Adsorption refrigeration performance evaluation method and related equipment

Abstract

The embodiment of the invention provides an adsorption refrigeration performance evaluation method and related equipment, and belongs to the technical field of heat pumps. The method comprises the following steps: obtaining a plurality of core structure parameters of the metal organic framework material through molecular simulation; the equilibrium adsorption isotherm and the adsorption enthalpy of each metal organic framework material are predicted through Monte Carlo simulation; performing molecular dynamics simulation to obtain a diffusion coefficient, a heat conductivity coefficient and a permeability equation of each metal organic framework material; constructing a plurality of metal organic framework material models, and setting parameters of the metal organic framework material models; and the parameter files of the multiple metal organic framework materials are input into the corresponding metal organic framework material models, the metal organic framework material models are called to output real-time data, and the refrigerating performance coefficient and the specific refrigerating capacity are calculated based on the real-time data. According to the embodiment of the invention, rapid evaluation and accurate prediction of the adsorption performance of the large-scale metal organic framework material can be realized.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of heat pumps, in particular to an adsorption refrigeration performance evaluation method and related equipment. BACKGROUND

[0002] In the related art, according to statistics, more than ten thousand kinds of MOFs materials (metal organic framework materials) have been synthesized. If the performance of each MOF and refrigerant pair is tested by using the traditional experimental method, it is not only high in cost, time-consuming and laborious, but also almost impossible to realize in actual operation.

[0003] In summary, the technical problems existing in the related art need to be improved. SUMMARY

[0004] The main purpose of the embodiments of the present application is to provide an adsorption refrigeration performance evaluation method and related equipment to realize rapid evaluation and accurate prediction of the adsorption performance of large-scale metal organic framework materials.

[0005] To achieve the above-mentioned purpose, one aspect of the embodiments of the present application provides an adsorption refrigeration performance evaluation method, which comprises: Obtaining core structure parameters of a plurality of metal organic framework materials from a metal organic framework material database based on molecular simulation, wherein the core structure parameters include density and restricted pore diameter; Predicting the equilibrium adsorption isotherm and adsorption enthalpy of each metal organic framework material by Monte Carlo simulation; Performing molecular dynamics simulation based on the restricted pore diameter to obtain the diffusion coefficient, thermal conductivity coefficient and permeability equation of each metal organic framework material; Constructing a plurality of metal organic framework material models, and setting parameters of the metal organic framework material models by using the equilibrium adsorption isotherm, the adsorption enthalpy, the diffusion coefficient, the thermal conductivity coefficient and the permeability equation; Inputting the parameter files of a plurality of metal organic framework materials into the corresponding metal organic framework material models, calling the metal organic framework material models to output real-time data, and calculating the refrigeration performance coefficient and specific refrigeration capacity based on the real-time data, wherein the real-time data includes temperature field distribution in the adsorption bed, ethanol concentration field change, adsorption rate dynamic curve and instantaneous adsorption amount data.

[0006] In some embodiments, the method further comprises: Performing multi-physical field coupling setting and boundary condition setting; Performing mesh division setting; Performing solver setting.

[0007] In some embodiments, the mesh division setting comprises: In the grid module of the metal organic framework material model, a free triangular grid is selected; A coarse grid, a fine grid and a very fine grid are generated through the free triangular grid; Transient calculation is performed on the same metal organic framework material through the coarse grid, the fine grid and the very fine grid respectively, and transient calculation results are obtained; The target grid of the free triangular grid is determined based on the transient calculation results.

[0008] In some embodiments, the metal organic framework material model is constructed, and the parameter setting of the metal organic framework material model is performed through the equilibrium adsorption isotherm, the adsorption enthalpy, the diffusion coefficient, the thermal conductivity coefficient and the permeability equation, including: Obtain the aluminum pipe size parameter, the heat flow channel size parameter and the metal organic framework material size parameter input by the user; Based on the aluminum pipe size parameter, the heat flow channel size parameter and the metal organic framework material size parameter, a metal organic framework material model is constructed, the metal organic framework material model adopts a three-dimensional adsorption pipe model, the three-dimensional adsorption pipe model includes an aluminum pipe, a pipe heat flow, an adsorbent and an adsorbate, and the adsorbent adopts the metal organic framework material.

