JP2023009931A - Subcriticality evaluation method, subcriticality monitoring method, subcriticality evaluation device, and subcriticality monitoring device - Google Patents

Abstract

To provide a subcriticality evaluation method capable of quantitatively evaluating the subcriticality of an unknown system containing nuclear fuel.SOLUTION: The subcriticality evaluation method for quantifying estimated critical limits for evaluating that an unknown system containing nuclear fuel is subcritical executes: a step of selecting multiple critical experiment systems and acquiring systematic information about the selected multiple critical experiment systems; a step of calculating the prompt neutron decay constant of the critical experiment systems based on the acquired systematic information by using a calculation model for evaluation; and a step of statistically processing the plurality of calculated prompt neutron decay constants to calculate the estimated critical limit value of the prompt neutron decay constant.SELECTED DRAWING: Figure 2

Description

The present disclosure relates to a subcriticality evaluation method, a subcriticality monitoring method, a subcriticality evaluation device, and a subcriticality monitoring device.

BACKGROUND ART Conventionally, a subcriticality measuring device for measuring the subcriticality of a system containing nuclear fuel is known (see, for example, Patent Document 1). The subcriticality measuring device has a radiation detector that detects neutrons from the system, and calculates the effective multiplication factor (keff) and the subcriticality (-ρ) based on the output of the radiation detector. Then, the subcriticality of the system is evaluated based on the effective multiplication factor and the subcriticality calculated by the subcriticality measuring device.

JP 2014-145720 A

As in Patent Document 1, it is generally difficult to directly measure the effective multiplication factor (or the degree of subcriticality). In the measurement of the effective multiplication factor (or subcriticality), neutrons from the system are detected using a neutron detector, and the neutron count data obtained by the detection of the neutron detector and the dynamic parameters (delayed neutron rate, Measured effective multiplication factors (and subcriticality) are evaluated by combining calculated values of neutron production time, etc.).

When evaluating the measured value of the effective multiplication factor, the prompt neutron attenuation constant α, which is the measured value based on the neutron count data, is evaluated, and the prompt neutron attenuation constant α is converted to the effective multiplication factor. In this case, not only the uncertainty of the prompt neutron attenuation constant α but also the uncertainty of the conversion factor to the effective multiplication factor must be considered, and the uncertainty must be overestimated. In addition, when the specification data (geometric shape, composition, temperature, etc.) of the system to be measured are known, conversion factors such as dynamic characteristic parameters can be predicted with high accuracy. It is necessary to take into consideration the uncertainty of input conditions when calculating conversion factors such as characteristic parameters.

Thus, when subcriticality is evaluated by converting the prompt neutron attenuation constant α into the effective multiplication factor, it is necessary to allow for large uncertainties. Therefore, it was difficult to rationally evaluate whether an unknown system containing nuclear fuel is subcritical.

Therefore, the present disclosure provides a subcriticality evaluation method, a subcriticality monitoring method, a subcriticality evaluation device, and a subcriticality monitoring device that can quantitatively evaluate whether an unknown system containing nuclear fuel is subcritical. The task is to

The subcriticality evaluation method of the present disclosure is a subcriticality evaluation method for quantifying an estimated criticality limit value for evaluating whether an unknown system containing nuclear fuel is subcritical, and a plurality of criticality test systems are selected. obtaining system information of a plurality of the selected critical experiment systems; and calculating prompt neutron decay constants of the critical experiment systems using a computational model for evaluation based on the obtained system information. and statistically processing a plurality of the calculated prompt neutron decay constants to calculate the estimated critical limit of the prompt neutron decay constant.

The subcriticality monitoring method of the present disclosure uses the estimated criticality limit value quantified by the subcriticality evaluation method described above to monitor whether the unknown system is subcritical. , the step of obtaining neutron counting data in the unknown system, the step of calculating the prompt neutron decay constant as a measured value using a computational model based on the neutron counting data, and the calculated measured value is greater than said estimated critical limit.

