Calcium-based thermochemical heat storage reactor fluid flow channel design method and system based on topological optimization and storage medium

Abstract

The invention discloses a method and a system for designing a fluid flow channel of a calcium-based thermochemical heat storage fixed bed reactor based on topological optimization and a storage medium. The method comprises the following steps: S1, constructing a geometric model of a design domain of the reactor; s2, constructing an objective function and establishing a two-dimensional topological optimization mathematical model based on a control equation of conjugate heat transfer and fluid flow; s3, solving the mathematical model to obtain an optimal fluid flow channel two-dimensional topological structure; s4, performing geometric reconstruction on the two-dimensional topological structure obtained in the step S3, converting the two-dimensional topological structure into a Bezier curve, and integrating the Bezier curve into a geometric model corresponding to the original design domain; s5, establishing a finite element model of the reactor; s6, temperature field and pressure field distribution is calculated based on CFD simulation, whether the heat storage performance target is met or not is judged, and if not, corresponding control parameters are adjusted to return to the step S3 until the heat storage performance target is met; the device can optimize the heat transfer and mass transfer performance of the reactor at the same time, and the optimization design efficiency is high.

Description

Technical Field

[0001] The present invention relates to a thermochemical heat storage reactor, and in particular to a fluid flow channel design method, system and storage medium of a calcium-based thermochemical heat storage reactor based on topology optimization. Background Art

[0002] Thermochemical heat storage stores and releases heat energy through reversible chemical reactions. It offers the advantages of high heat storage density, low heat loss, and long-term heat storage, making it an important technical means of achieving efficient energy utilization. Fixed-bed reactors are widely used in thermochemical heat storage systems due to their simple structure and ease of operation. The chemical equation for the thermochemical heat storage reaction of calcium carbonate decomposition is as follows:

[0003]

[0004] However, traditional fixed-bed reactors often encounter problems such as uneven fluid distribution, low heat transfer efficiency, and insufficient reaction during operation, which seriously restrict the progress of the thermochemical heat storage process in the reactor. Therefore, how to improve the heat and mass transfer process of the fixed-bed reactor has become the key to improving its performance. At present, traditional research mainly focuses on the optimization of the heat transfer or mass transfer performance of fixed-bed reactors. However, in actual operation, the heat transfer and mass transfer performance in the fixed bed are often coupled with each other. Poor heat transfer performance will further lead to deterioration of mass transfer performance, and vice versa. Therefore, how to achieve the coordinated optimization of the heat and mass transfer performance of fixed-bed reactors is an urgent problem that needs to be solved. Summary of the Invention

[0005] Purpose of the invention: The purpose of the present invention is to provide a fluid flow channel design method, system and storage medium for a calcium-based thermochemical heat storage reactor based on topology optimization, which can simultaneously optimize the heat transfer and mass transfer performance of the reactor and have high optimization design efficiency.

[0006] Technical solution: The method for designing fluid flow channels in a calcium-based thermochemical heat storage fixed-bed reactor based on topology optimization of the present invention comprises the following steps:

[0007] S1. Construct a geometric model of the reactor design domain based on the heat source distribution, heat source representation, fluid physical properties, reactor size parameters, and channel inlet parameters;

[0008] S2. Based on the conjugate heat transfer theory, with the objective function of maximizing heat transfer performance and minimizing fluid dissipation work, a two-dimensional topology optimization mathematical model is established based on the governing equations of conjugate heat transfer and fluid flow;

[0009] S3, solving the mathematical model using an optimization solver to obtain an optimal two-dimensional topological structure of the fluid flow channel;

[0010] S4, geometrically reconstructing the two-dimensional topological structure obtained in step S3, converting it into a Bezier curve and integrating it into the geometric model corresponding to the original design domain;

[0011] S5. Setting the inlet flow rate, temperature, and outlet pressure boundary conditions to establish a finite element model of the reactor;

[0012] S6. Calculate the temperature field and pressure field distribution based on CFD simulation to determine whether the heat storage performance target is met. If not, adjust the corresponding control parameters and return to step S3 until the heat storage performance target is met.

