WO2021014820A1 - Nuclear characteristic predicting method and nuclear characteristic predicting apparatus - Google Patents

Nuclear characteristic predicting method and nuclear characteristic predicting apparatus Download PDF

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WO2021014820A1
WO2021014820A1 PCT/JP2020/023414 JP2020023414W WO2021014820A1 WO 2021014820 A1 WO2021014820 A1 WO 2021014820A1 JP 2020023414 W JP2020023414 W JP 2020023414W WO 2021014820 A1 WO2021014820 A1 WO 2021014820A1
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nuclear
constant
core
reactor
calculation
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PCT/JP2020/023414
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French (fr)
Japanese (ja)
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晃一 家山
友樹 竹本
雅文 松井
耕司 浅野
啓基 小池
健太郎 田中
大介 左藤
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三菱重工業株式会社
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    • G—PHYSICS
    • G21—NUCLEAR PHYSICS; NUCLEAR ENGINEERING
    • G21C—NUCLEAR REACTORS
    • G21C17/00—Monitoring; Testing ; Maintaining
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
    • Y02E30/00—Energy generation of nuclear origin
    • Y02E30/30—Nuclear fission reactors

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  • the present invention relates to a nuclear characteristic prediction method and a nuclear characteristic prediction device for predicting the nuclear characteristics of a nuclear reactor.
  • the calculation is divided into two stages, the aggregate calculation in the first stage and the core calculation in the second stage.
  • the aggregate calculation uses the micro cross-sections of various nuclides as input values and performs various calculations in consideration of the detailed space and energy dependence of the neutron flux to obtain a homogenized nuclear constant (macrocross-section). Calculated as an output value.
  • the nuclear constant calculated in the aggregate calculation is used as an input value, and the core characteristics are calculated as an output value by performing the calculation in consideration of the fuel system of the core.
  • the core characteristics are predicted by performing the core calculation using the nuclear constants.
  • the nuclear characteristics as the analysis result are approximated to the measurement results of the nuclear characteristics measured by the measuring device provided in the core to improve the reproducibility.
  • a method for adjusting the nuclear constant data assimilation method
  • the core calculation is performed after the aggregate calculation is performed using the adjusted micro cross-sectional area. The characteristics will be calculated.
  • the micro covariance data which is the data related to the uncertainty of the micro cross-sectional area, is also adjusted. Therefore, the nuclear characteristics based on the adjusted micro covariance data Uncertainty can be evaluated.
  • Non-Patent Document 1 since it is necessary to perform a huge amount of aggregate calculation, the calculation cost increases by the amount of performing the aggregate calculation.
  • the aggregate calculation takes into consideration the detailed space and energy dependence of the neutron flux, so that the calculation load is large and the calculation cost is large as compared with the core calculation.
  • the method for predicting nuclear characteristics of the present invention corresponds to a step of measuring the nuclear characteristics of the reactor that changes due to the operation of fluctuations in the core output of the reactor and acquiring a measured value of the change in the nuclear characteristics, and the measured values.
  • a step of calculating the calculated value of the nuclear characteristic to be performed by performing the core calculation using the nuclear constant before correction, and the perturbation data of the nuclear constant prepared based on the macro covariance data prepared in advance A step of acquiring a plurality of the nuclear characteristics by perturbing the nuclear constants and performing a core calculation, calculating sensitivity data based on the acquired plurality of the acquired nuclear characteristics, and the calculated value so as to reproduce the measured value.
  • the step of calculating the correction amount of the nuclear constant based on the sensitivity data and the nuclear constant corrected by the correction amount the change in the nuclear characteristics of the reactor changed by the next core output fluctuation operation. Includes steps to predict.
  • the nuclear characteristic prediction device of the present invention is a nuclear characteristic prediction device including a control unit for predicting the nuclear characteristics of the reactor that changes due to the core output fluctuation operation of the nuclear reactor, and the control unit is the core of the nuclear reactor.
  • the step of measuring the nuclear characteristics of the reactor that changes due to the output fluctuation operation and acquiring the measured value of the change in the nuclear characteristics, and the calculated value of the nuclear characteristics corresponding to the measured values are the nuclear constants before correction.
  • the step of calculating the above and the step of predicting the change in the nuclear characteristics of the reactor that will change in the next core output fluctuation operation by using the nuclear constant corrected by the correction amount are executed.
  • FIG. 1 is a schematic configuration diagram schematically showing a covariance data creation device according to the present embodiment.
  • FIG. 2 is a schematic configuration diagram schematically showing the core analysis apparatus according to the present embodiment.
  • FIG. 3 is an explanatory diagram relating to the prediction of nuclear characteristics according to the present embodiment.
  • FIG. 4 is a flowchart relating to the creation of macro covariance data.
  • FIG. 5 is a flowchart relating to the correction of the nuclear constant.
  • FIG. 6 is a graph of N-January core characteristics.
  • FIG. 7 is a graph relating to the core characteristics of the N month.
  • the nuclear characteristics of the nuclear reactor are predicted periodically.
  • macro-covariance data is created in advance, and perturbation data of nuclear constants created based on the macro-covariance data is created.
  • the macro covariance data is created by the covariance data creation device shown in FIG. First, the covariance data creation device will be described with reference to FIG.
  • FIG. 1 is a schematic configuration diagram schematically showing a covariance data creation device according to the present embodiment.
  • the covariance data creation device 10 is a first input composed of a first calculation unit 11 capable of executing various programs and performing calculations, a first storage unit 12 for storing various programs and data, and an input device such as a keyboard. It has a unit 13 and a first output unit 14 composed of an output device such as a monitor.
  • the covariance data creation device 10 may be composed of a single device, a device integrated with the core analysis device 20 described later, or a plurality of devices in which a calculation device, a data server, and the like are combined. It may be, and is not particularly limited.
  • a nuclear constant calculation code C1 used for calculating a nuclear constant (macro cross-sectional area) and a covariance data creation program used for creating macro covariance data.
  • P1 is stored.
  • data for example, a cross-sectional area library that summarizes the cross-sectional areas, a macro cross-sectional area calculated by aggregate calculation, and macro covariance data calculated based on the macro cross-sectional area are stored in the first storage unit 12. And are remembered including.
  • FIG. 2 is a schematic configuration diagram schematically showing the core analyzer.
  • the core analysis device 20 functions as a nuclear characteristic prediction device that predicts the nuclear characteristics of the core by performing core analysis using macrocovariance data.
  • the core analysis device 20 is a second input unit 23 composed of a second calculation unit 21 capable of executing various programs and performing calculations, a second storage unit 22 for storing various programs and data, and an input device such as a keyboard.
  • a second output unit 24 composed of an output device such as a monitor.
  • the core analysis device 20 may be configured as a single device, or may be integrated with the covariance data creation device 10, like the covariance data creation device 10, a calculation device, a data server, or the like. It may be composed of a plurality of devices in which
  • the core calculation code C2 used for calculating the nuclear characteristics and the nuclear constant (macro cross-sectional area) used as an input value for the core calculation are corrected.
  • the number correction program P2 is stored.
  • data for example, sensitivity data which is data related to a change in nuclear characteristics due to a change in macrocross section, and nuclear characteristic measurement data measured by a measuring device for measuring nuclear characteristics. , Data on the amount of correction for correcting the nuclear constant, and stored.
  • FIG. 3 is an explanatory diagram relating to the prediction of nuclear characteristics according to the present embodiment. Prediction of nuclear properties is performed on a regular basis, for example, monthly, as shown in FIG.
  • the prediction is made using the measured values and the calculated values of the nuclear characteristics in the N-January, which is one (previous) before the N month.
  • a stem-free operation will be performed to confirm the plant function.
  • the core output fluctuation operation is performed by inserting and removing the control rods into the core, and the measured values of the nuclear characteristics are acquired.
  • the nuclear characteristics are, for example, the output distribution in the axial direction of the core (the axial direction of the control rods), and specifically, the deviation ( ⁇ I) of the output in the axial direction.
  • the nuclear characteristic may be an output distribution in the radial direction of the core.
  • the nuclear characteristic ⁇ I that fluctuates due to the stem-free operation is measured by a measuring device (not shown), and the measured value is used as the nuclear characteristic measurement data in the second storage unit 22 of the core analysis device 20.
  • the calculated value of the nuclear characteristic ⁇ I corresponding to the measured value is calculated in the core using the nuclear constant before correction. That is, the core state in which the stem-free operation is performed is simulated, and the core characteristic ⁇ I at that time is calculated using the core constant before correction.
  • the correction amount of the nuclear constant is calculated based on the nuclear characteristic ⁇ I as the measured value in N-January and the nuclear characteristic ⁇ I as the calculated value, and the corrected nuclear constant is used based on the calculated correction amount.
  • the core characteristic ⁇ I in January is calculated by performing the core calculation.
  • the nuclear constant calculation code C1 is a calculation code used for the aggregate calculation
  • the core calculation code C2 is a calculation code used for the core calculation.
  • the nuclear constant calculation code C1 uses the specification data related to the fuel assembly and the micro cross-sectional area acquired from the cross-sectional area library stored in the first storage unit 12 of the co-dispersion data creation device 10 as input values, and this micro-disconnection. Various calculations such as resonance calculation, neutron transport calculation, combustion calculation, and aggregate (nuclear constant) calculation are performed based on the area.
