realistic criticality assessment without being overly conservative.SOLUTION: An assessment method is provided, comprising computing an effective multiplication factor multiple times by performing criticality computation while changing parameters used for criticality assessment, deriving a distribution of occurrence probabilities of the computed effective multiplication factors, and deriving criticality occurrence probability and added reactivity based on the distribution to derive a value obtained by multiplying the criticality occurrence probability and the added reactivity.SELECTED DRAWING: Figure 1

Description

[Technical Field]

[0001] The present disclosure relates to an evaluation method, an evaluation device, and a program. [Background technology]

[0002] Criticality assessments of fuel debris during decommissioning work and assessments of recriticality behavior are performed under conservative and strict conditions similar to those used for conventional power reactors and reprocessing facilities. While conventional assessment methods are appropriate from the perspective of criticality safety, they set overly conservative and unrealistic conditions when considered for practical application to the decommissioning phase (e.g., debris retrieval). Attempting to meet criticality safety standards using conventional assessment methods can make it difficult to implement criticality prevention equipment, such as boric acid water circulation systems. Therefore, streamlining criticality assessments—for example, quantitatively reflecting the low probability of criticality during debris retrieval—is required. Regarding the possibility that conventional criticality assessments may lead to overly conservative equipment requirements, Non-Patent Document 1, for example, discloses a method in which parameters related to criticality assessment are sampled, criticality calculations are performed using the continuous energy Monte Carlo method, and the calculation results (whether criticality occurs or not) are statistically processed. [Prior art documents] [Non-patent literature]

[0003] [Non-Patent Document 1] "Development of criticality control technology for fuel debris (30) Proposal of statistical criticality assessment method for Fukushima Daiichi Nuclear Power Plant", [Online], Atomic Energy Society of Japan, 2017 Autumn Conference, 2017, [Retrieved January 15, 2024], Internet<https: / / confit.atlas.jp / guide / event-img / aesj2017f / 2G17 / public / pdf?type=in> Summary of the Invention [Problem to be solved by the invention]

[0004] The method in Non-Patent Document 1 rationally (probabilistically) evaluates whether or not criticality will occur. However, when evaluating the magnitude of the impact of exposure after criticality occurs, it is necessary to consider not only whether or not criticality will occur, but also the magnitude of the impact when criticality occurs. There is a need for a method to rationally evaluate the impact of criticality by considering both the probability of criticality occurring and the magnitude of the impact when criticality occurs.

[0005] The present disclosure provides an evaluation method, an evaluation device, and a program that can solve the above problems. [Means for solving the problem]

[0006] The evaluation method disclosed herein is an evaluation method executed by a computer, and includes the steps of calculating the effective multiplication factor multiple times by performing criticality calculations while changing parameters used in criticality evaluation, calculating a distribution of the occurrence frequency of the calculated effective multiplication factors, and calculating the occurrence probability of criticality and added reactivity based on the distribution, and multiplying the occurrence probability by the added reactivity to calculate a value indicating the impact of criticality.

[0007] The evaluation device disclosed herein includes a means for calculating an effective multiplication factor multiple times by performing criticality calculations while changing parameters used in criticality evaluation, a means for calculating a distribution of the occurrence frequency of the calculated effective multiplication factor, and a means for calculating a criticality occurrence probability and an additive reactivity based on the distribution, and for calculating a value indicating the impact of criticality by multiplying the occurrence probability and the additive reactivity.

[0008] In addition, the program disclosed herein causes a computer to execute the steps of calculating the effective multiplication factor multiple times by performing criticality calculations while changing parameters used in criticality evaluation, calculating a distribution of the occurrence frequency of the calculated effective multiplication factor, and calculating the occurrence probability of criticality and the added reactivity based on the distribution, and multiplying the occurrence probability by the added reactivity to calculate a value indicating the impact of criticality. [Effects of the Invention]

[0009] According to the evaluation method, evaluation device, and program of the present disclosure, it is possible to evaluate the impact of criticality by taking into account the probability of criticality occurring and the magnitude of the impact when criticality occurs. [Brief explanation of the drawings]

[0010] [Figure 1] FIG. 1 is a block diagram illustrating an example of an evaluation device according to an embodiment. [Figure 2] FIG. 10 is a diagram illustrating an example of the relationship between criticality occurrence and the value of each parameter according to the embodiment. [Figure 3] FIG. 10 is a diagram illustrating an impact assessment of criticality according to the embodiment. [Figure 4] FIG. 1 is a diagram illustrating radiation exposure assessment according to an embodiment. [Figure 5] 10 is a flowchart illustrating an example of an evaluation process according to the embodiment. [Figure 6] FIG. 2 illustrates an example of a hardware configuration of an evaluation apparatus according to an embodiment. DETAILED DESCRIPTION OF THE INVENTION

