JP7614979B2 - Neutron monitoring device and method for managing criticality of spent nuclear fuel - Google Patents

Description

Embodiments of the present invention relate to a neutron monitoring device and a method for managing criticality of spent nuclear fuel.

Spent nuclear fuel used in nuclear power plants is generally cooled for a specified period of time, then stored in transport containers and transported to an intermediate storage facility or a reprocessing facility. Spent nuclear fuel sent to this intermediate storage facility is further cooled for several decades before being permanently disposed of or sent to a reprocessing facility.

At the reprocessing facility, the spent nuclear fuel is removed from the transport container and transport data from the power plant is compared with the actual item, and non-destructive testing such as burnup is conducted to confirm that the spent nuclear fuel was transported correctly. After being stored for an appropriate period of time, the spent nuclear fuel is reprocessed according to a prescribed schedule.

In the reprocessing process at a reprocessing facility, first, rod-shaped spent fuel rods, which have nuclear fuel pellets packed inside their cladding tubes, are sheared to lengths of about 3-5 cm and dissolved in boiling nitric acid to become a fuel solution (aqueous phase). However, the cladding tubes do not dissolve and are treated as dissolved residue (hulls).

The concentration of the fuel solution is adjusted in accordance with standards for ensuring criticality safety, after which fission products and transplutonium elements are removed. The remaining uranium (U) and plutonium (Pu) are then separated and refined in a TBP (tributyl phosphate) organic phase. These steps are carried out over a multi-stage process, with many processing tanks and towers at each stage.

In the reprocessing process at the reprocessing facility, the equipment that constantly handles nuclear fuel materials such as plutonium and uranium is designed to have an effective neutron multiplication factor of less than 1 to ensure that it does not go critical. That is, each of these devices is designed to limit the shape, dimensions, volume, etc., so that it always remains subcritical even in the face of possible changes, taking into consideration the acidity of the solution supplied, the concentration of nuclear fuel materials such as plutonium and uranium in it, and even abnormalities in the concentration of plutonium and uranium components in the nitric acid aqueous solution and organic solvent.

On the other hand, the equipment attached to each of the above devices that controls criticality based on plutonium concentration is designed with relaxed restrictions on the shape, dimensions, and volume of the equipment, taking into account processing efficiency, since only small amounts of plutonium or almost no plutonium flow into the equipment during normal operation.

However, in the unlikely event that plutonium were to leak for some reason and cause criticality to occur, measures have been taken such as installing neutron and gamma ray detectors in various locations to detect increases in radiation levels and sound an alarm to alert operators and other personnel to the danger, or halting part of the reprocessing process at the discretion of the operators.

Plutonium is a particularly important nuclide in terms of criticality control in the reprocessing process, and as mentioned above, conventionally, the level of neutron emissions from plutonium has been measured to ensure subcriticality, but the number of neutrons emitted from plutonium is not necessarily proportional to the concentration of plutonium. This is because the number of neutrons emitted from plutonium varies greatly depending on the plutonium isotope composition ratio, and the plutonium isotope composition ratio also varies greatly depending on the initial uranium enrichment and irradiation history of the reprocessed fuel.

In addition, when reprocessing spent mixed oxide (MOX) fuel, the amount of plutonium handled may increase, and the range of plutonium isotope compositions may also become wider. In the case of MOX fuel, plutonium, not uranium, is the fissile material. In addition to the fissile isotopes Pu-239 and Pu-241, plutonium also contains Pu-240 and Pu-242, which are less likely to undergo fission. There is a certain degree of variation in the plutonium isotope composition in new MOX fuel. This is because the operational history of the spent uranium fuel causes variation in the plutonium isotope composition produced. For example, it is known that higher burnup uranium fuel contains a larger proportion of Pu-240 and Pu-242 in the total Pu isotopes than lower burnup uranium fuel. In addition, when MOX fuel is manufactured, the amount of all plutonium isotopes in the fuel (initial plutonium enrichment) is adjusted to preserve the fissile isotopes in Pu (Pu-239 and Pu-241) in order to suppress variation in reactivity. This is called "reactivity compensation design." As a result, the variation in the proportion of non-fissile Pu such as Pu-240 and Pu-242 increases even more.

