Flow and boiling heat exchange rapid analysis method and device based on porous medium

Abstract

The invention provides a flow and boiling heat exchange rapid analysis method and device based on a porous medium, and relates to the technical field of porous medium heat transfer characteristic measurement, and the method comprises the steps: obtaining initial experiment data through an experiment device, and the initial experiment data comprises on-way pressure drop, wall surface temperature data and inlet and outlet temperature data of the porous medium; the fluid velocity and the fluid viscosity of the fluid in the porous medium are measured; based on the on-way pressure drop, the fluid flow velocity and the fluid viscosity, the resistance coefficient of the porous medium is obtained through calculation, and the resistance coefficient comprises an inertia resistance coefficient and a viscous resistance coefficient; calculating an equivalent heat conductivity coefficient of the porous medium according to the wall surface temperature data and the inlet and outlet temperature data; on the basis of a reduced-order one-dimensional N-S equation, a flow and heat exchange analysis model is built in combination with the physical property of the water vapor surface; and substituting the resistance coefficient and the equivalent heat conductivity coefficient into a flow and heat exchange analysis model, and predicting flow characteristics and heat exchange characteristics of the porous medium under different flow and pressure conditions. The flow and heat exchange characteristics of the porous medium material can be rapidly analyzed.

Description

Technical Field

[0001] This application relates to the technical field of measuring the heat transfer characteristics of porous media, and specifically relates to a rapid analysis method and device for flow and boiling heat transfer based on porous media. Background Technique

[0002] When an aircraft is flying at high speeds, especially under supersonic and hypersonic conditions, the aerodynamic heating effect is significant, resulting in extremely high thermal loads on the aircraft surface. The thermal protection problem has become a key factor affecting the performance and safety of the aircraft. Traditional thermal protection technologies mostly rely on passive cooling methods, such as using thermal protection coatings, thermal insulation materials, etc., but these methods are prone to performance degradation or failure during long-term use or in extreme environments.

[0003] Active cooling technologies have received extensive attention because they can effectively cope with high-temperature environments. Among them, active cooling technologies based on porous media have gradually become a research hotspot due to the high thermal conductivity and good heat transfer ability of porous media materials. Through a complex internal distribution structure and a large specific surface area, porous media can significantly enhance the heat transfer performance of fluids and, to a certain extent, disperse thermal stress. However, different porous media materials and their structural designs have a significant impact on fluid flow resistance and heat transfer characteristics. For example, parameters such as porosity, pore size distribution, and material thermal conductivity will change the efficiency and stability of the cooling system. Therefore, to optimize the thermal protection design of aircraft, it is necessary to systematically study and rapidly analyze the flow resistance characteristics and heat transfer characteristics of porous media materials.

[0004] Current research shows that there is a complex coupling relationship between the flow resistance characteristics and heat transfer performance of porous media, and the selection of different materials and structures will directly affect the performance indicators of the cooling system. Rapidly analyzing and evaluating these characteristics is of great significance for determining the best application plan of porous media materials. However, there are still relatively few studies on the rapid analysis of the flow resistance and heat transfer characteristics of porous media, and there is a lack of systematic modeling tools and experimental verification methods. Therefore, a rapid analysis method for the flow and heat transfer characteristics of porous media materials is needed. Summary of the Invention

[0005] This application provides a rapid analysis method and device for flow and boiling heat transfer based on porous media, which can rapidly analyze the flow and heat transfer characteristics of porous media materials.

[0006] In the first aspect of this application, a rapid analysis method for flow and boiling heat transfer based on porous media is provided. The method includes:

[0007] Obtain initial experimental data through an experimental device. The initial experimental data includes the pressure drop along the porous media, wall temperature data, inlet and outlet temperature data, as well as the fluid velocity and fluid viscosity of the fluid inside the porous media;

[0008] Based on the above-mentioned pressure drop along the way, the fluid flow velocity, and the fluid viscosity, the resistance coefficient of the porous medium is calculated, and the resistance coefficient includes an inertial resistance coefficient and a viscous resistance coefficient;

[0009] According to the wall temperature data and the inlet and outlet temperature data, the equivalent thermal conductivity of the porous medium is calculated;

[0010] Based on the reduced-order one-dimensional N-S equation, a flow and heat transfer analysis model is constructed by combining the physical properties of the steam table;

[0011] Substitute the resistance coefficient and the equivalent thermal conductivity into the flow and heat transfer analysis model to predict the flow characteristics and heat transfer characteristics of the porous medium under different flow rates and pressure conditions.

[0012] Based on the above technical solutions, preferably, the calculating the resistance coefficient of the porous medium based on the pressure drop along the way, the fluid flow velocity, and the fluid viscosity specifically includes:

[0013] Based on the initial experimental data and the initial assumed values of the porous medium material, use the one-dimensional reduced-order momentum equation and energy equation to solve and obtain the initial guess value;

[0014] Use the inertial resistance coefficient and the viscous resistance coefficient of the initial guess value to preliminarily calculate the preliminary pressure drop through the momentum equation;

[0015] Assume the local thermal equilibrium of the porous medium, calculate the equivalent thermal conductivity, and preliminarily solve the energy equation according to the temperature gradient to obtain the temperature distribution;

[0016] Based on the initial calculation results, use an iterative algorithm to correct the input parameters. Among them, based on the preliminary pressure drop and the temperature distribution, use the fitting formula to recalculate the inertial resistance coefficient and the viscous resistance coefficient, and adjust the resistance term in the momentum equation. For the local non-equilibrium model, there is heat exchange between the fluid and the solid, and the fluid and solid temperatures need to be updated separately;

[0017] Judge whether the change amount of pressure, or the change amount of temperature, or the change amount of the resistance coefficient in two adjacent iterative processes is less than the preset threshold;

[0018] If it is determined that in two adjacent iterative processes, the change amount of the pressure, or the change amount of the temperature, or the change amount of the resistance coefficient is less than the preset threshold, then extract the resistance coefficient according to the calculation results.

[0019] Based on the above technical solutions, preferably, based on the initial experimental data and the initial assumed values of the porous medium material, the one-dimensional reduced momentum equation and energy equation are used for solution, and the physical properties of the fluid working medium are called in real time in combination with the steam table to obtain an initial guess value, where the momentum equation is expressed as follows:

[0020]

[0021] Where, ρ f is the fluid density, V is the fluid velocity of the fluid in the porous medium, ε is the porosity of the porous medium, t is the time, P is the pressure, τ is the stress tensor, g is the gravity, and S m is the resistance source term of the porous medium;

[0022] Where, the energy equation is expressed as follows:

[0023]

[0024] Where, ε is the porosity of the porous medium, h t is the fluid static enthalpy, u is the velocity in the x direction, T f is the fluid temperature, T s is the solid temperature, h v is the volume convective heat transfer coefficient.

[0025] Based on the above technical solutions, preferably, substituting the resistance coefficient and the equivalent thermal conductivity into the flow and heat transfer analysis model to predict the flow characteristics and heat transfer characteristics of the porous medium under different flow rates and pressure conditions specifically includes:

[0026] Obtain input data, where the input data includes the resistance coefficient, the equivalent thermal conductivity, and fluid parameters;

[0027] Set the boundary conditions of the flow and heat transfer analysis model, where the boundary conditions include the flow rate range and the pressure range;

[0028] According to the actual application, select different ranges of flow rate, pressure, and heat flux density working conditions, divide the entire analysis range into multiple sub-intervals, and each sub-interval corresponds to a preset pressure difference, flow velocity, and heat transfer condition;

[0029] Based on the influence of viscous resistance and inertial resistance on the flow, analyze the flow characteristics of the fluid in the porous medium through the flow and heat transfer analysis model;

[0030] Use the one-dimensional reduction method to simplify the calculation process, calculate the changes in flow velocity, pressure, and temperature at the outlet point by point from the inlet, and in each step of the calculation, call the steam table in real time according to the fluid state to adjust the physical properties of the fluid working medium;

[0031] Obtain the heat transfer characteristics of the fluid in the porous medium according to the calculation results;

[0032] Output the flow characteristics and heat transfer characteristics of the porous medium.