[0011] <Embodiment> The evaluation device of the present disclosure will be described below with reference to FIGS. (composition) 1 is a block diagram showing an example of an evaluation device according to an embodiment. The evaluation device 10 performs realistic evaluation of the effects of criticality and radiation exposure in a light water reactor such as a PWR (Pressurized Water Reactor). The evaluation device 10 includes an input receiving unit 11, an evaluation unit 12, an output unit 13, and a storage unit 14.

[0012] The input receiving unit 11 receives information, instructions, and the like input using an input device such as a keyboard, a mouse, a touch panel, or a button. For example, the input receiving unit 11 receives input of information necessary for realistic criticality impact assessment and radiation exposure impact assessment. The input receiving unit 11 records the received information in the storage unit 14 and outputs it to the evaluation unit 12.

[0013] The evaluation unit 12 calculates an index value indicating the impact of criticality taking into account both the probability of criticality and the magnitude of the impact when criticality occurs, and evaluates the impact of radiation exposure based on the calculated index value. The evaluation unit 12 includes an impact evaluation unit 121 and an exposure amount evaluation unit 122. The impact evaluation unit 121 calculates the probability of criticality occurring and calculates an additive reactivity ρ indicating the magnitude of the impact when criticality occurs. The evaluation unit 12 then calculates a reasonable index value (impact I, described below) indicating the impact of criticality by multiplying the additive reactivity ρ by the probability of occurrence of criticality whose magnitude of impact is the additive reactivity ρ. Furthermore, the exposure amount evaluation unit 122 calculates the exposure amount based on the calculated index value. The calculated exposure amount is a realistic exposure amount that is not overly conservative and is based on a reasonable impact of criticality. Below, the method for calculating the impact and exposure amount will be described in detail.

[0014] The impact assessment unit 121 calculates the index value described above. An example of a method for calculating this index value will be described with reference to Figs. 2 and 3. Fig. 2 shows the relationship between the occurrence of criticality and three representative parameters related to the occurrence of criticality: the water-to-debris volume ratio, the structural material mixing ratio, and the debris composition. The impact assessment unit 121 creates multiple combinations of parameter values when these three parameters are changed within the range of values that each parameter can take (a conservative range of values). For example, if the combination of values for the water-to-debris volume ratio, structural material mixing ratio, and debris composition is represented as (x, y, z), and the minimum and maximum values that each parameter can take are represented as 0% and 100%, respectively, the impact assessment unit 121 will create combinations such as (0%, 0%, 0%), (0%, 0%, 100%), (0%, 100%, 0%), (100%, 0%, 0%), (0%, 100%, 100%), (100%, 100%, 100%), (0%, 50%, 50%), (50%, 50%, 50%), (100%, 50%, 0%), ... (for example, 1000 combinations will be created). The created parameter combinations become input parameters for criticality analysis codes such as MVP, a computer program that can simulate the state of the core and debris and evaluate the occurrence of criticality. The impact evaluation unit 121 inputs a certain created combination of parameters into the criticality analysis code and performs a criticality calculation to evaluate whether criticality occurs when the three parameters have set values, i.e., whether the effective multiplication factor exceeds 1.0. A rectangular parallelepiped 200 in FIG. 2 indicates the range of the three parameters when criticality occurs. The impact evaluation unit 121 performs a criticality calculation based on the criticality analysis code for each created combination of the three parameters and records the input values of the three parameters and the effective multiplication factor calculated by the criticality analysis code in association with each other in the storage unit 14. The impact evaluation unit 121 analyzes the relationship between the three parameters and the effective multiplication factor from the information on the values of the three parameters and the effective multiplication factor recorded in the storage unit 14, and derives, for example, a function or map that outputs the effective multiplication factor when the values of the three parameters (x, y, z) are input.

[0015] Next, the impact evaluation unit 121 creates a large number of combinations of the three parameter values. For example, the impact evaluation unit 121 randomly generates values for each parameter by generating random numbers for the water-to-debris volume ratio, the structural material mixture ratio, and the debris composition, and performs a process of combining the generated values thousands to tens of thousands of times or more. The impact evaluation unit 121 inputs the created combinations of the three parameter values into a derived function, map, etc., calculates the effective multiplication factor, and records the calculated value in the storage unit 14. This process allows thousands to tens of thousands of times or more to obtain effective multiplication factor values. The impact evaluation unit 121 organizes the number of times (occurrence frequency) that each value was calculated for each calculated effective multiplication factor value, and creates a distribution curve of the occurrence frequency of the effective multiplication factor, as shown in FIG. 3.

