Multi-physical field coupling heat exchange tube thermal performance simulation design system

Abstract

This invention discloses a multiphysics-coupled simulation design system for the thermal performance of heat exchanger tubes, belonging to the field of thermal energy engineering simulation technology. It includes modules for model building, condition setting, fluid solving, solid solving, and coupled calculation. The model building module establishes a three-dimensional geometric model including the heat exchanger tube wall thickness, the cross-sectional shape of the internal flow channel, and the structural parameters of the external fins. The condition setting module sets the initial simulation conditions and the material properties of the tube wall and the fluid. The fluid solving module independently solves the velocity and pressure field distributions of the turbulent flow inside the tube, while the solid solving module independently solves the solid reference temperature field distribution of the tube wall under fluidless conditions. The coupled calculation module couples the three fields, completing data exchange and iterating to convergence through the conservation of energy at the fluid-solid boundary and the heat conduction equation, outputting a comprehensive temperature field and heat flux density distribution. This system can block interference from fluid-solid calculation parameters, improving the numerical accuracy and physical state reproduction of heat exchanger tube heat transfer simulation.

Description

Technical Field

[0001] This invention belongs to the field of thermal energy engineering simulation technology, specifically a multi-physics field coupled heat exchanger tube thermal performance simulation design system. Background Technology

[0002] Most existing simulations of the thermal performance of heat exchanger tubes adopt a direct fluid-structure interaction simulation mode. During the modeling process, geometric parameters such as heat exchanger tube wall thickness, inlet flow channel cross-sectional shape, and external fin structure are directly integrated. Initial conditions such as inlet temperature and inlet velocity of the fluid inside the tube, ambient temperature outside the tube, and pressure boundary are set simultaneously, as well as material properties such as thermal conductivity, specific heat capacity, density, and viscosity of the tube wall and the fluid. The fluid flow inside the tube and the heat transfer between the solid and the tube wall are then solved and calculated together.

[0003] This type of direct-coupled simulation method does not separate the solution for fluid flow and solid heat transfer. Fluid turbulence calculations and pipe wall temperature field calculations are performed simultaneously, leading to potential interference between flow and temperature parameters. Furthermore, the solid temperature field calculation cannot be separated from the fluid conditions to form an independent benchmark. The fluid-structure interaction interface only uses conventional heat transfer correlation equations for data exchange, failing to rely on boundary energy conservation and heat conduction equations for targeted heat transfer calculations. This results in numerical deviations during the coupling iteration process, making it difficult to accurately reproduce the true heat transfer state under multi-physics coupling in the heat exchanger tube.

[0004] Existing simulations cannot independently solve for the velocity and pressure fields of the fluid inside the tube, nor can they obtain the steady-state reference temperature field of the heat exchanger tube wall under fluidless conditions. The data exchange method of fluid-structure interaction lacks the constraints of boundary energy conservation and heat conduction equations, which cannot meet the needs of accurate simulation of the thermal performance of heat exchanger tubes. Summary of the Invention

[0005] This invention aims to solve at least one of the technical problems existing in the prior art;

[0006] To this end, the present invention proposes a multi-physics coupled heat exchanger tube thermal performance simulation design system, including:

[0007] The model building module establishes a three-dimensional geometric model of the heat exchange tube, which includes the wall thickness parameters, the cross-sectional shape parameters of the flow channel inside the tube, and the structural parameters of the fins outside the tube.

[0008] The condition setting module sets the initial conditions and material properties for multiphysics coupling simulation. The initial conditions include the inlet temperature of the fluid inside the pipe, the inlet velocity, the ambient temperature outside the pipe, and the pressure boundary conditions. The material properties include the thermal conductivity, specific heat capacity, and density of the pipe wall material, and the viscosity, specific heat capacity, and thermal conductivity of the fluid.

[0009] The fluid solving module solves for the turbulent flow state of the fluid in the pipe based on the inlet velocity, the pressure boundary conditions, and the viscosity of the fluid, generating the fluid velocity field distribution and the fluid pressure field distribution.

[0010] The solid solution module solves for the steady-state temperature distribution of the heat exchange tube wall under fluidless conditions based on the ambient temperature outside the tube, the thermal conductivity of the tube wall material, the specific heat capacity, and the density, generating a solid reference temperature field distribution.

[0011] The coupling calculation module performs coupled calculations on the fluid velocity field distribution, the fluid pressure field distribution, and the solid reference temperature field distribution. It exchanges data through the energy conservation and heat conduction equations at the fluid-solid boundary, updates the fluid temperature field and the heat exchange tube wall temperature field until the convergence criterion is reached, and generates the coupled comprehensive temperature field distribution and heat flux density distribution.

[0012] Furthermore, based on the inlet flow velocity, the pressure boundary conditions, and the viscosity of the fluid, the turbulent flow state of the fluid inside the pipe is solved to generate the fluid velocity field distribution and the fluid pressure field distribution, including:

[0013] Based on the three-dimensional geometric model of the heat exchange tube, the flow channel region inside the tube is spatially discretized to generate a fluid computational grid.

[0014] Apply the inlet velocity and the pressure boundary conditions to the fluid computation grid, and specify the viscosity and density parameters of the fluid;

[0015] Using the eddy viscosity turbulence model, the momentum conservation equations, which include convection, diffusion, and pressure gradient terms, are solved to calculate the velocity vector and pressure scalar within each fluid computational grid cell.

[0016] The velocity vector and pressure scalar of the fluid computation grid cell are statistically analyzed across the entire field to form a continuous fluid velocity field distribution and a fluid pressure field distribution.

[0017] The fluid velocity field distribution is post-processed to extract the velocity profile of the flow channel section, the location of the flow separation zone, and the near-wall velocity gradient data.

[0018] Furthermore, based on the ambient temperature outside the tube, the thermal conductivity of the tube wall material, the specific heat capacity, and the density, the steady-state temperature distribution of the heat exchange tube wall under fluidless conditions is solved to generate a solid reference temperature field distribution, including:

[0019] Based on the three-dimensional geometric model of the heat exchange tube, the heat exchange tube wall and the external fin structure are spatially discretized to generate a solid computational mesh.

[0020] The ambient temperature outside the tube is applied to the outer boundary of the solid computing grid, and preset conditions for adiabatic or convective heat transfer are applied to the inner boundary of the solid computing grid.

[0021] Using the thermal conductivity, specific heat capacity, and density of the pipe wall material, a transient heat conduction control equation for the solid region is constructed, and the transient heat conduction control equation is simplified into a steady-state equation for solution.

[0022] Solve the steady-state equation to calculate the steady-state temperature of each solid computational grid cell under pure thermal conduction and preset boundary conditions;

[0023] The steady-state temperature values ​​of all solid computational grid cells are integrated to generate the solid reference temperature field distribution, and the temperature gradient distribution and isotherm data inside the wall are extracted from it.

[0024] Furthermore, the fluid velocity field distribution, the fluid pressure field distribution, and the solid reference temperature field distribution are coupled and calculated, and data exchange is performed through the energy conservation and heat conduction equations at the fluid-solid boundary, including:

[0025] Define a fluid-structure interaction interface, which is the interface where the fluid computation mesh and the solid computation mesh overlap;

[0026] At the fluid-structure interaction interface, the solid-side temperature at the interface is obtained from the solid reference temperature field distribution and used as the boundary condition of the fluid energy equation, which is then passed to the fluid solver module.