[0033] Based on the above technical solutions, preferably, the resistance coefficient of the porous medium is calculated based on the frictional pressure drop, the fluid velocity, and the fluid viscosity, and the calculation principle of the resistance coefficient is as follows:

[0034]

[0035] where ΔP is the frictional pressure drop, V is the fluid velocity, L is the length of the porous medium, μ m is the fluid viscosity, ρ m is the fluid density, C2 is the inertial resistance coefficient, and a is the viscous resistance coefficient.

[0036] Based on the above technical solutions, preferably, the equivalent thermal conductivity of the porous medium is calculated according to the wall temperature data and the inlet and outlet temperature data, specifically including:

[0037] According to the temperature distribution of the inlet and outlet fluids and the wall surface under the steady state, directly convert the equivalent thermal conductivity, and the specific calculation is carried out through the following formula:

[0038]

[0039] where t in is the inlet fluid temperature, t out is the outlet fluid temperature, k eff is the equivalent thermal conductivity, t w-mean is the average temperature of the pipe wall surface, and q is the side wall heating power.

[0040] Based on the above technical solutions, preferably, the reduced-order one-dimensional N-S equation includes a continuity equation and a simplified momentum equation, and based on the reduced-order one-dimensional N-S equation, a flow and heat transfer analysis model is constructed by combining the physical properties of the steam table, specifically including:

[0041] According to the law of conservation of mass, the flow in the porous medium is processed in a volume-averaged manner to obtain the expression of the continuity equation as follows:

[0042]

[0043] where ε is the porosity of the porous medium, ρ f is the fluid density, and u is the velocity in the x direction;

[0044] Under one-dimensional steady-state conditions, the time derivative term is removed from the momentum equation, and the expression of the simplified momentum equation is obtained as follows:

[0045]

[0046] Where P is the pressure distribution, g is the acceleration due to gravity, μ is the fluid viscosity, α is the permeability, C2 is the inertial resistance coefficient, ρ f is the fluid density, and u is the velocity in the x direction.

[0047] In a second aspect of the present application, a rapid analysis device for flow and boiling heat transfer based on a porous medium is provided. The device includes an acquisition module, a processing module, and an output module, where:

[0048] The acquisition module is used to obtain initial experimental data through an experimental device. The initial experimental data includes the pressure drop along the porous medium, the wall temperature data and the inlet and outlet temperature data, as well as the fluid velocity and fluid viscosity of the fluid in the porous medium;

[0049] The processing module is used to calculate the resistance coefficient of the porous medium based on the pressure drop along the way, the fluid velocity, and the fluid viscosity. The resistance coefficient includes an inertial resistance coefficient and a viscous resistance coefficient;

[0050] The processing module is used to calculate the equivalent thermal conductivity of the porous medium according to the wall temperature data and the inlet and outlet temperature data;

[0051] The processing module is used to construct a flow and heat transfer analysis model based on the reduced-order one-dimensional N-S equation and the physical properties of the steam table;

[0052] The output module is used to substitute the resistance coefficient and the equivalent thermal conductivity into the flow and heat transfer analysis model to predict the flow characteristics and heat transfer characteristics of the porous medium under different flow rates and pressure conditions.

[0053] Based on the above technical solutions, preferably, the processing module is used to solve using the one-dimensional reduced-order momentum equation and energy equation based on the initial experimental data and the initial assumed values of the porous medium material to obtain an initial guess value;

[0054] The processing module is used to preliminarily calculate the preliminary pressure drop through the momentum equation using the inertial resistance coefficient and the viscous resistance coefficient of the initial guess value;

[0055] The processing module is used to assume local thermal equilibrium of the porous medium, calculate the equivalent thermal conductivity, and preliminarily solve the energy equation according to the temperature gradient to obtain the temperature distribution;

[0056] The processing module is configured to correct the input parameters using an iterative algorithm based on the initial calculation results. Specifically, based on the preliminary pressure drop and temperature distribution, fitting formulas are used to recalculate the inertial resistance coefficient and viscous resistance coefficient, and the resistance term in the momentum equation is adjusted. For the local non-equilibrium model, there is heat exchange between the fluid and the solid, and the temperatures of the fluid and the solid need to be updated separately.

[0057] The processing module is configured to determine whether the change in pressure, or the change in temperature, or the change in resistance coefficient in two adjacent iterative processes is less than a preset threshold.

[0058] If it is determined that the change in pressure, or the change in temperature, or the change in resistance coefficient in two adjacent iterative processes is less than the preset threshold, the processing module is configured to extract the resistance coefficient according to the calculation results.

[0059] Based on the above technical solutions, preferably, the processing module is configured to use the one-dimensional reduced-order momentum equation and energy equation to solve based on the initial experimental data and the initial assumed values of the porous medium material, and call the physical properties of the fluid working medium in real time in combination with the steam table to obtain an initial guess value. The momentum equation is expressed as follows:

[0060]

[0061] where ρ f is the fluid density, V is the fluid velocity of the fluid in the porous medium, ε is the porosity of the porous medium, t is the time, P is the pressure, τ is the stress tensor, g is the gravity, and S m is the resistance source term of the porous medium;

[0062] The energy equation is expressed as follows:

[0063]

[0064] where ε is the porosity of the porous medium, h t is the fluid static enthalpy, u is the velocity in the x direction, T f is the fluid temperature, T s is the solid temperature, h v is the volume convective heat transfer coefficient.

[0065] Based on the above technical solutions, preferably, the acquisition module is configured to acquire input data, and the input data includes the resistance coefficient, the equivalent thermal conductivity, and fluid parameters.

[0066] The processing module is configured to set the boundary conditions of the flow and heat transfer analysis model, and the boundary conditions include a flow rate range and a pressure range.

[0067] The processing module is configured to select different ranges of flow rate, pressure, and heat flux density conditions according to the actual application, divide the entire analysis range into multiple sub-ranges, and each of the sub-ranges corresponds to a preset pressure difference, flow velocity, and heat transfer condition;

[0068] The processing module is configured to analyze the flow characteristics of the fluid in the porous medium through the flow and heat transfer analysis model based on the influence of viscous resistance and inertial resistance on the flow;

[0069] The processing module is configured to simplify the calculation process using a one-dimensional reduction method, calculate the changes in flow velocity, pressure, and temperature at the outlet point by point from the inlet, and in each step of the calculation, call the steam table in real time according to the fluid state to adjust the physical properties of the fluid working medium;

[0070] The processing module is configured to obtain the heat transfer characteristics of the fluid in the porous medium according to the calculation results;

[0071] The output module is configured to output the flow characteristics and heat transfer characteristics of the porous medium.

[0072] Based on the above technical solutions, preferably, the processing module is configured to calculate the resistance coefficient of the porous medium based on the frictional pressure drop, the fluid flow velocity, and the fluid viscosity, and the calculation principle of the resistance coefficient is as follows:

[0073]

[0074] Where ΔP is the frictional pressure drop, V is the fluid flow velocity, L is the length of the porous medium, μ m is the fluid viscosity, ρ m is the fluid density, C2 is the inertial resistance coefficient, and a is the viscous resistance coefficient.