[0009] In some embodiments, the metal organic framework material model is constructed, and the parameter setting of the metal organic framework material model is performed through the equilibrium adsorption isotherm, the adsorption enthalpy, the diffusion coefficient, the thermal conductivity coefficient and the permeability equation, further including: Determine the type of pipe heat flow, and obtain the heat flow material parameter corresponding to the type of pipe heat flow; Obtain the aluminum pipe material parameter; Obtain the constant pressure heat capacity of the metal organic framework material, and construct the metal organic framework material parameter through the constant pressure heat capacity, the density of the metal organic framework material, the thermal conductivity coefficient of the metal organic framework material and the permeability equation of the metal organic framework material; Determine the type of working fluid, and obtain the fluid material parameter corresponding to the type of working fluid; Apply the heat flow material parameter, the aluminum pipe material parameter, the metal organic framework material parameter and the fluid material parameter through the three-dimensional adsorption pipe model.

[0010] In some embodiments, the solver setting is performed, including: Add a transient study in a solver, the solver is used to execute the transient study, and the transient study is used to call the metal organic framework material model to output real-time data; The time range, output time step, relative tolerance, and absolute tolerance of the transient study are set.

[0011] To achieve the above object, another aspect of the embodiments of the present application provides an adsorption refrigeration performance evaluation device, which comprises: The parameter acquisition module is configured to obtain core structure parameters of a plurality of metal-organic framework materials based on a metal-organic framework material database through molecular simulation, wherein the core structure parameters include density and restricted pore diameter; The Monte Carlo simulation module is configured to predict an equilibrium adsorption isotherm and an adsorption enthalpy of each of the metal-organic framework materials through Monte Carlo simulation; The molecular dynamics simulation module is configured to perform molecular dynamics simulation based on the restricted pore diameter to obtain a diffusion coefficient, a thermal conductivity coefficient, and a permeability equation of each of the metal-organic framework materials; The model construction module is configured to construct a plurality of metal-organic framework material models, and perform parameter setting of the metal-organic framework material models through the equilibrium adsorption isotherm, the adsorption enthalpy, the diffusion coefficient, the thermal conductivity coefficient, and the permeability equation; The evaluation module is configured to input parameter files of a plurality of metal-organic framework materials into corresponding metal-organic framework material models, call the metal-organic framework material models to output real-time data, and calculate a refrigeration performance coefficient and a specific refrigeration capacity based on the real-time data, wherein the real-time data includes an adsorption bed temperature field distribution, an ethanol concentration field change, an adsorption rate dynamic curve, and instantaneous adsorption amount data.

[0012] To achieve the above object, another aspect of the embodiments of the present application provides an electronic device, which comprises a memory and a processor, wherein the memory stores a computer program, and the processor implements the above method when executing the computer program.

[0013] To achieve the above object, another aspect of the embodiments of the present application provides a computer readable storage medium, which stores a computer program, and the computer program implements the above method when executed by a processor.

[0014] To achieve the above object, another aspect of the embodiments of the present application provides a computer program product, which comprises a computer program, and the computer program implements the above method when executed by a processor.

