JP7565883B2 - Subcriticality assessment method, subcriticality monitoring method, subcriticality assessment device, and subcriticality monitoring device - Google Patents

Description

This disclosure relates to a subcriticality assessment method, a subcriticality monitoring method, a subcriticality assessment device, and a subcriticality monitoring device.

Conventionally, a subcriticality measurement device that measures the subcriticality of a system that includes nuclear fuel is known (see, for example, Patent Document 1). The subcriticality measurement device is equipped with 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. The subcriticality of the system is then evaluated based on the effective multiplication factor and the subcriticality calculated by the subcriticality measurement device.

JP 2014-145720 A

As in Patent Document 1, it is generally difficult to directly measure the effective multiplication factor (and subcriticality). In measuring the effective multiplication factor (and subcriticality), a neutron detector is used to detect neutrons from the system, and the measured value of the effective multiplication factor (and subcriticality) is evaluated by combining the neutron counting data obtained by detection by the neutron detector with the calculated values of the dynamic characteristic parameters (delayed neutron fraction, neutron generation time, etc.).

When evaluating the measured value of the effective multiplication factor, the prompt neutron attenuation constant α, which is a measured value based on neutron counting data, is evaluated, and the prompt neutron attenuation constant α is converted to an 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 it is necessary to estimate the uncertainty largely. Furthermore, when the characteristic data of the system to be measured (geometry, composition, temperature, etc.) are known, the conversion factor of the dynamic characteristic parameters, etc. can be predicted with high accuracy, but in the case of a system whose characteristic data is unknown, it is necessary to estimate the uncertainty of the input conditions when calculating the conversion factor of the dynamic characteristic parameters, etc.

In this way, when evaluating subcriticality by converting the prompt neutron attenuation constant α into an effective multiplication factor, it is necessary to allow for a large degree of uncertainty. This makes it difficult to rationally evaluate whether an unknown system containing nuclear fuel is subcritical.

The present disclosure aims to provide a subcriticality assessment method, a subcriticality monitoring method, a subcriticality assessment device, and a subcriticality monitoring device that can quantitatively assess whether an unknown system containing nuclear fuel is subcritical.

The subcriticality assessment method disclosed herein is a subcriticality assessment method that quantifies an estimated critical limit value for assessing whether an unknown system containing nuclear fuel is subcritical, and executes the steps of selecting multiple critical experiment systems and acquiring system information for the selected multiple critical experiment systems, calculating the prompt neutron attenuation constant of the critical experiment system using an evaluation calculation model based on the acquired system information, and statistically processing the calculated multiple prompt neutron attenuation constants to calculate the estimated critical limit value of the prompt neutron attenuation constant.

The subcriticality monitoring method disclosed herein is a subcriticality monitoring method that uses the estimated criticality limit value quantified by the above-mentioned subcriticality evaluation method to monitor whether the unknown system is subcritical, and executes the steps of acquiring neutron counting data in the unknown system, calculating the prompt neutron decay constant as a measured value using a measurement calculation model based on the neutron counting data, and monitoring whether the calculated measured value is greater than the estimated criticality limit value.

The subcriticality evaluation device disclosed herein is a subcriticality evaluation device that quantifies an estimated critical limit value for evaluating whether an unknown system containing nuclear fuel is subcritical, and includes a control unit that calculates the estimated critical limit value. The control unit executes the steps of selecting multiple critical experiment systems and acquiring system information for the selected multiple critical experiment systems, calculating the prompt neutron attenuation constant of the critical experiment system using an evaluation calculation model based on the acquired system information, and statistically processing the calculated multiple prompt neutron attenuation constants to calculate the estimated critical limit value of the prompt neutron attenuation constant.

The subcriticality monitoring device disclosed herein is a subcriticality monitoring device that uses the estimated criticality limit value evaluated by the subcriticality evaluation device to monitor whether the unknown system is subcritical, and includes a neutron detector that measures neutrons from the unknown system, and a monitoring control unit that acquires neutron counting data that is the detection result of the neutron detector and monitors the unknown system, and the monitoring control unit executes the steps of acquiring the neutron counting data, calculating the prompt neutron decay constant as a measured value using a measurement calculation model based on the neutron counting data, and monitoring whether the calculated measured value is greater than the estimated criticality limit value.