In addition, spent fuel contains small amounts of elements such as curium, which emit more neutrons than plutonium. Normally, these elements are removed in upstream processes, but if they are mixed in during this process due to some process abnormality, the neutron count rate will increase, which could cause a false alarm. The above-mentioned curium and other contaminants are also present in high concentrations in MOX fuel, which could increase the risk of false alarms.

For this reason, the degree of subcriticality (subcriticality) cannot be uniquely determined from the number of neutrons produced, and in general, the most conservative value is adopted when performing criticality safety management, which means that the largest possible margin must be taken.

As a result, the neutron generation rate level corresponding to the criticality alarm setting had to be set to the safest level, i.e., the lowest conceivable neutron generation rate. With this setting, in some cases the neutron generation rate could reach the alarm level even in a fully subcritical state, meaning that the reprocessing facility would have to be shut down each time this occurred, potentially reducing the operating efficiency of the facility.

Conventional methods involve estimating the plutonium isotopic composition in some way to improve the accuracy of the relationship between plutonium concentration and neutron count, but they have issues such as the need for additional measuring and analytical equipment, and the difficulty of dealing with fluctuations in the neutron count rate due to the inclusion of curium, etc.

The neutron effective multiplication factor k is used as an indicator of subcriticality. k is the ratio of neutron production to neutron annihilation; k = 1 indicates criticality, and k < 1 indicates subcriticality. The unit dollar is sometimes used to express subcriticality. Using the delayed neutron production rate β, k/β is called a dollar. Even if the fuel actually becomes critical, explosive energy is not released immediately. When k exceeds β, it becomes an uncontrollable state called "prompt criticality". At this time, a reactivity of 1 dollar is said to have been input. Sometimes cents are used as 1/100 of a dollar. When subcritical, k < 1, but when k is small and far from 1, the subcriticality is said to be "deep", and when k is close to 1, the subcriticality is said to be "shallow".

Currently known subcriticality measurement techniques include:
(1) Negative period method, (2) Control rod drop method, (3) Compensation method, (4) Neutron source multiplication method, (5) Inverse dynamics method, (6) Reactor noise analysis method, (7) Pulsed neutron source method,
Among these methods, methods (1), (2), and (3) are used for reactors that go critical, and are not suitable for reprocessing processes that are always subcritical. Method (7) allows for absolute measurement of the degree of subcriticality without bringing the reactor to a critical state, but requires an accelerator to inject neutron pulses into the reactor, which necessitates new large additional equipment and is difficult to apply to existing reprocessing processes. For these reasons, methods (4) to (6) are more suitable.

The neutron source multiplication method (4) can measure subcriticality down to a depth of several tens of nuclei, but requires calibration in a known subcritical state. The technology for measuring neutrons from plutonium and monitoring subcriticality shown in the prior art corresponds to the neutron source multiplication method (4), and is usually calibrated periodically using a calibration neutron source. However, as mentioned above, there is an issue of false alarms due to fluctuations in neutron intensity, such as changes in plutonium composition or the inclusion of curium.

In addition, it has been reported, for example in Non-Patent Document 1, that the inverse dynamics method (5) or the reactor noise analysis method (6) can be used to provide the calibration value.

The inverse dynamics method (5) estimates the degree of subcriticality from the time change when the subcritical state fluctuates. For example, Patent Document 2 describes a method of estimating the neutron source strength from time series data and estimating the degree of subcriticality. In addition, since the sensitivity increases as the criticality is approached, it is suitable for warning when criticality is approached rapidly.

