JPS6217720B2 - - Google Patents

Description

[Detailed Description of the Invention] The present invention provides an online core monitoring method for a fast reactor.
The present invention relates to a fast reactor core monitoring method and an apparatus for estimating power distribution and temperature distribution in a nuclear reactor core using estimation results based on a power distribution calculation model and measurement results of coolant temperature and flow rate.

In order to operate fast reactors safely and efficiently,
It is necessary to quickly and accurately grasp the reactor core status online. For this purpose, it is necessary to accurately determine the power distribution of the nuclear reactor, and conventional methods such as solving a three-dimensional multigroup diffusion equation have been used, but from the viewpoint of calculation time it is difficult to apply it to online calculations. It's inappropriate. For this reason, various approximate calculation methods shown below have been proposed. For example, there are (1) three-dimensional (modified) one-group coarse mesh method, (2) energy mode method, (3) synthesis method, and (4) influence function method.

On the other hand, there is a method of arranging a large number of neutron detectors inside the reactor and obtaining the output distribution from the readings.
A certain number of in-reactor neutron detectors are installed in thermal neutron reactors. In the case of fast reactors, the inside of the reactor core is a harsh environment with high temperature sodium, high neutron flux, etc., and the power density is large, so a small detector is required. is currently still in the development stage. For this reason, in the past, researchers relied only on calculations or experience to understand the core status. Recently, a method has been proposed that reflects information on measured values of coolant temperature and flow rate for fast reactors, but as with conventional thermal neutron reactors, the calculation results are matched with the corresponding measured data using a power distribution calculation model. This will be corrected to make it possible. This method is suitable for cases such as thermal neutron reactors, where a value corresponding to the direct power distribution can be measured using an in-reactor neutron detector, and the measurement accuracy is relatively good; however, such as for fast reactors, where the direct power distribution is It is inappropriate in situations where it cannot be measured and the measurement accuracy cannot necessarily be said to exceed the calculation accuracy.

It is an object of the present invention to eliminate the drawbacks of the above-mentioned conventional techniques and to provide a highly reliable method and device for core monitoring of a fast reactor by effectively utilizing measured data of coolant temperature and flow rate. It is.

The present invention uses the above-mentioned approximate calculation method to calculate the spatial output distribution and the aggregate average output in a short time, and also calculates the aggregate average output from the measured values of the inlet temperature difference and flow rate of the aggregate, The power distribution and temperature distribution of the reactor core are estimated by finding the most probable values of both and their accuracy.

The present invention will be explained in detail below with reference to embodiments shown in the drawings.

FIG. 1 is a block diagram showing the configuration of an embodiment of a core monitoring system according to the present invention, and the system according to the present invention is composed of a process computer designated by the reference numeral 100. Operation data given in advance, such as the position of control rods (not shown), core flow rate, thermal output, etc., is sent to the power distribution calculation unit 1, and the reactor power is determined by a modified first group diffusion calculation based on the core geometric dimensions and nuclear constants. The spatial distribution P _C (r ₁ z) ±ΔP _C (r ₁ z) is approximately calculated. Here, ΔP _C (r ₁ z) represents the accuracy of the output distribution determined by this calculation unit 1, and it is the accuracy of detailed calculations (difference from measured values) confirmed in various mock-up tests and the accuracy of the output distribution used in this calculation unit 1. It is determined by the accuracy of the approximate calculation method (difference from the detailed calculation value), and is evaluated in advance as a function of burnup, etc. The signal of the spatial output distribution value calculated by the output distribution calculation section 1 is sent to the aggregate output calculation section 2 and the output distribution most probable value calculation section 9. The aggregate output calculation unit 2 integrates the spatial output distribution value in the axial direction for each aggregate to calculate the output P _Ci +ΔP _Ci (i is the aggregate number) for each aggregate.

The output distribution most probable value calculation unit 9 will be described later.

On the other hand, actual measurement data during reactor operation is obtained from the flow rate detector 102 and temperature detector 103 inside the reactor vessel 101.
The information from the temperature detector 104 is sent to the reactor inlet temperature measurement processing section 3, and the information from the temperature detector 103 is sent to the assembly outlet temperature. Information from the measurement processing unit 4 and the flow rate detector 102 are sent to the aggregate flow rate measurement processing unit, respectively.
Each of these processing units 3 to 5 obtains the measured value at the present time, and periodically performs statistical processing to obtain the average value and the amount of fluctuation.