This disclosure makes it possible to quantitatively evaluate whether an unknown system containing nuclear fuel is subcritical.

FIG. 1 is a block diagram that diagrammatically illustrates a subcriticality evaluation apparatus according to the present embodiment. FIG. 2 is a flowchart showing the subcriticality evaluation method according to the present embodiment. FIG. 3 is an explanatory diagram showing the critical experiment to be selected. FIG. 4 is a diagram showing parameters for selecting a critical experiment. FIG. 5 is an explanatory diagram regarding the evaluation calculation model. FIG. 6 is a distribution diagram of prompt neutron attenuation constants. FIG. 7 is a block diagram that diagrammatically illustrates the subcriticality monitoring device according to this embodiment. FIG. 8 is a flowchart showing the sub-criticality monitoring method according to the present embodiment. FIG. 9 is a graph showing the change over time of the measured prompt neutron decay constant.

Below, an embodiment of the present invention will be described in detail with reference to the drawings. Note that the present invention is not limited to this embodiment. Furthermore, the components in the following embodiment include those that are easily replaceable by a person skilled in the art, or those that are substantially the same. Furthermore, the components described below can be combined as appropriate, and when there are multiple embodiments, the respective embodiments can also be combined.

[Embodiment]
The subcriticality evaluation method and the subcriticality evaluation device 10 according to the present embodiment are a method and a device for quantifying an estimated criticality limit value for evaluating whether an unknown system is subcritical in a system in which the geometric shape and composition conditions of the nuclear fuel are unknown. As the estimated criticality limit value, a prompt neutron attenuation constant α is used, and is a value representing an upper limit value of the prompt neutron attenuation constant α at which the system of interest is estimated to be in a critical state. The prompt neutron attenuation constant α is a time constant when the number of neutrons exponentially decays when neutrons are implanted in a pulsed manner into a subcritical system. When the contribution of delayed neutrons can be ignored, the prompt neutron attenuation constant α means that the system is subcritical when α>0, that the system is critical when α=0, and that the system is supercritical when α<0. In other words, when α>0, the number of neutrons in the system exponentially decays. Also, when α=0, the number of neutrons in the system becomes constant. Furthermore, when α<0, the number of neutrons in the system amplifies exponentially.

(Subcriticality evaluation device)
A subcriticality evaluation apparatus 10 will be described with reference to Fig. 1. Fig. 1 is a block diagram showing a schematic representation of the subcriticality evaluation apparatus according to the present embodiment. The subcriticality evaluation apparatus 10 includes a control unit 11, a storage unit 12, an output unit 13, and an input unit 14.

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

(Subcriticality evaluation method)
Next, a subcriticality evaluation method executed by the subcriticality evaluation device 10 will be described with reference to Fig. 2 to Fig. 6. Fig. 2 is a flow chart of the subcriticality evaluation method according to this embodiment. Fig. 3 is an explanatory diagram showing a critical experiment to be selected. Fig. 4 is a diagram showing parameters for selecting a critical experiment. Fig. 5 is an explanatory diagram of an evaluation calculation model. Fig. 6 is a distribution diagram of prompt neutron attenuation constants.

The subcriticality evaluation method is a method of calculating a prompt neutron attenuation constant α, which is a quantified estimated critical limit value. As shown in FIG. 2, in the subcriticality evaluation method, multiple critical experiment systems are selected, and system information for the multiple critical experiment systems is obtained (step S1). In step S1, the input unit 14 obtains the multiple system information as input information, and the obtained multiple system information is stored in the memory unit 12.

Here, we will explain the multiple critical experiments that are selected. The critical experiments used in the subcriticality assessment are selected from a database of accumulated critical experiments. As shown in Figure 3, the range of the selected critical experiments is wider than the assumed range of unknown systems, and includes unknown systems. The range of the critical experiments is determined using five parameters as indicators, and these parameters serve as indicators for selecting the critical experiments.