As a method simpler than the inverse dynamics method, period monitoring is also suitable for warning when criticality is approached. The period is defined as the time when the neutron count rate becomes e times higher. Although it is difficult to directly calculate the subcriticality from the period, it is possible to detect the approach of criticality by, for example, issuing an alarm when the period becomes shorter than about 100 seconds. Period monitoring is also used in the operation of nuclear reactors, so it is a proven method. Since it does not require the processing of complex time-series data, as in the inverse dynamics method, it can be configured with a simple circuit. It can also be used in conjunction with the inverse dynamics method. On the other hand, both the inverse dynamics method and the period method are suitable when criticality is approached or when the subcriticality changes over time, but it is difficult to apply to deep subcriticality or when the change in subcriticality over time is small.

The reactor noise analysis methods in (6) include (8) the Rossi alpha method, (9) the Feynman alpha method, (10) the breakpoint frequency method, and (11) the Mihalzo method. The reactor noise analysis method used in Non-Patent Document 1 is the breakpoint frequency method in (10).

The Rossi α method in (8) obtains the prompt neutron attenuation constant α from the distribution of the time interval τ between neutron pulses observed in a nuclear reactor, which deviates from the Poisson distribution and has a component proportional to e ^-ατ . The relationship between the prompt neutron attenuation constant α and the neutron multiplication factor k is α＝{1-(1-β)k}/L ……(1)
The neutron multiplication factor is obtained by giving the delayed neutron production rate β and the prompt neutron lifetime L (see, for example, "Nuclear Reactor Physics Experiments" Corona Publishing).

The Feynman α method in (9) uses the fact that the variance-to-mean ratio of the count value M of a neutron pulse within a certain time width deviates from "1" in the case of a Poisson distribution to obtain the prompt neutron decay constant α in the same way as the Rossi α method in (8) (see, for example, Non-Patent Document 2).

The break point frequency method (10) utilizes the fact that the frequency characteristics of the neutron count rate are determined by the reactor transfer function in a subcritical state, and that the break point frequency coincides with the prompt neutron attenuation constant α.

In this way, all of methods (8) to (10) calculate the prompt neutron decay constant α, and then input the delayed neutron production rate β and the prompt neutron lifetime L into equation (1) to obtain the neutron multiplication factor. In contrast, the Mihalzo method (11) allows for absolute measurement of the neutron multiplication factor, but requires the installation of a special neutron detector with a built-in Cf-252 neutron source in the reactor core and the target system, which requires the introduction of new equipment into the existing reprocessing process, making it difficult to apply.

All of the above technologies were developed for the purpose of measuring the neutron multiplication factor of a nuclear reactor, but Patent Document 1 discloses a technology for monitoring criticality safety by applying the Rossi alpha method (8) or the Feynman alpha method (9) when storing spent fuel assemblies removed from a nuclear reactor in a storage rack or transport/storage container.

The delayed neutron fraction β and prompt neutron lifetime L are given in advance in the analysis. In the case of the reprocessing process, the shape of the dissolution tank and other equipment is fixed, and the ratio of the solution to the fissile material is also almost constant, so the changes in β and L are small, and the impact of errors caused by giving them in the analysis is thought to be small.

The above methods (8) to (10) can estimate the degree of subcriticality by processing time-series data from existing neutron detectors, so there is no need to introduce new equipment. Of the methods (8) to (10), only the Feynman alpha method (9) is considered applicable to deep subcriticality, and is a method suitable for the reprocessing process.

On the other hand, as described in Patent Document 1, the Feynman α method requires fitting operations from the distribution related to the measurement time of the coefficient Y obtained from the variance and average to derive the attenuation constant α, and in order to improve statistical accuracy, fitting requires several minutes to several tens of minutes, resulting in a time delay. For this reason, it is difficult to immediately determine whether there is an abnormality when an alarm is issued.

JP 2005-106611 A JP 2014-137259 A Japanese Patent Application Publication No. 3-237392 Patent Registration No. 3524203

US ORNL Report, ORNL-TM-3716, 1973. Kyoto University Reactor KUCA Experimental Textbook "Neutron Correlation Experiment Feynman-α Method", www.rri.kyoto-u.ac.jp/CAD/Insei/2003Text/Chap4_7-2_r0.pdf. Report of the Japan Atomic Energy Research Institute, JAERI 1187, pp. 75-78, 1970.