The output from the measurement processing units 3 to 5 above is T _IN ±ΔT
_IN , T _SAi ±ΔT _SAi , F _SAi ±ΔF _SAi , the measurement accuracy ΔT _IN , ΔT _SAi , ΔF _SAi is the sensor,
It is determined by the accuracy of the measurement circuit, etc., the accuracy determined by the installation conditions of the actual machine, and the amount of fluctuation in the measured value. Of the above, the measured flow rate F _SAi ±ΔF _SAi is input to the most probable flow rate calculation unit 7 together with the calculated value F _Ci ±ΔF _Ci (stored in the aggregate flow rate distribution storage unit 6) obtained in advance by offline detailed calculation. Then, the most probable value F _i ±ΔF _i of the flow rate distribution is determined. 8 is an aggregate output converter, which converts the above T _IN ±ΔT _IN , T _SAi ±ΔT _SAi , F _i ±
The aggregate output P _Mi ±ΔP _Mi is calculated from ΔF _i using the following formula.

P _Mi =F _i・C _P・(T _SAi −T _IN )…(1) Here, C _P is the specific heat of the coolant.

The signal of the output distribution value calculated from the actual measurement data in this way is sent to the output distribution most probable value calculation section 9, and in the output distribution most probable value calculation section 9, the output distribution value calculation section 2 and the aggregate output calculation section The most probable value P _i of the aggregate output and its precision ΔP _i are calculated from the signal sent from 8. This is calculated as follows.

That is, the output P _Ci ±ΔP _Ci of the aggregate output calculation unit 2
Assuming that the probability distributions of P _Mi ±ΔP Mi and the output P Mi ±ΔP _Mi of the aggregate output converter 8 both follow a normal distribution, the most probable value Pi and its accuracy ΔP _i are determined by the following equations. FIG. 2 is a diagram showing its principle.

P _i =(ΔP _Ci ) ²・P _Mi +(ΔP _Mi ) ²・
P _Ci /(ΔP _Ci ) ² + (ΔP _Mi ) ² …(3) Note that, regarding the axial distribution of output, the output distribution form determined by the output distribution calculation section is applied.

The most probable value of the aggregate output P _i obtained by the most probable output distribution value calculation section 1 and the signal of the most probable value of the flow rate distribution obtained from the most probable flow rate value calculation section 7 are sent to the temperature distribution calculation section 10 . The temperature distribution calculation section 10 calculates the coolant temperature, fuel cladding temperature, and fuel pellet temperature from the output distribution and flow rate distribution, and calculates the maximum temperature by taking into account the hot spot coefficient and local peaking coefficient. This temperature is constantly compared and monitored with the permissible temperature. That is, the coolant temperature distribution is determined by the following equation using the heat generation density P _i (z) of the aggregate i determined by the output distribution most probable value calculation unit 9. In general, the coolant density ρ and specific heat C _P are functions of temperature, so these points are also taken into account.

T _i (Z + ΔZ) = T _i (Z) + P _i (Z) ΔZA / V _i ρ (T _i (Z)) C _P (T _i (Z)) ...... (5) Here, V _i : Cooling Material volumetric flow rate ΔZ: Axial mesh width A: Aggregate cross-sectional area If the coolant reactor inlet temperature (measured value) is given as an initial value in the above equation, the axial distribution for each aggregate can be obtained. Next, the fuel cladding surface temperature, the fuel cladding inner surface temperature, the fuel pellet surface temperature, and the fuel pellet center temperature are successively determined using the basic formula for steady heat conduction. Since the above value is an aggregate average value, it is corrected by the hot spot coefficient and the local peaking coefficient within the aggregate. The hot spot coefficient is based on an engineering uncertainty coefficient, and is calculated by using a multiplication term M _ij (power distribution error, reactor thermal output error, inter-assembly flow distribution error, flow rate deformation error, etc.) that performs multiplication processing, and statistical processing. There are statistical terms F _ij (channel cross-sectional area manufacturing tolerance, pellet manufacturing tolerance, thermal conductivity error, heat transfer coefficient error, etc.) to be performed. Of M _ij , the output distribution error and the inter-fluid flow rate distribution error are determined by each of the calculation units 7 and 9 shown in FIG. The hot spot temperature _THS is expressed by the following equation.

Here, T _IN : Reactor inlet temperature T _j : Amount of temperature rise at each part (nominal value) The details of the flow rate most probable value calculation section are based on the same principle as the power distribution most probable value calculation section, so
Detailed explanation will be omitted.

Among the values obtained by each of the above calculation units, the value signals of the flow rate most probable value calculation unit 7, the power distribution most probable value calculation unit 9, and the temperature distribution calculation unit 10 are displayed on the display unit 13, for example, on a cathode ray tube, and are displayed to reactor operators. Displayed as information. Of course, other calculated value signals may also be displayed if necessary. For example, if abnormality determination information for a nuclear reactor, which will be described next, is displayed, the reliability will be even higher.

