A Comprehensive Design Method for a Micro Reactor Brayton Cycle System

Abstract

The present invention discloses a comprehensive design method for a micro-reactor Brayton cycle system. This method considers the coupling relationship between component performance and cycle parameters, constructing a micro-reactor Brayton cycle-component joint design program. The thermodynamic parameters at each cycle point serve as component design boundary conditions, and the component design results serve as component performance input values within the cycle. The cycle thermodynamic calculation results and the component design results are interactively and iteratively corrected until the cycle efficiency error between the two calculations meets the required error. Component performance and basic dimensions can be obtained during the cycle design phase, enabling the simultaneous design of cycle and component parameters and significantly improving the accuracy of the design results. Furthermore, the present invention creatively proposes replacing the traditional cycle efficiency optimization target with "system power density" and employs a genetic optimization algorithm to optimize the cycle design parameters, resulting in a micro-reactor Brayton cycle system design scheme that balances high efficiency and compactness.

Description

Technical Field

[0001] The present invention belongs to the fields of nuclear energy application technology and power engineering technology, and in particular relates to a comprehensive design method for a micro-reactor Brayton cycle system. Background Art

[0002] With the rapid development of fourth-generation nuclear reactor technology, miniaturized mobile reactor technology has attracted great attention from researchers in various countries. The power level of micro reactors is between 1-20MW, with high power density, good reliability, and a life cycle of up to several years. They can be quickly moved and deployed by vehicles, aircraft, and ships. Micro reactor power systems can provide electricity and heat in high-altitude, polar, and ocean environments, and have potential application value in military power, ocean scientific research, and disaster relief. Micro reactor types include high-temperature gas-cooled reactors and heat pipe reactors, which usually use the Brayton cycle as a thermoelectric conversion method. The overall system is efficient, compact, and flexible. The schematic diagram of the micro reactor Brayton cycle system is shown below. Figure 1 As shown, the system consists of a reactor heat source, heater, turbine, regenerator, cooler, compressor, and generator. The working fluid is first pressurized by the compressor (1-2), then enters the low-temperature side of the regenerator to recover heat (2-3). It is then heated to the highest temperature in the cycle in the heater (3-4). The high-temperature, high-pressure working fluid then enters the turbine to expand and perform work (4-5). After completing this work, the working fluid enters the high-temperature side of the regenerator to release heat (5-6). Finally, the working fluid, with residual heat, is cooled to the lowest temperature in the cycle in the cooler (6-1). To ensure compactness, the compressor and turbine in this system are coaxial, maintaining consistent rotational speeds.

[0003] In the traditional Brayton cycle design method, it is first necessary to assume that the performance of the components is a certain value (compressor, turbine equal entropy efficiency, pressure loss in the heat exchanger) based on the boundary conditions and design requirements, and give the range of variation of the key design parameters, build a thermodynamic model, and use the optimization algorithm to find the optimal cycle design parameters with the maximum cycle efficiency as the goal. The preliminary design of the components includes the one-dimensional flow structure design of the impeller machinery and the heat exchanger structure design. After obtaining the optimized thermodynamic parameters of the system (temperature, pressure, flow, etc.), the preliminary design of the key components is carried out to obtain the basic structure and performance parameters of the impeller machinery and heat exchanger that can meet the performance requirements. The flow chart of the traditional Brayton cycle design method is as follows Figure 2 shown.

[0004] In traditional Brayton cycle design methods, the turbomachinery isentropic efficiency and heat exchanger pressure drop are typically assumed to be constants. However, component performance and cycle parameters are coupled. Cycle parameters such as pressure ratio and power rating determine the cycle flow rate and the thermal state at each point, namely, the component inlet and outlet conditions. Generally, higher power ratings lead to higher cycle flow rates and higher turbomachinery efficiency. Furthermore, the impeller isentropic efficiency directly determines compressor power consumption and turbine power output, making cycle efficiency dependent on component performance. As boundary conditions change, component performance assumptions are not always reasonable. Component performance obtained using traditional design methods is likely to deviate from the assumed values. Overly high component performance assumptions can lead to suboptimal component design; underlying them can result in suboptimal cycle performance. Both of these scenarios lead to inaccurate cycle parameter design results.