The present invention was made in consideration of the above-mentioned conventional circumstances, and aims to provide a neutron monitor and criticality control method that can determine without time delay whether a change in the neutron count rate is due to a change in subcriticality, a change in the isotopic composition of plutonium, or a change in the number of neutrons generated due to interfering nuclides such as curium, thereby improving the operation rate of reprocessing facilities.

A neutron monitor device according to an embodiment includes a neutron count rate measuring means for measuring a neutron count rate from plutonium in a reprocessing process in a reprocessing facility , a plutonium concentration monitoring means for calculating a plutonium concentration from the neutron count rate and generating an alarm if the plutonium concentration exceeds a set value, a period monitoring means for calculating a period from time series data of the neutron count rate after the alarm is generated by the plutonium concentration monitoring means and determining that an abnormality has occurred and stopping the process if the period is shorter than a set value, and a neutron count rate measuring means for measuring a neutron count rate from plutonium in a reprocessing process in a reprocessing facility. a variance-to-mean ratio monitoring means for calculating a variance-to-mean ratio, which is the ratio of the variance to the mean of a plurality of neutron count rate data for a certain measurement time width, from time-series data of the neutron count rate, and determining that an abnormality has occurred and stopping the process if the variance-to-mean ratio exceeds a set value; and a means for calculating a prompt neutron decay constant α based on a reactor noise method if the variance-to-mean ratio calculated by the variance-to-mean ratio monitoring means is equal to or less than a set value, and calculating a neutron multiplication factor using the prompt neutron decay constant α, a delayed neutron fraction β obtained in advance by analysis, and a prompt neutron lifetime L to determine the degree of subcriticality and detect the abnormality .

According to the embodiment, when there is a change in the neutron count rate, it is possible to determine without time delay whether the cause is a change in subcriticality, a change in the isotopic composition of plutonium, or a change in the number of neutrons generated due to interfering nuclides such as curium, and it is possible to provide a neutron monitor device and a criticality control method that can improve the operation rate of reprocessing facilities.

1 is a block diagram showing a schematic configuration of a neutron monitor device and a method for criticality control of spent nuclear fuel according to a first embodiment; 1 is a flow chart showing the procedure of a neutron monitor device and a method for criticality management of spent nuclear fuel according to a first embodiment; FIG. 11 is a block diagram showing a schematic configuration of a neutron monitor device and a method for controlling criticality of spent nuclear fuel according to a second embodiment. FIG. 11 is a flow chart showing the procedure of a neutron monitor device and a method for criticality management of spent nuclear fuel according to a second embodiment. Graph showing an example of experimental results obtained in the critical experiment facility.

Below, the neutron monitor device and the method for criticality management of spent nuclear fuel according to the embodiment will be described with reference to the drawings.

Figures 1 and 2 show the configuration of an example in which a neutron monitor device and a method for criticality control of spent nuclear fuel according to an embodiment are applied to monitoring the plutonium concentration in a dissolution tank in a reprocessing facility, with Figure 1 being a block diagram and Figure 2 being a flow diagram.

As shown in FIG. 1, the dissolution tank 3 is provided with two detectors, neutron detector 1 and neutron detector 2. The neutron monitor device according to the embodiment also includes a neutron count rate measurement unit 101, a plutonium concentration monitoring unit 102, a time series data analysis unit 103, a period monitoring unit 104, a variance-to-mean ratio monitoring unit 105, a Feynman alpha monitoring unit 106, and a subcriticality calculation unit 107.

In the normal process, neutrons are generated from plutonium, and the plutonium composition is within a certain range, so the plutonium concentration and the neutron count rate are proportional. For this reason, a neutron count rate corresponding to the plutonium concentration to be restricted is preset, and the neutron count rate is obtained from the detection signals obtained from neutron detectors 1 and 2 by neutron count rate measurement unit 101 (step 201 in FIG. 2), and the neutron count rate is compared with the set value and monitored by plutonium concentration monitoring unit 102 (step 202 in FIG. 2).