[0027] The fluid solving module recalculates based on the updated boundary conditions, generates an updated in-pipe fluid temperature field, and extracts the fluid-side heat flux density at the fluid-structure interaction interface from the updated in-pipe fluid temperature field.

[0028] The fluid-side heat flux density of the fluid-structure interaction interface is used as the heat flux boundary condition of the fluid-structure interaction interface in the solid solution module and is passed to the solid solution module.

[0029] The solid solution module recalculates based on the heat flow boundary conditions, generates an updated temperature field of the heat exchanger tube wall, and extracts the solid-side temperature of the fluid-structure interaction interface from it, completing one iteration of coupled data exchange.

[0030] Furthermore, the updating of the fluid temperature field inside the tube and the heat exchange tube wall temperature field until the convergence criterion is met includes:

[0031] After each iteration of the coupling data exchange, the updated solid-side temperature at the fluid-structure interaction interface is compared with the corresponding temperature value of the previous iteration, and the maximum temperature residual across the entire field is calculated.

[0032] Compare the updated heat flux density on the fluid side of the fluid-structure interaction interface with the corresponding heat flux density value from the previous iteration, and calculate the maximum heat flux residual across the entire field.

[0033] The maximum temperature residual across the entire field is compared with a preset temperature convergence threshold, and the maximum heat flux residual across the entire field is compared with a preset heat flux convergence threshold.

[0034] If the maximum temperature residual across the entire field is less than the preset temperature convergence threshold, and the maximum heat flux residual across the entire field is less than the preset heat flux convergence threshold, then the fluid-structure-thermal coupling iterative calculation is determined to have reached the convergence criterion, and the iteration is terminated.

[0035] If the convergence condition is not met simultaneously, the latest updated temperature field of the heat exchanger tube wall and the temperature field of the fluid inside the tube will be used as the input for the next iteration, and the coupled data exchange iteration process will be repeated.

[0036] Furthermore, the generation of the coupled integrated temperature field distribution and heat flux density distribution includes:

[0037] When the fluid-structure-thermal coupling iterative calculation reaches the convergence criterion, the converged heat exchanger tube wall temperature field obtained from the last iteration is recorded.

[0038] Record the converged temperature field of the fluid inside the tube obtained from the last iteration;

[0039] The converged temperature field of the heat exchanger tube wall and the converged temperature field of the fluid inside the tube are spatially fused to generate the comprehensive temperature field distribution covering the entire heat exchanger tube wall and the fluid field inside the tube.

[0040] Based on the temperature gradient of the comprehensive temperature field distribution, the thermal conductivity of the tube wall material is used to calculate the thermal flux density field inside the heat exchange tube wall.

[0041] Based on the convergent temperature field and velocity field distribution of the fluid inside the pipe, the convective heat flux density field between the fluid inside the pipe and the wall is calculated using the fluid convection heat transfer formula.

[0042] Furthermore, the model building module establishes a three-dimensional geometric model of the heat exchanger tube, including:

[0043] Based on the user-inputted heat exchanger tube design parameters, the design parameters include basic tube diameter, tube length, wall thickness, flow channel cross-sectional shape, fin type, fin height, fin spacing, and fin thickness.

[0044] The parametric geometry modeling engine is invoked, and based on the design parameters, a preliminary three-dimensional solid model is generated using predefined mathematical expressions and Boolean operations. This model includes a smooth inner flow channel surface, a pipe wall of equal wall thickness, and a periodic outer fin array.

[0045] For all adjacent curved surfaces in the preliminary three-dimensional solid model, round or chamfer the corners automatically to eliminate geometric singularities and generate transition features that are more in line with the actual manufacturing process, forming a continuous and smooth geometric model.

[0046] The continuous and smooth geometric model is subjected to virtual assembly interference check to ensure that the inner flow channel space is completely surrounded by the pipe wall entity and that the outer fin array is seamlessly connected to the pipe wall entity without any geometric errors of penetration or overlap.

[0047] The geometric model that has passed the interference check is converted into a boundary representation model and attribute labels are attached. The attribute labels are used to identify the flow channel region, solid tube wall region and fin region, thus completing the construction of the three-dimensional geometric structure model.

[0048] Furthermore, the eddy viscosity turbulence model is used to solve the momentum conservation equation, which includes convection, diffusion, and pressure gradient terms. Specifically, this includes:

[0049] The governing equations for the eddy viscosity turbulence model are constructed. The governing equations include the Reynolds-averaged continuity equation, the Reynolds-averaged momentum equation, the turbulent kinetic energy transport equation, and the turbulent dissipation rate transport equation or the transport equation for a specific turbulent flow rate.

[0050] An eddy viscosity coefficient is introduced into the Reynolds-averaged momentum equation. The eddy viscosity coefficient is expressed as a function of turbulent kinetic energy and turbulent dissipation rate or a specific turbulent flow rate to simulate the Reynolds stress term caused by velocity fluctuations. The effect of turbulent fluctuations is then correlated to the solution of the average flow through the eddy viscosity coefficient.

[0051] On the fluid computation grid, the finite volume method is used to spatially discretize the governing equations, and the implicit scheme is used to discretize them in time, thus constructing a set of nonlinear algebraic equations concerning the velocity, pressure, turbulent kinetic energy, and turbulent dissipation rate or specific turbulent flow rate of each grid cell.

[0052] The nonlinear algebraic equations are solved using a semi-implicit method or pressure correction algorithm known in the art for pressure coupling equations. In each iteration step, the discretized momentum equation, pressure correction equation, turbulent kinetic energy transport equation, and turbulent dissipation rate or specific turbulent flow rate transport equation are solved sequentially to realize the update calculation of the velocity vector, pressure scalar, turbulent kinetic energy, and turbulent dissipation rate or specific turbulent flow rate values ​​of each grid cell.

[0053] In the near-wall region, the standard wall function method or the enhanced wall treatment method is used to correlate the no-slip boundary conditions at the wall with the logarithmic velocity distribution, and the flow variables and eddy viscosity coefficients of the first layer of grid cells near the wall are corrected to accurately capture the flow and heat transfer characteristics in the boundary layer at high Reynolds numbers.

[0054] Furthermore, based on the converged temperature field and velocity field distribution of the fluid inside the pipe, the convective heat flux density field between the fluid inside the pipe and the wall is calculated using the fluid convection heat transfer formula, including:

[0055] Based on the converged fluid temperature field inside the pipe, the fluid temperature at the center of the first layer of grid cells in the fluid domain near the fluid-structure interaction interface is extracted as the near-wall fluid temperature.

[0056] From the fluid velocity field distribution, the fluid velocity on the wall surface at the fluid-structure interaction interface is extracted, wherein the normal velocity at the wall surface is zero, and the tangential velocity is determined to be zero based on the no-slip boundary condition;

[0057] The Prandtl number of the fluid is calculated based on the thermal conductivity of the pipe wall material, the viscosity of the fluid, and the specific heat capacity of the fluid.

[0058] Based on the velocity gradient data in the fluid velocity field distribution, the local velocity gradient of the wall at the fluid-structure interaction interface is calculated.

[0059] Calculate the local shear stress at the wall surface based on the local velocity gradient, the viscosity and density of the fluid;

[0060] Based on the local shear stress, the density and specific heat capacity of the fluid, and the Prandtl number, the local convective heat transfer coefficient at each local location of the fluid-structure interaction interface is calculated using the Reynolds analogy.