[0015] The embodiments of the present application at least have the following beneficial effects: The present application provides an adsorption refrigeration performance evaluation method, device, electronic equipment, storage medium and program product. The scheme obtains core structure parameters of a plurality of metal organic framework materials based on a metal organic framework material database through molecular simulation; predicts the equilibrium adsorption isotherm and adsorption enthalpy of each metal organic framework material through Monte Carlo simulation; performs molecular dynamics simulation based on the restricted pore diameter to obtain the diffusion coefficient, thermal conductivity coefficient and permeability equation of each metal organic framework material; constructs a plurality of metal organic framework material models, and sets parameters of the metal organic framework material models through the equilibrium adsorption isotherm, adsorption enthalpy, diffusion coefficient, thermal conductivity coefficient and permeability equation; inputs the parameter files of the plurality of metal organic framework materials into the corresponding metal organic framework material models, calls the metal organic framework material models to output real-time data, calculates the refrigeration performance coefficient and specific refrigeration capacity based on the real-time data, and realizes rapid evaluation and accurate prediction of the adsorption performance of large-scale metal organic framework materials. Through the cooperative calculation of the multi-scale models, the real-time data of the adsorbent adsorption process can be effectively obtained, the core performance indicators such as the refrigeration performance coefficient and specific refrigeration capacity of the adsorption heat pump are processed, and efficient screening of the metal organic framework materials is realized. BRIEF DESCRIPTION OF DRAWINGS

[0016] Figure 1 is a flowchart of the adsorption refrigeration performance evaluation method provided by the embodiments of the present application; Figure 2 is a flowchart of the model setting step of the adsorption refrigeration performance evaluation method provided by the embodiments of the present application; Figure 3 is a flowchart of step S104 in Figure 1 Figure 4 is a flowchart of step S201 in Figure 2 Figure 5 is a specific implementation flowchart when the adsorption refrigeration performance evaluation method provided by the embodiments of the present application is applied to a multi-scale coupling system for evaluating the heat pump performance of a MOFs working medium pair; Figure 6 is a schematic diagram of a MOFs working medium pair heat pump provided by the embodiments of the present application; Figure 7 is a structural schematic diagram of the adsorption refrigeration performance evaluation device provided by the embodiments of the present application; Figure 8 is a hardware structure schematic diagram of the electronic equipment provided by the embodiments of the present application. DETAILED DESCRIPTION

[0017] ​​In order to make the purposes, technical solutions, and advantages of the present application clearer, the present application will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only intended to explain the present application and are not intended to limit the present application. When the following description refers to the accompanying drawings, identical numbers in different drawings represent identical or similar elements unless otherwise indicated. The implementations described in the following exemplary embodiments do not represent all implementations consistent with embodiments of the present application, but are merely examples of apparatuses and methods consistent with some aspects of the embodiments of the present application as detailed in the appended claims.

[0018] It can be understood that the terms “first”, “second”, and the like used in the present application can be used herein to describe various concepts, but unless specifically stated, these concepts are not limited by these terms. These terms are only used to distinguish one concept from another. For example, without departing from the scope of the embodiments of the present application, the first information can also be referred to as the second information, and similarly, the second information can also be referred to as the first information. Depending on the context, the word “if” as used herein can be interpreted as “when” or “upon” or “in response to a determination”.

[0019] The terms “at least one”, “multiple”, “each”, “any”, and the like used in the present application include one, two, or more than two, multiple includes two or more than two, each refers to each of the corresponding multiple, and any refers to any one of the multiple.

[0020] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which the present application belongs. The terms used herein are only for the purpose of describing the embodiments of the present application and are not intended to limit the present application.

[0021] Before the embodiments of the present application are described in detail, first, some nouns and terms involved in the embodiments of the present application are described, and the nouns and terms involved in the embodiments of the present application are applicable to the following explanations.

[0022] 1) MOFs (Metal-Organic Frameworks), a class of porous materials assembled by metal ions or metal clusters and organic ligands through coordination.

[0023] 2) COMSOL Multiphysics, a powerful simulation software platform for modeling and simulation of multi-physical field problems. COMSOL Multiphysics allows users to perform coupled simulations between multiple physical domains such as fluid mechanics, heat conduction, electromagnetism, structural mechanics, chemical reactions, etc. COMSOL is widely used in engineering, scientific research, and industrial fields.

[0024] 3) Lennard-Jones potential, a classical mathematical model used to describe the interaction forces between molecules or atoms, particularly at close distances.

