Helium-Xenon Cooling Reactor Control Method, Device and Electronic Equipment

Abstract

The present invention provides a control method, device and electronic equipment for a helium-xenon cooled reactor, which relates to the technical field of nuclear reactors. The above-mentioned control method for a helium-xenon cooled reactor includes: during the operation of the helium-xenon cooled reactor, monitoring the operation state information of the helium-xenon cooled reactor, and obtaining a mathematical model of the helium-xenon cooled reactor constructed in advance; performing numerical simulation on the mathematical model based on the current operation state information to obtain a numerical simulation result; adjusting each control parameter of the helium-xenon cooled reactor based on the numerical simulation result so that the power generation power of the helium-xenon cooled reactor reaches a preset power generation power. The present invention can adaptively control each control parameter of the reactor according to the operation state of the reactor, and improves the reliability of the control of the helium-xenon cooled reactor.

Description

Technical Field

[0001] The present invention relates to the technical field of nuclear reactors, and in particular, to a control method, device, and electronic device for a helium-xenon cooled reactor. Background Art

[0002] Currently, in order to enable a helium-xenon cooled reactor to operate stably for a long time while meeting the load requirements, it is necessary to adjust the control parameters of the nuclear reactor in real time and quickly for load changes (such as changes in power generation), so that the power generation of the reactor can follow the set power generation. Due to the characteristics of the dynamic uncertainty, non-linearity, and strong coupling between the main parameters of the reactor's mathematical model, how to achieve adaptive and reliable control of the helium-xenon cooled reactor has become an urgent problem to be solved. Summary of the Invention

[0003] In view of this, the purpose of the present invention is to provide a control method, device, and electronic device for a helium-xenon cooled reactor, which can adaptively control the control parameters of the reactor according to the operating state of the reactor, and improve the reliability of the control of the helium-xenon cooled reactor.

[0004] To achieve the above purpose, the technical solutions adopted in the embodiments of the present invention are as follows:

[0005] In a first aspect, an embodiment of the present invention provides a control method for a helium-xenon cooled reactor, including:

[0006] During the operation of the helium-xenon cooled reactor, monitor the operation state information of the helium-xenon cooled reactor, and obtain the pre-constructed mathematical model of the helium-xenon cooled reactor; the operation state information includes the main loop flow rate, the pre-cooler side flow rate, and the core reflector withdrawal distance; perform numerical simulation on the mathematical model based on the current operation state information to obtain a numerical simulation result; adjust the control parameters of the helium-xenon cooled reactor based on the numerical simulation result, so that the power generation of the helium-xenon cooled reactor reaches a preset power generation.

[0007] Further, the embodiment of the present invention provides a first possible implementation manner of the first aspect, where

[0008] The step of performing numerical simulation on the mathematical model based on the current operation state information to obtain a numerical simulation result includes: performing a thermal cycle calculation on the helium-xenon cooled reactor based on the current operation state information to obtain the core inlet temperature and the core outlet temperature; performing a thermal-hydraulic calculation on the core region based on the core inlet temperature and the core outlet temperature to obtain the temperatures at various places inside the core; performing a neutron physics calculation on the core region based on the temperatures at various places inside the core to obtain the current power generation of the helium-xenon cooled reactor in the current operation state.

[0009] Further, the embodiment of the present invention provides a second possible implementation manner of the first aspect. Wherein, the numerical simulation result includes the current power generation. The step of adjusting each control parameter of the helium-xenon cooling reactor based on the numerical simulation result to make the power generation of the helium-xenon cooling reactor reach the preset power generation includes: calculating each control parameter of the helium-xenon cooling reactor at the next moment based on the current power generation and the preset power generation, and controlling the operation of each device of the helium-xenon cooling reactor based on the control parameter to make the power generation of the helium-xenon cooling reactor reach the preset power generation; wherein, the control parameters include the main loop flow rate, the pre-cooler side flow rate, and the core reflector draw distance.

[0010] Further, the embodiment of the present invention provides a third possible implementation manner of the first aspect. Wherein, the step of calculating each control parameter of the helium-xenon cooling reactor at the next moment based on the current power generation and the preset power generation includes: performing a sensitivity analysis on the mathematical model based on the current power generation and the preset power generation to determine the control parameter of the helium-xenon cooling reactor at the next moment.

[0011] Further, the embodiment of the present invention provides a fourth possible implementation manner of the first aspect. Wherein, the helium-xenon cooling reactor control method further includes: performing a state prediction on the helium-xenon cooling reactor based on a neural network and the operation state information to obtain a state prediction result; determining whether the state prediction result exceeds a preset physical thermal constraint, and if so, controlling the helium-xenon cooling reactor to execute an accident control step.

[0012] Further, the embodiment of the present invention provides a fifth possible implementation manner of the first aspect. Wherein, the helium-xenon cooling reactor control method further includes: if the state prediction result does not exceed the preset physical thermal constraint, returning to execute the step of performing a numerical simulation on the mathematical model based on the current operation state information to obtain a numerical simulation result.

[0013] Further, the embodiment of the present invention provides a sixth possible implementation manner of the first aspect. Wherein, the step of performing a state prediction on the helium-xenon cooling reactor based on a neural network and the operation state information to obtain a state prediction result includes: inputting the power generation in the operation state information into a neural network model, online training the neural network model based on the power generation, and performing a single-step prediction on the helium-xenon cooling reactor based on the neural network model to obtain a state prediction result.

[0014] In a second aspect, an embodiment of the present invention further provides a control device for a helium-xenon cooled reactor, including: a monitoring module, configured to monitor the operating state information of the helium-xenon cooled reactor during operation of the helium-xenon cooled reactor, and obtain the mathematical model of the helium-xenon cooled reactor pre-constructed; the operating state information includes the main loop flow rate, the pre-cooler side flow rate, and the core reflector withdrawal distance; a simulation module, configured to perform numerical simulation on the mathematical model based on the current operating state information to obtain a numerical simulation result; a control module, configured to adjust each control parameter of the helium-xenon cooled reactor based on the numerical simulation result, so that the power generation power of the helium-xenon cooled reactor reaches a preset power generation power.

[0015] In a third aspect, an embodiment of the present invention provides an electronic device, including: a processor and a storage device; a computer program is stored on the storage device, and when the computer program is run by the processor, it executes the method according to any one of the first aspect.

[0016] In a fourth aspect, an embodiment of the present invention provides a computer-readable storage medium, on which a computer program is stored, and when the computer program is run by a processor, it executes the steps of the method according to any one of the first aspect.