[0075] Based on the above technical solutions, preferably, the processing module is configured to calculate the equivalent thermal conductivity of the porous medium according to the wall temperature data and the inlet and outlet temperature data, specifically including:

[0076] The processing module is configured to directly convert the equivalent thermal conductivity according to the temperature distribution of the inlet and outlet fluids and the wall temperature under the steady state, and specifically calculate it through the following formula:

[0077]

[0078] Where t in is the inlet fluid temperature, t out is the outlet fluid temperature, k eff is the equivalent thermal conductivity, t w-mean is the average temperature of the pipe wall, and q is the heating power of the side wall.

[0079] Based on the above technical solutions, preferably, the processing module is configured to process the flow in the porous medium in a volume-averaged manner according to the mass conservation to obtain the following expression of the continuity equation:

[0080]

[0081] where ε is the porosity of the porous medium, ρ f is the fluid density, and u is the velocity in the x direction;

[0082] The processing module is configured to remove the time derivative term from the momentum equation under one-dimensional steady-state conditions to obtain the following expression of the simplified momentum equation:

[0083]

[0084] where P is the pressure distribution, g is the acceleration due to gravity, μ is the fluid viscosity, α is the permeability, C2 is the inertial drag coefficient, ρ f is the fluid density, and u is the velocity in the x direction.

[0085] In a third aspect of the present application, an electronic device is provided, including a processor, a memory, a user interface, and a network interface. The memory is used to store instructions, the user interface and the network interface are both used to communicate with other devices, and the processor is used to execute the instructions stored in the memory so that the electronic device executes the method described in any one of the above.

[0086] In a fourth aspect of the present application, a computer-readable storage medium is provided. The computer-readable storage medium stores instructions that, when executed, execute the method described in any one of the above.

[0087] In summary, one or more technical solutions provided in the embodiments of the present application have at least the following technical effects or advantages:

[0088] 1. First, initial data such as the pressure drop along the way, flow velocity, fluid viscosity, and wall and inlet / outlet temperature data are obtained through experiments, providing an accurate physical basis for the model. Then, the resistance coefficient and equivalent thermal conductivity calculated based on these data can reflect the flow and heat transfer characteristics between the fluid and the porous medium. Second, by using the reduced-order one-dimensional N-S equation, the originally complex three-dimensional problem is simplified to a one-dimensional problem, greatly reducing the computational complexity while ensuring the accuracy of flow and heat transfer analysis. Finally, by substituting these calculated resistance coefficients and equivalent thermal conductivities, the model can quickly predict under different flow rate and pressure conditions, so as to efficiently obtain the flow and heat transfer characteristics of the porous medium.

[0089] 2. Through the iterative optimization process, the resistance coefficient of the porous medium can be effectively calculated and corrected, ensuring the accurate prediction of flow and heat transfer characteristics. By combining initial experimental data and assumed values, the one-dimensional reduced-order momentum equation and energy equation are used for preliminary calculations, and then the inertial resistance coefficient and viscous resistance coefficient are continuously corrected through an iterative algorithm to achieve a more accurate flow and heat transfer model. Finally, by setting a preset threshold to judge the iterative convergence, the resistance coefficient that conforms to the actual working conditions can be quickly obtained, providing efficient and accurate calculation results for the prediction of flow and heat transfer characteristics.

[0090] 3. By substituting the resistance coefficient and equivalent thermal conductivity into the flow and heat transfer analysis model, the flow and heat transfer characteristics of the porous medium can be accurately predicted under different flow rates and pressure conditions. By setting reasonable boundary conditions, dividing multiple working condition intervals, simplifying the calculation process, and updating the fluid physical property parameters in real time, the flow and heat transfer behavior of the fluid can be efficiently analyzed, and key parameters such as flow velocity, pressure, and temperature can be accurately obtained, providing a precise basis for the optimization and design of the thermal flow characteristics of the porous medium. Description of the Drawings

[0091] Figure 1 is a schematic flowchart of a rapid analysis method for flow and boiling heat transfer based on a porous medium disclosed in an embodiment of the present application;

[0092] Figure 2 is a schematic diagram of an experimental device disclosed in an embodiment of the present application;

[0093] Figure 3 is a schematic diagram of the modules of a rapid analysis device for flow and boiling heat transfer based on a porous medium disclosed in an embodiment of the present application;

[0094] Figure 4 is a schematic diagram of the structure of an electronic device disclosed in an embodiment of the present application.

[0095] Description of the reference numerals: 301, acquisition module; 302, processing module; 303, output module; 401, processor; 402, communication bus; 403, user interface; 404, network interface; 405, memory. Detailed Embodiments

[0096] In order to enable those skilled in the art to better understand the technical solutions in this specification, the technical solutions in the embodiments of this specification will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of this specification. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments.

[0097] In the description of the embodiments of the present application, words such as "for example" or "for instance" are used to give examples, illustrations or explanations. Any embodiment or design solution described as "for example" or "for instance" in the embodiments of the present application should not be construed as being more preferred or having more advantages than other embodiments or design solutions. Rather, the use of words such as "for example" or "for instance" is intended to present relevant concepts in a specific manner.

[0098] In the description of the embodiments of the present application, the term "a plurality of" means two or more. For example, a plurality of systems means two or more systems, and a plurality of screen terminals means two or more screen terminals. In addition, the terms "first" and "second" are only used for descriptive purposes and cannot be construed as indicating or implying relative importance or implicitly specifying the indicated technical features. Thus, the features defined with "first" and "second" may explicitly or implicitly include one or more of such features. The terms "comprising", "including", "having" and their variants all mean "including but not limited to", unless otherwise specifically emphasized in other ways.

[0099] High-speed aircraft face extremely high thermal loads due to aerodynamic heating effects under supersonic and hypersonic conditions. Traditional passive cooling methods are difficult to meet the requirements of extreme environments. Active cooling technologies, especially those based on porous media, have received attention due to their excellent heat conduction and heat transfer capabilities. Porous media significantly enhance heat transfer performance and disperse thermal stress by virtue of their complex structure and large specific surface area. However, its flow resistance and heat transfer characteristics are significantly affected by parameters such as porosity and pore size distribution, and it is urgent to optimize the design through rapid analysis and evaluation. However, there is currently a lack of systematic modeling tools and experimental verification methods. Therefore, it is of great significance to develop a rapid analysis method for the flow resistance and heat transfer characteristics of porous media.

[0100] This embodiment discloses a rapid analysis method for flow and boiling heat transfer based on porous media, referring to Figure 1 , including the following steps S11-S150:

[0101] S110, obtain initial experimental data through an experimental device.

[0102] A rapid analysis method for flow and boiling heat transfer based on porous media disclosed in the embodiments of the present application is applied to a server. The server includes, but is not limited to, electronic devices such as mobile phones, tablet computers, wearable devices, and PCs (Personal Computers), and may also be a background server running a rapid analysis method for flow and boiling heat transfer based on porous media. The server can be implemented by an independent server or a server cluster composed of multiple servers.

[0103] The server obtains initial experimental data including the pressure drop along the porous medium, wall temperature data, inlet and outlet temperature data, as well as the fluid velocity and fluid viscosity of the fluid within the porous medium through an experimental device. The porous medium materials include, but are not limited to, metal foams, ceramic materials, and polymer porous materials. The experimental device consists of two parts: an experimental device for measuring the viscous resistance coefficient, inertial resistance coefficient, and equivalent thermal conductivity of the porous medium material, and a one-dimensional porous medium flow and heat transfer rapid analysis program based on the MATLAB program. Substitute the measured values into the program and combine with the IAPWS_IF97 steam table to call the physical properties of the fluid working medium in real time to improve the calculation and solution accuracy, so as to achieve a rapid prediction of the flow boiling heat transfer model in the porous medium pipeline.