  • the specification data includes, for example, the radius of the fuel rods, the gap between the aggregates, the fuel composition, the fuel temperature, the moderator temperature, and the like.
  • the nuclear constant calculation code C1 uses a quadrangular geometric shape as a cross section of the fuel assembly cut by a plane orthogonal to the axial direction as a two-dimensional analysis target region, and a nuclear constant including a macro cross-sectional area in this analysis target region. It is a calculable code.
  • the nuclear constant is an input value used in the core calculation code C2, and the nuclear constant includes a fuel macro constant including an absorption cross section, a removal cross section, and a production cross section, a xenon micro constant, and a control rod macro constant. and so on. That is, the nuclear constant, which is an input value for the core calculation, is generated by performing the aggregate calculation using the nuclear constant calculation code C1.
  • the core calculation code C2 calculates the core by setting the calculated nuclear constants in the fuel nodes (not shown) that divide the fuel assembly into a plurality of pieces in the axial direction and have a small volume in the shape of a rectangular parallelepiped. Multiple fuel nodes represent the core, and the core calculation code C2 can evaluate the nuclear characteristics (core characteristics) in the core such as output distribution, critical boron concentration, and reactivity coefficient by performing core calculation. Code.
  • the covariance data creation device 10 causes the first calculation unit 11 to execute the nuclear constant calculation code C1 stored in the first storage unit 12 based on the input parameters input from the first input unit 13. Then, the covariance data creation device 10 calculates the nuclear constant in the analysis target region of the fuel assembly by performing the aggregate calculation using the nuclear constant calculation code C1. Further, the core analysis device 20 causes the second calculation unit 21 to execute the core calculation code C2 stored in the second storage unit 22 based on the calculated nuclear constant. Then, the core analysis device 20 derives the core characteristics of the core 5 by performing the core calculation using the core calculation code C2. Then, the core analyzer 20 corrects the nuclear constants and predicts the nuclear characteristics based on the derived nuclear characteristics.
  • the core analyzer 20 has a function of correcting the nuclear constant and a function of predicting the nuclear characteristics.
  • the core analysis device 20 may be a separate device separated into a device having a function of correcting the nuclear constant and a device having a function of predicting the nuclear characteristics, and is not particularly limited.
  • FIG. 4 is a flowchart relating to the creation of macro covariance data.
  • the covariance data creation device 10 executes a process of generating macro covariance data by executing the covariance data creation program P1.
  • the first calculation unit 11 first acquires micro covariance data which is data on the uncertainty of the micro cross-sectional area included in the cross-sectional area library stored in the first storage unit 12. (Step S11). Next, the first calculation unit 11 calculates N perturbation quantities of the micro cross-sectional area by the random sampling (random sampling) method using the micro covariance data. By calculating the perturbation amount of the micro cross-sectional area by the random sampling method, it is possible to incorporate the remarkable hydrothermal force and combustion feedback effect in the core of the light water reactor. Then, the first calculation unit 11 generates the calculated perturbation amount of the L micro cross-sectional areas as micro perturbation data (step S12). Then, the first calculation unit 11 stores the generated micro-perturbation data in the first storage unit 12.
  • the first calculation unit 11 executes an aggregate calculation based on the generated micro-perturbation data, that is, based on each micro cross-sectional area which is a perturbation quantity from 1 to L, and from 1 to L.
  • L nuclear constants (macro cross-sectional area) corresponding to the perturbation amount of are derived (step S13).
  • a calculation condition for executing the assembly calculation a predetermined representative parameter is selected in advance as a representative parameter from the parameters related to the core state of the core including the fuel assembly.
  • the aggregate calculation based on the micro perturbation data is executed with the selected representative parameter as the calculation condition. Therefore, by selecting the parameters, the number of combinations of parameters can be reduced, and the load of aggregate calculation can be reduced.
  • the first arithmetic unit 11 generates macro covariance data, which is data on the uncertainty of the nuclear constants, based on the calculated L nuclear constants (step S14).
  • the macro covariance data is, for example, the standard deviation of the calculated L nuclear constants.
  • the first calculation unit 11 stores the generated macro covariance data in the first storage unit 12.
  • the first arithmetic unit 11 calculates M perturbation quantities of nuclear constants by a random sampling (random sampling) method using the generated macro covariance data.
  • the first calculation unit 11 generates the calculated perturbation amount of M nuclear constants as macro perturbation data (step S15). Then, the first calculation unit 11 stores the generated macro perturbation data in the first storage unit 12 and outputs the generated macro perturbation data to the core analysis device 20.
  • the covariance data creation device 10 develops the uncertainty of the nuclear constant as the uncertainty of the macro cross-sectional area by executing the process of generating the macro covariance data, and the macro based on the uncertainty of the nuclear constant. Generate perturbation data.
  • FIG. 5 is a flowchart relating to the correction of the nuclear constant.
  • the core analyzer 20 executes a process of correcting the nuclear constant by executing the nuclear constant correction program P2.
  • the macro perturbation data output from the covariance data creation device 10 is stored in advance in the second storage unit 22.
  • the second calculation unit 21 first, based on the macro perturbation data stored in the second storage unit 22, that is, based on each nuclear constant that is a perturbation amount from 1 to M. Each core calculation is executed, and M nuclear characteristics corresponding to the perturbation amounts from 1 to M are derived (step S21). After that, the second calculation unit 21 determines the relationship between the change in the M nuclear constants and the change in the M nuclear characteristics accompanying the change in the M nuclear constants based on the calculated M nuclear characteristics. , Derived and acquired as sensitivity data (step S22). This sensitivity data may be stored in the second storage unit 22.
  • the second calculation unit 21 acquires the core characteristic ⁇ I measured by the measuring device for measuring the core characteristic as the core characteristic measurement data (step S23).
  • This core characteristic measurement data is the nuclear characteristic ⁇ I measured during the stem-free operation in the N month, and is stored in the second storage unit 22.
  • the measured value is measured in the period H from the change start point S1 at which the change in the nuclear characteristic ⁇ I of the reactor is started by the stem-free operation to the point S2 where the differential value of the change in the nuclear characteristic becomes almost zero. Is being measured (see FIG. 6).
  • the point S2 is, for example, the lower limit of the nuclear characteristic ⁇ I.
  • the measured value is measured at a plurality of arbitrary measurement points during the period H.
  • the second calculation unit 21 simulates the core state during the stem-free operation, executes the core calculation based on the macro perturbation data, that is, based on the nuclear constant before correction, and calculates the nuclear characteristic ⁇ I.
  • Step S24 the nuclear characteristic ⁇ I, which is a calculated value corresponding to the measured value, is acquired. That is, in step S24, the nuclear characteristic ⁇ I is acquired at a point corresponding to a plurality of arbitrary measurement points.
  • the nuclear constant is obtained from the calculation formula of the following equation (1) based on the acquired sensitivity data.
  • the correction amount for correcting the above is calculated (step S25).
  • Equation (1) is as follows. [Delta] T ADJ: perturbation amount of the correction amount [Delta] T :( the input value) Nuclear constant of nuclear constants [Delta] R T: the (output value by perturbation of nuclear constants) perturbation of nuclear characteristics [Delta] R: difference in nuclear constants (R e - R c (T 0 )) V e: uncertainty V m of the measured values become neutronic characteristics: Calculated become uncertainty due to calculation methods of the nuclear characteristics (m) R e: measurement become neutronic characteristics ([Delta] I) R c (T 0 ): Nuclear characteristics calculated based on the unadjusted (before correction) nuclear constant T 0 (calculated nuclear characteristics ⁇ I)
  • the nuclear constants corrected based on the correction amount ( ⁇ T ADJ ) are at least a fuel macro constant, a xenon micro constant, and a control rod macro constant.
  • the fuel macro constant, the xenon micro constant, and the control rod macro constant are corrected as the nuclear constants, but the fuel temperature may be corrected.
  • the second calculation unit 21 executes the core calculation based on the corrected nuclear constant, and derives the nuclear characteristics in the N month (step S27). As described above, in step S27, the second calculation unit 21 acquires the nuclear characteristics calculated by the corrected nuclear constant T, which is calculated so as to reproduce the measured value of the nuclear characteristics.
  • the core analyzer 20 executes the process of correcting the nuclear constant so as to approximate the calculated value of the nuclear characteristic to the measured value of the nuclear characteristic in N-January, and uses the corrected nuclear constant.
  • the nuclear characteristics with high prediction accuracy are calculated with respect to the measured values in the N month.
  • FIG. 6 is a graph of N-January core characteristics.
  • FIG. 7 is a graph relating to the core characteristics of the N month.
  • the horizontal axis represents time and the vertical axis represents nuclear characteristics.
  • the line T1 in FIGS. 6 and 7 is the nuclear characteristic ⁇ I as a measured value
  • the line T2 is the nuclear characteristic ⁇ I calculated by the nuclear constant before correction
  • the line T3 is the nuclear characteristic after correction. It is a nuclear characteristic ⁇ I calculated by.