[0017] An embodiment of the present invention provides a control method, device and electronic device for a helium-xenon cooled reactor. The above control method for a helium-xenon cooled reactor includes: during the operation of the helium-xenon cooled reactor, monitoring the operating state information of the helium-xenon cooled reactor, and obtaining the mathematical model of the helium-xenon cooled reactor pre-constructed; the operating state information includes the main loop flow rate, the pre-cooler side flow rate, and the core reflector withdrawal distance; performing numerical simulation on the mathematical model based on the current operating state information to obtain a numerical simulation result; adjusting each control parameter of the helium-xenon cooled reactor based on the numerical simulation result, so that the power generation power of the helium-xenon cooled reactor reaches a preset power generation power. The above control method for a helium-xenon cooled reactor, by monitoring the operating state information of the reactor during the operation of the helium-xenon cooled reactor, performing numerical simulation according to the current operating state information of the reactor, and adjusting the control parameters of the reactor according to the numerical simulation result, enables the power generation power of the reactor to follow the preset power generation power, realizes the adaptive control of each control parameter of the reactor according to the operating state of the reactor, meets the load demand, and improves the stability of the reactor operation.

[0018] Other features and advantages of the embodiments of the present invention will be described in the subsequent description, or, some features and advantages can be inferred from the description or determined without doubt, or can be known by implementing the above technologies of the embodiments of the present invention.

[0019] To make the above objects, features, and advantages of the present invention more obvious and understandable, the following specifically presents preferred embodiments and, in conjunction with the accompanying drawings, provides a detailed description as follows. Description of the Drawings

[0020] In order to more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the following will briefly introduce the drawings required for the description of the specific embodiments or the prior art. Obviously, the drawings in the following description are some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can also be obtained based on these drawings.

[0021] Figure 1 Shows a flowchart of a helium-xenon cooled reactor control method provided by an embodiment of the present invention;

[0022] Figure 2 Shows a schematic diagram of a Brayton cycle provided by an embodiment of the present invention;

[0023] Figure 3 Shows a schematic diagram of an Elman neural network structure provided by an embodiment of the present invention;

[0024] Figure 4 Shows a flowchart of an intelligent control provided by an embodiment of the present invention;

[0025] Figure 5 Shows a schematic diagram of the structure of a helium-xenon cooled reactor control device provided by an embodiment of the present invention;

[0026] Figure 6 Shows a schematic diagram of the structure of an electronic device provided by an embodiment of the present invention.

[0027] Reference Signs:

[0028] 201 - Reactor; 202 - Turbine; 203 - Regenerator; 204 - Pre-cooler; 205 - Compressor; 206 - Generator. Detailed Embodiments

[0029] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the following will describe the technical solutions of the present invention in conjunction with the drawings. Obviously, the described embodiments are some, but not all, of the embodiments of the present invention.

[0030] At present, in order to enable a nuclear reactor to operate in an expected manner or to operate automatically according to certain criteria, many scholars have conducted research on reactor control. However, there is little research on small helium-xenon cooled reactors. Moreover, small helium-xenon cooled reactors have the requirement of long-term unmanned operation, and thus have relatively high requirements for control reliability. Embodiments of the present invention provide a control method, device and electronic device for a helium-xenon cooled reactor. This technology can be applied to improve the control reliability of a helium-xenon cooled reactor. The following provides a detailed introduction to the embodiments of the present invention.

[0031] This embodiment provides a control method for a helium-xenon cooled reactor. This method can be applied to electronic devices such as computers. Refer to Figure 1 the flowchart of the control method for a helium-xenon cooled reactor shown in

[0032] Step S102, during the operation of the helium-xenon cooled reactor, monitor the operation state information of the helium-xenon cooled reactor, and obtain the pre-constructed mathematical model of the helium-xenon cooled reactor.

[0033] The above-mentioned operation state information includes the main loop flow rate, the flow rate on the precooler side, and the core reflector withdrawal distance. The main loop flow rate, the flow rate on the precooler side, and the core reflector withdrawal distance of the helium-xenon cooled reactor are detected in real time or at a preset time interval.

[0034] The components of the reactor for control include: a turbine valve, a cold-side valve of the precooler, and a core pull-out reflector, which respectively control the main loop flow rate, the flow rate on the precooler side, and the core reflector withdrawal distance. During the operation of the helium-xenon cooled reactor, the current opening degrees of the turbine valve and the cold-side valve of the precooler are respectively detected to obtain the main loop flow rate and the flow rate on the precooler side.

[0035] Based on parameters such as the geometric parameters, environmental heat dissipation coefficient, and wall friction factor of the helium-xenon cooled reactor, a mathematical model of the helium-xenon cooled reactor is constructed, that is, the geometric parameters, environmental heat dissipation coefficient, and wall friction factor of the helium-xenon cooled reactor are input into a preset modeling software (such as CFD (Computational Fluid Dynamics) modeling software) for model construction to obtain the mathematical model of the helium-xenon cooled reactor.

[0036] Step S104, perform numerical simulation on the mathematical model based on the current operation state information to obtain a numerical simulation result.

[0037] Taking the detected main circuit flow rate, the flow rate on the pre-cooler side, and the core reflector pull-out distance as input data, input them into the mathematical model of the helium-xenon cooled reactor, and control the mathematical model of the helium-xenon cooled reactor to perform synchronous power generation simulation calculations, so that the mathematical model of the helium-xenon cooled reactor can simulate and calculate the core thermal power under the current operating state information according to the current operating state information.

[0038] Step S106, adjust each control parameter of the helium-xenon cooled reactor based on the numerical simulation results, so that the power generation power of the helium-xenon cooled reactor reaches the preset power generation power.

[0039] In order to enable the reactor to operate stably for a long time and meet the load demand, according to the core thermal power of the helium-xenon cooled reactor under the current operating state, quickly adjust each control parameter of the helium-xenon cooled reactor in real time, so that the power generation power of the helium-xenon cooled reactor can follow the preset power generation power, that is, control the helium-xenon cooled reactor to be able to approach the power generation power set by the user.

[0040] The above control parameters are the parameters of the controllable equipment in the reactor. The above control parameters include the control parameters of the turbine valve, the cold-side valve of the pre-cooler, and the core pull-out reflector in the helium-xenon cooled reactor, that is, the main circuit flow rate, the flow rate on the pre-cooler side, and the core reflector pull-out distance. Repeat the above steps S104 to S106 to enable the power generation power of the reactor to operate following the power generation power curve set by the user.

[0041] The above-mentioned helium-xenon cooled reactor control method provided by this embodiment, by monitoring the operating state information of the reactor during the operation of the helium-xenon cooled reactor, performing numerical simulation according to the current operating state information of the reactor, and adjusting the control parameters of the reactor according to the numerical simulation results, so that the power generation power of the reactor follows the preset power generation power, realizes the adaptive control of each control parameter of the reactor according to the operating state of the reactor, meets the load demand, and improves the stability of the reactor operation.