[0104] Refer to Figure 2 , the experimental device includes a flow supply and control system for precise control of the inlet flow rate and temperature; a fiberglass heating tape: a special tooling is designed for the installation of the test piece, and the fiberglass heating tape is used to uniformly heat the surface of the test piece. The heating power can be adjusted with the heating tape, and the controllable temperature can reach up to 200 °C. A data acquisition system: collect temperature and pressure. The equivalent thermal conductivity at the average temperature of the porous medium and the fluid is calculated from the wall temperature and the inlet and outlet water temperatures obtained through the experiment. And based on the inertial resistance coefficient, viscous resistance coefficient, and equivalent heat transfer coefficient of the porous medium, the N-S equation is reduced to one-dimensional solution under the local thermal equilibrium sidewall heating and local non-equilibrium tail heating states, and the physical properties of the fluid working medium are called in real time in combination with the steam table to improve the calculation and solution accuracy, so as to achieve a rapid prediction of the flow boiling heat transfer model in the porous medium pipeline.

[0105] S120, calculate the resistance coefficient of the porous medium based on the pressure drop along the way, fluid velocity, and fluid viscosity.

[0106] In a possible implementation, based on the pressure drop along the way, fluid flow rate, and fluid viscosity, the resistance coefficient of the porous medium is calculated, specifically including: based on the initial experimental data and the initial assumed values of the porous medium material, using the one-dimensional reduced-order momentum equation and energy equation for solution to obtain the initial guess value; using the inertial resistance coefficient and viscous resistance coefficient of the initial guess value, initially calculating the preliminary pressure drop through the momentum equation; assuming local thermal equilibrium of the porous medium, calculating the equivalent thermal conductivity, and initially solving the energy equation based on the temperature gradient to obtain the temperature distribution; based on the initial calculation results, using an iterative algorithm to correct the input parameters, where, based on the preliminary pressure drop and temperature distribution, using a fitting formula to recalculate the inertial resistance coefficient and viscous resistance coefficient, adjusting the resistance term in the momentum equation, for the local non-equilibrium model, there is heat exchange between the fluid and the solid, and the fluid and solid temperatures need to be updated separately; determining whether the change in pressure, or the change in temperature, or the change in resistance coefficient in two adjacent iterative processes is less than a preset threshold; if it is determined that the change in pressure, or the change in temperature, or the change in resistance coefficient in two adjacent iterative processes is less than the preset threshold, then extracting the resistance coefficient according to the calculation results.

[0107] Specifically, configure a flow regulating valve and a fluid pressurization system to precisely control the inlet flow rate, pressure, and temperature. Uniformly heat the surface of the porous medium with a fiberglass heating tape, with a controllable design power and a maximum heating temperature of 200 °C. Configure high-precision temperature sensors and pressure sensors to collect the wall temperature, fluid inlet and outlet temperatures, and the pressure drop along the way. Conduct preliminary tests through standard porous medium materials to verify the stability and measurement accuracy of the device.

[0108] Under one-dimensional steady-state conditions, assuming that the fluid velocity is mainly along the pipeline direction, use the implicit Runge-Kutta method for iterative solution, and dynamically call the IAPWS_IF97 water vapor table to obtain fluid physical properties such as density, viscosity, and enthalpy value. Run the experiment under the preset flow rate range (0.1 - 10 g / s) and pressure range (0.1 - 10 MPa). Measure the pressure drop, inlet and outlet temperatures, and wall temperature under different working conditions. According to the pressure drop formula:

[0109]

[0110] where, ΔP is the pressure drop along the way, V is the fluid flow rate, L is the length of the porous medium, μ m is the fluid viscosity, ρ m is the fluid density, C2 is the inertial resistance coefficient, and a is the viscous resistance coefficient.

[0111] According to the pressure drop formula, use the experimental data to fit the equation y = Ax 2 + Bx, and solve for the viscous resistance coefficient and inertial resistance coefficient. A and B respectively correspond to and The two coefficients are then used to calculate the reciprocals of the viscous drag coefficient and the inertial drag coefficient.

[0112] Furthermore, first, based on the experimental data and the empirical knowledge of the porous medium material such as the structural parameters, porosity, permeability, etc. of the porous medium, initial assumed values of the inertial drag coefficient and the viscous drag coefficient are set. At the same time, it is assumed that the system temperature field is linearly distributed, or set to other simple distribution forms according to the initial experimental temperature field.

[0113] Using the one-dimensional reduced form of the momentum equation and the energy equation, a preliminary solution is carried out by numerical methods such as the finite difference method, the finite volume method or other numerical discretization methods. The steam table (three steam tables) is retrieved in reverse to obtain the dryness, and it is judged whether the working fluid is in the gas phase or the liquid phase. The initial distributions of the velocity field and the temperature field are obtained. These initial results are used for subsequent iterative corrections. At the same time, a function is called to calculate the physical property parameters of the working fluid, and the new physical property parameters are brought into the next calculation for accurate and rapid analysis. The momentum equation is expressed as follows:

[0114]

[0115] Among them, ρ f is the fluid density, V is the fluid velocity, ε is the porosity of the porous medium, t is the time, P is the pressure, τ is the stress tensor, g is the gravity, and S m is the resistance source term of the porous medium;

[0116] Among them, the energy equation is expressed as follows:

[0117]

[0118] Among them, ε is the porosity of the porous medium, h t is the fluid static enthalpy, u is the velocity in the x direction, T f is the fluid temperature, T s is the solid temperature, h v is the volume convective heat transfer coefficient.

[0119] S130. According to the wall temperature data and the inlet and outlet temperature data, calculate the equivalent thermal conductivity of the porous medium.

[0120] According to the distribution of the inlet and outlet fluid temperatures and the wall temperature under the steady state, the equivalent thermal conductivity is directly converted, and it is specifically calculated by the following formula:

[0121]

[0122] Among them, t in is the inlet fluid temperature, t out is the outlet fluid temperature, k eff is the equivalent thermal conductivity, tw-mean is the average temperature of the pipe wall, and q is the heating power of the side wall.

[0123] When the system reaches a steady state, that is, the temperature distribution does not change with time, the heat transfer power remains constant, the fluid flows in the pipe, and the wall transfers heat to the fluid through the side wall heating power. This process involves convection and heat conduction. The equivalent thermal conductivity comprehensively describes the ability of the fluid to transfer heat during the flow process, which is equivalent to an average thermal conductivity, facilitating engineering calculations and analysis. Therefore, the heat transfer intensity is measured through the wall power, the average temperature during the fluid heat transfer process is estimated using the inlet fluid temperature and the outlet fluid temperature, the wall temperature is used to represent the heat source temperature of the system, and the overall heat transfer ability of the fluid is equivalent to a heat conduction process to obtain the equivalent thermal conductivity.

[0124] Then use the energy equation:

[0125]

[0126] Numerically solve the temperature gradient to obtain the initial temperature distribution of the system. According to the preliminary pressure drop and temperature distribution, correct the inertial resistance coefficient and viscous resistance coefficient through the fitting formula. For example, the correction formula for the coefficient is fitted based on experimental data and flow characteristics:

[0127] C f = f1(ΔP, T), μ eff = f2(ΔP, T)

[0128] Adjust the resistance term in the momentum equation and recalculate the velocity field and pressure drop.

[0129] If the local non-equilibrium heat transfer model is adopted, the temperature distributions of the fluid and the solid need to be updated separately. Using the energy equation based on the local fluid / solid thermal equilibrium equation, it is as follows:

[0130]

[0131] Among them, due to the slow flow velocity of the fluid in the porous medium, the changes in the convection phase and viscous resistance phase are ignored in the energy equation. Where L is the pipe perimeter, A is the cross-sectional area, G is the mass flow rate per unit area, T is the temperature, and q is the heating power of the side wall.