[0013] This method takes maximizing heat transfer performance and minimizing fluid dissipation work as objective functions, establishes a two-dimensional topology optimization mathematical model based on the control equations of conjugate heat transfer and fluid flow, and solves the mathematical model to obtain a two-dimensional topological structure. Based on this, geometric reconstruction is performed and integrated into the geometric model corresponding to the original design domain. Then, a finite element model is constructed to perform simulation calculations to determine whether the design is qualified. If it is unqualified, the topology optimization solution is returned and re-solved until it meets the requirements. This design takes into account both the heat transfer and mass transfer performance of the reactor. Moreover, compared with traditional empirical design, design through topology optimization has high stability and high design efficiency. The topological structure obtained by topology optimization solution based on comprehensive consideration of multiple factors can show more superior effects in fluid flow, heat transfer, etc., and can effectively improve the performance of the reactor.

[0014] The fluid flow channel design system of the calcium-based thermochemical heat storage fixed-bed reactor based on topology optimization of the present invention comprises:

[0015] Geometric model construction module: used to construct the geometric model of the reactor design domain based on the heat source distribution, heat source representation form, fluid physical properties, reactor size parameters and channel inlet parameters;

[0016] Mathematical model building module: Based on the conjugate heat transfer theory, with maximizing heat transfer performance and minimizing fluid dissipation work as the objective function, it establishes a two-dimensional topology optimization mathematical model based on the governing equations of conjugate heat transfer and fluid flow;

[0017] Solving module: used for solving the mathematical model using an optimization solver to obtain an optimal two-dimensional topological structure of the fluid flow channel;

[0018] Geometric reconstruction module: used to geometrically reconstruct the two-dimensional topological structure obtained by the solution module, convert it into a Bezier curve, and integrate it into the geometric model corresponding to the original design domain;

[0019] Finite element model building module: used to set the inlet flow rate, temperature and outlet pressure boundary conditions and build the finite element model of the reactor;

[0020] Verification module: used to calculate the temperature field and pressure field distribution based on CFD simulation to determine whether the heat storage performance target is met. If not, the corresponding control parameters are adjusted and returned to the solution module until the heat storage performance target is met.

[0021] The computer-readable storage medium storing one or more programs according to the present invention includes one or more programs including instructions, which, when executed by a computing device, enable the computing device to perform any of the above methods.

[0022] Beneficial effects: Compared with the prior art, the present invention has the following significant effects: by taking maximization of heat transfer performance and minimization of fluid dissipation work as the objective function, the heat transfer and mass transfer performance of the reactor are taken into account at the same time. By combining the objective function, conjugate heat transfer and fluid flow control equations, a two-dimensional topology optimization mathematical model is established and optimized solution and simulation verification are performed until the design requirements are met. Compared with traditional empirical design, such design has high stability and high design efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] Figure 1 is a flow chart of the present method;

[0024] Figure 2 It is a schematic diagram of the topology optimization geometric model;

[0025] Figure 3 is a schematic diagram of the fluid channel structure obtained by topology optimization;

[0026] Figure 4 This is a schematic diagram of the temperature distribution in a thermochemical heat storage fixed-bed reactor;

[0027] Figure 5 This is a schematic diagram of the conversion rate distribution of solid reactants in a thermochemical heat storage fixed bed reactor. DETAILED DESCRIPTION

[0028] As shown in the figure, the method for designing fluid flow channels in a calcium-based thermochemical heat storage fixed-bed reactor based on topology optimization according to the present invention includes the following steps:

[0029] S1. Construct a geometric model of the reactor design domain based on the heat source distribution, heat source representation, reactor channel inlet parameters, and fluid physical properties.