[0025] 4) Darcy's Law, one of the fundamental laws describing the flow of fluids in porous media, used to describe the flow of water or other fluids through porous media such as soil, rock, etc.

[0026] 5) Coefficient of Performance (COP), a dimensionless parameter used to measure the efficiency of a refrigeration system or heat pump. The COP represents the amount of refrigeration (or heating) produced per unit of power consumption. The higher the COP, the better the refrigeration (or heating) effect and the higher the energy efficiency of the device.

[0027] 6) Specific Cooling Power (SCP), the refrigeration capacity per unit mass, which represents the refrigeration effect per unit mass.

[0028] In related technologies, according to statistics, more than ten thousand kinds of MOFs (Metal-Organic Frameworks) materials have been synthesized. If the traditional experimental method is used to test the performance of each MOF and refrigerant working pair, not only the cost is high, time-consuming and laborious, but also it is almost impossible to realize in actual operation.

[0029] In summary, the technical problems in related technologies need to be improved.

[0030] In view of this, the application provides an adsorption refrigeration performance evaluation method and related equipment. The scheme obtains core structure parameters of a plurality of metal organic framework materials based on a metal organic framework material database through molecular simulation; predicts the equilibrium adsorption isotherm and adsorption enthalpy of each metal organic framework material through Monte Carlo simulation; performs molecular dynamics simulation based on the restricted pore diameter to obtain the diffusion coefficient, thermal conductivity coefficient, and permeability equation of each metal organic framework material; constructs a plurality of metal organic framework material models, and sets the parameters of the metal organic framework material models through the equilibrium adsorption isotherm, adsorption enthalpy, diffusion coefficient, thermal conductivity coefficient, and permeability equation; inputs the parameter files of the plurality of metal organic framework materials into the corresponding metal organic framework material models, calls the metal organic framework material models to output real-time data, calculates the refrigeration performance coefficient and specific refrigeration capacity based on the real-time data, and realizes rapid evaluation and accurate prediction of the adsorption performance of large-scale metal organic framework materials. Through the collaborative calculation of multi-scale models, real-time data of the adsorption process of the adsorbent can be effectively obtained, core performance indicators such as the refrigeration performance coefficient and specific refrigeration capacity of the adsorption heat pump are processed, and efficient screening of metal organic framework materials is realized.

[0031] The adsorption refrigeration performance evaluation method provided in the application is related to the technical field of heat pumps. The adsorption refrigeration performance evaluation method provided in the application can be applied to a terminal, can also be applied to a server, and can be software running in a terminal or a server. In some embodiments, the terminal can be a smart phone, a tablet computer, a notebook computer, a desktop computer, a smart speaker, a smart watch, a vehicle-mounted terminal, and the like, but is not limited thereto; the server end can be configured as a standalone physical server, can also be configured as a server cluster or a distributed system composed of multiple physical servers, can also be configured as a cloud server providing basic cloud computing services such as cloud service, cloud database, cloud computing, cloud function, cloud storage, network service, cloud communication, middleware service, domain name service, security service, CDN, and big data and artificial intelligence platform, and the server can also be a node server in a blockchain network; the software can be an application that implements the adsorption refrigeration performance evaluation method, and the like, but is not limited to the above forms.

[0032] The application is operable in a variety of general purpose or special purpose computer systems environments or configurations. Examples of well-known computing systems, environments, and / or configurations that can be suitable for use with the application include personal computers, server computers, handheld or laptop devices, tablet devices, multiprocessor systems, microprocessor-based systems, set top boxes, programmable consumer electronics, network PCs, minicomputers, mainframe computers, distributed computing environments that include any of the above systems or devices, and the like. The application can be described in the general context of computer-executable instructions, such as program modules, being executed by a computer. Generally, program modules include routines, programs, objects, components, data structures, and the like, that perform particular tasks or implement particular abstract data types. The application can also be practiced in distributed computing environments where tasks are performed by remote processing devices that are linked through a communications network. In a distributed computing environment, program modules can be located in both local and remote computer storage media including memory storage devices.