[0132] In the local non-equilibrium model, there is a temperature difference between the fluid and the solid, so there is heat exchange between the fluid and the solid. The energy equation is divided into the solid energy equation and the fluid energy equation. Among them, the fluid energy equation is expressed as follows:

[0133]

[0134] The solid energy equation is expressed as follows:

[0135]

[0136] Among them, h v is the volumetric convective heat transfer coefficient, V is the velocity, h t is the fluid static enthalpy, e s is the solid internal energy, τ is the stress tensor, k f is the fluid thermal conductivity, k s is the solid thermal conductivity, S fe is the fluid energy source, S se is the solid energy source term, T f is the fluid temperature, T s is the solid temperature.

[0137] The simplification of the fluid continuity and momentum equations in the local non-equilibrium model is the same as that in the local equilibrium model. There are differences in the energy equation. The fluid and solid energy equations are simplified as follows:

[0138]

[0139]

[0140] Among them, g is the acceleration due to gravity, T f is the fluid temperature, T s is the solid temperature, u is the velocity in the x direction, k f is the fluid thermal conductivity, k s is the solid thermal conductivity, h t is the fluid static enthalpy, ε is the porosity of the porous medium.

[0141] After each iteration, compare whether the change in pressure, temperature, or drag coefficient between two adjacent iterations is less than a preset threshold (such as 1e-5). The specific judgment condition is:

[0142] |ΔP (n) -ΔP (n-1) |<∈ P ,|T (n) -T (n-1) |<∈ T

[0143] If the condition is satisfied, the iteration terminates; otherwise, continue the iteration. Extract the stable inertial drag coefficient and viscous drag coefficient from the final iteration results as the flow and heat transfer characteristic parameters of the porous medium under the given conditions, and conduct verification and analysis.

[0144] S140. Based on the reduced-order one-dimensional N-S equation, a flow and heat transfer analysis model is constructed by combining the physical properties of the steam table.

[0145] Based on the reduced-order one-dimensional Navier-Stokes equations and combined with the physical properties of the steam table, a flow and heat transfer analysis model is constructed. The reduced-order one-dimensional Navier-Stokes equations include the continuity equation and the simplified momentum equation. The flow in the porous medium is treated in a volume-averaged manner according to the mass conservation, and the expression of the continuity equation is obtained as follows:

[0146]

[0147] where ε is the porosity of the porous medium, ρ f is the fluid density, and u is the velocity in the x direction. The continuity equation describes the mass conservation of the fluid in the porous medium. It ensures the mass balance between the inflow and outflow of the fluid.

[0148] Under one-dimensional steady-state conditions, the time derivative term is removed from the momentum equation, and the expression of the simplified momentum equation is obtained as follows:

[0149]

[0150] where P is the pressure distribution, g is the acceleration due to gravity, μ is the fluid viscosity, α is the permeability, C2 is the inertial resistance coefficient, ρ f is the fluid density, and u is the velocity in the x direction. The momentum equation describes the momentum conservation of the fluid in the porous medium, including the effects of external forces and resistances on the flow.

[0151] Assuming that the fluid and solid temperatures are equal, the energy equation is expressed as:

[0152]

[0153] where ε is the porosity, the ratio of the volume of the fluid in the porous medium to the total volume, ρ f is the fluid density, representing the mass of the fluid per unit volume, which usually varies with temperature and pressure, h t is the fluid static enthalpy, representing the specific enthalpy of the fluid in the thermodynamic state, used to describe the energy of the fluid, u is the velocity of the fluid in the x direction, representing the flow rate of the fluid, k eff is the equivalent thermal conductivity, comprehensively considering the thermal conductivities of the solid and fluid in the porous medium, used to characterize the heat conduction ability, T is the temperature, describing the thermodynamic state of the fluid and solid under local thermal equilibrium conditions, q is the sidewall heating power, the heating power per unit area, representing the heat source provided by the outside, L is the length of the porous medium, A is the cross-sectional area of the porous medium, representing the effective area of the flow channel of the porous medium, G is the mass flow rate per unit area, representing the mass flow rate of the fluid through the cross-sectional area per unit time. S g is the fluid energy source term, used to describe the external energy input or the internal heat source. This equation is simplified under the assumption of local thermal equilibrium, and only one energy equation is needed to describe the temperature changes of the fluid and solid, used to calculate the temperature distribution and heat transfer performance.

[0154] Based on the temperature difference between the fluid and the solid, the energy equation corresponds to the fluid energy equation and the solid energy equation. The fluid energy equation is expressed as follows:

[0155]

[0156] where T f is the fluid temperature, representing the thermodynamic state of the fluid in the porous medium, Ts is the solid temperature, representing the thermodynamic state of the solid skeleton, h v is the volumetric convective heat transfer coefficient, characterizing the heat exchange ability between the fluid and the solid, g is the acceleration due to gravity, used to describe the influence of the fluid in the gravitational field. In the local non-equilibrium model, the fluid energy equation describes the change of internal energy within the fluid and the heat exchange between the fluid and the solid.

[0157] The solid energy equation is expressed as follows:

[0158]

[0159] where ρ s is the solid density, representing the mass per unit volume of the solid skeleton, e s is the specific internal energy of the solid, describing the energy of the solid thermodynamic state, k s is the solid thermal conductivity, used to describe the ability of the solid to conduct heat, S se is the solid energy source term, used to describe the energy absorbed or generated by the solid. This equation is used to calculate the temperature distribution of the solid, especially in the case where there is a significant temperature difference between the solid and the fluid.

[0160] S150, substitute the drag coefficient and the equivalent thermal conductivity into the flow and heat transfer analysis model to predict the flow characteristics and heat transfer characteristics of the porous medium under different flow rates and pressures.

[0161] In a possible implementation, the drag coefficient and the equivalent thermal conductivity are substituted into the flow and heat transfer analysis model to predict the flow characteristics and heat transfer characteristics of the porous medium under different flow rates and pressure conditions, specifically including: obtaining input data, which includes the drag coefficient, the equivalent thermal conductivity, and fluid parameters; the boundary conditions of the equipment flow and heat transfer analysis model, where the boundary conditions include the flow rate range and the pressure range; selecting different ranges of flow rate, pressure, and heat flux density working conditions according to the actual application, dividing the entire analysis range into multiple sub-intervals, and each sub-interval corresponds to a preset pressure difference, flow velocity, and heat transfer condition; based on the influence of viscous resistance and inertial resistance on the flow, analyzing the flow characteristics of the fluid in the porous medium through the flow and heat transfer analysis model; using a one-dimensional reduced-order method to simplify the calculation process, calculating the changes in flow velocity, pressure, and temperature at the outlet point by point from the inlet, and in each step of the calculation, calling the physical property database (steam table) in real time according to the fluid state to adjust the physical properties of the fluid working medium, where the physical properties of the fluid working medium include density, viscosity, and thermal conductivity; obtaining the heat transfer characteristics of the fluid in the porous medium according to the calculation results; and outputting the flow characteristics and heat transfer characteristics of the porous medium.

[0162] Specifically, obtain the required input parameters from experiments or databases, including the drag coefficient, which is composed of the inertial drag coefficient and the viscous drag coefficient and reflects the pressure loss when the fluid flows in the porous medium; the equivalent thermal conductivity, which is calculated based on the thermal conductivities and porosities of the porous medium and the fluid and describes the comprehensive heat conduction ability between the fluid and the solid; fluid parameters: including fluid density, viscosity, specific heat capacity, initial temperature, and pressure, etc.