  • the nuclear characteristic ⁇ I calculated from the corrected nuclear constant is an accurate reproduction of the measured nuclear characteristic ⁇ I.
  • the corrected nuclear constant is a value that can accurately reproduce the measured nuclear characteristic ⁇ I.
  • the present embodiment it is possible to improve the prediction accuracy of the nuclear characteristic ⁇ I by performing the core calculation using the corrected nuclear constant. Moreover, since the core calculation based on the nuclear constant can be performed using the macrocovariance data, the core calculation can be performed in consideration of the uncertainty of the nuclear constant.
  • the fuel macro constant, the control rod macro constant, and the xenon micro constant are applied as the nuclear constants to be corrected, so that the nuclear constants that affect the core output distribution (nuclear characteristic ⁇ I) are appropriate. Can be corrected to.
  • the fuel temperature may be further applied as the nuclear constant to be corrected, and in this case as well, the nuclear constant that affects the output distribution of the core (nuclear characteristic ⁇ I) can be appropriately corrected.
  • the output distribution of the core in the axial direction of the reactor can be accurately predicted as the nuclear characteristic ⁇ I.
  • ⁇ I nuclear characteristic
  • the measured value can be measured in a period in which the differential value of the change in nuclear characteristics becomes almost zero from the change start point at which the change in the core output of the reactor is started by the stem-free operation. it can. Therefore, since the correction amount of the nuclear constant can be calculated using the measured value measured during the period when the change in the nuclear characteristics is large, it is possible to calculate the correction amount with high accuracy that can reproduce the measured value. ..
  • the nuclear characteristics are predicted in the order of step S22 to step S24, but the order of these steps may be changed as appropriate.
  • step S23 or step S24 may be performed before step S22.
  • Covariance data creation device 11 1st calculation unit 12 1st storage unit 13 1st input unit 14 1st output unit 20 Core analysis device (nuclear characteristic prediction device) 21 Second calculation unit 22 Second storage unit 23 Second input unit 24 Second output unit C1 Nuclear constant calculation code C2 Core calculation code P1 Covariance data creation program P2 Nuclear constant correction program

Abstract

A nuclear characteristic predicting method comprises: step S23 of measuring a nuclear characteristic of a reactor that changes due to a reactor core power changing operation at a nuclear power plant to obtain a measured value of the change in the nuclear characteristic; step S24 of determining a calculated value of the nuclear characteristic corresponding to the measured value through reactor core calculation using an uncorrected nuclear constant; step S22 of acquiring a plurality of values of the nuclear characteristic through reactor core calculation with the nuclear constant perturbed using perturbation data of the nuclear constant created on the basis of prepared macro covariance data and calculating sensitivity data based on the plurality of values of the nuclear characteristic acquired; step S25 of calculating a correction amount for the nuclear constant on the basis of the sensitivity data so that the calculated value reproduces the measured value; and step S27 of predicting a change in the nuclear characteristic of the reactor due to a next reactor core power changing operation using the nuclear constant corrected with the correction amount.

Description

核特性の予測方法及び核特性予測装置Prediction method of nuclear characteristics and nuclear characteristic prediction device
　本発明は、原子炉の核特性を予測する核特性の予測方法及び核特性予測装置に関するものである。 The present invention relates to a nuclear characteristic prediction method and a nuclear characteristic prediction device for predicting the nuclear characteristics of a nuclear reactor.
　従来、燃料集合体を含む炉心の炉心解析（核設計計算）では、前段となる集合体計算と後段となる炉心計算との２段階に分けて計算を行っている。集合体計算は、様々な核種のミクロ断面積を入力値として、中性子束の詳細な空間及びエネルギー依存性を考慮して各種計算を行うことにより、均質化された核定数（マクロ断面積）を出力値として算出する。炉心計算は、集合体計算において算出された核定数を入力値として、炉心の燃料体系を考慮して計算を行うことにより、炉心の核特性を出力値として算出する。そして、炉心の核特性を予測する場合には、核定数を用いて炉心計算を行うことにより、炉心の核特性を予測している。 Conventionally, in the core analysis (nuclear design calculation) of the core including the fuel assembly, the calculation is divided into two stages, the aggregate calculation in the first stage and the core calculation in the second stage. The aggregate calculation uses the micro cross-sections of various nuclides as input values and performs various calculations in consideration of the detailed space and energy dependence of the neutron flux to obtain a homogenized nuclear constant (macrocross-section). Calculated as an output value. In the core calculation, the nuclear constant calculated in the aggregate calculation is used as an input value, and the core characteristics are calculated as an output value by performing the calculation in consideration of the fuel system of the core. When predicting the core characteristics of the core, the core characteristics are predicted by performing the core calculation using the nuclear constants.
　このような炉心解析において、核特性の予測精度を向上させるべく、解析結果としての核特性を、炉心に設けられた計測装置により計測された核特性の計測結果に近似させて、再現性を高めるように核定数を調整する手法（データ同化手法）が知られている（例えば、非特許文献１参照）。この調整手法では、集合体計算の入力値となるミクロ断面積を調整対象としていることから、調整済みのミクロ断面積を用いて、集合体計算を行った後、炉心計算を行うことで、核特性を算出することとなる。また、この調整手法では、ミクロ断面積を調整することにより、ミクロ断面積の不確かさに関するデータであるミクロ共分散データについても調整されることから、調整済のミクロ共分散データに基づく核特性の不確かさの評価が可能となる。 In such core analysis, in order to improve the prediction accuracy of the nuclear characteristics, the nuclear characteristics as the analysis result are approximated to the measurement results of the nuclear characteristics measured by the measuring device provided in the core to improve the reproducibility. As described above, a method for adjusting the nuclear constant (data assimilation method) is known (see, for example, Non-Patent Document 1). In this adjustment method, since the micro cross-sectional area that is the input value of the aggregate calculation is the adjustment target, the core calculation is performed after the aggregate calculation is performed using the adjusted micro cross-sectional area. The characteristics will be calculated. In addition, in this adjustment method, by adjusting the micro cross-sectional area, the micro covariance data, which is the data related to the uncertainty of the micro cross-sectional area, is also adjusted. Therefore, the nuclear characteristics based on the adjusted micro covariance data Uncertainty can be evaluated.
　また、炉心解析において、核特性の解析精度を向上させるべく、過去のプラントデータ及びそれを用いた解析結果を記憶しておき、それらの関係を回帰分析等を用いて分析し、分析結果を用いることにより、核定数を計測データを用いて補正する原子炉炉心性能計算装置が知られている（例えば、特許文献１参照）。 In addition, in core analysis, in order to improve the analysis accuracy of nuclear characteristics, past plant data and analysis results using it are stored, their relationships are analyzed using regression analysis, etc., and the analysis results are used. As a result, a nuclear reactor core performance calculation device that corrects the nuclear constant using measurement data is known (see, for example, Patent Document 1).
特開平１０－３３５２９０号公報Japanese Unexamined Patent Publication No. 10-335290
　しかしながら、非特許文献１の調整方法では、膨大な集合体計算を行う必要があることから、集合体計算を行う分、計算コストが増大してしまう。特に、集合体計算は、中性子束の詳細な空間及びエネルギー依存性を考慮することから、計算負荷が大きなものとなり、炉心計算に比して計算コストが大きなものとなっている。 However, in the adjustment method of Non-Patent Document 1, since it is necessary to perform a huge amount of aggregate calculation, the calculation cost increases by the amount of performing the aggregate calculation. In particular, the aggregate calculation takes into consideration the detailed space and energy dependence of the neutron flux, so that the calculation load is large and the calculation cost is large as compared with the core calculation.
　また、特許文献１の方法では、回帰分析等を用いて分析することから、核定数の不確かさを考慮することができないものとなる。 Further, in the method of Patent Document 1, since the analysis is performed by using regression analysis or the like, the uncertainty of the nuclear constant cannot be taken into consideration.
　そこで、本発明は、核定数の不確かさを考慮しつつ、核特性の予測精度の向上を図ることができる核特性の予測方法及び核特性予測装置を提供することを課題とする。 Therefore, it is an object of the present invention to provide a method for predicting nuclear characteristics and a device for predicting nuclear characteristics, which can improve the prediction accuracy of nuclear characteristics while considering the uncertainty of nuclear constants.
　本発明の核特性の予測方法は、原子炉の炉心出力変動操作により変化する前記原子炉の核特性を測定して、前記核特性の変化の測定値を取得するステップと、前記測定値に対応する前記核特性の計算値を、補正前の核定数を用いて炉心計算を行うことにより算出するステップと、予め準備したマクロ共分散データに基づいて作成した前記核定数の摂動データを用いて、前記核定数を摂動させて炉心計算を行うことにより複数の前記核特性を取得し、取得した複数の前記核特性に基づく感度データを算出するステップと、前記計算値が前記測定値を再現するように、前記感度データに基づいて前記核定数の補正量を算出するステップと、前記補正量により補正した前記核定数を用いて、次回の炉心出力変動操作により変化する前記原子炉の核特性の変化を予測するステップと、を含む。 The method for predicting nuclear characteristics of the present invention corresponds to a step of measuring the nuclear characteristics of the reactor that changes due to the operation of fluctuations in the core output of the reactor and acquiring a measured value of the change in the nuclear characteristics, and the measured values. Using the step of calculating the calculated value of the nuclear characteristic to be performed by performing the core calculation using the nuclear constant before correction, and the perturbation data of the nuclear constant prepared based on the macro covariance data prepared in advance, A step of acquiring a plurality of the nuclear characteristics by perturbing the nuclear constants and performing a core calculation, calculating sensitivity data based on the acquired plurality of the acquired nuclear characteristics, and the calculated value so as to reproduce the measured value. In addition, using the step of calculating the correction amount of the nuclear constant based on the sensitivity data and the nuclear constant corrected by the correction amount, the change in the nuclear characteristics of the reactor changed by the next core output fluctuation operation. Includes steps to predict.