A subcriticality evaluation apparatus of the present disclosure is a subcriticality evaluation apparatus that quantifies an estimated criticality limit value for evaluating whether an unknown system containing nuclear fuel is subcritical, and the estimated criticality limit value is The control unit selects a plurality of critical experiment systems, acquires system information of the selected plurality of critical experiment systems, and calculates a calculation model for evaluation based on the acquired system information. and calculating the estimated critical limit of the prompt neutron decay constant by statistically processing the plurality of calculated prompt neutron decay constants using and run

The subcriticality monitoring device of the present disclosure uses the estimated criticality limit value evaluated by the subcriticality evaluation device to monitor whether the unknown system is subcritical, A neutron detector that measures neutrons from the unknown system, and a supervisory control unit that acquires neutron count data that is a detection result of the neutron detector and monitors the unknown system, and the supervisory control a step of obtaining the neutron count data; a step of calculating the prompt neutron decay constant as a measured value using a calculation model for measurement based on the neutron count data; and monitoring for greater than said estimated critical limit.

According to the present disclosure, it is possible to quantitatively assess whether an unknown system containing nuclear fuel is subcritical.

FIG. 1 is a block diagram schematically showing a subcriticality evaluation device according to this embodiment. FIG. 2 is a flowchart relating to the subcriticality evaluation method according to this embodiment. FIG. 3 is an explanatory diagram showing selected critical experiments. FIG. 4 is a diagram showing parameters for selecting a critical experiment. FIG. 5 is an explanatory diagram relating to the calculation model for evaluation. FIG. 6 is a distribution diagram of prompt neutron decay constants. FIG. 7 is a block diagram schematically showing the subcriticality monitoring device according to this embodiment. FIG. 8 is a flowchart relating to the subcriticality monitoring method according to this embodiment. FIG. 9 is a graph showing temporal changes in the prompt neutron decay constant, which is a measured value.

EMBODIMENT OF THE INVENTION Below, embodiment which concerns on this invention is described in detail based on drawing. In addition, this invention is not limited by this embodiment. In addition, components in the following embodiments include components that can be easily replaced by those skilled in the art, or components that are substantially the same. Furthermore, the components described below can be combined as appropriate, and when there are multiple embodiments, each embodiment can be combined.

[Embodiment]
The subcriticality evaluation method and subcriticality evaluation device 10 according to the present embodiment provide an estimated criticality limit value for evaluating whether an unknown system is subcritical in a system in which the geometry and composition conditions of nuclear fuel are unknown. A method and apparatus for quantifying. As the estimated critical limit value, the prompt neutron damping constant α is used, and is a value representing the upper limit of the prompt neutron damping constant α at which the system of interest is estimated to be in a critical state. The prompt neutron decay constant α is the time constant when the number of neutrons decays exponentially in a subcritical system when neutrons are injected into the system in pulses. Prompt neutron decay constant α, when the contribution of delayed neutrons is negligible, means that the system is subcritical when α>0, and critical when α=0, When α<0, it means that the system is supercritical. That is, for α>0, the number of neutrons in the system decays exponentially. Also, when α=0, the number of neutrons in the system is constant. Furthermore, for α<0, the number of neutrons in the system increases exponentially.

(Subcriticality evaluation device)
A subcriticality evaluation device 10 will be described with reference to FIG. FIG. 1 is a block diagram schematically showing a subcriticality evaluation device according to this embodiment. The subcriticality evaluation device 10 has a control section 11 , a storage section 12 , an output section 13 and an input section 14 .

The control unit 11 includes, for example, an integrated circuit such as a CPU (Central Processing Unit). Based on the input information, the control unit 11 uses an evaluation calculation model to perform processing such as calculating an estimated critical limit value for evaluating the subcriticality of an unknown system. The memory unit 12 is an arbitrary memory device such as a semiconductor memory device and a magnetic memory device. The storage unit 12 stores various programs for executing various processes and various data used for the processes. The various programs are an evaluation calculation model for calculating the estimated critical limit value, and the various data are input information to be input to the evaluation calculation model. The output unit 13 is, for example, a display device such as a liquid crystal display. The input unit 14 is, for example, an input device such as a keyboard and mouse.