[0061] Based on the local convective heat transfer coefficient, the near-wall fluid temperature, and the corresponding wall temperature extracted from the converged heat exchanger tube wall temperature field, the convective heat flux density at each local location of the fluid-structure interaction interface is calculated using Newton's cooling formula.

[0062] The convective heat flux density at all local locations on the fluid-structure interaction interface is integrated to form a spatially continuous convective heat flux density field, and the convective heat flux density field is visualized and rendered to identify the high and low distribution areas of heat flux density.

[0063] Furthermore, the system also includes a thermal stress analysis module, used to perform thermal stress analysis based on the comprehensive temperature field distribution and heat flux density distribution, as follows:

[0064] From the converged temperature field of the heat exchanger tube wall, extract the temperature values ​​of the heat exchanger tube at different spatial locations;

[0065] Based on the thermal expansion coefficient and elastic modulus parameters of the tube wall material, and the temperature value, the thermal strain field caused by the uneven temperature distribution in the heat exchange tube is calculated.

[0066] The thermal strain field is used as the initial strain condition and applied to the structural mechanical analysis model of the heat exchanger tube.

[0067] Solve the structural mechanics analysis model to calculate the thermal stress distribution and structural deformation displacement distribution of the heat exchanger tube wall under thermal load;

[0068] Identify high stress concentration areas in the thermal stress distribution and record the location and stress peak value of the high stress concentration areas.

[0069] Compared with the prior art, the beneficial effects of the present invention are:

[0070] The turbulent flow state of the fluid inside the pipe is solved independently based on the inlet flow velocity, pressure boundary conditions, and fluid viscosity, yielding the corresponding fluid velocity field distribution and fluid pressure field distribution. Then, the steady-state temperature of the heat exchange tube wall under fluidless conditions is solved independently based on the ambient temperature outside the tube, the thermal conductivity, specific heat capacity, and density of the tube wall material, yielding the solid reference temperature field distribution. This step-by-step independent solution method can prevent parameter interference between the flow field calculation and the solid temperature calculation. The solutions for the fluid velocity field and pressure field conform to the physical laws of turbulent flow inside the tube, and the calculation of the solid reference temperature field conforms to the inherent heat transfer characteristics of the tube wall material under fluidless conditions.

[0071] The fluid velocity field distribution, fluid pressure field distribution, and solid reference temperature field distribution obtained independently are coupled for calculation. Data exchange is completed through energy conservation and heat conduction equations at the fluid-solid boundary. The fluid temperature field and heat exchange tube wall temperature field are updated iteratively until the convergence criterion is reached. The boundary energy conservation and heat conduction equations can constrain the heat transfer calculation logic at the fluid-solid interface. The comprehensive temperature field distribution and heat flux density distribution formed by the iteration can match the actual thermal state under the multi-physics coupling effect of the heat exchange tube. Data exchange at the fluid-solid interface can reduce numerical deviation during the coupled calculation process. Attached Figure Description

[0072] Figure 1 This is a timing diagram of the multi-physics field coupled heat exchanger tube thermal performance simulation design system described in this invention.

[0073] Figure 2 A flowchart for solving the turbulent flow state of fluid inside a pipe and generating the velocity and pressure fields;

[0074] Figure 3 A flowchart for generating the solid reference temperature field distribution. Detailed Implementation

[0075] The technical solution of the present invention will be clearly and completely described below with reference to the embodiments. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0076] See Figure 1 This invention provides a simulation and design system for the thermal performance of heat exchanger tubes using multi-physics coupling. The specific system includes:

[0077] The model building module establishes a parametric three-dimensional geometric model based on the input heat exchanger tube design parameters. This model precisely includes the heat exchanger tube wall thickness, the cross-sectional shape of the internal flow channel, and the external fin structure. The condition setting module sets the initial conditions and material properties for the simulation, including the inlet state of the fluid inside the tube, external environmental conditions, and the thermophysical parameters of the solid and fluid materials. The system executes two solution processes in parallel: the fluid solution module solves for turbulent flow in the fluid domain based on the set inlet velocity, pressure boundary, and fluid viscosity, generating the fluid velocity and pressure field distributions; the solid solution module solves for the steady-state temperature distribution under pure thermal conductivity conditions in the solid domain based on the external ambient temperature and material properties, generating the solid reference temperature field distribution. The coupled calculation module is activated, establishing a data channel at the interface between the fluid and solid domains, and performing coupled iterative calculations on the velocity and pressure fields obtained from the fluid solution and the reference temperature field obtained from the solid solution. The coupling process exchanges data through the energy conservation and heat conduction equations at the fluid-solid interface, continuously updating the fluid and solid temperature fields until the temperature and heat flux residuals at the fluid-solid interface meet the convergence criteria. Upon iterative convergence, the system outputs the final integrated temperature field distribution and heat flux density distribution, completing a full simulation of the heat exchanger tube's thermal performance.

[0078] In one embodiment of the present invention, the fluid solution module begins operation after the model building module completes geometric modeling and the condition setting module completes parameter definition. (See also...) Figure 2This module spatially discretizes the flow channel region within the heat exchanger tube based on its three-dimensional geometric model, generating a fluid computational grid. On this grid, inlet velocity and pressure boundary conditions, specified by the condition setting module, are applied, along with the fluid viscosity and density parameters. An eddy viscosity turbulence model is used for solving the problem. This involves constructing the governing equations of the eddy viscosity turbulence model, which include Reynolds-averaged continuity equations, Reynolds-averaged momentum equations, turbulent kinetic energy transport equations, and turbulent dissipation rate transport equations or transport equations for specific turbulent flow rates. An eddy viscosity coefficient is introduced into the Reynolds-averaged momentum equations, expressed as a function of turbulent kinetic energy and turbulent dissipation rate or specific turbulent flow rate. On the fluid computational grid, the governing equations are spatially discretized using the finite volume method, and time-separated using an implicit scheme, constructing a set of nonlinear algebraic equations concerning the velocity, pressure, turbulent kinetic energy, and turbulent dissipation rate or specific turbulent flow rate of each grid cell. A semi-implicit method or pressure correction algorithm, both well-known in the art, is employed to solve this nonlinear algebraic equation system. Within each iteration step, the discretized momentum equation, pressure correction equation, turbulent kinetic energy transport equation, and turbulent dissipation rate or specific turbulent flow rate transport equation are solved sequentially. In the near-wall region, the flow variables and eddy viscosity coefficients of the first layer of grid cells near the wall are corrected using the standard wall function method or enhanced wall treatment method. Through the above solution process, the velocity vector and pressure scalar within each fluid computational grid cell are calculated. Full-field statistics are performed on the velocity vectors and pressure scalars of all fluid computational grid cells to form a continuous fluid velocity field distribution and fluid pressure field distribution. The generated fluid velocity field distribution is post-processed to extract the velocity profile of the flow channel section, the location of the flow separation zone, and the near-wall velocity gradient data.

[0079] In a specific implementation, for a circular heat exchanger tube with annular fins on its outer wall and a circular flow channel inside the tube, when the fluid solver module starts working, it first discretizes the circular flow channel region inside the tube spatially based on the three-dimensional geometric model of the heat exchanger tube established by the model building module, generating an unstructured tetrahedral mesh or multiple structured hexahedral meshes as the fluid calculation mesh. In some embodiments, the fluid calculation mesh is refined in the near-wall region to meet the requirements of the subsequent turbulence model for near-wall analysis. After the fluid calculation mesh is generated, an inlet velocity set by the condition setting module is applied to the inlet boundary of the mesh, for example, set to 2.5 m / s, and a pressure outlet boundary condition is applied to the outlet boundary, for example, setting the static pressure to 1 standard atmosphere, and a no-slip boundary condition is applied to the mesh wall, while specifying the viscosity and density parameters of the fluid.