[0016] The vertical axis of the graph in Figure 3 represents the number of effective multiplication factor values (frequency of occurrence) included in the calculation results when the effective multiplication factor is calculated using randomly generated combinations of three parameter values, while the horizontal axis represents the effective multiplication factor value. Criticality occurs when the effective multiplication factor value exceeds 1.0. The value obtained by subtracting 1 from the effective multiplication factor value is called the additive reactivity ρ. The additive reactivity ρ indicates the magnitude of the impact on the occurrence of criticality, and the larger this value, the greater the impact on the environment. As shown in the figure, the additive reactivity ρ can take on various values depending on the effective multiplication factor value. For example, when the effective multiplication factor value is k1, the additive reactivity is ρ1, and when the effective multiplication factor value is k2, the additive reactivity is ρ2. ρ1 is a relatively small additive reactivity value. In contrast, ρ2 is a large additive reactivity value. In conventional criticality assessments and radiation exposure assessments, the additive reactivity ρ is often maximized using ρ2 to ensure safety. However, as shown in the figure, the frequency of occurrence of criticality resulting in additive reactivity ρ2 is very low (f2). In contrast, the frequency of occurrence of criticality resulting in additive reactivity ρ1 is f1, which is a large value compared to the probability of occurrence of criticality resulting in additive reactivity ρ2. In this embodiment, in order to realistically evaluate the impact of criticality, the additive reactivity ρ is multiplied by the occurrence probability p of criticality of a magnitude that results in additive reactivity ρ to calculate an index value (impact I) for evaluating the impact of criticality when it occurs. For example, the impact evaluation unit 121 converts the occurrence frequency f1 to the occurrence probability p1 and calculates the impact I1 of criticality resulting in additive reactivity ρ1 by multiplying the probability p1 by p1. Furthermore, the impact evaluation unit 121 converts the occurrence frequency f2 to the occurrence probability p2 and calculates the impact I2 of criticality resulting in additive reactivity ρ2 by multiplying the probability p2 by p2. Similarly, the impact evaluation unit 121 calculates the realistic impact I of criticality when the additive reactivity ρ takes another value (for example, ρ3) based on the distribution curve of FIG. 3. The impact evaluation unit 121 records the calculated multiple impacts I in the storage unit 14. The impact I indicates a realistic impact of criticality that takes into account the probability of such criticality occurring, in addition to the additive reactivity ρ that indicates the magnitude of the impact of criticality.

[0017] The radiation exposure assessment unit 122 calculates the radiation exposure based on the impact I calculated by the impact assessment unit 121. There are two types of radiation exposure assessment: (1) assessment of "worker exposure" and (2) assessment of "site boundary amount." In the following explanation, the radiation exposure refers to, for example, the radiation exposure of debris removal workers. The radiation exposure assessment unit 122 inputs dynamic characteristic parameters such as debris characteristics, heat generation amount, heat removal amount, and delayed neutron fraction, in addition to the impact I, into an analysis code such as PORCAS-F, which is a computer program that evaluates the radiation exposure impact in the event of criticality, to calculate the radiation exposure. Generally, the added reactivity ρ, rather than the impact I, is input into the analysis code that evaluates the radiation exposure impact. The analysis code that evaluates the radiation exposure impact calculates and outputs a larger radiation exposure as the added reactivity ρ increases, provided that other conditions are the same. Conventionally, analysis codes for evaluating radiation effects often input the additive reactivity ρ2 for the case where the effect is greatest to evaluate the radiation effects. However, evaluating radiation effects based on additive reactivity ρ2, which has an extremely low probability of occurrence, tends to result in an overly conservative evaluation. Therefore, in this embodiment, the radiation effects are evaluated using an impact I, which takes into account the occurrence frequency, as an input parameter instead of the additive reactivity ρ. For example, the radiation exposure assessment unit 122 reads multiple I values recorded in the storage unit 14, sets predetermined values for the other input parameters, and inputs the read I values into the analysis code one by one to calculate the radiation exposure each time. In other words, the radiation exposure assessment unit 122 calculates radiation exposures for the number of recorded impacts I. The relationship between the radiation exposure calculated by this process and the additive reactivity ρ is shown in the graph of FIG. 4. The vertical axis of the graph in FIG. 4 represents the radiation exposure calculated by the analysis code for evaluating radiation effects, and the horizontal axis represents the additive reactivity ρ. In conventional radiation exposure impact assessments, the radiation exposure is calculated using the most conservative ρ2, resulting in the radiation exposure e2 shown in Fig. 4. In contrast, in the radiation exposure impact assessment of the present application, the radiation exposure is calculated based on the influence I2 obtained by multiplying the additive reactivity ρ2 by the occurrence probability p2, and therefore the radiation exposure corresponding to the additive reactivity ρ2 is a value smaller than the radiation exposure e2 in conventional assessments ("radiation exposure e2 according to this embodiment illustrated in Fig. 4"). The evaluation result of the radiation exposure calculated based on a large number of influences I will be, for example, something like the curve illustrated in Fig. 4.The exposure dose in this example is the maximum value e1 on the curve shown in the figure, which is a smaller value than the evaluation result e2 obtained by the conventional method. The exposure dose e1 calculated by the evaluation method according to this embodiment is a realistic exposure dose that is not overly conservative, calculated based on the influence I of many realistic criticalities calculated by the above processing. By presenting the exposure dose e1, it can be explained that the realistic exposure dose is a smaller value than the exposure dose e2 obtained by the conventional method. Note that by using the influence I, it is possible to perform realistic exposure assessments that are not overly conservative not only for the evaluation of (1) "worker exposure" but also for the evaluation of (2) "site boundary dose."