[0030] Determine the boundary conditions and dimensional parameters of the fixed bed reactor, including:

[0031] The heat source of a chemical reaction and the magnitude of the exothermic reaction rate, where the heat source is represented by temperature or heat flux density;

[0032] The temperature or heat flux density information at the boundary of the fixed bed reactor is known;

[0033] The geometric model size parameters of the fixed bed reactor include length L and height H, and the size parameters of the gas inlet channel and outlet channel include length l and height h.

[0034] Determine the boundary conditions for the gas inlet and outlet channels

[0035] According to the heat release characteristics of the thermochemical heat storage reactor, the independent parameters of the inlet channel are determined to include the inlet pressure P0 and the inlet temperature T0, and the physical properties of the fluid include the thermal conductivity λ f Specific heat capacity at constant pressure C p and density ρ.

[0036] Establishing a 2D topology optimization geometry model

[0037] The actual model of the thermochemical heat storage fixed bed reactor is simplified, the heat source representation form and boundary conditions are equivalent, the heat source and boundary conditions are set, and the following is established: Figure 2 The simplified geometric model is shown.

[0038] S2. Based on the conjugate heat transfer theory, with the objective function of maximizing heat transfer performance and minimizing fluid dissipation work, a two-dimensional topology optimization mathematical model is established based on the governing equations of conjugate heat transfer and fluid flow;

[0039] The optimization idea of topology optimization technology is to simplify complex structural design problems into optimization problems of material distribution in the design domain. For the topology optimization process where the optimization object is fluid, the main goal of the optimization is to accurately divide the solid domain and fluid domain in the design domain during the iterative calculation process. In order to ensure that the results of topology optimization are accurate enough, the present invention adopts a convex function interpolation model. The core idea of topology optimization is to convert the topological configuration design problem into a material distribution problem. For topology optimization involving fluids, the central task is to clarify the distribution of solid domains and fluid domains. Convex function interpolation associates the resistance coefficient with the design variables of the unit domain, thereby controlling the distribution of solid domains and fluid domains. In the convex function interpolation model of flow channel topology optimization, the distinction between solid and fluid is to achieve a continuous transition of material properties and to ensure that the optimization process can handle the physical characteristics of fluid flow.

[0040] The resistance coefficient α(x), thermal conductivity λ(x), density ρ(x) and specific heat capacity C in the convex function interpolation model p The interpolation functions of (x) are expressed as follows:

[0041]

[0042] Among them, γ(x) is the design variable function of topology optimization, α max and α min are the maximum resistance coefficient of the solid region and the minimum resistance coefficient of the fluid region, respectively, αis the penalty factor of the resistance coefficient; s and λ g are the thermal conductivities of solid and gas, q λ is the penalty factor of thermal conductivity; ρ s and ρ g are the densities of solid and gas, q ρ is the penalty factor of density; C p,s and C p,g are the specific heat capacities of solid and gas, respectively, is the penalty factor for specific heat capacity.

[0043] According to the thermal control requirements of the heat release process of the thermochemical heat storage fixed bed reactor, a topology optimization objective function is established. The research goal of the present invention is to design a fluid flow channel with better synergistic optimization effect of heat and mass transfer. In actual engineering applications, the influence of fluid viscosity dissipation work is usually taken into consideration during the optimization process. Under steady-state conditions, the heating capacity of the system is equal to the heat exchange of the system. In order to ensure the optimal heat transfer and fluid flow performance of the fluid channel, the present invention constructs a corresponding binary objective function. The purpose of this objective function is to achieve the optimization of heat transfer performance and the minimization of flow dissipation work, which is specifically expressed as:

[0044]

[0045] Among them, J is the objective function, w represents the weight coefficient of the objective function, Φ is the actual heat transfer potential dissipation, Φ max and Φ min are the maximum and minimum heat transfer potential dissipation respectively; Ψ represents the viscous dissipation work of the fluid during the fluid flow process, Ψ max and Ψ min are the set fluid viscous dissipation work respectively;

[0046] The calculation of Φ and Ψ is as follows:

[0047]

[0048] Where γ is the design variable for topology optimization, T is the actual temperature, T0 is the initial temperature, h is the full name of Heat generation coefficient, also known as heat generation coefficient or heat transfer coefficient; μ g is the fluid dynamic viscosity, and Ω is the design domain.