[0080] In practical implementation, the eddy viscosity turbulence model is used to solve the flow. The governing equations of the eddy viscosity turbulence model include the Reynolds-averaged continuity equation, the Reynolds-averaged momentum equation, the transport equation for turbulent kinetic energy, and the transport equation for turbulent dissipation rate. In the eddy viscosity turbulence model, the eddy viscosity coefficient is introduced to relate the effects of turbulent fluctuations. The eddy viscosity coefficient is a function of turbulent kinetic energy and turbulent dissipation rate. The relationship between the eddy viscosity coefficient and turbulent kinetic energy and turbulent dissipation rate can be expressed by the following formula:

[0081]

[0082] in: Indicates the eddy viscosity coefficient. Represents turbulent kinetic energy. Indicates the turbulent dissipation rate. These are model constants. This refers to the near-wall damping function. On the fluid computational grid, the finite volume method is used for spatial discretization of the governing equations, and a first-order implicit Euler scheme is used for temporal discretization, constructing a set of nonlinear algebraic equations concerning the velocity, pressure, turbulent kinetic energy, and turbulent dissipation rate of each grid cell. This can be understood as using a semi-implicit method with coupled pressure equations to solve the nonlinear algebraic equations, sequentially solving the discretized momentum equation, pressure correction equation, turbulent kinetic energy transport equation, and turbulent dissipation rate transport equation within each iteration step. In the near-wall region, the standard wall function method is used to handle the flow variables and eddy viscosity coefficients of the first layer of near-wall grid cells. The standard wall function method places the nodes of the first layer of wall grid cells in the region where the logarithmic law holds, and correlates the wall shear stress with the near-wall node velocity through the wall function. Optionally, when accurate analysis of the viscous sublayer is required, an enhanced wall treatment method is used. This method requires a sufficiently fine near-wall grid and modifies the turbulence model at low Reynolds numbers. Through the above solution process, the velocity vector and pressure scalar in each fluid computational grid cell are calculated.

[0083] In specific implementations, the velocity vectors and pressure scalars of all fluid computational grid cells undergo full-field statistical and interpolation processing to form spatially continuous fluid velocity and pressure field distributions. In some embodiments, the generated fluid velocity field distribution is post-processed to extract the velocity profile of the central symmetrical section of the flow channel, identify the location of the flow separation zone near the downstream pipe wall of the fins, and calculate the velocity gradient data in the near-wall region. The near-wall velocity gradient data is used to evaluate the wall shear stress. It can be understood that the extracted velocity profile, the location of the flow separation zone, and the near-wall velocity gradient data constitute a complete description of the turbulent flow state inside the pipe, providing flow input for subsequent coupled heat transfer calculations.

[0084] In one embodiment of the invention, the solid solution module is executed in parallel while the fluid solution module is running. See also Figure 3This module discretizes the heat exchanger tube wall and external fin structure based on the three-dimensional geometric model of the heat exchanger tube, generating a solid-state computational mesh. An external ambient temperature, specified by a condition setting module, is applied to the outer boundary of the generated solid-state computational mesh, while preset conditions for adiabatic or convective heat transfer are applied to the inner boundary. Using the thermal conductivity, specific heat capacity, and density of the tube wall material specified by the condition setting module, a transient heat conduction control equation for the solid region is constructed and simplified into a steady-state equation for solution. Solving this steady-state equation yields the steady-state temperature value for each solid-state computational mesh cell under pure thermal conductivity and preset boundary conditions. Integrating the steady-state temperature values ​​of all solid-state computational mesh cells generates a solid-state reference temperature field distribution. From this solid-state reference temperature field distribution, the temperature gradient distribution and isotherm data within the wall can be further extracted.

[0085] In a specific implementation, for a circular cross-section heat exchanger tube with annular fins on its outer wall, the tube wall material is aluminum. When the solid-state solver module starts working, it first discretizes the solid region, including the tube wall and the outer annular fins, based on the three-dimensional geometric model of the heat exchanger tube established by the model building module, generating a tetrahedral or hexahedral mesh as the solid-state computational mesh. In some embodiments, the solid-state computational mesh is locally refined at the junction of the fin roots and the tube wall, as well as at the fin tips, to more accurately capture the temperature gradient changes in these geometric feature regions. After the solid-state computational mesh is generated, the ambient temperature outside the tube, set by the condition setting module (e.g., 300 Kelvin), is applied to the outer boundary of the solid-state computational mesh. At the inner boundary of the solid-state computational mesh, i.e., the wall adjacent to the flow channel inside the tube, an adiabatic preset condition is applied, meaning that the initial assumption is that no heat is transferred from the fluid to the solid wall.

[0086] In practical implementation, the transient heat conduction control equations for the solid region are constructed using the thermal conductivity, specific heat capacity, and density of the pipe wall material specified by the condition setting module. These transient heat conduction control equations are then simplified to steady-state equations under steady-state assumptions for solution. The Laplace form of the steady-state heat conduction control equations is as follows:

[0087]

[0088] in: It is the Hamiltonian operator. This indicates the thermal conductivity of the pipe wall material. This represents the temperature of the solid region. It can be understood that solving this steady-state equation means calculating the temperature field of the solid computational grid cells that satisfy the equation under given boundary conditions. In some embodiments, the steady-state heat conduction control equation is discretized and numerically solved on the solid computational grid using the finite element method or the finite volume method, calculating the steady-state temperature value of each solid computational grid cell under pure heat conduction and preset boundary conditions. For example, the temperature of a cell located at the root of a fin is 315 Kelvin, while the temperature of a cell located at the tip of a fin is 305 Kelvin. Optionally, when the boundary conditions include convective heat transfer, the right-hand side of the steady-state equation is not zero, and a corresponding source term needs to be added according to Newton's law of cooling.

[0089] In practical implementation, the steady-state temperature values ​​of all solid-state computational grid cells are integrated, and the discrete cell temperature values ​​are reconstructed into a spatially continuous field through data interpolation, generating a solid-state reference temperature field distribution covering the entire heat exchanger tube wall and fin structure. From the solid-state reference temperature field distribution, the temperature gradient distribution along the wall thickness direction inside the wall, as well as isotherm data consisting of a series of points with the same temperature value, can be further extracted. It can be understood that the solid-state reference temperature field distribution is the initial temperature state determined only by the ambient temperature outside the tube and the thermal conductivity of the solid material, without considering the cooling or heating effects of the fluid inside the tube. This distribution provides a physically reasonable initial temperature field in the solid domain for subsequent fluid-structure interaction iterations.