[0005] To improve cycle efficiency, traditional Brayton cycle designs often employ complex cycle configurations such as heat recovery, intercooling, and reheating, while also increasing the heat exchanger area to maximize heat transfer. However, if the design parameters are not appropriate, these measures will significantly increase the overall size of the power system, contradicting the compactness goal of microreactor power systems. It is difficult to achieve a balance between efficiency and compactness. Summary of the Invention

[0006] In order to overcome the above-mentioned deficiencies in the prior art, the purpose of the present invention is to propose a comprehensive design method for a micro-reactor Brayton cycle system, which solves the problem of inaccurate cycle design results caused by unreasonable component performance assumptions in the prior art, and the problem that traditional design methods cannot take into account both system efficiency and compactness.

[0007] In order to achieve the above object, the technical solution adopted by the present invention is as follows:

[0008] A comprehensive design method for a micro-reactor Brayton cycle system includes the following steps:

[0009] (1) Establish a joint design procedure for the Brayton cycle and components of a microreactor, as follows;

[0010] (1.1) Based on the cycle boundary conditions, the initial design parameters of the micro-reactor Brayton cycle are given and the component performance parameters are assumed;

[0011] (1.2) Establish a Brayton cycle thermodynamic model and obtain the initial values of the thermal state and flow rate at each point in the micro-reactor Brayton cycle through thermodynamic calculations, which serve as the thermal parameter boundary conditions required for component design;

[0012] (1.3) Based on the thermal parameter boundary conditions required for component design, interactive iterative correction calculations are performed between the thermodynamic calculation results and the component design calculation results to obtain component design results including performance parameters and structural parameters, and thermodynamic calculation results including cycle efficiency and flow rate;

[0013] (1.4) Compare the cycle efficiency with the cycle efficiency value obtained from the last thermodynamic calculation. When the error between the two thermodynamic calculation results is less than or equal to the given error upper limit, end step (1.4). Otherwise, replace the original boundary conditions of the component with the cycle design parameters obtained from the last thermodynamic calculation, and return to step (1.3) to restart component design.

[0014] (1.5) Output power density D of micro-stack Brayton cycle system p ;

[0015] The mathematical expression of the micro reactor Brayton cycle-component joint design procedure is:

[0016]

[0017] Among them, D p is the power density of the micro-reactor Brayton cycle system, is the compressor inlet temperature, is the cooling medium outlet temperature, ε re is the regenerator efficiency, π C is the compressor pressure ratio;

[0018] (2) Using a genetic optimization algorithm, the cycle design parameters are optimized with the goal of maximizing the power density of the micro-reactor Brayton cycle system;

[0019] (3) Calculate and output the cycle optimization design results and component design results.

[0020] In step (1.3), an interactive iterative correction calculation is performed between the thermodynamic calculation results and the component design calculation results; the specific content of the interactive iterative correction calculation is: each time a component design calculation is completed, the original performance parameters of the component are replaced by the new component performance parameter calculation results, and a thermodynamic calculation is performed to update the thermal state and flow of each point in the micro-reactor Brayton cycle as the boundary conditions of the next component design calculation; during the design, the component performance parameters output by the previous component design calculation are used as the input values of this thermodynamic calculation, and the thermal state and flow of each point in the micro-reactor Brayton cycle output by this thermodynamic calculation are used as the input values of the next component design calculation; the calculation is performed in the order of heater, turbine, regenerator, cooler, and compressor. After completing the compressor design calculation and the corresponding thermodynamic calculation, the cycle efficiency is output. And the circulation flow mn, n represents the nth execution of step (1.3)), and step (1.3) ends.