If the neutron count rate is equal to or lower than the set value, it is determined that there is no abnormality and monitoring continues (Yes in step 202 in FIG. 2). On the other hand, if the neutron count rate exceeds the set value (No in step 202 in FIG. 2), an alarm is generated (step 203 in FIG. 2).

After an alarm is issued, the time series data of the neutron count rate is analyzed by the time series data analysis unit 103 (step 204 in FIG. 2), and the period monitoring unit 104 monitors the period. Then, the period is compared with a set value, and if the period is faster than the set value (Yes in step 205 in FIG. 2), it is determined that an abnormality has occurred and the process is stopped (step 206 in FIG. 2).

On the other hand, if the period is equal to or less than the set value (No in step 205 in FIG. 2), the variance-to-mean ratio monitor 105 calculates the variance-to-mean ratio (step 207 in FIG. 2) and monitors it. Then, if the variance-to-mean ratio is compared with the set value and the variance-to-mean ratio is higher than the set value (Yes in step 208 in FIG. 2), it is determined that an abnormality has occurred and the process is stopped (step 209 in FIG. 2).

On the other hand, if the variance-to-mean ratio is equal to or less than the set value (No in step 208 in FIG. 2), it is determined that there is no abnormality and no change in subcriticality. However, without stopping the process, as a precaution, the Feynman alpha monitoring unit 106 starts analysis using the Feynman alpha method over a measurement time (step 210 in FIG. 2), and the subcriticality calculation unit 107 calculates the subcriticality (step 211 in FIG. 2).

In monitoring Feynman α, as shown in FIG. 5 described later, accurate distribution of Y values and measurement time intervals (gate width) is required to derive the α value, but Ysat itself, at which the Y value saturates when the gate width becomes large, also changes significantly. Ysat is the variance-to-mean ratio minus 1, and the variance-to-mean ratio also behaves in a similar manner. Therefore, as in this embodiment, an abnormality can be detected simply by monitoring the variance-to-mean ratio over a certain gate width, for example, 0.1 seconds. In this case, a judgment is possible even with measurements over a period of several tens of seconds, and an abnormality can be detected without time delay.

A specific processing method of the Feynman α method will be described below.
The frequency of radioactive decay is based on the Poisson distribution, but it is known that it deviates from the Poisson distribution when multiple neutrons are generated simultaneously or when a chain reaction occurs due to fissile material (see, for example, Non-Patent Document 2). The ratio of the variance to the mean (variance-to-mean ratio) is used as an index of deviation from the Poisson distribution. If the neutron count for a certain time interval t _i to t _i +Δt is M(i) and there are imax pieces of data, the mean, variance, and variance/mean ratio can be expressed as follows:

average

Dispersion

Variance/mean ratio

Y=Ysat[1-{1-exp(-αΔt)}/αΔt]
where Ysat is a constant.

The prompt neutron attenuation constant α is obtained by plotting Δt and the obtained Y and fitting it with the above function. The graph in Figure 5 shows the results of an example of an experiment performed at the Toshiba Critical Assembly (NCA), and it can be seen that the prompt neutron attenuation constant α can be obtained from the relationship between the gate width (Δt) and Y. The water level shown in the figure indicates the water level (mm) of the core tank of the critical experiment assembly. The higher the water level, the higher the neutron multiplication factor, and a water level of 1000 is closer to the critical state than 900. The gate width corresponds to the above-mentioned Δt. The constant C can also be found at the same time by fitting.

The neutron multiplication factor k is obtained using the delayed neutron fraction β and prompt neutron lifetime L previously obtained by neutron transport analysis, and the above-mentioned relational expression (1) shown below.
α={1-(1-β)k}/L (1)

This method does not depend on the absolute value of the neutron count rate, and therefore has the advantage of being able to estimate the neutron multiplication factor k without being affected by the influence of interfering nuclides such as curium or fluctuations in the neutron count rate due to variations in the plutonium composition.