[0042] In order to calculate the current power generation power of the helium-xenon cooled reactor, this embodiment provides an implementation manner of performing numerical simulation on the mathematical model based on the current operating state information to obtain the numerical simulation results, which can be specifically executed according to the following steps (1) to (3):

[0043] Step (1): Perform a thermodynamic cycle calculation on the helium-xenon cooled reactor based on the current operating state information to obtain the core inlet temperature and the core outlet temperature.

[0044] See as Figure 2The schematic diagram of the Brayton cycle shown above. The helium-xenon cooling reactor includes a reactor 201, a turbine 202, a regenerator 203, a precooler 204, a compressor 205, and a generator 206. Based on the thermodynamic cycle relationship between the devices in the above Brayton cycle schematic diagram and the working principles of each device, the thermodynamic cycle of the helium-xenon cooling reactor is calculated using thermodynamic relationships to obtain the inlet and outlet temperatures of the reactor core.

[0045] Calculate the actual power consumption of the compressor based on the main circuit flow rate. The working principle of the compressor is as follows:

[0046] The pressure ratio γ of the compressor refers to the ratio of the pressure at the outlet of the compressor to the pressure at the inlet, and is also the ratio of the highest pressure to the lowest pressure in the entire cycle loop. For an adiabatic process, the relationship between the inlet and outlet temperatures of the compressor can be expressed by the following formula:

[0047]

[0048] Among them, φ 4-5 is the average adiabatic coefficient of the compressor thermodynamic process, T4 is the actual inlet working fluid temperature of the compressor (which is also the outlet temperature of the precooler), P4 is the actual inlet working fluid pressure of the compressor, P5 is the actual outlet working fluid pressure of the compressor, that is, P5 is the highest pressure in the entire loop ( Figure 2 the loop of 1-2-3-4-5-6-1 in the figure), and T 5s is the outlet working fluid temperature of the compressor in the adiabatic process.

[0049] The isentropic efficiency of the compressor is:

[0050]

[0051] Among them, H 5s is the specific enthalpy of the outlet working fluid in the adiabatic process, H5 is the specific enthalpy of the outlet working fluid of the compressor in the actual process, H4 is the specific enthalpy of the inlet working fluid of the compressor in the actual process, is the isobaric specific heat capacity of the compressor in the adiabatic process, is the isobaric specific heat capacity of the compressor in the actual process, T5 is the outlet working fluid temperature of the compressor in the actual process, and is also the cold-side inlet working fluid temperature of the regenerator. The relationship between the specific enthalpy, specific heat capacity of the working fluid and temperature, pressure can be obtained from the helium-xenon gas property table. Obtain the mechanical efficiency η C,M of the compressor, then the actual power consumption W C of the compressor is:

[0052]

[0053] Among them, G is the mass flow rate of the working fluid flowing through the compressor (that is, the main circuit flow rate G), and the mass flow rate is the same everywhere in the thermodynamic cycle.

[0054] Regenerator:

[0055] Energy conservation of fluid heat exchange between the cold side and the hot side of the regenerator:

[0056]

[0057] Among them, is Figure 2 the average constant pressure specific heat capacity of the 2-3 (hot side of the regenerator) thermodynamic process in, is Figure 2 the average constant pressure specific heat capacity of the 5-6 (cold side of the regenerator) thermodynamic process in. The specific heat capacity of the working fluid can be obtained by querying the physical property table of helium-xenon gas. T2 is the working fluid temperature at the inlet of the hot side of the regenerator and also the working fluid temperature at the outlet of the turbine; T3 is the working fluid temperature at the outlet of the hot side of the regenerator and also the working fluid temperature at the inlet of the precooler; T5 is the working fluid temperature at the inlet of the cold side of the regenerator and also the working fluid temperature at the outlet of the compressor; T6 is the working fluid temperature at the outlet of the cold side of the regenerator and also the working fluid temperature at the inlet of the reactor core.

[0058] The regeneration degree α of the regenerator r is defined as the ratio of the actual heat regeneration amount of the cycle to the maximum heat regeneration amount that can be achieved. The calculation formula for the regeneration degree is:

[0059]

[0060] Among them, H5 is the specific enthalpy of the working fluid at the outlet of the compressor (also the specific enthalpy of the working fluid at the inlet of the cold side of the regenerator), H6 is the specific enthalpy of the working fluid at the outlet of the cold side of the regenerator (also the specific enthalpy of the working fluid at the inlet of the reactor core), H2 is the specific enthalpy of the working fluid at the outlet of the turbine (also the specific enthalpy of the working fluid at the inlet of the hot side of the regenerator), C p,2 is the constant pressure specific heat capacity of the working fluid at the inlet of the hot side of the regenerator, C p,5 is the constant pressure specific heat capacity of the working fluid at the inlet of the cold side of the regenerator.

[0061] Turbine:

[0062] For the turbine, its isentropic efficiency η T,s is defined as the ratio of the actual expansion work of the working fluid in the turbine to the ideal expansion work. The larger the isentropic efficiency, the greater the actual work done by the turbine and the higher the thermal efficiency of the entire cycle. The calculation formula for the isentropic efficiency is:

[0063]

[0064] Among them, H 2s is the specific enthalpy of the working fluid at the outlet of the turbine in the adiabatic process, H2 is the specific enthalpy of the working fluid at the outlet of the turbine in the actual process, H1 is the specific enthalpy of the working fluid at the inlet of the turbine, is the constant pressure specific heat capacity in the adiabatic process of the turbine, is the constant pressure specific heat capacity in the actual process of the turbine, T 2sis the outlet working fluid temperature of the turbine in the adiabatic process, T2 is the outlet working fluid temperature of the turbine in the actual process, and T1 is the inlet working fluid temperature of the turbine.

[0065] Turbine output power W T The calculation formula is:

[0066]

[0067] Among them, η T,M is the mechanical efficiency of the turbine.

[0068] Front cooler:

[0069] When the precooler is in steady state, the heat exchange between the hot side and the cold side is equal, and the working fluid on the cold side is water.

[0070]

[0071] in, is the average constant-pressure specific heat capacity of the thermodynamic process on the hot side of the precooler, is the average constant-pressure specific heat capacity of the thermodynamic process on the cold side of the precooler, T 22 The outlet temperature of the working water on the cold side, T 21 is the inlet temperature of the working medium water on the cold side, G is the mass flow rate of the helium-xenon working medium flowing through the hot side of the precooler (i.e. the main circuit flow rate), G c is the mass flow rate of water flowing through the cold side of the precooler (i.e. the precooler side flow rate).

[0072] Based on the input main loop flow, forecooler side flow and core reflector withdrawal distance, the reactor core inlet and outlet temperatures can be calculated by combining the above formulas.

[0073] Step (2): Perform thermal calculations on the core region based on the core inlet temperature and the core outlet temperature to obtain the temperatures at various locations inside the core.