[0163] Set the boundary conditions of the model according to the research objectives, including setting the flow rate range, selecting the minimum and maximum flow rate values to define the operating range of the fluid flow; setting the pressure range, setting the pressure difference between the inlet and the outlet to reflect different flow conditions; setting the temperature or heat flux density, and determining the sidewall heat flux density or the wall temperature distribution according to the heating conditions. These boundary conditions are used as constraint conditions during the model calculation to ensure that the simulated conditions are consistent with the actual application.

[0164] Divide the entire flow and heat transfer analysis range into multiple sub-regions, and preset corresponding calculation conditions for each sub-region according to the pressure difference, flow velocity, and temperature change range. The basis for division is to densely divide the regions with a large pressure gradient and sparsely divide the regions with a small gradient; each sub-region corresponds to specific pressure difference, flow velocity, temperature, and heat transfer conditions for distributed calculation, thereby improving the calculation efficiency and accuracy of the model.

[0165] Using a flow and heat transfer analysis model, based on the effects of viscous resistance and inertial resistance, the flow characteristics of fluids in porous media are analyzed. Considering the flow resistance caused by fluid viscosity, which mainly acts in the low-speed region; and considering the inertial effect caused by the change in fluid velocity, which mainly acts in the high-speed region. The model calculates the velocity and pressure distributions of the fluid through the momentum equation, and analyzes the flow states under different flow rates and pressure conditions, including the characteristics of laminar flow, turbulent flow, and transitional regions.

[0166] Based on the reduced-order one-dimensional method, a three-dimensional problem is simplified to a one-dimensional problem along the flow direction. In the calculation process, starting from the inlet, the changes in fluid velocity, pressure, and temperature are calculated point by point until the outlet. In each step of the calculation, according to the fluid state (such as temperature and pressure), the physical property database (such as the IAPWS-IF97 water vapor table) is called in real time to adjust the physical properties of the fluid working medium, such as density, viscosity, and thermal conductivity. Through the reduced-order treatment, the calculation amount is greatly reduced while maintaining an accurate description of the changes in flow and heat transfer characteristics.

[0167] Under the assumption that the temperatures of the solid and the fluid are the same, the heat transfer amount and temperature distribution are calculated. Considering the temperature difference between the solid and the fluid, the temperature distributions of the solid and the fluid are calculated separately through the separated energy equation. Finally, the heat transfer coefficient, temperature distribution, and heat transfer efficiency are output, which are used to evaluate the heat transfer performance of the porous medium.

[0168] The calculation results are sorted out and output, including flow characteristics such as pressure distribution, velocity distribution, pressure loss, etc.; heat transfer characteristics such as temperature distribution, wall heat transfer coefficient, heat flux density distribution, etc. Through these results, the flow and heat transfer behaviors of the porous medium under different flow rates and pressure conditions can be predicted, providing a theoretical basis for design optimization or performance evaluation.

[0169] This embodiment also discloses a rapid analysis device for flow and boiling heat transfer based on porous media, referring to Figure 2 , the device includes an acquisition module 201, a processing module 202, and an output module 203, where:

[0170] The acquisition module 201 is used to obtain initial experimental data through an experimental device. The initial experimental data includes the along-channel pressure drop, wall temperature data, and inlet and outlet temperature data of the porous medium, as well as the fluid velocity and fluid viscosity of the fluid in the porous medium.

[0171] The processing module 202 is used to calculate the resistance coefficient of the porous medium based on the along-channel pressure drop, fluid velocity, and fluid viscosity. The resistance coefficient includes the inertial resistance coefficient and the viscous resistance coefficient.

[0172] The processing module 202 is used to calculate the equivalent thermal conductivity of the porous medium according to the wall temperature data and the inlet and outlet temperature data.

[0173] The processing module 202 is configured to construct a flow and heat transfer analysis model based on the reduced-order one-dimensional Navier-Stokes equations and in combination with the physical properties in the steam table.

[0174] The output module 203 is configured to substitute the resistance coefficient and the equivalent thermal conductivity into the flow and heat transfer analysis model to predict the flow characteristics and heat transfer characteristics of the porous medium under different flow rates and pressure conditions.

[0175] In a possible implementation manner, the processing module 202 is configured to solve using the one-dimensional reduced-order momentum equation and energy equation based on the initial experimental data and the initial assumed values of the porous medium material to obtain initial guess values.

[0176] The processing module 202 is configured to preliminarily calculate the preliminary pressure drop through the momentum equation using the inertial resistance coefficient and the viscous resistance coefficient of the initial guess values.

[0177] The processing module 202 is configured to assume local thermal equilibrium of the porous medium, calculate the equivalent thermal conductivity, and preliminarily solve the energy equation according to the temperature gradient to obtain the temperature distribution.

[0178] The processing module 202 is configured to correct the input parameters using an iterative algorithm based on the initial calculation results, wherein, based on the preliminary pressure drop and the temperature distribution, the inertial resistance coefficient and the viscous resistance coefficient are recalculated using a fitting formula, and the resistance term in the momentum equation is adjusted. For the local non-equilibrium model, there is heat exchange between the fluid and the solid, and the temperatures of the fluid and the solid need to be updated separately.

[0179] The processing module 202 is configured to determine whether the change amount of the pressure, or the change amount of the temperature, or the change amount of the resistance coefficient is less than a preset threshold value during two adjacent iterative processes.

[0180] The processing module 202 is configured to, if it is determined that the change amount of the pressure, or the change amount of the temperature, or the change amount of the resistance coefficient is less than a preset threshold value during two adjacent iterative processes, extract the resistance coefficient according to the calculation results.

[0181] In a possible implementation manner, the processing module 202 is configured to solve using the one-dimensional reduced-order momentum equation and energy equation based on the initial experimental data and the initial assumed values of the porous medium material and call the physical properties of the fluid working medium in real time in combination with the steam table to obtain initial guess values, wherein the momentum equation is expressed as follows:

[0182]

[0183] Wherein, ρ f is the fluid density, V is the fluid velocity of the fluid in the porous medium, ε is the porosity of the porous medium, t is the time, P is the pressure, τ is the stress tensor, g is the gravity, and S m is the resistance source term of the porous medium.

[0184] Among them, the energy equation is expressed as follows:

[0185]

[0186] Among them, ε is the porosity of the porous medium, h t is the fluid static enthalpy, u is the velocity in the x direction, T f is the fluid temperature, T s is the solid temperature, h v is the volume convective heat transfer coefficient.

[0187] In a possible implementation manner, the acquisition module 201 is configured to acquire input data, where the input data includes a drag coefficient, an equivalent thermal conductivity, and fluid parameters.

[0188] The processing module 202 is configured to set boundary conditions for the flow and heat transfer analysis model, where the boundary conditions include a flow rate range and a pressure range.

[0189] The processing module 202 is configured to select different ranges of flow rate, pressure, and heat flux density conditions according to actual applications, divide the entire analysis range into multiple sub-ranges, and each sub-range corresponds to a preset pressure difference, flow velocity, and heat transfer condition.

[0190] The processing module 202 is configured to analyze the flow characteristics of the fluid in the porous medium through the flow and heat transfer analysis model based on the effects of viscous drag and inertial drag on the flow.

[0191] The processing module 202 is configured to simplify the calculation process by using a one-dimensional reduced-order method, calculate the changes in flow velocity, pressure, and temperature at the outlet point by point from the inlet, and in each step of the calculation, call the steam table in real time according to the fluid state to adjust the physical properties of the fluid working medium.

[0192] The processing module 202 is configured to obtain the heat transfer characteristics of the fluid in the porous medium according to the calculation results.