[0018] The output unit 13 outputs the degree of influence I and the amount of exposure e evaluated by the evaluation unit 12 to a display device, an electronic file, or the like. The storage unit 14 stores various setting information, processing data during calculation, etc. The storage unit 14 also stores a criticality analysis code and an analysis code for evaluating the effects of radiation exposure.

[0019] (operation) Next, the operation of the evaluation device 10 will be described with reference to FIG. FIG. 5 is a flowchart illustrating an example of the evaluation process according to the embodiment. First, a user sets parameters related to the occurrence of criticality in the evaluation device 10 (step S1). Examples of parameters related to the occurrence of criticality include the water-to-debris volume ratio, the structural material mixing ratio, and the debris composition, as illustrated in FIG. 2. In addition to these, other parameters may be set, such as the debris's fragility (fracture energy and fuel debris hardness), debris particle size, the non-uniformity of the fragmented region, the fuel composition, the fuel arrangement, the moderation ratio, and non-homogeneity. The input receiving unit 11 receives the set parameters and records them in the storage unit 14. Next, the impact evaluation unit 121 calculates the relationship between the set parameter values and the effective multiplication factor (step S2). For example, the impact evaluation unit 121 sets various values for each of the set parameters and then inputs them into a criticality analysis code to perform a criticality calculation. The criticality analysis code performs a criticality calculation based on the input parameter values and outputs the effective multiplication factor, etc. The impact evaluation unit 121 derives a function or the like that indicates the relationship between the input parameter values and the effective multiplication factors calculated by the criticality analysis code. Next, the impact evaluation unit 121 calculates the frequency distribution of the effective multiplication factors (step S3). The impact evaluation unit 121 generates a large number of combinations of the values of the multiple parameters set in step S1 and inputs the generated combinations to the function derived in step S2. This results in a large number of effective multiplication factors. The impact evaluation unit 121 records the effective multiplication factors calculated by the function in the storage unit 14. Next, the impact evaluation unit 121 organizes the large number of effective multiplication factors recorded in the storage unit 14 by frequency and calculates a distribution curve of the occurrence frequency of the effective multiplication factors, as shown in FIG. 3.

[0020] Here, a function of the parameters and the effective multiplication factor is derived in step S2, and then the derived function is used to calculate a large number of effective multiplication factors for each combination of randomly generated parameter values.This is because the criticality calculation using the criticality analysis code places a heavy load on the calculation and requires a long time.The impact assessment unit 121 may instead generate a large number of combinations of the parameter values set in step S1, input each of the generated combinations into the criticality analysis code, and perform criticality calculations to calculate a large number of effective multiplication factors, thereby calculating the frequency distribution of the effective multiplication factors.