(Subcriticality evaluation method)
Next, a subcriticality evaluation method executed by the subcriticality evaluation apparatus 10 will be described with reference to FIGS. 2 to 6. FIG. FIG. 2 is a flowchart relating to the subcriticality evaluation method according to this embodiment. FIG. 3 is an explanatory diagram showing selected critical experiments. FIG. 4 is a diagram showing parameters for selecting a critical experiment. FIG. 5 is an explanatory diagram relating to the calculation model for evaluation. FIG. 6 is a distribution diagram of prompt neutron decay constants.

In the subcriticality evaluation method, the prompt neutron damping constant α, which is a quantified estimated critical limit value, is calculated. As shown in FIG. 2, in the subcriticality evaluation method, a plurality of critical experiment systems are selected and system information of the plurality of critical experiment systems is obtained (step S1). In step S<b>1 , the input unit 14 acquires a plurality of pieces of system information as input information, and the acquired pieces of system information are stored in the storage unit 12 .

A plurality of selected critical experiments will now be described. Critical experiments used for subcriticality evaluation are selected from a database of critical experiments. As shown in FIG. 3, the selected critical experiment range is wider than the assumed range of the unknown system and includes the unknown system. The range of the critical experiment is a range indexed by five parameters, and these parameters are the index for selecting the critical experiment.

As shown in FIG. 4, the parameters for selecting the critical experiment are specifically the enrichment of the nuclear fuel, the Pu content of the nuclear fuel, the size of the nuclear fuel, the fuel to moderator volume ratio, the type of structural material nuclide, etc. are mentioned. It should be noted that at least one parameter that characterizes the system information should be included, and parameter candidates are not limited to those listed in this specific example.

In step S1, when a plurality of critical experiments are selected and the systematic information of the plurality of critical experiments is acquired, the control unit 11 uses the computational model for evaluation based on the systematic information of each critical experiment to perform prompt neutron attenuation. Each constant α is calculated (step S2).

Next, the calculation model for evaluation will be described with reference to FIG. As shown in FIG. 5, the calculation model for evaluation is Formula (2) shown on the right side of FIG. The evaluation calculation model is a calculation model for calculating the prompt neutron attenuation constant α shown on the right side of FIG. 2) is derived from the formula. Equation (1) is a model for calculating the effective multiplication factor (keff) and the neutron flux ψ so that neutron annihilation (left side) and neutron generation (right side) are balanced. Formula (2) is a model for calculating prompt neutron decay constant α and neutron flux ψ so that neutron annihilation and neutron production are balanced when annihilation operator A in formula (1) is reduced by α/v. It has become. The calculated prompt neutron attenuation constant α includes uncertainty.

In step S2, the multiple prompt neutron attenuation constants α calculated using equation (2) contain uncertainties, and thus have a distribution as shown in FIG. Therefore, after executing step S2, the control unit 11 statistically processes the multiple calculated prompt neutron attenuation constants α to calculate an estimated critical limit value of the prompt neutron attenuation constant α (step S3).

In FIG. 6, the vertical axis is the number of samples, and the horizontal axis is the prompt neutron attenuation constant α [1/sec]. As shown in FIG. 6, the calculated multiple prompt neutron attenuation constants α have a distribution in which the number of samples increases near the average value and the number of samples decreases as the distance from the vicinity of the average value increases.

At step S3, an estimated critical limit value is calculated by statistical processing based on the following equation (3).

As shown in the formula (3), the estimated critical limit value α _limit is obtained by multiplying the standard deviation of the difference from the average value of the prompt neutron attenuation constant α by the reliability coefficient, and multiplying the calculated multiple prompt neutron attenuation constants. Calculated by adding to the average value of α. As a result, the estimated critical limit value α _limit is a value that takes into consideration the uncertainty of the prompt neutron attenuation constant α calculated by the calculation model shown in FIG.