[0021] In step (1.5), the output parameter is the power density of the micro-reactor Brayton cycle system; the power density of the micro-reactor Brayton cycle system D p It is defined as the net output power of the power system per unit system volume, which is numerically equal to the ratio of the net output power of the micro-reactor Brayton cycle system to the sum of the volumes of all components of the micro-reactor Brayton cycle system. If the core power is fixed, the net output power is equal to the product of the core power and the cycle efficiency. If the core power remains unchanged, the higher the cycle efficiency or the smaller the component size, the greater the power density of the micro-reactor Brayton cycle system. As a power cycle evaluation indicator, the power density of the micro-reactor Brayton cycle system can accurately reflect the degree of performance improvement brought about by increasing the system configuration complexity and the size of the heat exchange surface.

[0022]

[0023] in, is the core power, η cycle is the cycle efficiency, is the net output power of the system, V C , V T , V H , V R , V Co They represent the volumes of the compressor, turbine, heater, regenerator and cooler respectively. The component volumes are calculated based on the component size parameters.

[0024] In step (2), a genetic optimization algorithm is used to optimize the cycle parameters with the goal of maximizing the power density of the micro-reactor Brayton cycle system to obtain the best design scheme; the cycle parameters that need to be optimized include the compressor inlet temperature Cooling medium outlet temperature Regenerator efficiency ε re , compressor pressure ratio π C ; The specific expression is:

[0025] Optimization goal:

[0026] Constraints:

[0027]

[0028] In step 3, the cycle design parameters optimized in step 2 are used as input values of the micro-reactor Brayton cycle-component joint design program to calculate the cycle optimization design results and component design results under the optimal design scheme; the cycle optimization design results include cycle performance parameters and cycle design parameters; the output component design results include component performance parameters and component size parameters.

[0029] The present invention takes into account the coupling relationship between component performance and cycle parameters, constructs a system-level and component-level integrated design method, and enables interactive iterative correction of the cycle thermodynamic model calculation results and the initial component design results. Component performance and basic dimensions can be obtained during the cycle concept design stage, achieving the synchronous design of cycle parameters and component parameters, and significantly improving the accuracy of the design results. In addition, the present invention creatively proposes to replace the traditional cycle efficiency evaluation index with the "system power density" index. By optimizing the cycle design parameters with the system power density as the target, the resulting system design scheme takes into account both high efficiency and compactness. BRIEF DESCRIPTION OF THE DRAWINGS

[0030] Figure 1 This is a schematic diagram of the Brayton cycle system of a micro reactor;

[0031] Figure 2 Design a method flow chart for the traditional Brayton cycle;

[0032] Figure 3 A flow chart of the micro-reactor Brayton cycle-component joint design process proposed in the present invention;

[0033] Figure 4 This is the interactive iterative correction calculation flow chart proposed by the present invention. DETAILED DESCRIPTION

[0034] The technical solution of the present invention is further described in detail below with reference to the accompanying drawings.

[0035] The present invention proposes a comprehensive design method for a micro-reactor Brayton cycle system, constructs a micro-reactor Brayton cycle-component joint design program, enables interactive iterative correction calculations of cycle thermodynamic calculation results and component design results, searches for the optimal cycle design parameter combination with system power density as the optimization target, realizes the synchronous design of cycle parameters and component parameters, and solves the problems of inaccurate cycle design results caused by unreasonable component performance assumptions in traditional design methods, as well as the problem that traditional design methods cannot take into account both system efficiency and compactness.

[0036] like Figure 3 As shown, a comprehensive design method for a micro-reactor Brayton cycle system includes the following steps:

[0037] 1. Establish a joint design procedure for the Brayton cycle and components of a microreactor;

[0038] 2. Using a genetic optimization algorithm, the cycle design parameters are optimized with the goal of maximizing the power density of the micro-reactor Brayton cycle system;

[0039] 3. Calculate and output cycle optimization design results and component design results.

[0040] Specifically, in step 1, the steps for establishing the micro reactor Brayton cycle-component joint design program are as follows:

[0041] 1.1. Based on the known cycle boundary conditions, the initial design parameters of the micro-reactor Brayton cycle are given and the component performance parameters are assumed;

[0042] The required initial design parameters for the microreactor Brayton cycle include the compressor inlet temperature, the coolant outlet temperature, the compressor pressure ratio, and the regenerator efficiency. The assumed component performance parameters include the turbine isentropic efficiency, the compressor isentropic efficiency, the regenerator pressure drop across the chamber, the heater pressure drop, and the cooler pressure drop.