[0074] The core area consists of three parts: the matrix, fuel elements, coolant channels and cladding. The coolant channels, cladding and fuel elements are regularly arranged in the matrix, and the material of the matrix is graphite. The most basic unit of the repeated arrangement is a regular hexagonal structure. The fuel element is made of uranium carbide with a radius of 7mm. The distance P between the center of the fuel element and the center of the coolant channel is 17mm. The radius of the coolant channel is 3mm, the thickness of the cladding is 1mm, and the material is molybdenum alloy (Molybdenum-TZM, Ti-0.5, Zr-0.1, C-0.03).

[0075] The fuel element uses uranium carbide alloy, the matrix material is graphite, and the cladding material of the coolant channel is molybdenum alloy. Among the above three, the one with the worst temperature tolerance is molybdenum alloy. Therefore, in the preliminary thermal cycle design, only the maximum temperature of the cladding of the coolant channel in the reactor core is considered not to exceed 1400K.

[0076] The single-channel program is used for thermal calculation, and the main relationships involved include:

[0077] 1. The heat transfer relationship between helium and xenon. Under the same pipe and the same molar mass flow rate, the heat transfer coefficient h of the mixed working fluid and the heat transfer coefficient h of the pure helium working fluid He The ratio is defined as the relative heat transfer coefficient, which can be expressed by the basic physical property parameters of the mixed working fluid:

[0078]

[0079] Among them, μ is the viscosity of the mixed working fluid, M mix is the average molar mass of the mixed working fluid, C p is the specific heat capacity at constant pressure of the mixed working fluid, λ is the thermal conductivity of the mixed working fluid, and the calculation formula for the average molar mass of the mixed working fluid is:

[0080] M mix =αM He +(1-α)M Xe

[0081] Among them, α is the volume fraction of helium, M He is the molar mass of helium, with a value of 4g / mol, M Xe is the molar mass of xenon, with a value of 131.29g / mol.

[0082] The heat transfer coefficient h of the pure helium working fluid He is calculated according to the empirical relationship proposed by Taylor. The error of this empirical relationship is within 10% of the experimental value during low heat flux density heating and within 20% of the experimental value during high heat flux density heating.

[0083]

[0084] Among them, c = 0.57 - [1.59 / (z / D)], z is the distance from the inlet, D is the inner diameter of the pipe, Nu b 、Re b 、Pr b are the Nusselt number, Reynolds number, and Prandtl number of the mainstream respectively. They are three dimensionless numbers. h He is included in the definition of the dimensionless number and can be solved from the above empirical relationship. T s and T b are the wall temperature and the mainstream temperature respectively.

[0085] 2. Helium-xenon pressure drop relationship. When the temperature, pressure, and pipe geometry are the same, at the same molar mass flow rate, the ratio of the heat transfer pressure drop of the mixed working fluid to the pressure drop of the pure helium working fluid is defined as the relative pressure loss coefficient The calculation formula for the relative pressure loss coefficient is as follows:

[0086]

[0087] where μ is the viscosity of the mixed working fluid, M mix is the average molar mass of the mixed working fluid, and Z is the compressibility factor of the mixed working fluid. For the pure helium working fluid, when the Reynolds number is greater than 3000, the pressure drop friction coefficient f in the pipe can be calculated by the following formula:

[0088]

[0089] where Re s is the Reynolds number at the wall, and the pressure drop Δp of the pure helium working fluid He can be obtained by means of the pressure drop friction coefficient f of the pure helium working fluid in the single-channel program, and then the pressure drops at various parts inside the core under the actual mixed working fluid can be obtained.

[0090] The pressure loss is mainly composed of four parts: the pressure loss at the cold end of the recuperator, the pressure loss in the core, the pressure loss at the hot end of the recuperator, and the pressure loss of the precooler. The pressure loss ratio is defined as the ratio of the pressure loss of each part to the highest pressure of the cycle (p5 is the highest pressure of the entire loop 1-2-3-4-5-6-1, and p4 is the lowest pressure). The pressure loss of a certain component refers to the decrease value of the outlet pressure of the helium-xenon working fluid flowing through this component relative to the inlet pressure. The compressor is not in the following table because the pressure of the working fluid increases when flowing through this component, and the relationship between its inlet and outlet pressures is determined by the pressure ratio. For the pure helium working fluid, the specific value of its pressure drop Δp He (i.e., the pressure loss ratio) can be referred to Table 1 below:

[0091] Table 1 Pressure loss ratios of each part under pure helium working fluid

[0092] area pressure loss ratio cold end of recuperator 0.6％ core 0.7％ hot end of recuperator 0.4％ pre-cooler 0.5％ mixing box 0.2％

[0093] For the helium-xenon mixed working fluid, due to the introduction of xenon, the viscosity of the mixed working fluid increases, so the pressure loss of the mixed working fluid is greater than that of the pure helium working fluid. Define the relative pressure loss coefficient as the ratio of the pressure loss of the helium-xenon mixed working fluid to the pressure loss of the pure helium working fluid under the same conditions (when the temperature, pressure, and pipe geometry are the same). Therefore, the pressure drop ratio Δp of the helium-xenon mixed working fluid in each component can be obtained by multiplying the pressure loss ratio of the pure helium working fluid in each component (see Table 1) by the relative pressure loss coefficient Obtained. Thus, on the loop of 1-2-3-4-5-6-1, the pressure values at various locations can be determined. The pressure ratio of the turbine is obtained by calculating the pressure ratio of the compressor and the pressure loss of the loop.

[0094] Step (3): Based on the temperatures at various locations inside the reactor core, perform neutron physics calculations on the reactor core area to obtain the current power generation of the helium-xenon cooled reactor under the current operating state.

[0095] Obtain the material information of the reactor, referring to the material table of each part of the reactor shown in Table 1 below and the core material density table shown in Table 2:

[0096] Table 1 Material Table of Each Part of the Reactor

[0097]

[0098] Table 2 Core Material Density Table

[0099]

[0100] Use the Monte Carlo program for calculation, specify the geometric shape of the calculation domain and the physical properties of each zone, etc., then divide the grid, discretize the neutron transport equation, etc., and solve it to obtain the reactivity k and the core thermal power Q. The control variable "the extraction distance X of the reaction layer" is calculated here as one of the boundary conditions. The calculation formula for the core thermal power is:

[0101]

[0102] Among them, H1 is the specific enthalpy of the working fluid at the core outlet (also the specific enthalpy of the working fluid at the turbine inlet), is the average constant-pressure specific heat capacity of the 6-1 thermodynamic process (core heating).