　また、本発明の核特性予測装置は、原子炉の炉心出力変動操作により変化する原子炉の核特性を予測する制御部を備える核特性予測装置であって、前記制御部は、原子炉の炉心出力変動操作により変化する前記原子炉の核特性を測定して、前記核特性の変化の測定値を取得するステップと、前記測定値に対応する前記核特性の計算値を、補正前の核定数を用いて炉心計算を行うことにより算出するステップと、予め準備したマクロ共分散データに基づいて作成した前記核定数の摂動データを用いて、前記核定数を摂動させて炉心計算を行うことにより複数の前記核特性を取得し、取得した複数の前記核特性に基づく感度データを算出するステップと、前記計算値が前記測定値を再現するように、前記感度データに基づいて前記核定数の補正量を算出するステップと、前記補正量により補正した前記核定数を用いて、次回の炉心出力変動操作により変化する前記原子炉の核特性の変化を予測するステップと、を実行する。 Further, the nuclear characteristic prediction device of the present invention is a nuclear characteristic prediction device including a control unit for predicting the nuclear characteristics of the reactor that changes due to the core output fluctuation operation of the nuclear reactor, and the control unit is the core of the nuclear reactor. The step of measuring the nuclear characteristics of the reactor that changes due to the output fluctuation operation and acquiring the measured value of the change in the nuclear characteristics, and the calculated value of the nuclear characteristics corresponding to the measured values are the nuclear constants before correction. By using the steps calculated by performing the core calculation using the above and the perturbation data of the nuclear constants created based on the macro covariance data prepared in advance, the core calculations are performed by perturbing the nuclear constants. The step of acquiring the nuclear characteristics of the above and calculating the sensitivity data based on the acquired plurality of the acquired nuclear characteristics, and the correction amount of the nuclear constant based on the sensitivity data so that the calculated value reproduces the measured value. The step of calculating the above and the step of predicting the change in the nuclear characteristics of the reactor that will change in the next core output fluctuation operation by using the nuclear constant corrected by the correction amount are executed.
　本発明によれば、核定数の不確かさを考慮しつつ、核特性の予測精度の向上を図ることができる。 According to the present invention, it is possible to improve the prediction accuracy of nuclear characteristics while considering the uncertainty of nuclear constants.
図１は、本実施形態に係る共分散データ作成装置を模式的に表した概略構成図である。FIG. 1 is a schematic configuration diagram schematically showing a covariance data creation device according to the present embodiment. 図２は、本実施形態に係る炉心解析装置を模式的に表した概略構成図である。FIG. 2 is a schematic configuration diagram schematically showing the core analysis apparatus according to the present embodiment. 図３は、本実施形態に係る核特性の予測に関する説明図である。FIG. 3 is an explanatory diagram relating to the prediction of nuclear characteristics according to the present embodiment. 図４は、マクロ共分散データの作成に関するフローチャートである。FIG. 4 is a flowchart relating to the creation of macro covariance data. 図５は、核定数の補正に関するフローチャートである。FIG. 5 is a flowchart relating to the correction of the nuclear constant. 図６は、Ｎ－１月の核特性に関するグラフである。FIG. 6 is a graph of N-January core characteristics. 図７は、Ｎ月の核特性に関するグラフである。FIG. 7 is a graph relating to the core characteristics of the N month.
　以下に、本発明に係る実施形態を図面に基づいて詳細に説明する。なお、この実施形態によりこの発明が限定されるものではない。また、下記実施形態における構成要素には、当業者が置換可能かつ容易なもの、あるいは実質的に同一のものが含まれる。さらに、以下に記載した構成要素は適宜組み合わせることが可能であり、また、実施形態が複数ある場合には、各実施形態を組み合わせることも可能である。 Hereinafter, embodiments according to the present invention will be described in detail with reference to the drawings. The present invention is not limited to this embodiment. In addition, the components in the following embodiments include those that can be easily replaced by those skilled in the art, or those that are substantially the same. Further, the components described below can be appropriately combined, and when there are a plurality of embodiments, the respective embodiments can be combined.
［本実施形態］
　本実施形態に係る核特性の予測方法及び核特性予測装置では、原子炉の核特性を定期的に予測する。原子炉の核特性を予測するにあたっては、予めマクロ共分散データが作成されると共に、マクロ共分散データに基づいて作成した核定数の摂動データが作成される。マクロ共分散データは、図１に示す共分散データ作成装置により作成される。先ず、図１を参照して、共分散データ作成装置について説明する。 [The present embodiment]
In the nuclear characteristic prediction method and the nuclear characteristic prediction device according to the present embodiment, the nuclear characteristics of the nuclear reactor are predicted periodically. In predicting the nuclear characteristics of a nuclear reactor, macro-covariance data is created in advance, and perturbation data of nuclear constants created based on the macro-covariance data is created. The macro covariance data is created by the covariance data creation device shown in FIG. First, the covariance data creation device will be described with reference to FIG.
（共分散データ作成装置）
　図１は、本実施形態に係る共分散データ作成装置を模式的に表した概略構成図である。共分散データ作成装置１０は、各種プログラムを実行して演算可能な第一演算部１１と、各種プログラムおよびデータを記憶する第一記憶部１２と、キーボード等の入力デバイスで構成された第一入力部１３と、モニタ等の出力デバイスで構成された第一出力部１４とを有している。なお、共分散データ作成装置１０は、単体の装置で構成してもよいし、後述する炉心解析装置２０と一体の装置としてもよいし、演算装置及びデータサーバ等を組み合わせた複数の装置で構成してもよく、特に限定されない。 (Covariance data creation device)
FIG. 1 is a schematic configuration diagram schematically showing a covariance data creation device according to the present embodiment. The covariance data creation device 10 is a first input composed of a first calculation unit 11 capable of executing various programs and performing calculations, a first storage unit 12 for storing various programs and data, and an input device such as a keyboard. It has a unit 13 and a first output unit 14 composed of an output device such as a monitor. The covariance data creation device 10 may be composed of a single device, a device integrated with the core analysis device 20 described later, or a plurality of devices in which a calculation device, a data server, and the like are combined. It may be, and is not particularly limited.
　第一記憶部１２には、各種プログラムとして、例えば、核定数（マクロ断面積）を算出するために用いられる核定数計算コードＣ１、マクロ共分散データを作成するために用いられる共分散データ作成プログラムＰ１が記憶されている。また、第一記憶部１２には、データとして、例えば、断面積をまとめた断面積ライブラリと、集合体計算により算出されるマクロ断面積と、マクロ断面積に基づいて算出されるマクロ共分散データと、を含んで記憶されている。 In the first storage unit 12, as various programs, for example, a nuclear constant calculation code C1 used for calculating a nuclear constant (macro cross-sectional area) and a covariance data creation program used for creating macro covariance data. P1 is stored. Further, as data, for example, a cross-sectional area library that summarizes the cross-sectional areas, a macro cross-sectional area calculated by aggregate calculation, and macro covariance data calculated based on the macro cross-sectional area are stored in the first storage unit 12. And are remembered including.
　図２は、炉心解析装置を模式的に表した概略構成図である。図１に示すように、炉心解析装置２０は、マクロ共分散データを用いて炉心解析を行うことにより、炉心の核特性を予測する核特性予測装置として機能している。炉心解析装置２０は、各種プログラムを実行して演算可能な第二演算部２１と、各種プログラムおよびデータを記憶する第二記憶部２２と、キーボード等の入力デバイスで構成された第二入力部２３と、モニタ等の出力デバイスで構成された第二出力部２４とを有している。なお、炉心解析装置２０も、共分散データ作成装置１０と同様に、単体の装置で構成してもよいし、共分散データ作成装置１０と一体の装置としてもよいし、演算装置及びデータサーバ等を組み合わせた複数の装置で構成してもよく、特に限定されない。 FIG. 2 is a schematic configuration diagram schematically showing the core analyzer. As shown in FIG. 1, the core analysis device 20 functions as a nuclear characteristic prediction device that predicts the nuclear characteristics of the core by performing core analysis using macrocovariance data. The core analysis device 20 is a second input unit 23 composed of a second calculation unit 21 capable of executing various programs and performing calculations, a second storage unit 22 for storing various programs and data, and an input device such as a keyboard. And a second output unit 24 composed of an output device such as a monitor. The core analysis device 20 may be configured as a single device, or may be integrated with the covariance data creation device 10, like the covariance data creation device 10, a calculation device, a data server, or the like. It may be composed of a plurality of devices in which
　第二記憶部２２には、各種プログラムとして、例えば、核特性を算出するために用いられる炉心計算コードＣ２、炉心計算の入力値となる核定数（マクロ断面積）を補正するために用いられる核定数補正プログラムＰ２が記憶されている。また、第二記憶部２２には、データとして、例えば、マクロ断面積の変化に伴う核特性の変化に関するデータである感度データと、核特性を計測する計測装置により計測された核特性計測データと、核定数を補正するための補正量に関するデータと、を含んで記憶されている。 In the second storage unit 22, as various programs, for example, the core calculation code C2 used for calculating the nuclear characteristics and the nuclear constant (macro cross-sectional area) used as an input value for the core calculation are corrected. The number correction program P2 is stored. Further, in the second storage unit 22, as data, for example, sensitivity data which is data related to a change in nuclear characteristics due to a change in macrocross section, and nuclear characteristic measurement data measured by a measuring device for measuring nuclear characteristics. , Data on the amount of correction for correcting the nuclear constant, and stored.