[0021] Next, the impact assessment unit 121 generates a large number of combinations of the additive reactivity ρ in the case where criticality occurs and the probability p of criticality occurring such that the additive reactivity ρ occurs, based on the frequency distribution calculated in step S3, and calculates an impact I for each of the generated combinations (step S4). When evaluating the magnitude of the impact of exposure after criticality occurs, it is necessary to simultaneously consider whether or not criticality occurs and the magnitude of the impact when criticality occurs. However, calculating the impact I makes it possible to evaluate from the perspective of "probability of reaching criticality occurrence x magnitude of impact when criticality occurs." The impact assessment unit 121 records the many calculated impacts I in the memory unit 14.

[0022] Next, the radiation exposure assessment unit 122 assesses the radiation exposure based on the impact I calculated in step S4 (step S5). For example, the radiation exposure assessment unit 122 reads out the impact I recorded in the storage unit 14 and inputs it into an analysis code for assessing the radiation exposure impact. The analysis code calculates and outputs the radiation exposure according to the impact I. The radiation exposure assessment unit 122 calculates the radiation exposure for each of the multiple impacts I recorded in the storage unit 14 using the analysis code for assessing the radiation exposure impact. The radiation exposure assessment unit 122 selects the largest value from the calculated radiation exposures and outputs it to the output unit 13. Next, the output unit 13 outputs the assessment result of the radiation exposure (step S6). The output unit 13 outputs the radiation exposure selected in step S5 to a display device or the like.

[0023] (effect) As described above, according to this embodiment, instead of the additive reactivity ρ (e.g., the additive reactivity ρ2 according to the conventional method shown in FIG. 4 ) that conservatively indicates the magnitude of the impact of criticality occurring, the probability of criticality and the impact of criticality occurring (the magnitude and impact of criticality) are statistically evaluated through multiple evaluations in which multiple parameters related to the occurrence of criticality are varied. The impact I is calculated by multiplying the magnitude of the impact of criticality occurring by the probability of criticality occurring, and the impact of radiation exposure is evaluated based on the impact I. This enables a realistic evaluation that takes into account both the probability of criticality occurring and the magnitude of the impact of criticality occurring, rather than an overly conservative evaluation result. For example, when the statistical probability of criticality is extremely low or the external impact (radiation exposure) at the time of criticality is extremely low, the evaluation method of this embodiment calculates a smaller radiation exposure than conventional methods, enabling debris retrieval work with relaxed constraints from the perspective of criticality safety. This also eliminates the need for the installation of excessive equipment to prevent criticality, contributing to rapid decommissioning work.

[0024] FIG. 6 is a diagram illustrating an example of a hardware configuration of the evaluation device. The computer 900 includes a CPU 901, a main memory device 902, an auxiliary memory device 903, an input / output interface 904, and a communication interface 905. The evaluation device 10 described above is implemented in the computer 900. The above-described functions are stored in the auxiliary memory device 903 in the form of a program. The CPU 901 reads the program from the auxiliary memory device 903, loads it into the main memory device 902, and executes the above-described processing in accordance with the program. The CPU 901 also allocates a storage area in the main memory device 902 in accordance with the program. The CPU 901 also allocates a storage area in the auxiliary memory device 903 for storing data being processed in accordance with the program.

[0025] Alternatively, a program for implementing all or part of the functions of the evaluation device 10 may be recorded on a computer-readable recording medium, and the program may be loaded into a computer system and executed to perform processing by each functional unit. The term "computer system" as used herein includes hardware such as an OS and peripheral devices. Furthermore, if a WWW system is used, the term "computer system" also includes a homepage provision environment (or display environment). Furthermore, the term "computer-readable recording medium" refers to portable media such as CDs, DVDs, and USBs, as well as storage devices such as hard disks built into the computer system. Furthermore, if the program is distributed to the computer 900 via a communication line, the computer 900 that receives the program may load the program into the main storage device 902 and execute the above-described processing. Furthermore, the program may be for implementing part of the above-described functions, or may be capable of implementing the above-described functions in combination with a program already stored in the computer system.

[0026] As described above, several embodiments according to the present disclosure have been described, but all of these embodiments are presented as examples and are not intended to limit the scope of the invention. These embodiments can be implemented in various other forms, and various omissions, substitutions, and modifications can be made without departing from the spirit of the invention. These embodiments and their modifications are included in the scope of the invention and its equivalents as defined in the claims, as well as in the scope and spirit of the invention.

[0027] <Additional Notes> The analysis method, evaluation device, and program described in the embodiments can be understood, for example, as follows.