[0103] Most of the shaft work input by the generator is converted into electrical output, and the rest is dissipated in the form of heat energy. Let the power generation efficiency of the generator (obtained based on the core thermal power) be η G , then the power generation of the generator W G is:

[0104] W G = η G (W T - W C )

[0105] In a specific implementation manner, calculate the control parameters of the helium-xenon cooled reactor at the next moment based on the current power generation and the preset power generation, and control the operation of each device of the helium-xenon cooled reactor based on the control parameters so that the power generation of the helium-xenon cooled reactor reaches the preset power generation; among them, the control parameters include the main loop flow rate, the flow rate on the pre-cooler side, and the extraction distance of the core reflector.

[0106] There are three components for reactor control, namely the turbine valve, the cold side valve of the precooler, and the core pull-out reflector. The corresponding control variables are: the main circuit flow rate M1 (kg / s), the cold side flow rate M2 (kg / s) of the precooler, and the reflector pull-out distance X (cm). (That is, the main circuit flow rate G, the cold side flow rate G of the precooler in the above mathematical model formula c and the reflector pull-out distance X).

[0107] Since the compressor, turbine, and generator are connected by a single shaft, their rotational speeds are the same at steady state. When the system is operating in a steady state, the rotor torque is balanced and the turbine speed is maintained constant; when the turbine speed is not equal to the power consumption of the compressor, the rotor will accelerate or decelerate under the action of the torque. The speed of the turbine is mainly adjusted by the intake air volume M1.

[0108] When the flow rate of the helium-xenon gas in the closed cycle changes, the cooling capacity of the precooler also needs to change accordingly, which is mainly achieved by adjusting the cooling water flow rate M2 on the cold side of the precooler. By changing the reflector pull-out distance X, the neutron leakage of the core is adjusted to control the core reactivity, shut down the reactor or adjust the reactor power level.

[0109] To improve the reliability of reactor control, this embodiment provides a specific implementation method for calculating the control parameters of the helium-xenon cooled reactor at the next moment based on the current power generation and the preset power generation: perform a sensitivity analysis on the mathematical model based on the current power generation and the preset power generation to determine the control parameters of the helium-xenon cooled reactor at the next moment.

[0110] The above preset power generation can be obtained from the preset power generation curve stored in the computer. To make the power generation of the reactor operate according to the preset power generation curve, the preset power generation of the reactor is obtained at every preset time interval to track the actual power generation of the reactor.

[0111] Taking the current time step t = k as an example, the current preset power generation (i.e., the power generation set point) is y set ; let the measured value of the power generation at the time step t = k be The power difference between the two is denoted as:

[0112]

[0113] For the mathematical model of the above helium-xenon cooled reactor, an online sensitivity analysis method is used to obtain the sensitivity matrix between the power generation and the control variables. For θ key parameters (main circuit flow rate, cold side flow rate of the precooler, and core reflector pull-out distance) selected in the mathematical model a small change Δp is made c,j, for example, when it is increased by 5% and a certain control parameter is changed while the other two remain unchanged, since there are 3 control parameters, that is to say, the model needs to be calculated 3 times. Assume that the calculated value of the current power generation of the current state (M1, M2, X) is y. Calculate the power generation y + Δy1 when (M1 + ΔM1, M2, X), the power generation y + Δy2 when (M1, M2 + ΔM2, X), and the power generation y + Δy3 when (M1, M2, X + ΔX) respectively.

[0114] Successively use the mathematical model of the reactor to obtain the calculated value y of the power generation after the parameter change k (p j +Δp c,j ) relative to the measured value of the power generation before the parameter change of change ε k , and find the partial derivatives of the power generation with respect to each control parameter to obtain the sensitivity matrix (after normalization):

[0115]

[0116] where j = 1Lθ, y k is the calculated value of the power generation at time step t = k (that is, the power generation W of the generator calculated at t = k G ), considering equal time steps, the possible influence brought by different time steps can be ignored.

[0117] According to the deviation value between the preset power generation of the current time step and the actual power generation of the reactor (the calculated current power generation), find the value of the new control variable.

[0118] Calculate the adjustment amount of the control parameter based on the following formula:

[0119] Δp k = S + ·R k

[0120] where S + represents the pseudo-inverse of the sensitivity matrix S. For N reference physical quantities (the total number of model parameters and control parameters), M parameters to be adjusted (that is, model parameters or control parameters), S + is calculated as:

[0121]

[0122] For the power generation control of the helium-xenon small reactor, N = 1, M = 3. In order to avoid the correction of parameters exceeding their physical meaning range and considering faster convergence, the gain factor a can be set. Then the control parameters of the model should be adjusted to:

[0123] P k+1 = Pk +a*ΔP k

[0124] That is, the control parameter P at the next time step is obtained. k+1 , which will be applied to adjust the power generation of the reactor at the next time step.

[0125] The above sensitivity analysis algorithm refers to changing each control parameter in the mathematical model of the helium-xenon cooled reactor, calculating the sensitivity of the reactor power generation with respect to the control parameters, and calculating the control parameters of the mathematical model at the next moment according to the difference between the obtained power generation of the reactor and the preset power generation. After calculating the control parameters of the above mathematical model, the computer applies the control parameters at the next moment to each device of the reactor, such as increasing or decreasing the main circuit flow rate, the flow rate on the pre-cooler side, and the core reflector withdrawal distance.

[0126] In a specific embodiment, before the above step S104, the above method further includes the following steps a to c:

[0127] Step a: Perform state prediction on the helium-xenon cooled reactor based on the neural network and the operating state information to obtain a state prediction result.

[0128] Input the current operating state information detected by the sensors from the reactor into the neural network for future state prediction, and determine whether the operating state of the reactor at a certain future moment exceeds the physical thermal-hydraulic constraints.

[0129] In a specific embodiment, input the power generation in the operating state information into the neural network model, online train the neural network model based on the power generation, and perform single-step prediction on the helium-xenon cooled reactor based on the neural network model to obtain a state prediction result. The above neural network model can be an Elman neural network, a forward neural network, or a recurrent neural network (such as a cyclic neural network or a long short-term memory network, etc.).

[0130] When the above neural network model is an Elman neural network, refer to the Figure 3 schematic diagram of the Elman neural network structure shown. The above neural network model includes an input layer, a hidden layer, and an output layer. Obtain the time series data y of the power generation k+1 = f(y k , y k-1 , L, y k-s+1), time series data is a series of data points arranged in chronological order. In time series data, time is usually an independent variable. Therefore, for time series data with equal time intervals, the time term is often omitted and only the data sequence is retained. The value of the next step is determined by the data of s historical time steps (where t = k is the current time step), which can be regarded as an input-output system determined by a nonlinear mechanism, in which the relationship f can be obtained by fitting and other methods.