　ここで、図３を参照して、核特性の予測に関して説明する。図３は、本実施形態に係る核特性の予測に関する説明図である。核特性の予測は、定期的に行われており、例えば、図３に示すように、１か月ごとに行われる。ここで、Ｎ月の核特性を予測する場合には、Ｎ月の一つ前（前回）となるＮ－１月における核特性の測定値と計算値とを用いて予測が行われる。 Here, the prediction of nuclear characteristics will be described with reference to FIG. FIG. 3 is an explanatory diagram relating to the prediction of nuclear characteristics according to the present embodiment. Prediction of nuclear properties is performed on a regular basis, for example, monthly, as shown in FIG. Here, when predicting the nuclear characteristics of the N month, the prediction is made using the measured values and the calculated values of the nuclear characteristics in the N-January, which is one (previous) before the N month.
　Ｎ－１月では、プラント機能の確認のため、ステムフリー操作が行われる。ステムフリー操作では、炉心に対して制御棒の挿入や引抜を行うことで、炉心出力変動操作が行われ、核特性の測定値が取得される。核特性としては、例えば、炉心の軸方向（制御棒の軸方向）における出力分布であり、具体的には、軸方向における出力の偏差（ΔＩ）である。なお、核特性としては、炉心の径方向における出力分布であってもよい。 In N-January, a stem-free operation will be performed to confirm the plant function. In the stem-free operation, the core output fluctuation operation is performed by inserting and removing the control rods into the core, and the measured values of the nuclear characteristics are acquired. The nuclear characteristics are, for example, the output distribution in the axial direction of the core (the axial direction of the control rods), and specifically, the deviation (ΔI) of the output in the axial direction. The nuclear characteristic may be an output distribution in the radial direction of the core.
　Ｎ－１月では、ステムフリー操作が行われることで変動する核特性ΔＩを、図示しない計測装置により計測し、計測された測定値を核特性計測データとして炉心解析装置２０の第二記憶部２２に記憶する。また、Ｎ－１月では、測定値に対応する核特性ΔＩの計算値を、補正前の核定数を用いて炉心計算する。つまり、ステムフリー操作が行われる炉心状態を模擬し、そのときの核特性ΔＩを、補正前の核定数を用いて炉心計算する。 In N-January, the nuclear characteristic ΔI that fluctuates due to the stem-free operation is measured by a measuring device (not shown), and the measured value is used as the nuclear characteristic measurement data in the second storage unit 22 of the core analysis device 20. Remember in. Further, in N-January, the calculated value of the nuclear characteristic ΔI corresponding to the measured value is calculated in the core using the nuclear constant before correction. That is, the core state in which the stem-free operation is performed is simulated, and the core characteristic ΔI at that time is calculated using the core constant before correction.
　そして、Ｎ－１月における測定値としての核特性ΔＩと、計算値としての核特性ΔＩとに基づいて、核定数の補正量を算出し、算出した補正量に基づいて補正した核定数を用いて炉心計算を行うことで、Ｎ月における核特性ΔＩを計算する。 Then, the correction amount of the nuclear constant is calculated based on the nuclear characteristic ΔI as the measured value in N-January and the nuclear characteristic ΔI as the calculated value, and the corrected nuclear constant is used based on the calculated correction amount. The core characteristic ΔI in January is calculated by performing the core calculation.
　次に、核設計計算に用いられる核定数計算コードＣ１及び炉心計算コードＣ２について説明する。核定数計算コードＣ１は、集合体計算に用いられる計算コードとなっており、炉心計算コードＣ２は、炉心計算に用いられる計算コードとなっている。 Next, the nuclear constant calculation code C1 and the core calculation code C2 used in the nuclear design calculation will be described. The nuclear constant calculation code C1 is a calculation code used for the aggregate calculation, and the core calculation code C2 is a calculation code used for the core calculation.
　核定数計算コードＣ１は、燃料集合体に関する諸元データや、共分散データ作成装置１０の第一記憶部１２に記憶された断面積ライブラリから取得されるミクロ断面積を入力値とし、このミクロ断面積に基づいて、共鳴計算、中性子輸送計算、燃焼計算及び集合体（核定数）計算等の各種計算を行っている。なお、諸元データとしては、例えば、燃料棒の半径、集合体間ギャップ、燃料組成、燃料温度や減速材温度等である。 The nuclear constant calculation code C1 uses the specification data related to the fuel assembly and the micro cross-sectional area acquired from the cross-sectional area library stored in the first storage unit 12 of the co-dispersion data creation device 10 as input values, and this micro-disconnection. Various calculations such as resonance calculation, neutron transport calculation, combustion calculation, and aggregate (nuclear constant) calculation are performed based on the area. The specification data includes, for example, the radius of the fuel rods, the gap between the aggregates, the fuel composition, the fuel temperature, the moderator temperature, and the like.
　核定数計算コードＣ１は、燃料集合体を軸方向に直交する面で切った断面となる四角形の幾何形状を二次元の解析対象領域としており、この解析対象領域におけるマクロ断面積を含む核定数を算出可能なコードとなっている。なお、核定数は、炉心計算コードＣ２に用いられる入力値となっており、核定数としては、吸収断面積、除去断面積および生成断面積を含む燃料マクロ定数、キセノンミクロ定数、制御棒マクロ定数などがある。つまり、核定数計算コードＣ１を用いて集合体計算を行うことにより、炉心計算用の入力値である核定数を生成している。 The nuclear constant calculation code C1 uses a quadrangular geometric shape as a cross section of the fuel assembly cut by a plane orthogonal to the axial direction as a two-dimensional analysis target region, and a nuclear constant including a macro cross-sectional area in this analysis target region. It is a calculable code. The nuclear constant is an input value used in the core calculation code C2, and the nuclear constant includes a fuel macro constant including an absorption cross section, a removal cross section, and a production cross section, a xenon micro constant, and a control rod macro constant. and so on. That is, the nuclear constant, which is an input value for the core calculation, is generated by performing the aggregate calculation using the nuclear constant calculation code C1.
　炉心計算コードＣ２は、燃料集合体を軸方向に複数に分割して直方体形状の小体積となる燃料ノード（図示省略）に、算出された核定数をそれぞれ設定して炉心計算を行っている。複数の燃料ノードは、炉心を表現しており、炉心計算コードＣ２は、炉心計算を行うことにより、出力分布、臨界ホウ素濃度、反応度係数等の炉心内の核特性（炉心特性）を評価可能なコードとなっている。 The core calculation code C2 calculates the core by setting the calculated nuclear constants in the fuel nodes (not shown) that divide the fuel assembly into a plurality of pieces in the axial direction and have a small volume in the shape of a rectangular parallelepiped. Multiple fuel nodes represent the core, and the core calculation code C2 can evaluate the nuclear characteristics (core characteristics) in the core such as output distribution, critical boron concentration, and reactivity coefficient by performing core calculation. Code.
　共分散データ作成装置１０は、第一入力部１３から入力された入力パラメータに基づいて、第一記憶部１２に記憶された核定数計算コードＣ１を、第一演算部１１において実行させる。すると、共分散データ作成装置１０は、核定数計算コードＣ１を用いて集合体計算を行うことにより、燃料集合体の解析対象領域における核定数を算出する。また、炉心解析装置２０は、算出された核定数に基づいて、第二記憶部２２に記憶された炉心計算コードＣ２を、第二演算部２１において実行させる。すると、炉心解析装置２０は、炉心計算コードＣ２を用いて炉心計算を行うことにより、炉心５の核特性を導出する。そして、炉心解析装置２０は、導出した核特性に基づいて、核定数の補正を行ったり、核特性の予測を行ったりする。つまり、炉心解析装置２０は、核定数を補正する機能と、核特性を予測する機能とを有したものとなっている。なお、炉心解析装置２０は、核定数を補正する機能を有する装置と、核特性を予測する機能を有する装置とに分離した、別体の装置であってもよく、特に限定されない。 The covariance data creation device 10 causes the first calculation unit 11 to execute the nuclear constant calculation code C1 stored in the first storage unit 12 based on the input parameters input from the first input unit 13. Then, the covariance data creation device 10 calculates the nuclear constant in the analysis target region of the fuel assembly by performing the aggregate calculation using the nuclear constant calculation code C1. Further, the core analysis device 20 causes the second calculation unit 21 to execute the core calculation code C2 stored in the second storage unit 22 based on the calculated nuclear constant. Then, the core analysis device 20 derives the core characteristics of the core 5 by performing the core calculation using the core calculation code C2. Then, the core analyzer 20 corrects the nuclear constants and predicts the nuclear characteristics based on the derived nuclear characteristics. That is, the core analyzer 20 has a function of correcting the nuclear constant and a function of predicting the nuclear characteristics. The core analysis device 20 may be a separate device separated into a device having a function of correcting the nuclear constant and a device having a function of predicting the nuclear characteristics, and is not particularly limited.