[0028] (1) The evaluation method according to the first aspect is an evaluation method executed by a computer, and includes the steps of: calculating an effective multiplication factor multiple times by performing criticality calculations while changing parameters used in criticality evaluation; calculating a distribution of the occurrence frequency of the calculated effective multiplication factors; and calculating a criticality occurrence probability and an additional reactivity based on the distribution, and multiplying the occurrence probability by the additional reactivity to calculate a value indicating the impact of criticality. This allows us to simultaneously consider whether criticality will occur and the magnitude of the impact if criticality occurs, and to perform a realistic assessment of the impact of criticality without being overly conservative.

[0029] (2) The evaluation method according to the second aspect is the evaluation method of (1), wherein the step of calculating the effective multiplication factor multiple times includes the steps of: deriving a function showing the relationship between the parameter and the effective multiplication factor by performing critical calculations in which the value of the parameter is changed; and calculating multiple values that the parameter takes using random numbers, and calculating multiple effective multiplication factors based on the calculated values and the function. This reduces the calculation load for the effective multiplication factor.

[0030] (3) The evaluation method according to the third aspect is an evaluation method according to (1) to (2), further comprising a step of calculating the radiation exposure effect by inputting the value indicating the degree of impact into an analysis code that evaluates the radiation exposure effect. This allows for a realistic assessment of the effects of radiation exposure that is not overly conservative.

[0031] (4) The evaluation device according to the fourth aspect includes a means for calculating the effective multiplication factor multiple times by performing criticality calculations while changing parameters used in criticality evaluation, a means for calculating a distribution of the occurrence frequency of the calculated effective multiplication factor, and a means for calculating the occurrence probability of criticality and the additional reactivity based on the distribution, and for calculating a value indicating the impact of criticality by multiplying the occurrence probability by the additional reactivity. This allows us to simultaneously consider whether criticality will occur and the magnitude of the impact if criticality occurs, and to perform a realistic assessment of the impact of criticality without being overly conservative.

[0032] (5) A program according to a fifth aspect causes a computer to execute the steps of: calculating the effective multiplication factor multiple times by performing criticality calculations while changing parameters used in criticality assessment; calculating a distribution of the occurrence frequency of the calculated effective multiplication factor; and calculating the occurrence probability of criticality and the added reactivity based on the distribution, and multiplying the occurrence probability by the added reactivity to calculate a value indicating the impact of criticality. This allows us to simultaneously consider whether criticality will occur and the magnitude of the impact if criticality occurs, and to perform a realistic assessment of the impact of criticality without being overly conservative. [Explanation of symbols]

[0033] 10. Evaluation device 11 Input reception section 12. Evaluation section 121 Impact Assessment Section 122 Exposure Dose Assessment Section 13. Output section 14...Storage section 900···Computer 901 CPU 902...Main memory 903...Auxiliary storage device 904 Input / Output Interface 905···Communication Interface

Claims

1. 1. A computer-implemented evaluation method comprising: a step of calculating the effective multiplication factor multiple times by performing criticality calculations while changing parameters used in criticality evaluation; Calculating a distribution of occurrence frequencies of the calculated effective multiplication factors; calculating a criticality occurrence probability and an additional reactivity based on the distribution, and multiplying the occurrence probability by the additional reactivity to calculate a value indicating the impact of criticality; An evaluation method having the following characteristics.

2. The step of calculating the effective multiplication factor multiple times includes: deriving a function indicating the relationship between the parameter and the effective multiplication factor by performing criticality calculations while changing the value of the parameter; calculating a plurality of values that the parameter takes using random numbers, and calculating a plurality of effective multiplication factors based on the calculated values and the function; The evaluation method according to claim 1 , comprising:

3. a step of calculating the radiation exposure effect by inputting the value indicating the degree of effect into an analysis code for evaluating the radiation exposure effect; The evaluation method according to claim 1 or 2, further comprising:

4. a means for calculating the effective multiplication factor multiple times by performing criticality calculations while changing parameters used in criticality evaluation; a means for calculating a distribution of occurrence frequencies of the calculated effective multiplication factors; means for calculating a criticality occurrence probability and an additional reactivity based on the distribution, and for calculating a value indicating the influence of criticality by multiplying the occurrence probability by the additional reactivity; An evaluation device having the following:

5. On the computer, a step of calculating the effective multiplication factor multiple times by performing criticality calculations while changing parameters used in criticality evaluation; Calculating a distribution of occurrence frequencies of the calculated effective multiplication factors; calculating a criticality occurrence probability and an additional reactivity based on the distribution, and multiplying the occurrence probability by the additional reactivity to calculate a value indicating the impact of criticality; A program that executes the following.

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