[0043] 1.2. Establish a Brayton cycle thermodynamic model and obtain the initial values of the thermal state and flow rate at each point in the micro-reactor Brayton cycle through thermodynamic calculations, which serve as the thermal parameter boundary conditions required for component design;

[0044] The conventional simple Brayton cycle thermodynamic model is based on the energy conservation equation, the continuity equation, and the REFPROP standard working fluid property library. This thermodynamic model has been extensively studied in the field of power engineering. Based on given cycle boundary conditions (microreactor core power, core operating temperature, and ambient temperature), initial cycle design parameters (compressor pressure ratio, compressor inlet temperature, coolant outlet temperature, and regenerator efficiency), and assumed component performance parameters (compressor and turbine isoentropic efficiencies, regenerator pressure drop across the regenerator, heater pressure drop, and cooler pressure drop), this thermodynamic model calculates the flow rate and working fluid thermodynamic state at each cycle node.

[0045] The present invention uses the Ebsilon thermodynamic simulation platform to establish and solve the Brayton cycle thermodynamic model to obtain cycle performance parameters and state parameters at each point (Ebsilon is a system thermodynamic simulation software). The working fluid physical properties are calculated using the unified NIST refprop physical property database.

[0046] 1.3. Based on the thermal parameter boundary conditions required for component design, interactive iterative correction calculations are performed between the thermodynamic calculation results and the component design calculation results to obtain component design results including performance parameters and structural parameters, and thermodynamic calculation results including cycle efficiency and flow rate;

[0047] The component design method includes a one-dimensional design method for an impeller and a design method for a heat exchanger. The one-dimensional design method for an impeller uses boundary conditions (the inlet temperature and pressure, outlet pressure, and mass flow rate of the impeller) and assumed values of performance parameters (isentropic efficiency of the impeller) as input values, and calculates and outputs the dimensional parameters (number of blades, impeller outer diameter, axial length, etc.) and performance parameters (isentropic efficiency of the impeller); the heat exchanger design method uses boundary conditions (the inlet temperature and pressure, outlet temperature, and mass flow rate of the heat exchanger) as input values, and calculates and outputs the dimensional parameters (heat exchange area, flow channel length, etc.) and performance parameters (pressure loss of the heat exchanger). The one-dimensional design method for an impeller used in the specific embodiment of the present invention is based on the reference document "Yang Ce, Shi Xin. Theory and Design of Radial Impellers. 2004. National Defense Industry Press"; the heat exchanger design method is based on the reference document "Yu Jianzu. Principles and Design of Heat Exchangers. 2006. Beijing University of Aeronautics and Astronautics." The component design method is written into a function using Matlab software, the component inlet and outlet boundary conditions are input, and the output parameters are the component structure size and performance parameters.

[0048] In step 1.3, in order to improve the calculation stability and convergence, interactive iterative correction calculation is performed between the thermodynamic calculation results and the component design calculation results. The interactive iterative correction calculation process is shown in Figure 4 . The specific content of the interactive iterative correction calculation is: each time a component design calculation is completed, the original performance parameters of the component are replaced by the new component performance parameter calculation results, and a thermodynamic calculation is performed to update the thermal state and flow rate of each point in the micro-reactor Brayton cycle as the boundary conditions for the next component design calculation. During the design, the component performance parameters output by the previous component design calculation are used as the input values of this thermodynamic calculation, and the thermal state and flow rate of each point in the micro-reactor Brayton cycle output by this thermodynamic calculation are used as the input values of the next component design calculation. This process is the interactive iterative correction calculation of the thermodynamic calculation results and the component design calculation results. The calculation is performed in the order of heater, turbine, regenerator, cooler, and compressor. After completing the compressor design calculation and the corresponding thermodynamic calculation, the cycle efficiency is output. (n represents the nth execution of step 1.3), and step 1.3 ends.