[0049] Based on the topology optimization method, combined with the steady-state conjugate heat transfer and fluid laminar flow control equations, a topology optimization mathematical model is established:

[0050] findγ

[0051]

[0052] in, is the Hamiltonian operator, ρ is the density, μ is the fluid dynamic viscosity, C p is the specific heat capacity at constant pressure, f V is the fluid volume fraction, T in is the inlet temperature.

[0053] S3, using an optimization solver to solve the mathematical model to obtain an optimal two-dimensional topological structure of the fluid flow channel; specifically comprising the following sub-steps:

[0054] S3.1. Perform finite element meshing based on the two-dimensional topology optimization mathematical model established in step S2. Specifically, free meshing, mapped meshing, or swept meshing may be used.

[0055] S3.2. Adjoint method is used to solve sensitivity. Sensitivity refers to the gradient of the design variable with respect to the objective function. It quantifies the direction and magnitude of the contribution of each design variable unit to the overall performance optimization. It is a necessary process for solving two-dimensional topological structures. Topological optimization relies on gradient information (sensitivity) to guide the iterative update of design variables. After solving the sensitivity, the optimization algorithm (such as SNOPT) can determine how to adjust the flow channel structure to approach the optimal solution.

[0056] Then the gradient-based continuous quadratic programming algorithm SNOPT (Sparse Nonlinear Optimizer) is used to solve the two-dimensional topology structure, and the termination condition of the solution is set to the number of iteration steps reaching the upper limit or |J k+1 -J k |≤10 -6 , where J k is the objective function value obtained at the kth iteration. The upper limit of the number of iteration steps can be set to 300 steps or adjusted according to actual conditions.

[0057] Density filtering and projection processing are used in the SNOPT solution process to eliminate the checkerboard phenomenon and grayscale units; density filtering uses the Helmholtz partial differential equation, specifically

[0058]

[0059] Where r is the filter radius, is the Hamiltonian operator, γ p is the smoothing filter variable obtained by density filtering, γ is the design variable of topology optimization, that is, the filtering variable obtained by the SNOPT algorithm; by appropriately setting the value of r, a low-pass filter effect can be produced on the original scalar function, thereby generating a smoothing filter variable.

[0060] The projection processing uses the hyperbolic tangent projection function, which can reduce the grayscale unit and obtain a clear fluid channel topology optimization structure. The specific projection function is

[0061]

[0062] Among them, γ f is the design variable after projection, that is, all the design variables (or filtering variables) of the two-dimensional topological structure finally obtained in step S3.2 are γ f , γ δ is the projection point, and β is the slope.

[0063] All the filter variables obtained by the SNOPT algorithm are subjected to density filtering and projection processing in sequence, which can eliminate the checkerboard phenomenon and grayscale units in the two-dimensional topological structure. However, the two-dimensional topological structure obtained in this way still has blurred boundaries and needs to be further optimized through step S4.

[0064] S4, geometrically reconstructing the two-dimensional topological structure obtained in step S3, converting it into a Bezier curve and integrating it into the geometric model corresponding to the original design domain; specifically, the steps include:

[0065] S4.1. Re-mesh the two-dimensional topological structure obtained in step S3. The meshing method is the same as that in step S3.1, that is, free meshing, mapped meshing or swept meshing.

[0066] S4.2. Solve the two-dimensional topological structure using the same method as step S3.2, that is, use the adjoint method to solve the sensitivity, and the gradient-based continuous quadratic programming algorithm SNOPT to solve the two-dimensional topological structure. Set the termination condition of the solution to the number of iteration steps reaching the upper limit or |J k+1 -J k |≤10 -6 , where J k is the objective function value obtained at the kth iteration; the detailed process is described above.