　次に、図４を参照して、上記の共分散データ作成装置１０によりマクロ共分散データを生成する処理について説明する。図４は、マクロ共分散データの作成に関するフローチャートである。共分散データ作成装置１０は、共分散データ作成プログラムＰ１を実行することで、マクロ共分散データを生成する処理を実行する。 Next, with reference to FIG. 4, a process of generating macro covariance data by the above-mentioned covariance data creation device 10 will be described. FIG. 4 is a flowchart relating to the creation of macro covariance data. The covariance data creation device 10 executes a process of generating macro covariance data by executing the covariance data creation program P1.
　共分散データ作成装置１０において、第一演算部１１は、先ず、第一記憶部１２に記憶されている断面積ライブラリに含まれるミクロ断面積の不確かさに関するデータであるミクロ共分散データを取得する（ステップＳ１１）。次に、第一演算部１１は、ミクロ共分散データを用いて、ランダムサンプリング（無作為抽出）法により、ミクロ断面積の摂動量をＮ個算出する。ランダムサンプリング法によりミクロ断面積の摂動量を算出することで、軽水炉の炉心で顕著な熱水力及び燃焼フィードバック効果を取り込むことが可能となる。そして、第一演算部１１は、算出したＬ個のミクロ断面積の摂動量をミクロ摂動データとして生成する（ステップＳ１２）。そして、第一演算部１１は、生成したミクロ摂動データを、第一記憶部１２に記憶する。 In the covariance data creation device 10, the first calculation unit 11 first acquires micro covariance data which is data on the uncertainty of the micro cross-sectional area included in the cross-sectional area library stored in the first storage unit 12. (Step S11). Next, the first calculation unit 11 calculates N perturbation quantities of the micro cross-sectional area by the random sampling (random sampling) method using the micro covariance data. By calculating the perturbation amount of the micro cross-sectional area by the random sampling method, it is possible to incorporate the remarkable hydrothermal force and combustion feedback effect in the core of the light water reactor. Then, the first calculation unit 11 generates the calculated perturbation amount of the L micro cross-sectional areas as micro perturbation data (step S12). Then, the first calculation unit 11 stores the generated micro-perturbation data in the first storage unit 12.
　次に、第一演算部１１は、生成したミクロ摂動データに基づいて、つまり、１からＬまでの摂動量となる各ミクロ断面積に基づいて、それぞれ集合体計算を実行し、１からＬまでの摂動量に対応するＬ個の核定数（マクロ断面積）をそれぞれ導出する（ステップＳ１３）。ここで、集合体計算を実行するための計算条件として、燃料集合体を含む炉心の炉心状態に関するパラメータの中から、代表となる所定のパラメータが代表パラメータとして予め選定されている。そして、ステップＳ１３では、選定された代表パラメータを計算条件として、ミクロ摂動データに基づく集合体計算を実行する。このため、パラメータを選定することで、パラメータの組み合わせ数を減じることができるため、集合体計算の負荷を軽減できる。なお、代表パラメータは、生成されるマクロ共分散データに対して依存性の高いパラメータが選定されている。この後、第一演算部１１は、算出したＬ個の核定数に基づいて、核定数の不確かさに関するデータであるマクロ共分散データを生成する（ステップＳ１４）。マクロ共分散データは、例えば、算出したＬ個の核定数の標準偏差である。そして、第一演算部１１は、生成したマクロ共分散データを、第一記憶部１２に記憶する。 Next, the first calculation unit 11 executes an aggregate calculation based on the generated micro-perturbation data, that is, based on each micro cross-sectional area which is a perturbation quantity from 1 to L, and from 1 to L. L nuclear constants (macro cross-sectional area) corresponding to the perturbation amount of are derived (step S13). Here, as a calculation condition for executing the assembly calculation, a predetermined representative parameter is selected in advance as a representative parameter from the parameters related to the core state of the core including the fuel assembly. Then, in step S13, the aggregate calculation based on the micro perturbation data is executed with the selected representative parameter as the calculation condition. Therefore, by selecting the parameters, the number of combinations of parameters can be reduced, and the load of aggregate calculation can be reduced. As the representative parameters, parameters that are highly dependent on the generated macrocovariance data are selected. After that, the first arithmetic unit 11 generates macro covariance data, which is data on the uncertainty of the nuclear constants, based on the calculated L nuclear constants (step S14). The macro covariance data is, for example, the standard deviation of the calculated L nuclear constants. Then, the first calculation unit 11 stores the generated macro covariance data in the first storage unit 12.
　続いて、第一演算部１１は、生成したマクロ共分散データを用いて、ランダムサンプリング（無作為抽出）法により、核定数の摂動量をＭ個算出する。第一演算部１１は、算出したＭ個の核定数の摂動量をマクロ摂動データとして生成する（ステップＳ１５）。そして、第一演算部１１は、生成したマクロ摂動データを、第一記憶部１２に記憶すると共に、炉心解析装置２０へ向けて出力する。 Subsequently, the first arithmetic unit 11 calculates M perturbation quantities of nuclear constants by a random sampling (random sampling) method using the generated macro covariance data. The first calculation unit 11 generates the calculated perturbation amount of M nuclear constants as macro perturbation data (step S15). Then, the first calculation unit 11 stores the generated macro perturbation data in the first storage unit 12 and outputs the generated macro perturbation data to the core analysis device 20.
　このように、共分散データ作成装置１０は、マクロ共分散データを生成する処理を実行することで、核定数の不確かさをマクロ断面積の不確かさとして展開し、核定数の不確かさに基づくマクロ摂動データを生成する。 In this way, the covariance data creation device 10 develops the uncertainty of the nuclear constant as the uncertainty of the macro cross-sectional area by executing the process of generating the macro covariance data, and the macro based on the uncertainty of the nuclear constant. Generate perturbation data.
　次に、図５を参照して、上記の炉心解析装置２０により核定数を補正する処理について説明する。図５は、核定数の補正に関するフローチャートである。炉心解析装置２０は、核定数補正プログラムＰ２を実行することで、核定数を補正する処理を実行する。この炉心解析装置２０は、共分散データ作成装置１０から出力されたマクロ摂動データが、予め第二記憶部２２に記憶されている。 Next, with reference to FIG. 5, a process of correcting the nuclear constant by the above core analyzer 20 will be described. FIG. 5 is a flowchart relating to the correction of the nuclear constant. The core analyzer 20 executes a process of correcting the nuclear constant by executing the nuclear constant correction program P2. In the core analysis device 20, the macro perturbation data output from the covariance data creation device 10 is stored in advance in the second storage unit 22.
　炉心解析装置２０において、第二演算部２１は、先ず、第二記憶部２２に記憶されているマクロ摂動データに基づいて、つまり、１からＭまでの摂動量となる各核定数に基づいて、それぞれ炉心計算を実行し、１からＭまでの摂動量に対応するＭ個の核特性をそれぞれ導出する（ステップＳ２１）。この後、第二演算部２１は、算出したＭ個の核特性に基づいて、Ｍ個の核定数の変化と、Ｍ個の核定数の変化に伴うＭ個の核特性の変化との関係を、感度データとして導出して取得する（ステップＳ２２）。この感度データは、第二記憶部２２に記憶してもよい。 In the core analyzer 20, the second calculation unit 21 first, based on the macro perturbation data stored in the second storage unit 22, that is, based on each nuclear constant that is a perturbation amount from 1 to M. Each core calculation is executed, and M nuclear characteristics corresponding to the perturbation amounts from 1 to M are derived (step S21). After that, the second calculation unit 21 determines the relationship between the change in the M nuclear constants and the change in the M nuclear characteristics accompanying the change in the M nuclear constants based on the calculated M nuclear characteristics. , Derived and acquired as sensitivity data (step S22). This sensitivity data may be stored in the second storage unit 22.