[0049] The Matlab main program can transfer parameters between the component design function and the thermodynamic model: the main program inputs the state parameters and flow of the internal nodes of the loop corresponding to the inlet and outlet of the component into the component design function. The component design function outputs the component size parameters and performance parameters after calculation and records them in the main program; the main program inputs the obtained component performance parameters into the Ebsilon thermodynamic model, obtains the state parameters and performance parameters of each point in the loop through cycle thermodynamic calculation, and saves them in the main program.

[0050] 1.4. Compare the cycle efficiency with the cycle efficiency value obtained from the last thermodynamic calculation. If the error between the two thermodynamic calculation results is less than or equal to the given error limit, end step 1.4. Otherwise, replace the original component boundary conditions with the cycle parameters obtained from the last thermodynamic calculation and return to step 1.3 to restart component design.

[0051] If the cycle efficiency obtained from the two calculations meets the convergence condition (ε is the upper limit of the given error of the cycle efficiency), then step 1.4 ends. Otherwise, the cycle design parameters obtained from the last thermodynamic calculation are used as boundary conditions, and the interactive iterative correction calculation is restarted in step 1.3.

[0052] 1.5 Output power density D of the micro-reactor Brayton cycle system p .

[0053] The mathematical expression of the micro reactor Brayton cycle-component joint design procedure is:

[0054]

[0055] Among them, D p is the power density of the micro-reactor Brayton cycle system, is the compressor inlet temperature, is the cooling medium outlet temperature, ε re is the regenerator efficiency, π C is the compressor pressure ratio.

[0056] Power density D of micro-reactor Brayton cycle system p This is defined as the net power output per unit system volume of the power system. It is numerically equal to the ratio of the net power output of the micro-reactor Brayton cycle system to the sum of the volumes of its components. If the core power is fixed, the system net power output is equal to the product of the core power and the cycle efficiency. For a given core power, higher cycle efficiency or smaller component size will increase the power density of the micro-reactor Brayton cycle system. As a power cycle evaluation metric, the power density of a micro-reactor Brayton cycle system accurately reflects the performance gains achieved through increased system configuration complexity and heat transfer surface size.

[0057]

[0058] in, is the core power, η cycle is the cycle efficiency, is the net output power of the system, V C , V T , V H , V R , VCo They represent the volumes of the compressor, turbine, heater, regenerator and cooler respectively. The component volumes are calculated based on the component size parameters.

[0059] Specifically, in step 2, a genetic optimization algorithm is used to optimize the cycle design parameters with the goal of maximizing the power density of the micro-reactor Brayton cycle system to obtain the best design solution. Genetic algorithm is a method that simulates biological evolution in nature. It is based on genetics and natural selection, searches for the optimal space through probabilistic methods, and automatically adjusts the search direction to ultimately obtain the optimal solution globally. With the help of Matlab's genetic algorithm toolkit, after determining the range of variation of the variables to be optimized and the genetic algorithm design parameters (population number, maximum iteration number, crossover probability, mutation probability, etc.), the optimal cycle parameter combination can be obtained through optimization calculation. The cycle parameters that need to be optimized include the compressor inlet temperature Cooling medium outlet temperature Regenerator efficiency ε re , compressor pressure ratio π C The specific expression is:

[0060] Optimization goal:

[0061] Constraints:

[0062]

[0063] Specifically, in step 3, the four cycle design parameters optimized in step 2 are used as input values for the micro-reactor Brayton cycle-component joint design program to calculate the cycle optimization design results and component design results under the optimal design scheme. The cycle optimization design results output in step 3 include cycle performance parameters such as system power density, cycle efficiency, working fluid flow rate, temperature and pressure at each point in the cycle, as well as cycle design parameters such as compressor pressure ratio, compressor inlet temperature, cooling medium outlet temperature, and regenerator efficiency; the component design results output include component performance parameters such as the isentropic efficiency of the compressor and turbine, pressure loss on both sides of the heat exchanger, and component size parameters such as the outer diameter, blade length, and axial length of the impeller.

[0064] In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Generally, the components of the embodiments of the present invention described and shown in the drawings herein can be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of the present invention provided in the drawings is not intended to limit the scope of the claimed invention, but merely represents selected embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0065] To demonstrate the superiority of the proposed method, a calculation example comparing the new method with a traditional optimization method is presented below. This example employs both the traditional design method and the integrated design method proposed in this invention to design a closed air Brayton cycle system for a 5MW micro-reactor.