(Subcritical monitoring device)
Next, the subcriticality monitor 20 will be described with reference to FIGS. 7 to 9. FIG. FIG. 7 is a block diagram schematically showing the subcriticality monitoring device according to this embodiment. The subcriticality monitoring device 20 has a control section (monitoring control section) 21 , a storage section 22 , an output section 23 , an input section 24 and a neutron detector 25 .

Like the control unit 11, the control unit 21 includes an integrated circuit such as a CPU (Central Processing Unit). Based on the input information, the control unit 21 uses the calculation model for measurement to perform processing such as calculating measured values for performing subcriticality monitoring of an unknown system. The storage unit 22, like the storage unit 12, is an arbitrary storage device such as a semiconductor storage device and a magnetic storage device. The storage unit 22 stores various programs for executing various processes and various data used for the processes. Various programs include a measurement calculation model for calculating measured values, and various data include an estimated critical limit value calculated by the subcriticality monitoring device 20 and input information to be input to the measurement calculation model. etc. The output unit 23 is, for example, a display device such as a liquid crystal display. The input unit 24 is, for example, an input device such as a keyboard and mouse.

A neutron detector 25 detects neutrons originating from an unknown system. The neutron detector 25 is connected to the input section 24, and the input section 24 acquires information from the neutron detector 25 as neutron count data.

(Subcriticality monitoring method)
Next, a subcriticality monitoring method executed by the subcriticality monitoring device 20 will be described with reference to FIGS. 8 and 9. FIG. FIG. 8 is a flowchart relating to the subcriticality monitoring method according to this embodiment. FIG. 9 is a graph showing temporal changes in the prompt neutron decay constant, which is a measured value.

In the subcriticality monitoring method, the estimated criticality limit value α _limit calculated by the subcriticality monitoring device 20 is used as a threshold value, and the unknown system is monitored for subcriticality based on the measured values obtained by measurement. It has become. As shown in FIG. 8, in the subcriticality monitoring method, the control unit 21 acquires neutron count data based on neutrons from an unknown system measured by the neutron detector 25 (step S11).

Subsequently, based on the obtained neutron count data, the control unit 21 uses the calculation model for measurement to calculate the prompt neutron attenuation constant α as a measured value (step S12). Here, step S12 will be specifically described with reference to FIG. In FIG. 9, the vertical axis is the prompt neutron attenuation constant α, and the horizontal axis is the time. In step S12, a calculation model based on the Feynman α method is used as the measurement calculation model. As shown in FIG. 9, in step S12, first, an initial measurement value α _meas (0) is calculated using a calculation model based on the Feynman α method. Further, in step S12, the initial measured value α _meas (0) is changed with time in consideration of the time change of the neutron count rate (CR(0)/CR(t)) based on the neutron count data. A measured value α _meas (t) is calculated. Note that CR(0) is the initial number of neutrons, and CR(t) is the number of neutrons after a predetermined time has elapsed.

Then, the control unit 21 monitors whether the calculated measured value α _meas (t) is larger than the estimated critical limit value α _limit (step S13). Thus, in step S13, the quantified prompt neutron decay constant α can be used to monitor that the unknown system is subcritical. Then, in the subcriticality monitoring method, after executing step S13, the continuation of the monitoring of the unknown system is stopped, and the processing related to the subcriticality monitoring method ends.

As described above, the subcriticality evaluation method, the subcriticality monitoring method, the subcriticality evaluation device 10, and the subcriticality monitoring device 20 described in the present embodiment are understood as follows, for example.

A subcriticality evaluation method according to a first aspect is a subcriticality evaluation method for quantifying an estimated criticality limit value α _limit for evaluating whether an unknown system containing nuclear fuel is subcritical, Step S1 of selecting a plurality of experimental systems and acquiring system information of the selected plurality of critical experiment systems; and based on the acquired system information, using a computational model for evaluation, prompt neutron attenuation of the critical experiment systems. a step S2 of calculating a constant α; and a step S3 of calculating the estimated critical limit value α _limit of the prompt neutron decay constant α by statistically processing the plurality of calculated prompt neutron attenuation constants α. .