[0193] The output module 203 is configured to output the flow characteristics and heat transfer characteristics of the porous medium.

[0194] In a possible implementation manner, the processing module 202 is configured to calculate the drag coefficient of the porous medium based on the pressure drop along the way, the fluid flow velocity, and the fluid viscosity, where the calculation principle of the drag coefficient is as follows:

[0195]

[0196] Among them, ΔP is the pressure drop along the way, V is the fluid flow velocity, L is the length of the porous medium, μ m is the fluid viscosity, ρ m is the fluid density, C2 is the inertial drag coefficient, and a is the viscous drag coefficient.

[0197] In a possible implementation, the processing module 202 is configured to calculate the equivalent thermal conductivity of the porous medium according to the wall temperature data and the inlet and outlet temperature data, specifically including:

[0198] The processing module 202 is configured to directly convert and calculate the equivalent thermal conductivity according to the temperature distribution of the inlet and outlet fluids and the wall surface under steady state conditions, specifically calculated by the following formula:

[0199]

[0200] Where, t in is the inlet fluid temperature, t out is the outlet fluid temperature, k eff is the equivalent thermal conductivity, t w-mean is the average temperature of the pipe wall surface, and q is the side wall heating power.

[0201] In a possible implementation, the processing module 202 is configured to process the flow in the porous medium in a volume-averaged manner according to the mass conservation, and obtain the continuity equation expression as follows:

[0202]

[0203] Where, ε is the porosity of the porous medium, ρ f is the fluid density, and u is the velocity in the x direction.

[0204] The processing module 202 is configured to remove the time derivative term from the momentum equation under one-dimensional steady state conditions, and obtain the simplified momentum equation expression as follows:

[0205]

[0206] Where, P is the pressure distribution, g is the acceleration due to gravity, μ is the fluid viscosity, α is the permeability, C2 is the inertial resistance coefficient, ρ f is the fluid density, and u is the velocity in the x direction.

[0207] It should be noted that: when the device provided in the above embodiment realizes its functions, only the above-mentioned division of each functional module is used for illustration. In actual application, the above functions can be allocated to different functional modules according to needs, that is, the internal structure of the device is divided into different functional modules to complete all or part of the functions described above. In addition, the device and method embodiments provided in the above embodiments belong to the same concept, and the specific implementation process can be found in the method embodiment, which will not be elaborated here.

[0208] This embodiment also discloses an electronic device, refer to Figure 3, the electronic device may include: at least one processor 401, at least one communication bus 402, a user interface 403, a network interface 404, and at least one memory 405.

[0209] Among them, the communication bus 402 is used to realize the connection and communication between these components.

[0210] Among them, the user interface 403 may include a display screen (Display) and a camera (Camera). Optionally, the user interface 403 may further include a standard wired interface and a wireless interface.

[0211] Among them, the network interface 404 may optionally include a standard wired interface and a wireless interface (such as a WI-FI interface).

[0212] Among them, the processor 401 may include one or more processing cores. The processor 401 uses various interfaces and circuits to connect various parts within the entire server. By running or executing instructions, programs, code sets, or instruction sets stored in the memory 405, and by calling data stored in the memory 405, it performs various functions of the server and processes data. Optionally, the processor 401 may be implemented in at least one hardware form of digital signal processing (DSP), field-programmable gate array (FPGA), or programmable logic array (PLA). The processor 401 may integrate a combination of one or more of a central processing unit (CPU), a graphics processing unit (GPU), and a modem, etc. Among them, the CPU mainly processes the operating system, user interface, and application programs, etc.; the GPU is responsible for the rendering and drawing of the content to be displayed on the display screen; the modem is used to process wireless communication. It can be understood that the above modem may not be integrated into the processor 401 and may be implemented separately by a single chip.

[0213] Among them, the memory 405 may include a Random Access Memory (RAM), or may also include a Read-Only Memory. Optionally, the memory includes a non-transitory computer-readable storage medium. The memory 405 can be used to store instructions, programs, codes, code sets, or instruction sets. The memory 405 may include a program storage area and a data storage area. Among them, the program storage area can store instructions for implementing the operating system, instructions for at least one function (such as touch function, sound playback function, image playback function, etc.), instructions for implementing the above-mentioned method embodiments, etc.; the data storage area can store the data involved in the above-mentioned method embodiments. The memory 405 may optionally also be at least one storage device located far from the aforementioned processor 401. The memory 405, as a computer storage medium, may include an operating system, a network communication module, a user interface 403 module, and an application program for a rapid analysis method of flow and boiling heat transfer based on porous media.

[0214] In Figure 4 In the electronic device shown, the user interface 403 is mainly used to provide an input interface for the user to obtain the data input by the user; and the processor 401 can be used to call the application program for a rapid analysis method of flow and boiling heat transfer based on porous media stored in the memory 405. When executed by one or more processors 401, the electronic device is caused to execute the method as described in one or more of the above embodiments.

[0215] It should be noted that for the foregoing method embodiments, for the sake of simple description, they are all expressed as a series of action combinations. However, those skilled in the art should know that this application is not limited by the described action sequence, because according to this application, certain steps can be performed in other sequences or simultaneously. Secondly, those skilled in the art should also know that the embodiments described in the specification are all preferred embodiments, and the actions and modules involved are not necessarily required by this application.

[0216] In the above embodiments, the descriptions of the various embodiments have their own emphases. For the parts not detailed in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0217] In several embodiments provided by the present application, it should be understood that the disclosed device can be implemented in other ways. For example, the device embodiments described above are merely illustrative. For example, the division of units is only a logical function division. In actual implementation, there may be other division methods. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the displayed or discussed coupling, direct coupling, or communication connection between each other can be through some service interfaces. The indirect coupling or communication connection of devices or units can be in electrical or other forms.

[0218] The units described as separate components may or may not be physically separated. The components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed to multiple network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0219] In addition, in each embodiment of the present application, each functional unit can be integrated in a processing unit, or each unit can exist physically alone, or two or more units can be integrated in one unit. The above-mentioned integrated units can be implemented in the form of hardware or in the form of software functional units.

[0220] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable memory. Based on such an understanding, the technical solution of the present application, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a memory 405 and includes several instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods in each embodiment of the present application. And the aforementioned memory 405 includes: various media such as USB flash drives, mobile hard disks, magnetic disks, or optical discs that can store program codes.

[0221] The present application also discloses a computer-readable storage medium that stores instructions. When executed by one or more processors 401, it causes the electronic device to execute the method as described in one or more of the above embodiments.

[0222] The above are only exemplary embodiments of the present disclosure, and the scope of the present disclosure cannot be limited thereby. That is, any equivalent changes and modifications made in accordance with the teachings of the present disclosure still fall within the scope covered by the present disclosure. After considering the specification and the disclosure of the practical truth, those skilled in the art will easily think of other implementation schemes of the present disclosure. This application is intended to cover any variations, uses or adaptive changes of the present disclosure, and these variations, uses or adaptive changes follow the general principles of the present disclosure and include the common general knowledge or conventional technical means in the technical field not recorded in the present disclosure. The specification and the embodiments are only regarded as exemplary, and the scope and spirit of the present disclosure are defined by the claims.