In this embodiment, an abnormality determination section 12 is provided so as to be able to deal with an abnormality such as flow path blockage or a sensor failure.

The abnormality determination section 12 includes a reactor inlet temperature measurement processing section 3, an assembly outlet temperature measurement processing section 4, an assembly flow rate measurement processing section 5, an assembly flow rate distribution storage section 6, and an assembly inlet/outlet temperature difference calculation section 11. information has been entered. As mentioned above, each measurement processing section 3, 4, 5
Now, regarding the temperature at the entrance and exit of the aggregate and the flow rate of the aggregate,
After regularly normalizing the heat output, its average value () and the amount of fluctuation (ΔX) are determined. For example, ΔX is set to three times the standard deviation. As a first step in abnormality determination, it is determined whether the current measured value is within ±ΔX. As a second step of abnormality determination, it is determined whether the probability of coincidence between the measured value and the calculated value is greater than or equal to a specified value. This probability PB
is the average value and standard deviation of the measured values, X _M , σ _M (in addition to the accuracy determined from the amount of fluctuation in the measured values above, it also depends on the accuracy of the sensor, the accuracy determined by the installation conditions of the actual machine, etc.), and the calculated value. Letting the average value and standard deviation be X _C and σ _C , it is given by the following formula.

At each determination stage, if the value deviates from the specified value, the type of abnormality is determined.

The temperature difference calculation section 11 at the entrance and exit of the assembly calculates the temperature difference at the entrance and exit of the assembly using the above equation (1) from the information on the assembly output and flow rate from the assembly flow rate measurement processing section 5 and the assembly output calculation section 2. The standard deviation value is calculated and compared with the standard deviation value in the same manner as described above.

The abnormality determination system is shown in FIG. Regarding the sensor, in the case of double elements, a mutual check is performed.

When a flow path abnormality is determined, the output distribution and temperature distribution are estimated based on the measured values as a routine calculation at the time of abnormality. That is, in FIG. 1, the most probable flow rate calculation section 7 and the most probable output distribution calculation section 9 receive the control signal 1 from the abnormality determination section regarding the aggregate of interest.
4, the output signals of the aggregate flow rate measurement processing section 5 and the aggregate output converting section 8 are output as they are.

If a sensor failure is determined by a mutual check of inter-sensor signals or a hardware check of the sensor, contrary to the above,
According to the control signal 14, the output distribution and temperature distribution are estimated based mainly on the corresponding calculated values without using the failed sensor signal.

As explained above, according to the present invention, even when measurement accuracy and calculation accuracy are the same as in fast reactors,
The power distribution within the reactor can be estimated online, at high speed, and accurately, providing operators with the necessary information and enabling safe and efficient operation of the reactor.

[Brief explanation of the drawing]

FIG. 1 is a block diagram of an embodiment of the present invention, FIG. 2 is a diagram showing the principle of the most probable value calculation section of the present invention, and FIG.
The figure is a system diagram showing an abnormality discrimination system in an embodiment of the present invention. 1... Output distribution calculation unit, 2... Aggregate output calculation unit,
3... Reactor inlet temperature measurement processing section, 4... Assembly outlet temperature measurement processing section, 5... Assembly flow rate measurement processing section, 6
... Aggregate flow rate distribution storage section, 7... Flow rate most probable value calculation section, 8... Aggregate output conversion section, 9... Output distribution most probable value calculation section, 10... Temperature distribution calculation section, 11... Aggregate inlet/outlet temperature difference calculation section, DESCRIPTION OF SYMBOLS 12... Abnormality determination part, 13... Display part, 14... Control signal, 100... Process computer.

Claims (1)

[Claims] 1. Approximately calculating the spatial distribution of reactor output from various operational data of the fast reactor, and calculating the distribution of reactor output from various actual measurement data during operation of the fast reactor, and calculating these two output distributions. A fast reactor core monitoring method that calculates the most probable value of power distribution and its accuracy from calculated values. 2. The fast reactor core monitoring method according to item 1, wherein abnormalities and abnormal portions of various data are determined, and depending on the results, the core monitoring is switched to perform core monitoring based on the approximate calculation or calculation based on actual measurement data. 3 Calculation means for calculating the spatial power distribution of the reactor and aggregate average power; measuring means for measuring the reactor inlet coolant temperature and aggregate outlet coolant temperature and flow rate; Based on the calculation means for calculating the aggregate average output from the measured values and the calculation results of the aggregate average output of both of the above,
A calculation means for determining the most probable value of the spatial output distribution and its accuracy, and a hot spot coefficient determined from the most probable value of the output distribution and flow rate distribution determined by this method and its accuracy,
A fast reactor core monitoring device comprising means for determining hot spot temperature inside the reactor core.