According to this configuration, it is possible to obtain a quantified estimated critical limit value α _limit that can be evaluated to be subcritical. Therefore, it is possible to evaluate whether an unknown system is subcritical using the prompt neutron decay constant α.

As a second aspect, in step S2 of calculating the estimated critical limit value α _limit , the estimated critical limit value α _limit is calculated by statistical processing based on equation (3).

According to this configuration, since the uncertainty of the prompt neutron attenuation constant α calculated using the evaluation calculation model can be taken into account by statistical processing, an appropriate estimated critical limit value α _limit can be calculated.

As a third aspect, in step S1 of acquiring the system information, the critical experiment system is selected, and at least one parameter that characterizes the system information is used as a parameter for selecting the critical experiment system. .

According to this configuration, since the critical experiment system can be selected with appropriate parameters, the prompt neutron decay constant α can be quantitatively evaluated favorably.

As a fourth aspect, in step S2 of calculating the prompt neutron attenuation constant, equation (2) is used as the calculation model for evaluation.

According to this configuration, it is possible to easily derive a calculation model for calculating the prompt neutron attenuation constant α by using the calculation model of the effective multiplication factor.

A subcriticality monitoring method according to a fifth aspect uses the estimated critical limit value α _limit quantified by the subcriticality evaluation method described above to monitor whether the unknown system is subcritical. A monitoring method comprising step S11 of acquiring neutron count data in the unknown system, and calculating the prompt neutron decay constant α as a measured value α _meas using a calculation model for measurement based on the neutron count data. and a step S13 of monitoring whether the calculated measured value α _meas is greater than the estimated critical limit value α _limit .

With this configuration, the quantified estimated critical limit value α _limit can be used to monitor the subcriticality of the unknown system based on the measured value α _meas . For this reason, it is possible to secure a margin for the estimated critical limit value α _limit in sub-criticality monitoring because it is not necessary to consider uncertainties and the like when converting to the effective multiplication factor. As a result, it becomes possible to improve the degree of freedom of operation at the time of state change for an unknown system.

As a sixth aspect, in step S12 of calculating the measured value, a calculation model based on the Feynman α method is used as the measurement calculation model.

According to this configuration, the prompt neutron attenuation constant α can be calculated with high accuracy using the neutron count data.

As a seventh aspect, in the step S12 of calculating the measured value, the neutron count rate ( _CR (0)/CR(t )), the time-varying measured value α _meas (t) is calculated, and in the monitoring step S13, it is constantly monitored that the unknown system is subcritical.

With this configuration, it is possible to constantly monitor whether the unknown system is subcritical.

A subcriticality evaluation device 10 according to an eighth aspect is a subcriticality evaluation device 10 that quantifies an estimated criticality limit value α _limit for evaluating whether an unknown system containing nuclear fuel is subcritical, , a control unit 11 for calculating the estimated critical limit value α _limit , wherein the control unit 11 selects a plurality of critical experiment systems and acquires system information of the selected plurality of critical experiment systems; Step S2 of calculating the prompt neutron damping constant α of the critical experiment system using a computational model for evaluation based on the obtained system information, and statistically processing the multiple prompt neutron damping constants α thus calculated, and a step S3 of calculating the estimated critical limit value α _limit of the prompt neutron attenuation constant α.

According to this configuration, it is possible to obtain a quantified estimated critical limit value α _limit that can be evaluated to be subcritical. Therefore, it is possible to evaluate whether an unknown system is subcritical using the prompt neutron decay constant α.