As shown in Figure 4, specific parameters for selecting a critical experiment include the enrichment of nuclear fuel, the Pu content of the nuclear fuel, the size of the nuclear fuel, the fuel to moderator volume ratio, and the type of structural material nuclide. Note that it is sufficient to include at least one parameter that characterizes the system information, and the parameter candidates are not limited to those given in this specific example.

In step S1, multiple critical experiments are selected and system information for the multiple critical experiments is acquired. The control unit 11 then calculates the prompt neutron attenuation constant α for each critical experiment using an evaluation calculation model based on the system information for each critical experiment (step S2).

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

In step S2, the multiple prompt neutron attenuation constants α calculated using equation (2) have uncertainties and therefore have a distribution as shown in FIG. 6. Therefore, after executing step S2, the control unit 11 performs statistical processing on 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 Figure 6, the vertical axis represents the number of samples, and the horizontal axis represents the prompt neutron decay constant α [1/sec]. As shown in Figure 6, the calculated multiple prompt neutron decay constants α are distributed such that the number of samples increases near the average value, and decreases as the number of samples moves away from the average value.

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

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

(Subcriticality monitoring device)
Next, the subcriticality monitoring device 20 will be described with reference to Fig. 7 to Fig. 9. Fig. 7 is a block diagram showing a schematic diagram of the subcriticality monitoring device according to the present embodiment. The subcriticality monitoring device 20 has a control unit (monitoring control unit) 21, a memory unit 22, an output unit 23, an input unit 24, and a neutron detector 25.

The control unit 21, like the control unit 11, includes an integrated circuit such as a CPU (Central Processing Unit). The control unit 21 executes a process of calculating measurement values for performing subcriticality monitoring of an unknown system using a measurement calculation model based on input information. The storage unit 22, like the storage unit 12, is an arbitrary storage device such as a semiconductor storage device or a magnetic storage device. This storage unit 22 stores various programs for executing various processes and various data used in the processes. The various programs are a measurement calculation model for calculating measurement values, and the various data are an estimated critical limit value calculated by the subcriticality monitoring device 20, input information input to the measurement calculation model, and the like. 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 a mouse.

The neutron detector 25 detects neutrons emitted from an unknown system. The neutron detector 25 is connected to the input unit 24, which acquires information from the neutron detector 25 as neutron counting data.

(Subcriticality monitoring method)
Next, a subcriticality monitoring method executed by the subcriticality monitoring device 20 will be described with reference to Fig. 8 and Fig. 9. Fig. 8 is a flowchart of the subcriticality monitoring method according to this embodiment. Fig. 9 is a graph showing the time change of the prompt neutron decay constant, which is a measured value.

In the subcriticality monitoring method, the unknown system is monitored for subcriticality based on measured values obtained by measurement, using the estimated critical limit value α _limit calculated by the subcriticality monitoring device 20 as a threshold value. As shown in Fig. 8, in the subcriticality monitoring method, the control unit 21 obtains neutron counting data based on neutrons from the unknown system measured by the neutron detector 25 (step S11).

Next, the control unit 21 calculates the prompt neutron decay constant α as a measured value using a measurement calculation model based on the acquired neutron counting data (step S12). Here, step S12 will be specifically described with reference to FIG. 9. In FIG. 9, the vertical axis represents the prompt neutron decay constant α, and the horizontal axis represents 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. In addition, in step S12, a time-varying measurement value α _meas (t) is calculated with respect to the initial measurement value α _meas (0) in consideration of the time change of the neutron counting rate (CR(0)/ _CR (t)) based on the neutron counting data. Note that CR(0) is the number of initial 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 greater than the estimated critical limit value α _limit (step S13). In this way, in step S13, it is possible to monitor whether the unknown system is subcritical by using the quantified prompt neutron attenuation constant α. Then, in the subcriticality monitoring method, after executing step S13, the process related to the subcriticality monitoring method is terminated by stopping the continuation of monitoring the unknown system.