[0067] After processing in steps S4.1 and S4.2, the two-dimensional topological structure obtained again has basically overcome the problem of fuzzy boundaries, but there may still be a small number of design variable values γ f It is still between (0,1) and it is unclear whether it is a solid or fluid unit, so further optimization in step S4.3 is required.

[0068] S4.3. Filter the two-dimensional topological structure obtained in step S4.2. Specifically, the following formula is used:

[0069]

[0070] This step is actually to set the design variable γ between (0,1) fAn approximation is made to clarify whether the unit is solid or fluid. After this treatment, all design variables of the two-dimensional topology structure are clear (that is, solid or fluid is clear).

[0071] S4.3. Input the filtered result into CAD software for geometric reconstruction, extract the curve information of the channel structure, and convert it into the form of Bezier curve. Then, integrate the converted Bezier curve into the geometry of the original design domain to form a union.

[0072] S5. Setting the boundary conditions of inlet flow rate, temperature and outlet pressure to establish a finite element model of the reactor; specifically comprising the following sub-steps:

[0073] S5.1. Import the geometric model obtained in step S4 into CAE, and set the heat source characteristics including heat source representation form and heat release power.

[0074] S5.2. Set the fluid flow boundary conditions of the reactor, including the fluid inlet velocity v0, inlet temperature T0, outlet pressure P0 and other boundary conditions. In the present invention, the other boundary conditions are that the outer wall temperature of the reactor is set to a constant temperature.

[0075] S5.3. According to the size parameters of the geometric model, set the mesh size, mesh the geometric model, and obtain a finite element model.

[0076] S6. Calculate the temperature and pressure field distributions based on CFD simulation to determine whether the heat storage performance target is met. If not, adjust the corresponding control parameters and return to step S3 until the heat storage performance target is met. The corresponding control parameters include optimization algorithm parameters and physical model parameters. The optimization algorithm parameters include the maximum number of iteration steps, filter radius, and projection function parameters, and the physical model parameters include velocity, temperature, and pressure.

[0077] Based on the finite element model constructed in step S5, a two-dimensional unsteady-state numerical simulation is performed to calculate the temperature distribution of the reactor model; the following data are calculated based on the temperature field distribution and the pressure field distribution to determine whether the expected design goals are met:

[0078]

[0079] ΔT=T max -T min

[0080] ΔP=P in -P out

[0081] in, is the average temperature, T i is the temperature of the i-th node, N is the number of nodes; ΔT is the maximum temperature difference, Tmax and T min are the highest and lowest temperatures of the reactor reaction process respectively; ΔP is the inlet and outlet pressure drop, P in is the inlet fluid pressure, P out is the outlet fluid pressure.

[0082] The design goal can be to set target thresholds for the three formulas calculated above. For example, the average temperature must reach its threshold, and the maximum temperature difference and inlet and outlet pressure drop must not exceed their thresholds to meet the design requirements.

[0083] The fluid flow channel design system of the calcium-based thermochemical heat storage fixed-bed reactor based on topology optimization of the present invention comprises:

[0084] Geometric model construction module: used to construct the geometric model of the reactor design domain based on the heat source distribution, heat source representation form, reactor channel inlet parameters and fluid physical properties;

[0085] Mathematical model building module: Based on the conjugate heat transfer theory, with maximizing heat transfer performance and minimizing fluid dissipation work as the objective function, it establishes a two-dimensional topology optimization mathematical model based on the governing equations of conjugate heat transfer and fluid flow;

[0086] Solving module: used for solving the mathematical model using an optimization solver to obtain an optimal two-dimensional topological structure of the fluid flow channel;

[0087] Geometric reconstruction module: used to geometrically reconstruct the two-dimensional topological structure obtained by the solution module, convert it into a Bezier curve, and integrate it into the geometric model corresponding to the original design domain;

[0088] Finite element model building module: used to set the inlet flow rate, temperature and outlet pressure boundary conditions and build the finite element model of the reactor;

[0089] Verification module: used to calculate the temperature field and pressure field distribution based on CFD simulation to determine whether the heat storage performance target is met. If not, the corresponding control parameters are adjusted and returned to the solution module until the heat storage performance target is met.