[0090] In one embodiment of the present invention, after the fluid solution module and the solid solution module generate their respective basic field distributions, the coupled calculation module initiates a coupled iteration process. The coupled calculation module first sets the fluid-structure interaction interface, which is the interface where the fluid computation grid and the solid computation grid coincide. In each coupled data exchange iteration, at the fluid-structure interaction interface, the solid-side temperature at the interface is obtained from the latest heat exchanger tube wall temperature field distribution and used as a boundary condition for the fluid energy equation, which is then passed to the fluid solution module. The fluid solution module recalculates based on the updated boundary conditions, generating an updated in-tube fluid temperature field, and extracts the fluid-side heat flux density of the fluid-structure interaction interface from this updated in-tube fluid temperature field. The extracted fluid-side heat flux density of the fluid-structure interaction interface is used as a heat flux boundary condition for the fluid-structure interaction interface in the solid solution module and passed to the solid solution module. The solid solution module recalculates based on this heat flux boundary condition, generating an updated heat exchanger tube wall temperature field, and extracts the solid-side temperature of the fluid-structure interaction interface from it, thereby completing one coupled data exchange iteration. After each coupling data exchange iteration, the system compares the updated solid-side temperature at the fluid-structure interaction interface with the corresponding temperature value from the previous iteration, calculating the maximum temperature residual across the entire field. It also compares the updated fluid-side heat flux density at the fluid-structure interaction interface with the corresponding heat flux density value from the previous iteration, calculating the maximum heat flux residual across the entire field. The calculated maximum temperature residual is compared to a preset temperature convergence threshold, and the maximum heat flux residual is compared to a preset heat flux convergence threshold. If both the maximum temperature residual and the maximum heat flux residual are less than the preset temperature convergence threshold, the fluid-structure interaction heat coupling iteration calculation is considered to have reached the convergence criterion, and the iteration terminates. If the convergence conditions are not simultaneously met, the latest updated heat exchanger wall temperature field and the internal fluid temperature field are used as inputs for the next iteration, and the above coupling data exchange iteration process is repeated.

[0091] In a specific implementation, for a circular cross-section heat exchanger tube with annular fins on its outer wall, after the fluid solver generates the fluid velocity and pressure field distributions, and the solid solver generates the solid reference temperature field distribution, the coupled calculation module begins to work. The coupled calculation module first defines the fluid-structure interaction interface, which is the interface where the fluid calculation mesh and the solid calculation mesh coincide on the inner wall of the heat exchanger tube. In some embodiments, the fluid-structure interaction interface is defined as a set of mesh surface elements sharing the same spatial coordinates, these mesh surface elements belonging to the fluid domain boundary and the solid domain boundary, respectively.

[0092] In the specific implementation, during the first coupling data exchange iteration, at the fluid-structure interaction interface, the solid-side temperature at the interface is obtained from the solid reference temperature field distribution generated by the solid solution module. This solid-side temperature is then used as the wall temperature boundary condition for the fluid energy equation and passed to the fluid solution module. The fluid solution module recalculates the fluid flow and heat transfer based on the updated wall temperature boundary condition, generating an updated in-pipe fluid temperature field and extracting the fluid-side heat flux density at the fluid-structure interaction interface from this updated field. This extracted fluid-side heat flux density is then used as the heat flux density boundary condition for the fluid-structure interaction interface in the solid solution module and passed to it. The solid solution module recalculates the solid heat conduction based on the heat flux density boundary condition, generating an updated heat exchange tube wall temperature field and extracting the solid-side temperature at the fluid-structure interaction interface from this updated field. This completes one full coupling data exchange iteration.

[0093] In practical implementation, after each coupling data exchange iteration, the system compares the updated solid-side temperature of the fluid-structure interaction interface with the corresponding temperature value from the previous iteration to calculate the maximum temperature residual across the entire field. Simultaneously, it compares the updated heat flux density of the fluid-structure interaction interface with the corresponding heat flux density value from the previous iteration to calculate the maximum heat flux residual across the entire field. It can be understood that residual calculation involves traversing all mesh elements on the fluid-structure interaction interface. The convergence of the coupling iteration is determined by comparing the residual with a threshold, and the judgment condition is defined by the following logical expression:

[0094]

[0095] in: This indicates the maximum temperature residual across the entire venue. This indicates the preset temperature convergence threshold. This represents the maximum residual heat flux throughout the entire event. Indicates the preset heat flux convergence threshold, symbol This represents a logical AND operation. The calculated maximum temperature residual across the entire field is compared with a preset temperature convergence threshold, and the maximum heat flux residual across the entire field is compared with a preset heat flux convergence threshold. In some embodiments, the preset temperature convergence threshold is set to 0.01 Kelvin, and the preset heat flux convergence threshold is set to 0.1 watts per square meter. If the maximum temperature residual across the entire field is less than the preset temperature convergence threshold, and the maximum heat flux residual across the entire field is less than the preset heat flux convergence threshold, then the fluid-structure-thermal coupling iterative calculation is determined to have reached the convergence criterion, and the iteration process is terminated. Optionally, the convergence thresholds can be adjusted according to the required calculation accuracy; for example, when higher accuracy is required, the preset temperature convergence threshold can be set to 0.001 Kelvin.

[0096] In practice, if the convergence condition is not met simultaneously, the latest updated heat exchanger tube wall temperature field and the fluid temperature field inside the tube are used as inputs for the next coupled data exchange iteration. This process, starting from transferring the solid-side temperature to the fluid solution module, is repeated until the convergence condition is met. The entire iterative process is automatic; a simplified iterative convergence process is shown in Table 1.

[0097] Table 1: Residual Variation Table of Fluid-Structure-Thermal Coupling Iteration

[0098] 1 15.7 1250.4 no 2 4.2 356.8 no 3 1.1 98.5 no 4 0.25 25.3 no 5 0.06 6.1 no 6 0.008 0.85 yes

[0099] In one embodiment of the present invention, when the fluid-structure interaction (FSI) iterative calculation reaches the convergence criterion, the coupling calculation module records the converged heat exchanger wall temperature field obtained from the last iteration and the converged in-tube fluid temperature field obtained from the last iteration. The converged heat exchanger wall temperature field and the converged in-tube fluid temperature field are spatially fused to generate a comprehensive temperature field distribution covering the entire heat exchanger wall and the in-tube flow field. Based on the temperature gradient in this comprehensive temperature field distribution, the thermal conductivity of the known wall material is used to calculate the internal thermal flux density field of the heat exchanger wall. Simultaneously, based on the converged in-tube fluid temperature field and fluid velocity field distribution, the convective heat flux density field between the in-tube fluid and the wall surface is calculated using the fluid convection heat transfer formula. This calculation process includes: extracting the fluid temperature at the center of the first layer of grid cells in the fluid domain near the fluid-structure interaction interface based on the converged in-tube fluid temperature field, as the near-wall fluid temperature; and extracting the fluid velocity on the wall surface at the fluid-structure interaction interface from the fluid velocity field distribution. The Prandtl number of the fluid is calculated based on the thermal conductivity of the pipe wall material, the viscosity of the fluid, and the specific heat capacity of the fluid. The local velocity gradient at the fluid-structure interaction interface is calculated based on the velocity gradient data in the fluid velocity field distribution. The local shear stress at the wall is calculated based on this local velocity gradient, the fluid viscosity, and the density. The local convective heat transfer coefficient at each local location of the fluid-structure interaction interface is calculated using the Reynolds analogy based on this local shear stress, the fluid density, specific heat capacity, and the Prandtl number. The convective heat flux density at each local location of the fluid-structure interaction interface is calculated using Newton's law of cooling based on the calculated local convective heat transfer coefficient, the near-wall fluid temperature, and the corresponding wall temperature extracted from the converged heat exchanger pipe wall temperature field. The convective heat flux densities at all local locations on the fluid-structure interaction interface are integrated to form a spatially continuous convective heat flux density field. In addition, the system includes a thermal stress analysis module, which extracts the temperature values ​​of the heat exchanger at different spatial locations from the converged heat exchanger pipe wall temperature field. Based on the thermal expansion coefficient and elastic modulus parameters of the tube wall material, as well as the extracted temperature values, the thermal strain field caused by the non-uniform temperature distribution in the heat exchange tube is calculated. This thermal strain field is used as the initial strain condition and applied to the structural mechanics analysis model of the heat exchange tube. Solving this structural mechanics analysis model yields the thermal stress distribution and structural deformation displacement distribution of the heat exchange tube wall under thermal load, and identifies the high stress concentration regions, their locations, and stress peak values ​​within the thermal stress distribution.