　次に、第二演算部２１は、炉心の核特性を計測する計測装置により計測された核特性ΔＩを、炉心特性計測データとして取得する（ステップＳ２３）。この炉心特性計測データは、Ｎ月においてステムフリー操作時に計測された核特性ΔＩとなっており、第二記憶部２２に記憶されている。具体的に、ステップＳ２３では、ステムフリー操作により原子炉の核特性ΔＩの変化が開始した変化開始点Ｓ１から、核特性の変化の微分値がほぼゼロとなる点Ｓ２まで期間Ｈにおいて、測定値を測定している（図６参照）。ここで、点Ｓ２は、例えば、核特性ΔＩの下限値である。ステップＳ２３は、期間Ｈにおいて、測定値を任意となる複数の測定点において計測している。 Next, the second calculation unit 21 acquires the core characteristic ΔI measured by the measuring device for measuring the core characteristic as the core characteristic measurement data (step S23). This core characteristic measurement data is the nuclear characteristic ΔI measured during the stem-free operation in the N month, and is stored in the second storage unit 22. Specifically, in step S23, the measured value is measured in the period H from the change start point S1 at which the change in the nuclear characteristic ΔI of the reactor is started by the stem-free operation to the point S2 where the differential value of the change in the nuclear characteristic becomes almost zero. Is being measured (see FIG. 6). Here, the point S2 is, for example, the lower limit of the nuclear characteristic ΔI. In step S23, the measured value is measured at a plurality of arbitrary measurement points during the period H.
　また、第二演算部２１は、ステムフリー操作時が行われる炉心状態を模擬し、マクロ摂動データに基づいて、つまり、補正前の核定数に基づいて炉心計算を実行し、核特性ΔＩを計算する（ステップＳ２４）。ステップＳ２４では、測定値に対応した計算値となる核特性ΔＩを取得する。つまり、ステップＳ２４では、任意となる複数の測定点に対応する点において、核特性ΔＩを取得している。 Further, the second calculation unit 21 simulates the core state during the stem-free operation, executes the core calculation based on the macro perturbation data, that is, based on the nuclear constant before correction, and calculates the nuclear characteristic ΔI. (Step S24). In step S24, the nuclear characteristic ΔI, which is a calculated value corresponding to the measured value, is acquired. That is, in step S24, the nuclear characteristic ΔI is acquired at a point corresponding to a plurality of arbitrary measurement points.
　第二演算部２１は、感度データ、測定値となる核特性ΔＩ及び計算値となる核特性ΔＩを取得すると、取得した感度データに基づいて、下記する（１）式の算出式から、核定数を補正する補正量を算出する（ステップＳ２５）。 When the second calculation unit 21 acquires the sensitivity data, the nuclear characteristic ΔI as the measured value, and the nuclear characteristic ΔI as the calculated value, the nuclear constant is obtained from the calculation formula of the following equation (1) based on the acquired sensitivity data. The correction amount for correcting the above is calculated (step S25).
Figure JPOXMLDOC01-appb-M000001
  
Figure JPOXMLDOC01-appb-M000001
  
　ここで、（１）式は、下記のとおりとなっている。
　ΔＴADJ：核定数の補正量
　ΔＴ：（入力値となる）核定数の摂動量
　ΔＲＴ：核定数の摂動による（出力値となる）核特性の摂動量
　ΔＲ：核定数の差異（Ｒｅ－Ｒｃ（Ｔ０））
　Ｖｅ：測定値となる核特性の不確かさ
　Ｖｍ：計算値となる核特性の計算手法（ｍ）に起因する不確かさ
　Ｒｅ：測定値となる核特性（ΔＩ）
　Ｒｃ（Ｔ０）：無調整（補正前）の核定数Ｔ０に基づいて算出された核特性（計算値となる核特性ΔＩ） Here, the equation (1) is as follows.
[Delta] T ADJ: perturbation amount of the correction amount [Delta] T :( the input value) Nuclear constant of nuclear constants [Delta] R T: the (output value by perturbation of nuclear constants) perturbation of nuclear characteristics [Delta] R: difference in nuclear constants (R e - R c (T 0 ))
V e: uncertainty V m of the measured values become neutronic characteristics: Calculated become uncertainty due to calculation methods of the nuclear characteristics (m) R e: measurement become neutronic characteristics ([Delta] I)
R c (T 0 ): Nuclear characteristics calculated based on the unadjusted (before correction) nuclear constant T 0 (calculated nuclear characteristics ΔI)
　第二演算部２１は、（１）式の算出式によって算出された補正量（ΔＴADJ）に基づいて、無調整の核定数（Ｔ０）を調整し、補正済みの核定数Ｔを、「Ｔ＝Ｔ０＋ΔＴADJ」の式から導出する（ステップＳ２６）。ここで、補正量（ΔＴADJ）に基づいて補正される核定数としては、少なくとも燃料マクロ定数、キセノンミクロ定数、制御棒マクロ定数である。なお、本実施形態では、核定数として、燃料マクロ定数、キセノンミクロ定数、制御棒マクロ定数を補正したが、燃料温度を補正してもよい。 The second calculation unit 21 adjusts the unadjusted nuclear constant (T 0 ) based on the correction amount (ΔT ADJ ) calculated by the calculation formula (1), and sets the corrected nuclear constant T to “. It is derived from the equation “T = T 0 + ΔT ADJ ” (step S26). Here, the nuclear constants corrected based on the correction amount (ΔT ADJ ) are at least a fuel macro constant, a xenon micro constant, and a control rod macro constant. In the present embodiment, the fuel macro constant, the xenon micro constant, and the control rod macro constant are corrected as the nuclear constants, but the fuel temperature may be corrected.
　そして、第二演算部２１は、補正済み核定数に基づいて炉心計算を実行し、Ｎ月における核特性を導出する（ステップＳ２７）。以上により、ステップＳ２７において、第二演算部２１は、核特性の測定値を再現するよう算出された、補正後の核定数Ｔによって算出された核特性を取得する。 Then, the second calculation unit 21 executes the core calculation based on the corrected nuclear constant, and derives the nuclear characteristics in the N month (step S27). As described above, in step S27, the second calculation unit 21 acquires the nuclear characteristics calculated by the corrected nuclear constant T, which is calculated so as to reproduce the measured value of the nuclear characteristics.
　このように、炉心解析装置２０は、Ｎ－１月において、核特性の計算値を、核特性の測定値に近似させるように、核定数を補正する処理を実行し、補正した核定数を用いてＮ月における炉心計算を行うことで、Ｎ月における測定値に対して予測精度の高い核特性を算出する。 In this way, the core analyzer 20 executes the process of correcting the nuclear constant so as to approximate the calculated value of the nuclear characteristic to the measured value of the nuclear characteristic in N-January, and uses the corrected nuclear constant. By performing the core calculation in the N month, the nuclear characteristics with high prediction accuracy are calculated with respect to the measured values in the N month.
　次に、図６及び図７を参照して、Ｎ－１月及びＮ月の核特性について説明する。図６は、Ｎ－１月の核特性に関するグラフである。図７は、Ｎ月の核特性に関するグラフである。図６及び図７において、横軸は時間となっており、縦軸は核特性となっている。また、図６及び図７におけるラインＴ１は、測定値となる核特性ΔＩであり、ラインＴ２は、補正前の核定数により算出される核特性ΔＩであり、ラインＴ３は、補正後の核定数により算出される核特性ΔＩである。 Next, the nuclear characteristics of N-January and N-month will be described with reference to FIGS. 6 and 7. FIG. 6 is a graph of N-January core characteristics. FIG. 7 is a graph relating to the core characteristics of the N month. In FIGS. 6 and 7, the horizontal axis represents time and the vertical axis represents nuclear characteristics. Further, the line T1 in FIGS. 6 and 7 is the nuclear characteristic ΔI as a measured value, the line T2 is the nuclear characteristic ΔI calculated by the nuclear constant before correction, and the line T3 is the nuclear characteristic after correction. It is a nuclear characteristic ΔI calculated by.
　図６に示すように、Ｎ－１月において、ラインＴ１とラインＴ２は差異がある一方で、ラインＴ１とラインＴ３とは近似した値となっている。このため、補正後の核定数により算出される核特性ΔＩは、測定値となる核特性ΔＩを精度良く再現したものとなっている。換言すれば、補正後の核定数は、測定値となる核特性ΔＩを精度良く再現可能な値となっている。 As shown in FIG. 6, in N-January, the line T1 and the line T2 have a difference, while the line T1 and the line T3 have similar values. Therefore, the nuclear characteristic ΔI calculated from the corrected nuclear constant is an accurate reproduction of the measured nuclear characteristic ΔI. In other words, the corrected nuclear constant is a value that can accurately reproduce the measured nuclear characteristic ΔI.
　図７に示すように、Ｎ月において、Ｎ－１月と同様に、ラインＴ１とラインＴ２は差異がある一方で、ラインＴ１とラインＴ３とは近似した値となっている。つまり、補正前の核定数により予測される核特性ΔＩは、測定値となる核特性ΔＩと差異があることから、予測精度向上の余地がある。一方で、補正後の核定数により予測される核特性ΔＩは、測定値となる核特性ΔＩを精度良く再現したものとなることが分かる。 As shown in FIG. 7, in N month, as in N-January, there is a difference between line T1 and line T2, while line T1 and line T3 have approximate values. That is, since the nuclear characteristic ΔI predicted by the nuclear constant before correction is different from the measured nuclear characteristic ΔI, there is room for improvement in prediction accuracy. On the other hand, it can be seen that the nuclear characteristic ΔI predicted by the corrected nuclear constant is an accurate reproduction of the measured nuclear characteristic ΔI.