[0090] The computer-readable storage medium storing one or more programs according to the present invention includes one or more programs including instructions, which, when executed by a computing device, enable the computing device to perform any of the above methods.

[0091] The optimization effect of the present invention can be further illustrated by the following simulation case:

[0092] 1. Model parameter setting

[0093] The thermochemical heat storage fixed-bed reactor measures 40 mm in height and 50 mm in length, with a 2 mm thick stainless steel outer wall. The gas inlet and outlet channels are both 3 mm in height and 10 mm in length. Nitrogen is introduced as a heat transfer gas through the inlet on the left side of the reactor to provide heat for the heat storage reaction. The inlet flow rate is 0.2 m / s, and the inlet gas temperature is 1148 K. The outlet boundary conditions are a constant pressure of 20,265 Pa, and the outer wall temperature is a constant 1148 K.

[0094] 2. Comparison of simulation results

[0095] The two-dimensional topological structure of the reactor obtained by the method of the present invention is simulated in CFD software with the following results:

[0096] Table 1 Performance comparison between two-dimensional topology optimization reactor design and traditional reactor design

[0097]

[0098] It can be seen from the simulation results in Table 1 that the flow channel structure designed by the method of the present invention can improve the performance of the reactor.

[0099] The present invention uses gas as the heat transfer medium and, based on this, describes a fluid flow channel design method based on two-dimensional topology optimization. However, the method is not limited to the use of gas and liquids can also be used. The optimized channel topology structure can be used for high thermal conductivity material filling or gas channels.

Claims

1. A method for designing fluid flow channels in a calcium-based thermochemical heat storage fixed-bed reactor based on topology optimization, characterized in that: The following steps are involved: S1. Construct a geometric model of the reactor design domain based on the heat source distribution, heat source representation, fluid physical properties, reactor size parameters, and channel inlet parameters; S2. Based on the conjugate heat transfer theory, with the objective function of maximizing heat transfer performance and minimizing fluid dissipation work, a two-dimensional topology optimization mathematical model is established based on the governing equations of conjugate heat transfer and fluid flow; S3, solving the mathematical model using an optimization solver to obtain an optimal two-dimensional topological structure of the fluid flow channel; S4, geometrically reconstructing the two-dimensional topological structure obtained in step S3, converting it into a Bezier curve and integrating it into the geometric model corresponding to the original design domain; S5. Setting the inlet flow rate, temperature, and outlet pressure boundary conditions to establish a finite element model of the reactor; S6. Calculate the temperature field and pressure field distribution based on CFD simulation to determine whether the heat storage performance target is met. If not, adjust the corresponding control parameters and return to step S3 until the heat storage performance target is met.

2. The design method according to claim 1, wherein: The objective function in step S2 is: Among them, J is the objective function, w represents the weight coefficient of the objective function, Φ is the actual heat transfer potential dissipation, Φ max and Φ min are the maximum and minimum heat transfer potential dissipation respectively; Ψ represents the viscous dissipation work of the fluid during the fluid flow process, Ψ max and Ψ min are the set fluid viscous dissipation work respectively; Φ and Ψ are calculated according to the following formulas: Among them, γ is the design variable of topology optimization, T is the actual temperature, T0 is the initial temperature, h is the heat source coefficient, μ g is the fluid dynamic viscosity, Ω is the design domain, α is the resistance coefficient, u i and u j are the components of the fluid velocity in the i and j directions respectively; x i and x j are the components of the position variable in the fluid flow direction in the i and j directions respectively.