[0100] In practical implementation, when the fluid-structure-thermal coupling iterative calculation reaches the convergence criterion of the above embodiment, the coupling calculation module records the converged heat exchanger tube wall temperature field obtained from the last iteration. This temperature field describes the stable temperature distribution of the aluminum tube wall and fins under coupled heat transfer. Simultaneously, it records the converged tube fluid temperature field obtained from the last iteration, which describes the temperature change of the fluid during flow. In practical implementation, the converged heat exchanger tube wall temperature field and the converged tube fluid temperature field are spatially fused to generate a unified data field covering the entire solid domain and internal fluid domain of the heat exchanger tube, i.e., the comprehensive temperature field distribution. Based on the temperature gradient in the comprehensive temperature field distribution, using the known thermal conductivity of the tube wall material, the thermal conductivity heat flux density vector at each point inside the heat exchanger tube wall is calculated using Fourier's law of thermal conductivity, thus forming a thermal conductivity heat flux density field.

[0101] In practical implementation, based on the convergent temperature and velocity field distributions of the fluid inside the pipe, the convective heat flux density field between the fluid and the wall is calculated using the fluid convection heat transfer formula. The calculation process includes: extracting the fluid temperature at the center of the first layer of grid cells in the fluid domain near the fluid-structure interaction interface based on the convergent temperature field of the fluid inside the pipe, as the near-wall fluid temperature. Extracting the fluid velocity on the wall at the fluid-structure interaction interface from the fluid velocity field distribution, where the normal velocity at the wall is zero, and the tangential velocity is determined to be zero based on the no-slip boundary condition. Calculating the Prandtl number of the fluid based on the thermal conductivity of the pipe wall material, the viscosity of the fluid, and the specific heat capacity of the fluid. Calculating the local velocity gradient on the wall at the fluid-structure interaction interface based on the velocity gradient data in the fluid velocity field distribution. Calculating the local shear stress at the wall based on the local velocity gradient, the viscosity and density of the fluid. Based on local shear stress, fluid density, specific heat capacity, and Prandtl number, the local convective heat transfer coefficient at each local location of the fluid-structure interaction interface is calculated using the Reynolds analogy. One expression of the Reynolds analogy is as follows:

[0102]

[0103] in: Indicates the local convective heat transfer coefficient. Indicates the local friction coefficient. Indicates fluid density, Indicates the specific heat capacity of a fluid. Indicates characteristic flow velocity, This represents the Prandtl number. It can be understood that the convective heat flux density at each local location of the fluid-structure interaction interface is calculated using Newton's law of cooling, based on the local convective heat transfer coefficient, the near-wall fluid temperature, and the corresponding wall temperature extracted from the convergent heat exchanger tube wall temperature field. The convective heat flux densities at all local locations on the fluid-structure interaction interface are then integrated to form a spatially continuous convective heat flux density field. In some embodiments, the convective heat transfer parameters at different locations are shown in Table 2.

[0104] Table 2: Local Convection Heat Transfer Parameters

[0105] 0.1 0 1250 15200 0.1 90 1180 14350 0.5 0 980 11900 0.5 90 1050 12750

[0106] In practical implementation, the thermal stress analysis module performs thermal stress analysis based on the comprehensive temperature field distribution and heat flux density distribution. From the converged temperature field of the heat exchanger tube wall, the module extracts temperature values ​​at different spatial locations of the heat exchanger tube, for example, extracting the temperature values ​​of ten thousand nodes on the tube wall and fins under thermal equilibrium. Based on the thermal expansion coefficient and elastic modulus parameters of the tube wall material, and the extracted temperature values, the module calculates the thermal strain field caused by the non-uniform temperature distribution in the heat exchanger tube. The thermal strain field characterizes the free expansion or contraction tendency of the material due to temperature changes. It can be understood that the thermal strain field is applied as an initial strain condition to the structural mechanics analysis model of the heat exchanger tube. The structural mechanics analysis model uses a structural mesh consistent with the solid calculation mesh in the solid solution module. Solving the structural mechanics analysis model calculates the thermal stress distribution and structural deformation displacement distribution of the heat exchanger tube wall under thermal load. In some embodiments, the thermal stress distribution shows stress concentration at the connection between the fin root and the tube wall. Optionally, high stress concentration areas in the thermal stress distribution can be identified, and the location and stress peak value of the high stress concentration areas can be recorded, such as recording the location coordinates and values ​​of the maximum principal stress.

[0107] In one embodiment of the present invention, the process of establishing a three-dimensional geometric model of the heat exchanger tube by the model building module includes: based on a series of heat exchanger tube design parameters input by the user, including the basic tube diameter, tube length, wall thickness, flow channel cross-sectional shape, fin type, fin height, fin spacing, and fin thickness; calling the parametric geometry modeling engine, and generating a preliminary three-dimensional solid model containing a smooth inner flow channel surface with equal wall thickness and a periodic outer fin array through predefined mathematical expressions and Boolean operations, according to these input design parameters; automatically rounding or chamfering the corners of all adjacent surfaces in the generated preliminary three-dimensional solid model to eliminate geometric singularities and generate transition features that better conform to the actual manufacturing process, thereby forming a continuous and smooth geometric model; and performing virtual assembly interference checks on the continuous and smooth geometric model to ensure that the inner flow channel space is completely surrounded by the tube wall solid and that the outer fin array is seamlessly connected to the tube wall solid without any geometric errors such as penetration or overlap. The geometric model that has passed the interference check is converted into a boundary representation model, and attribute labels are attached to different parts of the model. These attribute labels are used to clearly identify the flow channel region, solid tube wall region, and fin region, thus completing the construction of the three-dimensional geometric structure model.

[0108] In a specific implementation, for a circular cross-section heat exchanger tube with annular fins on its outer wall, the model building module starts working based on a series of heat exchanger tube design parameters input by the user. These parameters include the basic tube diameter, tube length, wall thickness, flow channel cross-sectional shape, fin type, fin height, fin spacing, and fin thickness. In some embodiments, the user-input basic tube diameter is 25 mm, tube length is 1 m, wall thickness is 2 mm, flow channel cross-sectional shape is circular, fin type is annular fins, fin height is 10 mm, fin spacing is 8 mm, and fin thickness is 1 mm. The model building module calls a parametric geometric modeling engine to generate a preliminary 3D solid model based on the input heat exchanger tube design parameters through predefined mathematical expressions and Boolean operations. The generation process includes generating a smooth inner flow channel surface by scanning along a path using a circular cross-section, generating a tube wall solid with uniform wall thickness through offset surface and fill operations, and generating a periodic outer fin array through array operations.

[0109] In practice, the parametric geometric modeling engine controls the periodic arrangement of the fins and the axial position of the fin centerline through mathematical expressions. From the formula:

[0110]

[0111] in: This indicates the starting axial coordinate of the first fin. Indicates the index number of the fin. This represents the axial spacing determined by the fin spacing input by the user. For all adjacent surface intersections in the generated preliminary 3D solid model, automatic filleting or chamfering is applied. For example, a 0.5 mm radius fillet is automatically added at the intersection of the fin root and the outer surface of the tube wall, and a 0.3 mm chamfer is automatically added at the edge of the flow channel inlet. This eliminates geometric singularities and generates transition features that better reflect actual manufacturing processes, resulting in a continuous and smooth geometric model. It is understandable that filleting or chamfering is a crucial step in avoiding low-quality elements in subsequent mesh generation.