In Figure 1, the time series data is analyzed using the Feynman alpha method, but the Rossi alpha method or the breakpoint frequency method may also be used. If a special neutron detector such as a Cf-252 neutron source is available, the Mihalzo method may also be used.

If the subcriticality fluctuates compared to the estimated value of subcriticality made in advance under normal circumstances, this may be due to an increase in the plutonium concentration itself. If there is no change in the subcriticality, this may be due to an interfering nuclide or an unexpected plutonium composition.

By analyzing multiple pieces of information, the cause can be identified early, leading to a quick recovery even if a decision is made to halt the process.

In addition, analysis of time-series data can be run at all times as a backup and not normally used to check for process abnormalities, but only when the neutron count rate increases abnormally.

Figures 3 and 4 show a modified example (second embodiment) of the embodiment shown in Figures 1 and 2, and parts corresponding to Figures 1 and 2 are given the same reference numerals. In the embodiment shown in Figures 3 and 4, in addition to the configuration of the embodiment shown in Figures 1 and 2, an inverse dynamics monitoring unit 108 that performs inverse dynamics monitoring and a subcriticality calculation unit 109 that calculates the subcriticality based on the results of the inverse dynamics monitoring are provided (steps 212 and 213 in Figure 4). The subcriticality can also be calculated by the inverse dynamics method, but the sensitivity is low when the subcriticality is deep. When the subcriticality is shallow, that is, when the neutron multiplication factor k is close to 1, the sensitivity is high and the response is fast. On the other hand, reactor noise analysis requires accumulation of counts, so it takes several minutes to several tens of minutes. Therefore, when the neutron multiplication factor k is close to 1, it is effective to calculate the subcriticality by inverse dynamics monitoring.

Also, when calculating the period, the counting rate may fluctuate greatly and the correct value may not be calculated. In such cases, the time fluctuation can be mitigated by using a first-order lag filter or a moving average filter.
For example, in the case of a first-order lag filter, the following processing is performed.
N(i)=(1-w)・n(i)+w・N(i-1)
N(i): Coefficient rate after the i-th filter process n(i): Coefficient rate before the i-th filter process w: First-order lag weight (0 to 1)

In addition, in the Feynman alpha method, the covariance of neutron detector 1 and neutron detector 2 may be used instead of the variance. Reactor noise analysis using covariance is also shown in literature such as "Journal of the Atomic Energy Society of Japan, vol. 37, No. 6 (1995) Measurement of Effective Delayed Neutron Fraction Based on the Covariance Method."

In nuclear instrumentation at nuclear power plants, the squared mean of the signal from the detector is often taken to reduce the gamma ray background, which is called MSV (Mean Square Voltage) mode. This squared mean has the same meaning as the variance mentioned above. If there is sufficient signal strength, the MSV mode signal can be used instead of the variance, and the variance-to-mean ratio can be calculated by taking the ratio of the MSV mode signal strength to the average signal strength.

Although several embodiments of the present invention have been described above, these embodiments are presented as examples and are not intended to limit the scope of the invention. These novel embodiments can be implemented in various other forms, and various omissions, substitutions, and modifications can be made without departing from the gist of the invention. These embodiments and their modifications are included within the scope and gist of the invention, and are included in the scope of the invention and its equivalents as set forth in the claims.

1...Neutron detector, 2...Neutron detector, 3...Melting tank, 101...Neutron count rate measurement unit, 102...Plutonium concentration monitoring unit, 103...Time series data analysis unit, 104...Period monitoring unit, 105...Variance-to-mean ratio monitoring unit, 106...Feynman alpha monitoring unit, 107...Subcriticality calculation unit.