Claims

1. A rapid analysis method for flow and boiling heat transfer based on porous media, characterized in that, The method includes: Obtaining initial experimental data through an experimental device, where the initial experimental data includes the along - the - path pressure drop of the porous medium, wall temperature data and inlet - outlet temperature data, as well as the fluid velocity and fluid viscosity of the fluid within the porous medium; Calculating the resistance coefficient of the porous medium based on the along - the - path pressure drop, the fluid velocity, and the fluid viscosity, where the resistance coefficient includes an inertial resistance coefficient and a viscous resistance coefficient; Calculating the equivalent thermal conductivity of the porous medium according to the wall temperature data and the inlet - outlet temperature data; Constructing a flow and heat transfer analysis model based on the reduced - order one - dimensional N - S equation and combining the physical properties of the water vapor table; Substituting the resistance coefficient and the equivalent thermal conductivity into the flow and heat transfer analysis model to predict the flow characteristics and heat transfer characteristics of the porous medium under different flow rate and pressure conditions.

2. The rapid analysis method for flow and boiling heat transfer based on porous media according to claim 1, wherein, The calculating the resistance coefficient of the porous medium based on the along - the - path pressure drop, the fluid velocity, and the fluid viscosity specifically includes: Based on the initial experimental data and the initial assumed values of the porous medium material, using the one - dimensional reduced - order momentum equation and energy equation for solution to obtain an initial guess value; Using the inertial resistance coefficient and viscous resistance coefficient of the initial guess value to preliminarily calculate the preliminary pressure drop through the momentum equation; Assuming local thermal equilibrium of the porous medium, calculating the equivalent thermal conductivity, and preliminarily solving the energy equation according to the temperature gradient to obtain the temperature distribution; Based on the initial calculation results, using an iterative algorithm to correct the input parameters. Among them, based on the preliminary pressure drop and the temperature distribution, using a fitting formula to recalculate the inertial resistance coefficient and viscous resistance coefficient, adjusting the resistance term in the momentum equation. For the local non - equilibrium model, there is heat exchange between the fluid and the solid, and the fluid and solid temperatures need to be updated separately; Judging whether the change in pressure, or the change in temperature, or the change in the resistance coefficient in two adjacent iterative processes is less than a preset threshold; If it is determined that in two adjacent iterative processes, the change in pressure, or the change in temperature, or the change in the resistance coefficient is less than the preset threshold, then extracting the resistance coefficient according to the calculation results.

3. A rapid analysis method for flow and boiling heat transfer based on porous media according to claim 2, characterized in that, Based on the initial experimental data and the initial assumed values of the porous medium material, using the one - dimensional reduced - order momentum equation and energy equation for solution and combining the real - time call of the physical properties of the fluid working medium with the water vapor table to obtain an initial guess value, where the momentum equation is expressed as follows: where ρ f is the fluid density, V is the fluid velocity of the fluid in the porous medium, ε is the porosity of the porous medium, t is time, P is pressure, τ is the stress tensor, g is gravity, and S m is the resistance source term of the porous medium; Wherein, the energy equation is expressed as follows: where ε is the porosity of the porous medium, h t is the hydrostatic enthalpy, u is the velocity in the x direction, T f is the fluid temperature, T s is the solid temperature, h v is the volumetric convective heat transfer coefficient.

4. A rapid analysis method for flow and boiling heat transfer based on porous media according to claim 1, characterized in that, The substituting the resistance coefficient and the equivalent thermal conductivity into the flow and heat transfer analysis model to predict the flow characteristics and heat transfer characteristics of the porous medium under different flow rate and pressure conditions specifically includes: Obtaining input data, where the input data includes the resistance coefficient, the equivalent thermal conductivity, and fluid parameters; Setting the boundary conditions of the flow and heat transfer analysis model, where the boundary conditions include the flow rate range and the pressure range; Selecting different flow rate, pressure, and heat flux density working condition ranges according to the actual application, dividing the entire analysis range into multiple sub - intervals, and each sub - interval corresponds to a preset pressure difference, flow velocity, and heat transfer condition; Based on the influence of viscous resistance and inertial resistance on the flow, analyze the flow characteristics of the fluid in the porous medium through the flow and heat transfer analysis model; Use the one-dimensional reduction method to simplify the calculation process, calculate the changes in fluid velocity, pressure, and temperature at the outlet point by point from the inlet. In each step of the calculation, call the steam table in real time according to the fluid state to adjust the physical properties of the fluid working medium; Obtain the heat transfer characteristics of the fluid in the porous medium according to the calculation results; Output the flow characteristics and heat transfer characteristics of the porous medium.

5. A rapid analysis method for flow and boiling heat transfer based on porous media according to claim 1, characterized in that Calculate the resistance coefficient of the porous medium based on the along-channel pressure drop, the fluid velocity, and the fluid viscosity. The calculation principle of the resistance coefficient is as follows: where ΔP is the frictional pressure drop, V is the fluid velocity, L is the length of the porous medium, μ m is the fluid viscosity, ρ m is the fluid density, C2 is the inertial resistance coefficient, and a is the viscous resistance coefficient.

6. A rapid analysis method for flow and boiling heat transfer based on porous media according to claim 1, characterized in that Calculate the equivalent thermal conductivity of the porous medium according to the wall temperature data and the inlet and outlet temperature data, specifically including: According to the temperature distribution of the inlet and outlet fluids and the wall temperature under the steady state, directly convert the equivalent thermal conductivity, which is specifically calculated by the following formula: where t in is the inlet fluid temperature, t out is the outlet fluid temperature, k eff is the equivalent thermal conductivity, t w-mean is the average temperature of the pipe wall, and q is the heating power of the side wall.

7. A rapid analysis method for flow and boiling heat transfer based on porous media according to claim 1, characterized in that, The reduced-order one-dimensional N-S equation includes the continuity equation and the simplified momentum equation. Based on the reduced-order one-dimensional N-S equation, a flow and heat transfer analysis model is constructed in combination with the physical properties of the steam table, specifically including: Treat the flow in the porous medium in a volume-averaged manner according to mass conservation to obtain the following expression of the continuity equation: where ε is the porosity of the porous medium, ρ f is the fluid density, and u is the velocity in the x direction; Under the one-dimensional steady-state condition, remove the time derivative term from the momentum equation to obtain the following expression of the simplified momentum equation: where P is the pressure distribution, g is the acceleration due to gravity, μ is the fluid viscosity, α is the permeability, C2 is the inertial resistance coefficient, ρ f is the fluid density, and u is the velocity in the x direction.

8. A rapid analysis device for flow and boiling heat transfer based on porous media, characterized in that, The device includes an acquisition module (301), a processing module (302), and an output module (303), where: The acquisition module (301) is used to obtain initial experimental data through an experimental device. The initial experimental data includes the along-channel pressure drop, wall temperature data, and inlet and outlet temperature data of the porous medium, as well as the fluid velocity and fluid viscosity of the fluid in the porous medium; The processing module (302) is used to calculate the resistance coefficient of the porous medium based on the along-channel pressure drop, the fluid velocity, and the fluid viscosity. The resistance coefficient includes the inertial resistance coefficient and the viscous resistance coefficient; The processing module (302) is used to calculate the equivalent thermal conductivity of the porous medium according to the wall temperature data and the inlet and outlet temperature data; The processing module (302) is used to construct a flow and heat transfer analysis model based on the reduced-order one-dimensional N-S equation in combination with the physical properties of the steam table; The output module (303) is used to substitute the resistance coefficient and the equivalent thermal conductivity into the flow and heat transfer analysis model to predict the flow characteristics and heat transfer characteristics of the porous medium under different flow rates and pressure conditions.

9. An electronic device, characterized in that, It includes a processor (401), a communication bus (402), a user interface (403), a network interface (404), and a memory (405). The memory (405) is used to store instructions. Both the user interface (403) and the network interface (404) are used to communicate with other devices. The communication bus (402) is used to realize the connection and communication between components within the electronic device. The processor (401) is used to execute the instructions stored in the memory (405) so that the electronic device executes the method according to any one of claims 1-7.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores instructions which, when executed, perform the method according to any one of claims 1-7.

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