A subcriticality monitoring device 20 according to a ninth aspect uses the estimated criticality limit value α _limit evaluated by the subcriticality evaluation device 10 to monitor whether the unknown system is subcritical. A criticality monitoring device 20, comprising a neutron detector 25 for measuring neutrons from the unknown system, and monitoring for monitoring the unknown system by acquiring neutron count data, which is the detection result of the neutron detector 25. a control unit 21, wherein the monitoring control unit 21 acquires the neutron count data in step S11, and measures the prompt neutron attenuation constant α using a calculation model for measurement based on the neutron count data. A step S12 of calculating the value α _meas and a step S13 of monitoring whether the calculated measured value α _meas is greater than the estimated critical limit value α _limit are performed.

With this configuration, the quantified estimated critical limit value α _limit can be used to monitor the subcriticality of the unknown system based on the measured value α _meas . For this reason, it is possible to secure a margin for the estimated critical limit value α _limit in sub-criticality monitoring because it is not necessary to consider uncertainties and the like when converting to the effective multiplication factor. As a result, it becomes possible to improve the degree of freedom of operation at the time of state change for an unknown system.

10 subcriticality evaluation device 11 control unit 12 storage unit 13 output unit 14 input unit 20 subcriticality monitoring device 21 control unit 22 storage unit 23 output unit 24 input unit 25 neutron detector

Claims (9)

A subcriticality evaluation method for quantifying an estimated criticality limit for evaluating the subcriticality of an unknown system containing nuclear fuel, comprising:
selecting a plurality of critical experiment systems and acquiring system information of the selected plurality of critical experiment systems;
calculating a prompt neutron damping constant of the critical experiment system using an evaluation calculation model based on the acquired system information;
statistically processing the plurality of calculated prompt neutron decay constants to calculate the estimated critical limit value of the prompt neutron decay constant. 2. The subcriticality evaluation method according to claim 1, wherein in the step of calculating the estimated critical limit value, the estimated critical limit value is calculated by statistical processing based on formula (1).

3. The system according to claim 1 or 2, wherein in the step of obtaining system information, the critical experiment system is selected, and at least one parameter characterizing the system information is used as a parameter for selecting the critical experiment system. Subcriticality evaluation method. 4. The subcriticality evaluation method according to any one of claims 1 to 3, wherein in the step of calculating the prompt neutron attenuation constant, Equation (2) is used as the calculation model for evaluation.

A subcriticality monitoring method for monitoring whether the unknown system is subcritical using the estimated critical limit value quantified by the subcriticality evaluation method according to any one of claims 1 to 4 There is
obtaining neutron counting data in the unknown regime;
calculating the prompt neutron decay constant as a measured value based on the neutron count data using a calculation model for measurement;
and monitoring that the calculated measured value is greater than the estimated critical limit value. 6. The subcriticality monitoring method according to claim 5, wherein in the step of calculating the measured value, a calculation model based on Feynman's α method is used as the measurement calculation model. In the step of calculating the measured value, the time-varying measured value is calculated in consideration of the time change of the neutron count rate based on the neutron count data with respect to the calculated measured value,
7. The subcriticality monitoring method according to claim 5, wherein in said monitoring step, said unknown system is constantly monitored for subcriticality. A subcriticality evaluator for quantifying an estimated criticality limit for evaluating the subcriticality of an unknown system containing nuclear fuel, comprising:
A control unit that calculates the estimated critical limit value,
The control unit
selecting a plurality of critical experiment systems and acquiring system information of the selected plurality of critical experiment systems;
calculating a prompt neutron damping constant of the critical experiment system using an evaluation calculation model based on the acquired system information;
statistically processing the plurality of calculated prompt neutron decay constants to calculate the estimated critical limit value of the prompt neutron decay constant. A subcriticality monitoring device for monitoring whether the unknown system is subcritical using the estimated criticality limit value evaluated by the subcriticality evaluation device according to claim 8,
a neutron detector that measures neutrons from the unknown system;
a monitoring control unit that acquires neutron count data, which is the detection result of the neutron detector, and monitors the unknown system;
The monitoring control unit is
obtaining the neutron count data;
calculating the prompt neutron decay constant as a measured value based on the neutron count data using a calculation model for measurement;
and monitoring that the calculated measured value is greater than the estimated critical limit value.

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