Claims (12)

A neutron count rate measuring means for measuring a neutron count rate from plutonium in a reprocessing process in a reprocessing facility ;
a plutonium concentration monitoring means for calculating a plutonium concentration from the neutron count rate and generating an alarm when the plutonium concentration exceeds a set value;
a period monitoring means for calculating a period from the time series data of the neutron count rate after the alarm is generated in the plutonium concentration monitoring means , and determining that an abnormality has occurred and stopping the process if the period is shorter than a set value;
a variance-to-mean ratio monitoring means for calculating a variance-to-mean ratio, which is a ratio of the variance to the mean of a plurality of pieces of neutron count rate data for a certain measurement time width, from the time-series data of the neutron count rate when the period is equal to or less than a set value in the period monitoring means, and determining that an abnormality has occurred and stopping the process when the variance-to-mean ratio exceeds a set value;
means for calculating a prompt neutron attenuation constant α based on a reactor noise method when the variance-to-mean ratio calculated by the variance-to-mean ratio monitoring means is equal to or less than a set value , calculating a neutron multiplication factor using the prompt neutron attenuation constant α, a delayed neutron ratio β previously obtained by analysis, and a prompt neutron lifetime L to determine a degree of subcriticality and detect an abnormality ;
A neutron monitor device comprising: In the time series data, from imax pieces of data of neutron count M(i) in the time interval ti to ti+Δt,

The average is calculated by

The variance is calculated by

The variance to mean ratio is calculated by
The neutron monitor device according to claim 1, characterized in that Y is plotted when Δt is changed, and the prompt neutron decay constant α is calculated by fitting using a constant Ysat and Y=Ysat[1-{1-exp(-αΔt)}/αΔt]. The neutron monitor device according to claim 1 or 2, further comprising a means for calculating the neutron multiplication factor from the time series data by an inverse dynamics method. The neutron monitor device according to any one of claims 1 to 3, characterized in that a filter process using the past neutron count rate is performed when calculating the period. The neutron monitor device according to claim 1, characterized in that the variance is the covariance of two neutron detectors. The neutron monitor device according to claim 1, characterized in that the variance is calculated using MSV (mean square voltage) mode. a neutron count rate measuring step for measuring a neutron count rate from plutonium in a reprocessing process at a reprocessing facility ;
a plutonium concentration monitoring step of calculating a plutonium concentration from the neutron count rate and generating an alarm when the plutonium concentration exceeds a set value;
a period monitoring step of calculating a period from the time series data of the neutron count rate after the alarm is generated in the plutonium concentration monitoring step , and determining that an abnormality has occurred and stopping the process when the period exceeds a set value;
a variance-to-mean ratio monitoring step of calculating a variance- to-mean ratio, which is a ratio of a variance to a mean, from a plurality of neutron count rate data for a certain measurement time width from the time-series data of the neutron count rate when the period is equal to or less than a set value in the period monitoring step, and determining that an abnormality has occurred and stopping the process when the variance-to-mean ratio exceeds a set value;
a step of calculating a prompt neutron attenuation constant α based on a reactor noise method when the variance-to-mean ratio calculated by the variance-to-mean ratio monitoring step is equal to or less than a set value , calculating a neutron multiplication factor using the prompt neutron attenuation constant α, a delayed neutron fraction β previously obtained by analysis, and a prompt neutron lifetime L to determine a degree of subcriticality and detect an abnormality ;
1. A method for managing criticality of spent nuclear fuel, comprising: In the time series data, from imax pieces of data of neutron count M(i) in the time interval ti to ti+Δt,

The average is calculated by

The variance is calculated by

The variance to mean ratio is calculated by
The method for managing criticality of spent nuclear fuel according to claim 7, characterized in that Y is plotted when Δt is changed, and the prompt neutron decay constant α is calculated by fitting using a constant Ysat and Y=Ysat[1-{1-exp(-αΔt)}/αΔt]. 9. The method for criticality management of spent nuclear fuel according to claim 7 or 8, further comprising the step of calculating the neutron multiplication factor from the time series data by an inverse kinetics method. The method for managing criticality of spent nuclear fuel according to any one of claims 7 to 9, characterized in that a filter process using the past neutron count rate is performed when calculating the period. The method for managing criticality of spent nuclear fuel according to claim 7, characterized in that the variance is the covariance of two neutron detectors. The method for managing criticality of spent nuclear fuel according to claim 7, characterized in that the variance is calculated using MSV (mean square voltage) mode.

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