[0131] The single-step prediction of the neural network refers to the use of s historical data of power generation to predict the power generation in the next step. The nonlinear state space expression of the Elman neural network is:

[0132] y(k)=g(w 3 x(k)

[0133] x(k)=f(w 1 x c (k)+w 2 u(k-1))

[0134] The receiving layer delays the output of the hidden layer by one step and feeds it back to the input of the hidden layer. Then:

[0135] x c (k) = x(k-1)

[0136] In the above formula, the activation functions of the hidden layer and the output layer are:

[0137]

[0138] g(x)=purelin(x)=x

[0139] The training of the neural network adjusts the weight w through the gradient descent learning algorithm to minimize the loss function, and the loss function used is the mean square error.

[0140] When the future operation status information of the reactor is predicted online based on the above neural network, the above neural network is trained online and predicts the future operation status information of the reactor online. Assume that the number of historical data during neural network training is s, the number of hidden layer nodes of the neural network model is a, and the structure of the network, that is, the number of nodes in the three layers, is recorded as sa-1. L is the number of samples required for each step of single-step prediction. Taking the kth time step as an example, the process of online single-step prediction of the neural network is:

[0141] According to the pre-set training sample L for each step, the experimental data y at the current time step is k Select L training samples continuously by moving forward window, where y k is the actual power generation of the reactor obtained at time k, that is, the first training sample is {(yk-s , y k-s+1 , L, y k-2 , y k-1 ), y k}, the second one is {(y k-s-1 , y k-s , L, y k-3 , y k-2 ), y k-1} and so on by recursion until L samples are selected as a training set to train the neural network model, that is:

[0142]

[0143] Among them, the first L columns in the above formula are L training samples. The last column is used for single-step prediction after training is completed. The first s rows are all inputs of the neural network, and the last row is the output of the neural network. The element y k+1 is initially set to be empty, representing the value to be obtained by single-step prediction The termination condition for training the neural network model is to reach the set training upper limit time T max , which is jointly restricted by the actual time step and the program calculation time.

[0144] After the training of the current step is completed, the adjusted weight W k is obtained, and a single-step prediction is performed using the current neural network. The network input is the latest s experimental data Y = (y k-s+1 , y k-s+2 , L, y k-1 , y k ), and the output of the neural network model is the result of single-step prediction:

[0145]

[0146] Repeatedly executing the above prediction steps can achieve multi-step prediction of the reactor operating state.

[0147] Step b: Judge whether the state prediction result exceeds the preset physical thermal constraints. If so, control the helium-xenon cooled reactor to execute the accident control steps.

[0148] The above accident control steps include: controlling the temperature and pressure reduction of the helium-xenon cooled reactor to make the helium-xenon cooled reactor operate smoothly. Refer to the intelligent control flow chart as Figure 4 shown. Predict the key physical quantity, i.e., the highest temperature of the cladding of the core flow channel, and give an early warning. If it is predicted that a temperature over-limit accident will occur, issue a high-temperature warning and perform accident response operations, that is, immediately perform in-core temperature and pressure reduction operations.

[0149] Step c: If the status prediction result does not exceed the preset physical thermal constraints, execute Step S104.

[0150] The above physical thermal constraints include: 1. Neutron physics constraints, manifested as criticality during normal reactor operation, and the effective multiplication factor is greater than 1; 2. Thermal-hydraulic constraints, manifested as the fuel center temperature and the highest temperature in the corresponding sensitive area not exceeding the material's tolerance temperature with a certain safety margin.

[0151] As Figure 4 shown, if the prediction result is that no temperature overlimit accident will occur, execute the above specific implementation method of adjusting the control parameters of the helium-xenon cooled reactor based on the numerical simulation results to make the power generation power of the helium-xenon cooled reactor reach the preset power generation power, that is, obtain the relationship between the objective function and the control variables at the current time step, calculate the value of the new control variable according to the deviation value between the actual power generation power and the preset power generation power at the current time step, apply the new control variable to the reactor for power generation power control, add 1 to the current time step, and repeat the above helium-xenon cooled reactor control method to achieve the adaptive control of the helium-xenon cooled reactor.

[0152] The above helium-xenon cooled reactor control method provided by this embodiment can achieve the adaptive control of the reactor, enable the reactor to operate stably, and improve the stability of the helium-xenon cooled reactor control.

[0153] On the basis of the foregoing embodiment, this embodiment provides an example of intelligent control of a small helium-xenon cooled solid reactor by applying the foregoing helium-xenon cooled reactor control method, which can be specifically executed according to the following Steps 1 to 4:

[0154] Step 1: Establish a mathematical model of the reactor thermal cycle and core neutron physics.

[0155] Analyze the internal coolant flow law of the helium-xenon cooled reactor, and combine it with core neutron physics to establish a mathematical model. According to the existing reliable data, select initial parameters for physical thermal numerical simulation calculations to verify the reliability and accuracy of the numerical calculations.

[0156] The above helium-xenon cooled reactor has strong coupling. The neutron physics and thermal-hydraulics of the core of the helium-xenon cooled reactor can numerically simulate the internal heat transfer process during reactor power generation; equipment such as compressors, precoolers, regenerators, turbines, reactors, and generators can be simulated and calculated using thermodynamic empirical relations.

[0157] The mathematical simulation of the reactor can be divided into three parts: 1. The thermal cycle part (outside the core part) using thermodynamic relationships; 2. Thermal calculations of the core area (including flow channels and solid areas) using a single-channel program; 3. Neutron physics calculations of the core area using a Monte Carlo program.

[0158] Step 2: Based on the mathematical model and online sensitivity analysis method, the sensitivity matrix between the generated power and the control variables is obtained.

[0159] For the current time step, obtain the relationship between the objective function and the control variable. In order to control the reactor, that is, to obtain the specific value of the current control variable, it is necessary to first find the relationship between the control variable and the objective function, that is, the power generation, that is, ΔY / ΔM1, ΔY / ΔM2, ΔY / ΔX. This step is obtained by changing the three control parameters separately (changing one of them while keeping the other two unchanged) and calculating the corresponding power generation change through the mathematical model (that is, combining the formula in Chapter 1 with the program iteration solution to achieve convergence) (that is, online sensitivity analysis).

[0160] Step 3: Solve the control variables based on the sensitivity matrix and the deviation between the current power generation and the set point.

[0161] The value of the new control variable is obtained according to the deviation between the power generation set point of the current time step and the actual power generation of the stack.

[0162] Step 4: Use neural network online prediction to achieve future short-term prediction of key physical quantities (maximum cladding temperature) for accident warning.

[0163] The key physical quantity, namely the maximum temperature of the core flow channel cladding, is predicted and early warning is given. If a temperature over-limit accident is expected to occur, the temperature and pressure in the reactor are immediately lowered. A neural network is used to make a short-term prediction of the maximum temperature of the cladding in the future.

[0164] In addition to the Elman neural network mentioned above, other types of neural networks can also be used in neural network prediction, such as forward neural networks, or recursive neural networks RNN, LSTM, etc.