[0066] Table 1 Component types used in the closed air circulation of micro-reactors

[0067]

[0068] Schematic diagram of closed air circulation of micro-stack Figure 1 As shown, the micro-reactor used in this example is based on the 5MWt-class heat pipe reactor designed by INL. It uses 20°C ambient air as the cooling medium, driven by a cold-end compressor to flow through the cooler. The types of system components used are listed in Table 1. A closed air circulation system thermodynamic model was established on the Ebsilon Professional 14.0 platform, and the main control program and component design function programs were written in Matlab. Matlab's built-in genetic optimization algorithm tool was used, and the parameter range of the genetic algorithm is shown in Table 2. The compressor inlet temperature, compressor pressure ratio, cooling medium outlet temperature, and regenerator efficiency were selected as optimization variables, and the cycle design parameters were optimized with the system power density as the optimization target.

[0069] Table 2 Range of parameters to be optimized by genetic optimization algorithm

[0070]

[0071] Table 3 shows the initial, pre-optimization, and post-optimization cycle design parameters. From the initial design to the pre-optimization design, the cycle parameters to be optimized remained unchanged; only component performance and cycle thermodynamic calculation results were modified. After modification, the cycle efficiency increased from 24.94% to 31.06%, the cycle flow rate increased from 30.07 kg / s to 33.28 kg / s, the external pressure drop of the cooler decreased from 10 kPa to 1.07 kPa, and the internal pressure drop increased from 5 kPa to 11.4 kPa. The pressure drop on the low-temperature side of the regenerator was reduced to half of its initial value. After modification, the turbine isentropic efficiency was 83.17%, and the compressor isentropic efficiency was 79.66%. The coaxial speed of the two was 36,400 rpm. The heat exchanger design dimensions and heat transfer coefficients are shown in Table 3. The combined volume of the heat pipe heater, regenerator, and cooler was 5.31 m². The system power density before optimization was 296.47 kW / m³. It can be seen from this that the comprehensive design method proposed in the present invention can effectively improve the accuracy of the cycle design results, and the errors between the component performance and the thermal parameters at each point in the cycle and the actual values are smaller.

[0072] Table 3 Initial design parameters of closed air Brayton cycle and design parameters before and after optimization

[0073]

[0074]

[0075] After optimization calculations targeting maximum system power density, the maximum system power density was found to be 402.34 kW / m³, corresponding to a total heat exchanger volume of 3.09 m³, a cycle efficiency of 24.86%, and a circulation flow rate of 25.43 kg / s. After optimization targeting system power density, the system size was reduced from the baseline design's 5.31 m³ to 3.09 m³, significantly improving system compactness. The optimization results of this example demonstrate the reliability of using system power density as a common evaluation metric for system efficiency and compactness. The comprehensive design method for a micro-reactor Brayton cycle system proposed in this invention can achieve an optimal design that balances both system efficiency and compactness.

[0076] The present invention takes into account the coupling relationship between component performance and cycle parameters, constructs a system-level and component-level integrated design method, and enables interactive iterative correction of the cycle thermodynamic model calculation results and the initial component design results. Component performance and basic dimensions can be obtained during the cycle concept design stage, achieving the synchronous design of cycle parameters and component parameters, and significantly improving the accuracy of the design results. In addition, the present invention creatively proposes to replace the traditional cycle efficiency evaluation index with the "system power density" index. By optimizing the cycle design parameters with the system power density as the target, the resulting system design scheme takes into account both high efficiency and compactness.