[0112] In practical implementation, a virtual assembly interference check is performed on the continuous and smooth geometric model. This check ensures that the inner flow channel space is completely surrounded by the pipe wall entity, and that the outer fin array is seamlessly connected to the pipe wall entity, without any geometric errors such as penetration or overlap. In some embodiments, the interference check is achieved by calculating the minimum distance and penetration depth between geometric entities. When a gap is detected between the inner flow channel surface and the inner surface of the pipe wall entity, or when the outer fins intersect with the pipe wall, the system reports a geometric error and highlights the problem area. The geometric model that passes the interference check is then converted into a boundary representation model. This model accurately describes the geometry using faces, edges, vertices, and their topological relationships. Optionally, after conversion to a boundary representation model, attribute labels are attached to different parts of the model. These labels identify the flow channel region, the solid pipe wall region, and the fin region. For example, the inner flow channel surface is labeled as a "fluid domain boundary," and the pipe wall entity and fins are labeled as "solid domains," thus completing the construction of the three-dimensional geometric structure model. It is understood that the three-dimensional geometric structure model with attribute labels provides clear geometric and attribute definitions for subsequent mesh generation and physical condition settings.

[0113] The above embodiments are only used to illustrate the technical methods of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical methods of the present invention without departing from the spirit and scope of the technical methods of the present invention.

Claims

1. A multi-physical field coupled heat exchange tube thermal performance simulation design system, characterized in that, include: The model building module establishes a three-dimensional geometric model of the heat exchange tube, which includes the wall thickness parameters, the cross-sectional shape parameters of the flow channel inside the tube, and the structural parameters of the fins outside the tube. The condition setting module sets the initial conditions and material properties for multiphysics coupling simulation. The initial conditions include the inlet temperature of the fluid inside the pipe, the inlet velocity, the ambient temperature outside the pipe, and the pressure boundary conditions. The material properties include the thermal conductivity, specific heat capacity, and density of the pipe wall material, and the viscosity, specific heat capacity, and thermal conductivity of the fluid. The fluid solving module solves for the turbulent flow state of the fluid in the pipe based on the inlet velocity, the pressure boundary conditions, and the viscosity of the fluid, generating the fluid velocity field distribution and the fluid pressure field distribution. The solid solution module solves for the steady-state temperature distribution of the heat exchange tube wall under fluidless conditions based on the ambient temperature outside the tube, the thermal conductivity of the tube wall material, the specific heat capacity, and the density, generating a solid reference temperature field distribution. The coupling calculation module performs coupled calculations on the fluid velocity field distribution, the fluid pressure field distribution, and the solid reference temperature field distribution. It exchanges data through the energy conservation and heat conduction equations at the fluid-solid boundary, updates the fluid temperature field and the heat exchange tube wall temperature field until the convergence criterion is reached, and generates the coupled comprehensive temperature field distribution and heat flux density distribution.

2. The multi-physics coupled heat transfer tube thermal performance simulation design system of claim 1, wherein, Based on the inlet flow velocity, the pressure boundary conditions, and the viscosity of the fluid, the turbulent flow state of the fluid inside the pipe is solved to generate the fluid velocity field distribution and the fluid pressure field distribution, including: Based on the three-dimensional geometric model of the heat exchange tube, the flow channel region inside the tube is spatially discretized to generate a fluid computational grid. Apply the inlet velocity and the pressure boundary conditions to the fluid computation grid, and specify the viscosity and density parameters of the fluid; Using the eddy viscosity turbulence model, the momentum conservation equations, which include convection, diffusion, and pressure gradient terms, are solved to calculate the velocity vector and pressure scalar within each fluid computational grid cell. The velocity vector and pressure scalar of the fluid computation grid cell are statistically analyzed across the entire field to form a continuous fluid velocity field distribution and a fluid pressure field distribution. The fluid velocity field distribution is post-processed to extract the velocity profile of the flow channel section, the location of the flow separation zone, and the near-wall velocity gradient data.

3. The multiphysics coupled heat exchanger tube thermal performance simulation and design system according to claim 1, characterized in that, Based on the ambient temperature outside the tube, the thermal conductivity of the tube wall material, the specific heat capacity, and the density, the steady-state temperature distribution of the heat exchange tube wall under fluidless conditions is solved to generate a solid reference temperature field distribution, including: Based on the three-dimensional geometric model of the heat exchange tube, the heat exchange tube wall and the external fin structure are spatially discretized to generate a solid computational mesh. The ambient temperature outside the tube is applied to the outer boundary of the solid computing grid, and preset conditions for adiabatic or convective heat transfer are applied to the inner boundary of the solid computing grid. Using the thermal conductivity, specific heat capacity, and density of the pipe wall material, a transient heat conduction control equation for the solid region is constructed, and the transient heat conduction control equation is simplified into a steady-state equation for solution. Solve the steady-state equation to calculate the steady-state temperature of each solid computational grid cell under pure thermal conduction and preset boundary conditions; The steady-state temperature values ​​of all solid computational grid cells are integrated to generate the solid reference temperature field distribution, and the temperature gradient distribution and isotherm data inside the wall are extracted from it.

4. The multiphysics coupled heat exchanger tube thermal performance simulation and design system according to claim 1, characterized in that, The fluid velocity field distribution, the fluid pressure field distribution, and the solid reference temperature field distribution are coupled and calculated, and data exchange is performed through energy conservation and heat conduction equations at the fluid-solid boundary, including: Define a fluid-structure interaction interface, which is the interface where the fluid computation mesh and the solid computation mesh overlap; At the fluid-structure interaction interface, the solid-side temperature at the interface is obtained from the solid reference temperature field distribution and used as the boundary condition of the fluid energy equation, which is then passed to the fluid solver module. The fluid solving module recalculates based on the updated boundary conditions, generates an updated in-pipe fluid temperature field, and extracts the fluid-side heat flux density at the fluid-structure interaction interface from the updated in-pipe fluid temperature field. The fluid-side heat flux density of the fluid-structure interaction interface is used as the heat flux boundary condition of the fluid-structure interaction interface in the solid solution module and is passed to the solid solution module. The solid solution module recalculates based on the heat flow boundary conditions, generates an updated temperature field of the heat exchanger tube wall, and extracts the solid-side temperature of the fluid-structure interaction interface from it, completing one iteration of coupled data exchange.

5. The multiphysics coupled heat exchanger tube thermal performance simulation design system according to claim 4, characterized in that, The process of updating the fluid temperature field inside the tube and the heat exchange tube wall temperature field until convergence criteria are met includes: After each iteration of the coupling data exchange, the updated solid-side temperature at the fluid-structure interaction interface is compared with the corresponding temperature value of the previous iteration, and the maximum temperature residual across the entire field is calculated. Compare the updated heat flux density on the fluid side of the fluid-structure interaction interface with the corresponding heat flux density value from the previous iteration, and calculate the maximum heat flux residual across the entire field. The maximum temperature residual across the entire field is compared with a preset temperature convergence threshold, and the maximum heat flux residual across the entire field is compared with a preset heat flux convergence threshold. If the maximum temperature residual across the entire field is less than the preset temperature convergence threshold, and the maximum heat flux residual across the entire field is less than the preset heat flux convergence threshold, then the fluid-structure-thermal coupling iterative calculation is determined to have reached the convergence criterion, and the iteration is terminated. If the convergence condition is not met simultaneously, the latest updated temperature field of the heat exchanger tube wall and the temperature field of the fluid inside the tube will be used as the input for the next iteration, and the coupled data exchange iteration process will be repeated.