3. The design method according to claim 1, wherein: The mathematical model of the two-dimensional topology optimization in step S2 is findγ λ▽ 2 T+h(T in -T)=0 Among them, γ is the design variable of topology optimization, ▽ is the Hamiltonian operator, ρ is the density, μ g is the fluid dynamic viscosity, C p is the specific heat capacity at constant pressure, f V is the fluid volume fraction, T in is the inlet temperature, is the fluid velocity, is the body force, λ is the thermal conductivity, and p is the pressure.

4. The design method according to claim 1, characterized in that: The step S3 includes the following sub-steps: S3.

1. Perform finite element meshing based on the two-dimensional topology optimization mathematical model established in step S2; S3.

2. Adjoint method is used to solve sensitivity, and gradient-based continuous quadratic programming algorithm SNOPT is used to solve the two-dimensional topological structure. The termination condition of the solution is set as the number of iteration steps reaches the upper limit or |J k+1 -J k |≤10 -6 , where J k For the kth time The objective function value obtained by iteration.

5. The design method according to claim 4, characterized in that: In step S3.1, the finite element meshing is performed by free meshing, mapped meshing or swept meshing; in step S3.2, density filtering and projection processing are performed to eliminate checkerboard phenomenon and grayscale units.

6. The design method according to claim 5, characterized in that: The density filtering adopts the Helmholtz partial differential equation, specifically -r 2 ▽ 2 γ p +γ p =γ Among them, r is the filter radius, ▽ is the Hamiltonian operator, γ p is the smoothing filter variable obtained after density filtering, and γ is the design variable for topology optimization; The projection process uses the hyperbolic tangent projection function, specifically: Among them, γ f is the design variable obtained by projection processing, γ δ is the projection point, and β is the slope.

7. The design method according to claim 6, characterized in that: The step S4 comprises the following sub-steps: S4.

1. Re-mesh the two-dimensional topological structure obtained in step S3; S4.

2. Solve the two-dimensional topological structure using the same method as step S3.2; S4.

3. Filter the two-dimensional topological structure obtained in step S4.

2. Specifically, the following formula is used: S4.

3. Input the filtered results into CAD software for geometric reconstruction, extract the curve information of the fluid channel and convert it into Bezier curves to integrate into the geometric model corresponding to the original design domain.

8. The design method according to claim 1, characterized in that: The step S5 comprises the following sub-steps: S5.

1. Import the geometric model obtained in step S4 into CAE and set the heat source characteristics; S5.

2. Set the reactor inlet flow rate v0, inlet temperature T0, outlet pressure P0 and other boundary conditions; S5.

3. According to the size parameters of the geometric model, set the mesh size, mesh the geometric model, and obtain a finite element model.

9. A fluid flow channel design system for a calcium-based thermochemical heat storage fixed-bed reactor based on topology optimization, characterized in that: The system comprises: Geometric model construction module: used to construct the geometric model of the reactor design domain based on the heat source distribution, heat source representation form, fluid physical properties, reactor size parameters and channel inlet parameters; Mathematical model building module: Based on the conjugate heat transfer theory, with maximizing heat transfer performance and minimizing fluid dissipation work as the objective function, it establishes a two-dimensional topology optimization mathematical model based on the governing equations of conjugate heat transfer and fluid flow; Solving module: used for solving the mathematical model using an optimization solver to obtain an optimal two-dimensional topological structure of the fluid flow channel; Geometric reconstruction module: used to geometrically reconstruct the two-dimensional topological structure obtained by the solution module, convert it into a Bezier curve, and integrate it into the geometric model corresponding to the original design domain; Finite element model building module: used to set the inlet flow rate, temperature and outlet pressure boundary conditions and build the finite element model of the reactor; Verification module: used to calculate the temperature field and pressure field distribution based on CFD simulation to determine whether the heat storage performance target is met. If not, the corresponding control parameters are adjusted and returned to the solution module until the heat storage performance target is met.

10. A computer-readable storage medium storing one or more programs, characterized in that: The one or more programs include instructions which, when executed by a computing device, cause the computing device to perform any one of the methods according to claims 1 to 8.

Images