　以上のように、本実施形態によれば、補正された核定数を用いて炉心計算を行うことにより、核特性ΔＩの予測精度の向上を図ることができる。また、マクロ共分散データを用いて、核定数に基づく炉心計算を行うことができるため、核定数の不確かさを考慮した炉心計算を行うことができる。 As described above, according to the present embodiment, it is possible to improve the prediction accuracy of the nuclear characteristic ΔI by performing the core calculation using the corrected nuclear constant. Moreover, since the core calculation based on the nuclear constant can be performed using the macrocovariance data, the core calculation can be performed in consideration of the uncertainty of the nuclear constant.
　また、本実施形態によれば、補正する核定数として、燃料マクロ定数、制御棒マクロ定数、キセノンミクロ定数が適用されるため、炉心の出力分布（核特性ΔＩ）に影響を与える核定数を適切に補正することができる。同様に、補正する核定数として、燃料温度もさらに適用してもよく、この場合においても、炉心の出力分布（核特性ΔＩ）に影響を与える核定数を適切に補正することができる。 Further, according to the present embodiment, the fuel macro constant, the control rod macro constant, and the xenon micro constant are applied as the nuclear constants to be corrected, so that the nuclear constants that affect the core output distribution (nuclear characteristic ΔI) are appropriate. Can be corrected to. Similarly, the fuel temperature may be further applied as the nuclear constant to be corrected, and in this case as well, the nuclear constant that affects the output distribution of the core (nuclear characteristic ΔI) can be appropriately corrected.
　また、本実施形態によれば、核特性ΔＩとして、原子炉の軸方向における炉心の出力分布を精度良く予測することができる。なお、核特性として、原子炉の径方向における炉心の出力分布を精度良く予測することも可能となる。 Further, according to the present embodiment, the output distribution of the core in the axial direction of the reactor can be accurately predicted as the nuclear characteristic ΔI. As a nuclear characteristic, it is also possible to accurately predict the output distribution of the core in the radial direction of the reactor.
　また、本実施形態によれば、ステムフリー操作により原子炉の炉心出力の変化が開始した変化開始点から、核特性の変化の微分値がほぼゼロとなる期間において、測定値を測定することができる。このため、核特性の変化が大きい期間において測定された測定値を用いて、核定数の補正量を算出することができることから、測定値を再現可能な精度のよい補正量を算出することができる。 Further, according to the present embodiment, the measured value can be measured in a period in which the differential value of the change in nuclear characteristics becomes almost zero from the change start point at which the change in the core output of the reactor is started by the stem-free operation. it can. Therefore, since the correction amount of the nuclear constant can be calculated using the measured value measured during the period when the change in the nuclear characteristics is large, it is possible to calculate the correction amount with high accuracy that can reproduce the measured value. ..
　なお、本実施形態では、ステップＳ２２からステップＳ２４の順で、核特性の予測を行ったが、これらのステップは順番を適宜入れ替えてもよい。例えば、ステップＳ２２の前に、ステップＳ２３またはステップＳ２４を行ってもよい。 In the present embodiment, the nuclear characteristics are predicted in the order of step S22 to step S24, but the order of these steps may be changed as appropriate. For example, step S23 or step S24 may be performed before step S22.
　１０　共分散データ作成装置
　１１　第一演算部
　１２　第一記憶部
　１３　第一入力部
　１４　第一出力部
　２０　炉心解析装置（核特性予測装置）
　２１　第二演算部
　２２　第二記憶部
　２３　第二入力部
　２４　第二出力部
　Ｃ１　核定数計算コード
　Ｃ２　炉心計算コード
　Ｐ１　共分散データ作成プログラム
　Ｐ２　核定数補正プログラム 10 Covariance data creation device 11 1st calculation unit 12 1st storage unit 13 1st input unit 14 1st output unit 20 Core analysis device (nuclear characteristic prediction device)
21 Second calculation unit 22 Second storage unit 23 Second input unit 24 Second output unit C1 Nuclear constant calculation code C2 Core calculation code P1 Covariance data creation program P2 Nuclear constant correction program

Claims (6)

  1. 　原子炉の炉心出力変動操作により変化する前記原子炉の核特性を測定して、前記核特性の変化の測定値を取得するステップと、
    　前記測定値に対応する前記核特性の計算値を、補正前の核定数を用いて炉心計算を行うことにより算出するステップと、
    　予め準備したマクロ共分散データに基づいて作成した前記核定数の摂動データを用いて、前記核定数を摂動させて炉心計算を行うことにより複数の前記核特性を取得し、取得した複数の前記核特性に基づく感度データを算出するステップと、
    　前記計算値が前記測定値を再現するように、前記感度データに基づいて前記核定数の補正量を算出するステップと、
    　前記補正量により補正した前記核定数を用いて、次回の炉心出力変動操作により変化する前記原子炉の核特性の変化を予測するステップと、を含む核特性の予測方法。     A step of measuring the nuclear characteristics of the reactor, which changes due to the operation of changing the core output of the reactor, and acquiring a measured value of the changes in the nuclear characteristics.
    A step of calculating the calculated value of the nuclear characteristic corresponding to the measured value by performing a core calculation using the nuclear constant before correction, and
    Using the perturbation data of the nuclear constant created based on the macro covariance data prepared in advance, the plurality of the nuclear characteristics are acquired by perturbing the nuclear constant and the core calculation is performed, and the acquired plurality of the nuclei. Steps to calculate sensitivity data based on characteristics,
    A step of calculating the correction amount of the nuclear constant based on the sensitivity data so that the calculated value reproduces the measured value, and
    A method for predicting nuclear characteristics, including a step of predicting a change in the nuclear characteristics of the reactor that changes in the next core output fluctuation operation using the nuclear constant corrected by the correction amount.
  2. 　前記核定数は、燃料マクロ定数、制御棒マクロ定数、キセノンミクロ定数を含む請求項１に記載の核特性の予測方法。 The method for predicting nuclear characteristics according to claim 1, wherein the nuclear constant includes a fuel macro constant, a control rod macro constant, and a xenon micro constant.
  3. 　前記核定数は、燃料温度をさらに含む請求項２に記載の核特性の予測方法。 The method for predicting nuclear characteristics according to claim 2, wherein the nuclear constant further includes a fuel temperature.
  4. 　前記核特性は、前記原子炉の軸方向における出力分布または前記原子炉の径方向における出力分布である請求項１から３のいずれか１項に記載の核特性の予測方法。 The method for predicting nuclear characteristics according to any one of claims 1 to 3, wherein the nuclear characteristics are an output distribution in the axial direction of the reactor or an output distribution in the radial direction of the reactor.
  5. 　前記測定値は、前記炉心出力変動操作により前記原子炉の炉心出力の変化が開始した変化開始点から、前記核特性の変化の微分値がゼロとなる期間において測定される請求項１から４のいずれか１項に記載の核特性の予測方法。 The measured values are measured from the change start point at which the change in the core output of the reactor is started by the core power fluctuation operation to the period in which the differential value of the change in the nuclear characteristics becomes zero, according to claims 1 to 4. The method for predicting nuclear characteristics according to any one item.
  6. 　原子炉の炉心出力変動操作により変化する原子炉の核特性を予測する制御部を備える核特性予測装置であって、
    　前記制御部は、
    　原子炉の炉心出力変動操作により変化する前記原子炉の核特性を測定して、前記核特性の変化の測定値を取得するステップと、
    　前記測定値に対応する前記核特性の計算値を、補正前の核定数を用いて炉心計算を行うことにより算出するステップと、
    　予め準備したマクロ共分散データに基づいて作成した前記核定数の摂動データを用いて、前記核定数を摂動させて炉心計算を行うことにより複数の前記核特性を取得し、取得した複数の前記核特性に基づく感度データを算出するステップと、
    　前記計算値が前記測定値を再現するように、前記感度データに基づいて前記核定数の補正量を算出するステップと、
    　前記補正量により補正した前記核定数を用いて、次回の炉心出力変動操作により変化する前記原子炉の核特性の変化を予測するステップと、を実行する核特性予測装置。     It is a nuclear characteristic prediction device equipped with a control unit that predicts the nuclear characteristics of the reactor that change due to the operation of fluctuations in the core output of the reactor.
    The control unit
    A step of measuring the nuclear characteristics of the reactor, which changes due to the operation of changing the core output of the reactor, and acquiring a measured value of the changes in the nuclear characteristics.
    A step of calculating the calculated value of the nuclear characteristic corresponding to the measured value by performing a core calculation using the nuclear constant before correction, and
    Using the perturbation data of the nuclear constant created based on the macro covariance data prepared in advance, the plurality of the nuclear characteristics are acquired by perturbing the nuclear constant and the core calculation is performed, and the acquired plurality of the nuclei. Steps to calculate sensitivity data based on characteristics,
    A step of calculating the correction amount of the nuclear constant based on the sensitivity data so that the calculated value reproduces the measured value, and
    A nuclear characteristic prediction device that executes a step of predicting a change in the nuclear characteristics of the reactor that changes in the next core output fluctuation operation using the nuclear constant corrected by the correction amount.
PCT/JP2020/023414 2019-07-19 2020-06-15 Nuclear characteristic predicting method and nuclear characteristic predicting apparatus WO2021014820A1 (en)

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