Claims

1. A comprehensive design method for a micro-reactor Brayton cycle system, characterized in that: The following steps are involved: (1) Establish a joint design procedure for the Brayton cycle and components of a microreactor, as follows; (1.1) Based on the cycle boundary conditions, the initial design parameters of the micro-reactor Brayton cycle are given and the component performance parameters are assumed; (1.2) Establish a Brayton cycle thermodynamic model and obtain the initial values of the thermal state and flow rate at each point in the micro-reactor Brayton cycle through thermodynamic calculations, which serve as the thermal parameter boundary conditions required for component design; (1.3) Based on the thermal parameter boundary conditions required for component design, interactive iterative correction calculations are performed between the thermodynamic calculation results and the component design calculation results to obtain component design results including performance parameters and structural parameters, and thermodynamic calculation results including cycle efficiency and flow rate; (1.4) Compare the cycle efficiency with the cycle efficiency value obtained from the last thermodynamic calculation. When the error between the two thermodynamic calculation results is less than or equal to the given error upper limit, end step (1.4). Otherwise, replace the original boundary conditions of the component with the cycle design parameters obtained from the last thermodynamic calculation, and return to step (1.3) to restart component design. (1.5) Output power density D of micro-stack Brayton cycle system p ; The mathematical expression of the micro reactor Brayton cycle-component joint design procedure is: Among them, D p is the power density of the micro-reactor Brayton cycle system, is the compressor inlet temperature, is the cooling medium outlet temperature, ε re is the regenerator efficiency, π C is the compressor pressure ratio; (2) Using a genetic optimization algorithm, the cycle design parameters are optimized with the goal of maximizing the power density of the micro-reactor Brayton cycle system; (3) Calculate and output the cycle optimization design results and component design results.

2. The integrated design method according to claim 1, characterized in that: In step (1.3), an interactive iterative correction calculation is performed between the thermodynamic calculation results and the component design calculation results; the specific content of the interactive iterative correction calculation is: each time a component design calculation is completed, the original performance parameters of the component are replaced by the new component performance parameter calculation results, and a thermodynamic calculation is performed to update the thermal state and flow of each point in the micro-reactor Brayton cycle as the boundary conditions of the next component design calculation; during the design, the component performance parameters output by the previous component design calculation are used as the input values of this thermodynamic calculation, and the thermal state and flow of each point in the micro-reactor Brayton cycle output by this thermodynamic calculation are used as the input values of the next component design calculation; the calculation is performed in the order of heater, turbine, regenerator, cooler, and compressor. After completing the compressor design calculation and the corresponding thermodynamic calculation, the cycle efficiency is output. and circulation flow m n , n means the nth execution of step (1.3), and step (1.3) ends.

3. The integrated design method according to claim 1, wherein: In step (1.5), the output parameter is the power density of the micro-reactor Brayton cycle system; the power density of the micro-reactor Brayton cycle system D p It is defined as the net output power of the power system per unit system volume, which is numerically equal to the ratio of the net output power of the micro-reactor Brayton cycle system to the sum of the volumes of all components of the micro-reactor Brayton cycle system. If the core power is fixed, the net output power is equal to the product of the core power and the cycle efficiency. If the core power remains unchanged, the higher the cycle efficiency or the smaller the component size, the greater the power density of the micro-reactor Brayton cycle system. As a power cycle evaluation indicator, the power density of the micro-reactor Brayton cycle system can accurately reflect the degree of performance improvement brought about by increasing the system configuration complexity and the size of the heat exchange surface. in, is the core power, η cycle is the cycle efficiency, is the net output power of the system, V C , V T , V H , V R , V Co They represent the volumes of the compressor, turbine, heater, regenerator and cooler respectively. The component volumes are calculated based on the component size parameters.

4. The integrated design method according to claim 1, wherein: In step (2), a genetic optimization algorithm is used to optimize the cycle parameters with the goal of maximizing the power density of the micro-reactor Brayton cycle system to obtain the best design scheme; the cycle parameters that need to be optimized include the compressor inlet temperature Cooling medium outlet temperature Regenerator efficiency ε re , compressor pressure ratio π C ; The specific expression is: Optimization goal: Constraints:

5. The comprehensive design method according to claim 1, characterized in that: In step (3), the cycle design parameters optimized in step (2) are used as input values of the micro-reactor Brayton cycle-component joint design program to calculate the cycle optimization design results and component design results under the best design scheme; the cycle optimization design results include cycle performance parameters and cycle design parameters; The output component design results include component performance parameters and component size parameters.

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