[0165] Corresponding to the helium-xenon cooling reactor control method provided in the above embodiment, the embodiment of the present invention provides a helium-xenon cooling reactor control device, see Figure 5 The schematic diagram of the structure of a helium-xenon cooled reactor control device is shown, and the device includes the following modules:

[0166] The monitoring module 51 is used to monitor the operation status information of the helium-xenon cooling reactor during its operation and obtain the pre-constructed mathematical model of the helium-xenon cooling reactor; the operation status information includes the main circuit flow rate, the flow rate on the pre-cooler side, and the core reflector pulling distance.

[0167] The simulation module 52 is used to perform numerical simulation on the mathematical model based on the current operation status information to obtain a numerical simulation result.

[0168] The control module 53 is used to adjust each control parameter of the helium-xenon cooling reactor based on the numerical simulation result so that the power generation of the helium-xenon cooling reactor reaches the preset power generation.

[0169] The above-mentioned helium-xenon cooling reactor control device provided in this embodiment monitors the operation status information of the reactor during the operation of the helium-xenon cooling reactor, performs numerical simulation according to the current operation status information of the reactor, and adjusts the control parameters of the reactor according to the numerical simulation result, so that the power generation of the reactor follows the preset power generation, realizing the adaptive control of each control parameter of the reactor according to the operation status of the reactor. While meeting the load demand, the stability of the reactor operation is improved.

[0170] In one implementation manner, the above-mentioned simulation module 52 is further used to perform a thermal cycle calculation on the helium-xenon cooling reactor based on the current operation status information to obtain the core inlet temperature and the core outlet temperature; perform a thermal-hydraulic calculation on the core region based on the core inlet temperature and the core outlet temperature to obtain the temperatures at various locations inside the core; perform a neutron physics calculation on the core region based on the temperatures at various locations inside the core to obtain the current power generation of the helium-xenon cooling reactor under the current operation status.

[0171] In one implementation manner, the above-mentioned control module 53 is further used to calculate each control parameter of the helium-xenon cooling reactor at the next moment based on the current power generation and the preset power generation, and control the operation of each device of the helium-xenon cooling reactor based on the control parameters so that the power generation of the helium-xenon cooling reactor reaches the preset power generation; wherein, the control parameters include the main circuit flow rate, the flow rate on the pre-cooler side, and the core reflector pulling distance.

[0172] In one implementation manner, the above-mentioned control module 53 is further used to perform a sensitivity analysis on the mathematical model based on the current power generation and the preset power generation to determine the control parameters of the helium-xenon cooling reactor at the next moment.

[0173] In one implementation manner, the above-mentioned device further includes:

[0174] A prediction module, configured to perform state prediction on a helium-xenon cooling reactor based on a neural network and operating status information to obtain a state prediction result; determine whether the state prediction result exceeds a preset physical thermal constraint, and if so, control the helium-xenon cooling reactor to execute accident control steps.

[0175] The prediction module is further configured to trigger the operation of the above-mentioned simulation module when the state prediction result does not exceed the preset physical thermal constraint.

[0176] The prediction module is further configured to input the generated power in the operating status information into a neural network model, online train the neural network model based on the generated power, and perform single-step prediction on the helium-xenon cooling reactor based on the neural network model to obtain a state prediction result.

[0177] The above-mentioned helium-xenon cooling reactor control device provided in this embodiment can achieve adaptive control of the reactor, enable the reactor to operate stably, and improve the stability of the control of the helium-xenon cooling reactor.

[0178] For the device provided in this embodiment, the implementation principle and the technical effects produced are the same as those of the foregoing embodiment. For a brief description, for the parts not mentioned in the device embodiment, reference may be made to the corresponding content in the foregoing method embodiment.

[0179] An embodiment of the present invention provides an electronic device, as Figure 6 shown in the schematic structural diagram of the electronic device. The electronic device includes a processor 61 and a memory 62. A computer program that can run on the processor is stored in the memory. When the processor executes the computer program, the steps of the method provided in the above embodiment are implemented.

[0180] See Figure 6 , the electronic device further includes: a bus 64 and a communication interface 63. The processor 61, the communication interface 63, and the memory 62 are connected through the bus 64. The processor 61 is configured to execute an executable module stored in the memory 62, such as a computer program.

[0181] Among them, the memory 62 may include a high-speed random access memory (RAM, Random Access Memory), and may also include a non-volatile memory, such as at least one disk memory. Through at least one communication interface 63 (which can be wired or wireless), a communication connection between this system network element and at least one other network element is realized, and the Internet, wide area network, local area network, metropolitan area network, etc. can be used.

[0182] The bus 64 can be an ISA (Industry Standard Architecture) bus, a PCI (Peripheral Component Interconnect) bus, an EISA (Extended Industry Standard Architecture) bus, or the like. The bus can be divided into an address bus, a data bus, a control bus, etc. For ease of representation, Figure 6 only a bidirectional arrow is used in Figure 6 , but it does not mean that there is only one bus or one type of bus.

[0183] Among them, the memory 62 is used to store a program. After receiving an execution instruction, the processor 61 executes the program. The method executed by the device defined by the flow process disclosed in any embodiment of the foregoing embodiments of the present invention can be applied to or implemented by the processor 61.

[0184] The processor 61 may be an integrated circuit chip with signal processing capabilities. In the implementation process, each step of the above method can be completed by the integrated logic circuit in the hardware of the processor 61 or by instructions in the form of software. The above-mentioned processor 61 can be a general-purpose processor, including a central processing unit (CPU for short), a network processor (NP for short), etc. It can also be a digital signal processor (DSP for short), an application specific integrated circuit (ASIC for short), a field-programmable gate array (FPGA for short), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components. It can implement or execute the various methods, steps, and logic block diagrams disclosed in the embodiments of the present invention. The general-purpose processor can be a microprocessor or the processor can also be any conventional processor, etc. The steps of the method disclosed in combination with the embodiments of the present invention can be directly embodied as being executed and completed by a hardware decoding processor, or by a combination of hardware and software modules in the decoding processor. The software module can be located in a mature storage medium in the art such as a random access memory, a flash memory, a read-only memory, a programmable read-only memory, or an electrically erasable programmable memory, a register, etc. This storage medium is located in the memory 62, and the processor 61 reads the information in the memory 62 and combines its hardware to complete the steps of the above method.

[0185] An embodiment of the present invention provides a computer-readable medium, wherein the computer-readable medium stores computer-executable instructions, and when the computer-executable instructions are called and executed by a processor, the computer-executable instructions cause the processor to implement the method described in the above embodiment.

[0186] Those skilled in the art can clearly understand that for the convenience and conciseness of description, the specific working process of the above-described system can refer to the corresponding process in the foregoing embodiment, and will not be elaborated herein.