As described above, the subcriticality assessment method, subcriticality monitoring method, subcriticality assessment device 10, and subcriticality monitoring device 20 described in this embodiment can be understood, for example, as follows.

A subcriticality assessment method according to a first aspect is a subcriticality assessment method for quantifying an estimated critical limit value α _limit for assessing whether an unknown system including nuclear fuel is subcritical, and includes the steps of: selecting a plurality of critical experiment systems and acquiring system information for the selected plurality of critical experiment systems; calculating a prompt neutron attenuation constant α of the critical experiment systems using an evaluation calculation model based on the acquired system information; and calculating the estimated critical limit value α _limit of the prompt neutron attenuation constant α by statistically processing the calculated plurality of 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 used to evaluate whether a system is subcritical. Therefore, it is possible to evaluate whether an unknown system is subcritical by using the prompt neutron attenuation 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, the uncertainty of the prompt neutron attenuation constant α calculated using the evaluation calculation model can be taken into consideration by statistical processing, so that an appropriate estimated critical limit value α _limit can be calculated.

In 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.

This configuration allows the critical experiment system to be selected with appropriate parameters, making it possible to perform a quantitative evaluation of the prompt neutron attenuation constant α.

In the fourth aspect, in step S2 of calculating the prompt neutron decay constant, formula (2) is used as the evaluation calculation model.

With this configuration, a calculation model for calculating the prompt neutron attenuation constant α can be easily derived using a calculation model for the effective multiplication factor.

A subcriticality monitoring method according to a fifth aspect is a subcriticality monitoring method for monitoring whether the unknown system is subcritical by using the estimated critical limit value α _limit quantified by the above-mentioned subcriticality evaluation method, and includes the steps of: acquiring neutron counting data in the unknown system, calculating the prompt neutron attenuation constant α as a measured value α _meas using a measurement calculation model based on the neutron counting data, and monitoring whether the calculated measured value α _meas is greater than the estimated critical limit value α _limit .

According to this configuration, the quantified estimated critical limit value α _limit can be used to monitor the subcriticality of an unknown system based on the measured value α _meas . Therefore, since there is no need to consider the uncertainty when converting to the effective multiplication factor, it is possible to secure a margin for the estimated critical limit value α _limit in the subcriticality monitoring. This makes it possible to improve the degree of freedom of operation when the state of an unknown system changes.

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

This configuration allows the prompt neutron attenuation constant α to be calculated with high accuracy using neutron counting data.

As a seventh aspect, in step S12 of calculating the measurement value, the time-varying measurement value α _meas (t) is calculated by taking into account the time change of the neutron counting rate (CR(0)/CR(t)) based on the neutron counting data for the calculated measurement value α _meas (0), and in step S13 of monitoring, it is constantly monitored whether the unknown system is sub-critical.

This configuration makes it possible to constantly monitor whether an unknown system is subcritical.

The subcriticality evaluation device 10 according to the eighth aspect is a subcriticality evaluation device 10 that quantifies an estimated critical limit value α _limit for evaluating whether an unknown system including nuclear fuel is subcritical, and includes a control unit 11 that calculates the estimated critical limit value α _limit . The control unit 11 executes the following steps: a step S1 of selecting a plurality of critical experiment systems and acquiring system information of the selected plurality of critical experiment systems; a step S2 of calculating a prompt neutron attenuation constant α of the critical experiment system using an evaluation calculation model based on the acquired system information; and a step S3 of statistically processing the calculated plurality of prompt neutron attenuation constants α to calculate 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 used to evaluate whether a system is subcritical. Therefore, it is possible to evaluate whether an unknown system is subcritical by using the prompt neutron attenuation constant α.