6. The multiphysics coupled heat exchanger tube thermal performance simulation design system according to claim 5, characterized in that, The generated coupled integrated temperature field distribution and heat flux density distribution include: When the fluid-structure-thermal coupling iterative calculation reaches the convergence criterion, the converged heat exchanger tube wall temperature field obtained from the last iteration is recorded. Record the converged temperature field of the fluid inside the tube obtained from the last iteration; The converged temperature field of the heat exchanger tube wall and the converged temperature field of the fluid inside the tube are spatially fused to generate the comprehensive temperature field distribution covering the entire heat exchanger tube wall and the fluid field inside the tube. Based on the temperature gradient of the comprehensive temperature field distribution, the thermal conductivity of the tube wall material is used to calculate the thermal flux density field inside the heat exchange tube wall. Based on the convergent temperature field and velocity field distribution of the fluid inside the pipe, the convective heat flux density field between the fluid inside the pipe and the wall is calculated using the fluid convection heat transfer formula.

7. The multiphysics coupled heat exchanger tube thermal performance simulation design system according to claim 1, characterized in that, The model building module establishes a three-dimensional geometric model of the heat exchanger tube, including: Based on the user-inputted heat exchanger tube design parameters, the design parameters include basic tube diameter, tube length, wall thickness, flow channel cross-sectional shape, fin type, fin height, fin spacing, and fin thickness. The parametric geometry modeling engine is invoked, and based on the design parameters, a preliminary three-dimensional solid model is generated using predefined mathematical expressions and Boolean operations. This model includes a smooth inner flow channel surface, a pipe wall of equal wall thickness, and a periodic outer fin array. For all adjacent curved surfaces in the preliminary three-dimensional solid model, round or chamfer the corners automatically to eliminate geometric singularities and generate transition features that are more in line with the actual manufacturing process, forming a continuous and smooth geometric model. The continuous and smooth geometric model is subjected to virtual assembly interference check to ensure that the inner flow channel space is completely surrounded by the pipe wall entity and that the outer fin array is seamlessly connected to the pipe wall entity without any geometric errors of penetration or overlap. The geometric model that has passed the interference check is converted into a boundary representation model and attribute labels are attached. The attribute labels are used to identify the flow channel region, solid tube wall region and fin region, thus completing the construction of the three-dimensional geometric structure model.

8. The multiphysics coupled heat exchanger tube thermal performance simulation and design system according to claim 2, characterized in that, The aforementioned method employs an eddy viscosity turbulence model to solve the momentum conservation equations, which include convection, diffusion, and pressure gradient terms. Specifically, this includes: The governing equations for the eddy viscosity turbulence model are constructed. The governing equations include the Reynolds-averaged continuity equation, the Reynolds-averaged momentum equation, the turbulent kinetic energy transport equation, and the turbulent dissipation rate transport equation or the transport equation for a specific turbulent flow rate. An eddy viscosity coefficient is introduced into the Reynolds-averaged momentum equation. The eddy viscosity coefficient is expressed as a function of turbulent kinetic energy and turbulent dissipation rate or a specific turbulent flow rate to simulate the Reynolds stress term caused by velocity fluctuations. The effect of turbulent fluctuations is then correlated to the solution of the average flow through the eddy viscosity coefficient. On the fluid computation grid, the finite volume method is used to spatially discretize the governing equations, and the implicit scheme is used to discretize them in time, thus constructing a set of nonlinear algebraic equations concerning the velocity, pressure, turbulent kinetic energy, and turbulent dissipation rate or specific turbulent flow rate of each grid cell. The nonlinear algebraic equations are solved using a semi-implicit method or pressure correction algorithm known in the art for pressure coupling equations. In each iteration step, the discretized momentum equation, pressure correction equation, turbulent kinetic energy transport equation, and turbulent dissipation rate or specific turbulent flow rate transport equation are solved sequentially to realize the update calculation of the velocity vector, pressure scalar, turbulent kinetic energy, and turbulent dissipation rate or specific turbulent flow rate values ​​of each grid cell. In the near-wall region, the standard wall function method or the enhanced wall treatment method is used to correlate the no-slip boundary conditions at the wall with the logarithmic velocity distribution, and the flow variables and eddy viscosity coefficients of the first layer of grid cells near the wall are corrected to accurately capture the flow and heat transfer characteristics in the boundary layer at high Reynolds numbers.

9. The multiphysics coupled heat exchanger tube thermal performance simulation design system according to claim 6, characterized in that, Based on the converged temperature field and velocity field distribution of the fluid inside the pipe, the convective heat flux density field between the fluid inside the pipe and the wall is calculated using the fluid convection heat transfer formula, including: Based on the converged fluid temperature field inside the pipe, the fluid temperature at the center of the first layer of grid cells in the fluid domain near the fluid-structure interaction interface is extracted as the near-wall fluid temperature. From the fluid velocity field distribution, the fluid velocity on the wall surface at the fluid-structure interaction interface is extracted, wherein the normal velocity at the wall surface is zero, and the tangential velocity is determined to be zero based on the no-slip boundary condition; The Prandtl number of the fluid is calculated based on the thermal conductivity of the pipe wall material, the viscosity of the fluid, and the specific heat capacity of the fluid. Based on the velocity gradient data in the fluid velocity field distribution, the local velocity gradient of the wall at the fluid-structure interaction interface is calculated. Calculate the local shear stress at the wall surface based on the local velocity gradient, the viscosity and density of the fluid; Based on the local shear stress, the density and specific heat capacity of the fluid, and the Prandtl number, the local convective heat transfer coefficient at each local location of the fluid-structure interaction interface is calculated using the Reynolds analogy. Based on the local convective heat transfer coefficient, the near-wall fluid temperature, and the corresponding wall temperature extracted from the converged heat exchanger tube wall temperature field, the convective heat flux density at each local location of the fluid-structure interaction interface is calculated using Newton's cooling formula. The convective heat flux density at all local locations on the fluid-structure interaction interface is integrated to form a spatially continuous convective heat flux density field, and the convective heat flux density field is visualized and rendered to identify the high and low distribution areas of heat flux density.

10. The multiphysics coupled heat exchanger tube thermal performance simulation design system according to claim 6, characterized in that, The system also includes a thermal stress analysis module, used to perform thermal stress analysis based on the comprehensive temperature field distribution and heat flux density distribution, as follows: From the converged temperature field of the heat exchanger tube wall, extract the temperature values ​​of the heat exchanger tube at different spatial locations; Based on the thermal expansion coefficient and elastic modulus parameters of the tube wall material, and the temperature value, the thermal strain field caused by the uneven temperature distribution in the heat exchange tube is calculated. The thermal strain field is used as the initial strain condition and applied to the structural mechanical analysis model of the heat exchanger tube. Solve the structural mechanics analysis model to calculate the thermal stress distribution and structural deformation displacement distribution of the heat exchanger tube wall under thermal load; Identify high stress concentration areas in the thermal stress distribution and record the location and stress peak value of the high stress concentration areas.

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