[0187] The computer program product of the helium-xenon cooled reactor control method, device and electronic device provided by the embodiment of the present invention includes a computer-readable storage medium storing program codes, and the instructions included in the program codes can be used to execute the method described in the foregoing method embodiment. For the specific implementation, reference can be made to the method embodiment, and will not be elaborated herein.

[0188] In addition, in the description of the embodiments of the present invention, unless otherwise clearly defined and limited, the terms "installation", "connection" and "connection" shall be understood in a broad sense. For example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be directly connected, or indirectly connected through an intermediate medium, and it can be the communication inside two elements. For those of ordinary skill in the art, the specific meanings of the above terms in the present invention can be understood according to specific situations.

[0189] If the above function is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on such an understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present invention. The foregoing storage medium includes: various media such as a USB flash drive, a mobile hard disk, a read-only memory (ROM, Read-Only Memory), a random access memory (RAM, Random Access Memory), a magnetic disk, or an optical disc that can store program codes.

[0190] In the description of the present invention, it should be noted that the orientation or positional relationship indicated by the terms "center", "upper", "lower", "left", "right", "vertical", "horizontal", "inner", "outer", etc. is based on the orientation or positional relationship shown in the drawings. It is only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation. Therefore, it should not be construed as a limitation on the present invention. In addition, the terms "first", "second", "third" are only used for descriptive purposes and cannot be construed as indicating or implying relative importance.

[0191] Finally, it should be noted that the above-described embodiments are only specific embodiments of the present invention, used to illustrate the technical solutions of the present invention, rather than limiting them. The protection scope of the present invention is not limited thereto. Although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that any person skilled in the art within the technical scope disclosed by the present invention can still modify the technical solutions described in the foregoing embodiments or can easily conceive of changes, or perform equivalent replacements on some of the technical features; and these modifications, changes or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present invention, and should all be covered by the protection scope of the present invention. Therefore, the protection scope of the present invention should be subject to the protection scope of the claims.

Claims

1. A control method for a helium-xenon cooling reactor, characterized in that, Including: During the operation of a helium-xenon cooled reactor, monitor the operation state information of the helium-xenon cooled reactor, and obtain the mathematical model of the helium-xenon cooled reactor pre-constructed; the operation state information includes the main circuit flow rate, the flow rate on the precooler side, and the core reflector pull distance. Perform numerical simulation on the mathematical model based on the current operation state information to obtain a numerical simulation result. Adjust each control parameter of the helium-xenon cooled reactor based on the numerical simulation result so that the power generation of the helium-xenon cooled reactor reaches a preset power generation. The step of performing numerical simulation on the mathematical model based on the current operation state information to obtain a numerical simulation result includes: Perform a thermal cycle calculation on the helium-xenon cooled reactor based on the current operation state information to obtain the core inlet temperature and the core outlet temperature; perform a thermal-hydraulic calculation on the core area based on the core inlet temperature and the core outlet temperature to obtain the temperatures at various locations inside the core; perform a neutron physics calculation on the core area based on the temperatures at various locations inside the core to obtain the current power generation of the helium-xenon cooled reactor under the current operation state. The numerical simulation result includes the current power generation. The step of adjusting each control parameter of the helium-xenon cooled reactor based on the numerical simulation result so that the power generation of the helium-xenon cooled reactor reaches a preset power generation includes: Calculate each control parameter of the helium-xenon cooled reactor at the next moment based on the current power generation and the preset power generation, and control the operation of each device of the helium-xenon cooled reactor based on the control parameter so that the power generation of the helium-xenon cooled reactor reaches a preset power generation; wherein, the control parameter includes the main circuit flow rate, the flow rate on the precooler side, and the core reflector pull distance.

2. The method according to claim 1, characterized in that, The step of calculating each control parameter of the helium-xenon cooled reactor at the next moment based on the current power generation and the preset power generation includes: Perform a sensitivity analysis on the mathematical model based on the current power generation and the preset power generation to determine the control parameter of the helium-xenon cooled reactor at the next moment.

3. The method according to claim 1, wherein Also including: Perform a state prediction on the helium-xenon cooled reactor based on a neural network and the operation state information to obtain a state prediction result. Judge whether the state prediction result exceeds the preset physical thermal-hydraulic constraint. If so, control the helium-xenon cooled reactor to execute an accident control step.

4. The method according to claim 3, characterized in that Also including: If the state prediction result does not exceed the preset physical thermal-hydraulic constraint, return to execute the step of performing numerical simulation on the mathematical model based on the current operation state information to obtain a numerical simulation result.

5. The method according to claim 3, characterized in that, The step of performing a state prediction on the helium-xenon cooled reactor based on a neural network and the operation state information to obtain a state prediction result includes: Input the power generation in the operation state information into a neural network model, online train the neural network model based on the power generation, and perform a single-step prediction on the helium-xenon cooled reactor based on the neural network model to obtain a state prediction result.

6. A helium-xenon cooling reactor control device, characterized in that, Including: A monitoring module, configured to monitor the operating state information of the helium-xenon cooling reactor during its operation, and obtain the pre-constructed mathematical model of the helium-xenon cooling reactor; the operating state information includes the main loop flow rate, the flow rate on the precooler side, and the core reflector withdrawal distance. A simulation module, configured to perform numerical simulation on the mathematical model based on the current operating state information to obtain a numerical simulation result. A control module, configured to adjust each control parameter of the helium-xenon cooling reactor based on the numerical simulation result, so that the power generation power of the helium-xenon cooling reactor reaches a preset power generation power. The simulation module is configured to perform a thermal cycle calculation on the helium-xenon cooling reactor based on the current operating state information to obtain the core inlet temperature and the core outlet temperature. Performing a thermal-hydraulic calculation on the core region based on the core inlet temperature and the core outlet temperature to obtain the temperatures at various locations inside the core; performing a neutron physics calculation on the core region based on the temperatures at various locations inside the core to obtain the current power generation power of the helium-xenon cooling reactor under the current operating state. The control module is configured to calculate each control parameter of the helium-xenon cooling reactor at the next moment based on the current power generation power and the preset power generation power, and control the operation of each device of the helium-xenon cooling reactor based on the control parameter, so that the power generation power of the helium-xenon cooling reactor reaches the preset power generation power; wherein, the control parameter includes the main loop flow rate, the flow rate on the precooler side, and the core reflector withdrawal distance.

7. An electronic device, characterized in that, Comprising: A processor and a storage device; A computer program is stored on the storage device, and the computer program, when run by the processor, executes the method according to any one of claims 1 to 5.

8. A computer-readable storage medium, on which a computer program is stored, characterized in that, The computer program, when run by the processor, executes the steps of the method according to any one of claims 1 to 5 above.

Images