The subcriticality monitoring device 20 according to the ninth aspect is a subcriticality monitoring device that monitors whether the unknown system is subcritical by using the estimated critical limit value α _limit evaluated by the subcriticality evaluation device 10 described above, and includes a neutron detector 25 that measures neutrons from the unknown system, and a monitoring control unit 21 that acquires neutron counting data that is the detection result of the neutron detector 25 and monitors the unknown system. The monitoring control unit 21 executes the following steps: a step S11 of acquiring the neutron counting data; a step S12 of calculating the prompt neutron decay constant α as a measured value α _meas based on the neutron counting data using a measurement calculation model; and a step S13 of monitoring whether the calculated measured value α _meas is greater than the estimated critical limit value α _limit .

According to this configuration, the quantified estimated critical limit value α _limit can be used to monitor the subcriticality of an unknown system based on the measured value α _meas . Therefore, since there is no need to consider the uncertainty when converting to the effective multiplication factor, it is possible to secure a margin for the estimated critical limit value α _limit in the subcriticality monitoring. This makes it possible to improve the degree of freedom of operation when the state of an unknown system changes.

REFERENCE SIGNS LIST 10 Subcriticality evaluation device 11 Control unit 12 Memory unit 13 Output unit 14 Input unit 20 Subcriticality monitoring device 21 Control unit 22 Memory unit 23 Output unit 24 Input unit 25 Neutron detector

Claims (8)

A subcriticality assessment method for quantifying an estimated criticality limit value for assessing whether an unknown system including nuclear fuel is subcritical, comprising:
selecting a plurality of critical experiment systems and acquiring system information of the selected plurality of critical experiment systems;
Calculating a prompt neutron attenuation constant of the critical experiment system using an evaluation calculation model based on the acquired system information;
and performing statistical processing on the calculated plurality of prompt neutron attenuation constants to calculate the estimated critical limit value of the prompt neutron attenuation constant,
A subcriticality evaluation method , in which in the step of calculating the estimated critical limit value, the estimated critical limit value is calculated by statistical processing based on equation (1) .

The subcriticality evaluation method according to claim 1, wherein in the step of acquiring the 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. 3. The subcriticality evaluation method according to claim 1, wherein in the step of calculating the prompt neutron decay constant, equation (2) is used as the evaluation calculation model.

A subcriticality monitoring method for monitoring whether the unknown system is subcritical by using the estimated critical limit value quantified by the subcriticality evaluation method according to any one of claims 1 to 3 , comprising:
acquiring neutron counting data in the unknown system;
calculating the prompt neutron decay constant as a measured value using a measurement calculation model based on the neutron counting data;
monitoring that the calculated measured value is greater than the estimated critical limit value. 5. The subcriticality monitoring method according to claim 4 , wherein in the step of calculating the measured value, a calculation model based on the Feynman alpha method is used as the measurement calculation model. In the step of calculating the measurement value, the measurement value that changes over time is calculated in consideration of a time change of a neutron counting rate based on the neutron counting data for the calculated measurement value,
6. The subcriticality monitoring method according to claim 4 , wherein said monitoring step constantly monitors whether said unknown system is subcritical. A subcriticality assessment device that quantifies an estimated criticality limit value for assessing whether an unknown system including nuclear fuel is subcritical, comprising:
A control unit is provided for calculating the estimated critical limit value,
The control unit is
selecting a plurality of critical experiment systems and acquiring system information of the selected plurality of critical experiment systems;
Calculating a prompt neutron attenuation constant of the critical experiment system using an evaluation calculation model based on the acquired system information;
and performing statistical processing on the calculated plurality of prompt neutron attenuation constants to calculate the estimated critical limit value of the prompt neutron attenuation constant,
In the step of calculating the estimated critical limit value, the estimated critical limit value is calculated by statistical processing based on equation (3) .

A subcriticality monitoring apparatus that monitors whether the unknown system is subcritical by using the estimated critical limit value evaluated by the subcriticality evaluation apparatus according to claim 7 ,
a neutron detector for measuring neutrons from the unknown system;
a monitoring control unit that acquires neutron counting data that is a detection result of the neutron detector and monitors the unknown system,
The monitoring control unit includes:
acquiring said neutron counting data;
calculating the prompt neutron decay constant as a measured value using a measurement calculation model based on the neutron counting data;
monitoring whether the calculated measured value is greater than the estimated critical limit value.

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