[0033] It should be noted that in each specific embodiment of the present application, when it is necessary to perform relevant processing according to user information, user behavior data, user history data, and user location information, and other data related to the identity or characteristics of the user, the user's permission or consent will be obtained first, and the collection, use, and processing of these data will comply with relevant laws, regulations, and standards. In addition, when the embodiments of the present application need to obtain sensitive personal information of the user, the separate permission or separate consent of the user will be obtained through a pop-up window or by jumping to a confirmation page, and after obtaining the separate permission or separate consent of the user, the necessary user-related data for enabling the embodiments of the present application to function normally will be obtained.

[0034] Figure 1 is an optional flowchart of the adsorption refrigeration performance evaluation method provided by the embodiments of the present application, Figure 1 The method in can include but is not limited to steps S101 to S105.

[0035] Step S101: obtaining core structure parameters of a plurality of metal organic framework materials based on a metal organic framework material database through molecular simulation.

[0036] Specifically, the core structure parameters include density and restricted pore diameter.

[0037] In some embodiments, the structure characteristics, adsorption isotherms, and diffusion coefficients of MOFs are obtained through molecular simulation, and relevant thermodynamic parameters are provided for multi-physical field simulation.

[0038] Optionally, first screen the metal organic framework material database to determine the metal organic framework materials that cannot obtain performance. The CoRE MOF database consists of 2932 structures, of which 2476 structures cannot obtain reasonable adsorption performance, thermophysical performance or dynamic transport diffusion performance before screening. Therefore, the target metal organic framework material that cannot obtain reasonable adsorption performance, thermophysical performance or dynamic transport diffusion performance is determined by screening, and the core structure parameters of the 2476 metal organic framework material structures are obtained.

[0039] Among them, the MOFs structure characteristics include density, specific surface area, effective pore volume, maximum pore diameter and restricted pore diameter.

[0040] In this embodiment, the core structure parameters of a plurality of metal organic framework materials are obtained based on the metal organic framework material database through molecular simulation, which prepares for subsequent model construction.

[0041] In step S102, the equilibrium adsorption isotherm and adsorption enthalpy of each metal organic framework material are predicted by Monte Carlo simulation.

[0042] In some embodiments, the Monte Carlo simulation predicts the equilibrium adsorption isotherm, such as the adsorption amount and the adsorption enthalpy.

[0043] Among them, the Monte Carlo simulation needs the crystal structure file of the adsorbent, which can be downloaded from the CCDC structure database, and the molecular file of the adsorbate, which is built by the research team, and the force field parameter comes from the public literature. The required working condition parameters include temperature and pressure.

[0044] In this embodiment, the equilibrium adsorption isotherm and adsorption enthalpy of each metal organic framework material are predicted by Monte Carlo simulation, which prepares for the parameter setting of the subsequent metal organic framework material model.

[0045] In step S103, molecular dynamics simulation is performed based on the restricted pore diameter to obtain the diffusion coefficient, thermal conductivity coefficient and permeability equation of each metal organic framework material.

[0046] In some embodiments, the transport diffusion properties of ethanol in MOFs are evaluated by molecular dynamics simulation. The diffusion coefficient KLDF of ethanol in the pore channel of MOFs is calculated, and the "degree of change of concentration distribution" in the molecular diffusion process is taken as the input of Darcy's law.

[0047] Among them, the thermal conductivity coefficient of MOFs is calculated by molecular dynamics simulation.

[0048] In this embodiment, molecular dynamics simulation is performed based on the restricted pore diameter to obtain the diffusion coefficient, thermal conductivity coefficient and permeability equation of each metal organic framework material, which prepares for the parameter setting of the subsequent metal organic framework material model.

[0049] Step S104, a plurality of metal organic framework material models are constructed, and parameter setting of the metal organic framework material models is performed through balance adsorption isotherm, adsorption enthalpy, diffusion coefficient, thermal conductivity coefficient and permeability equation.

[0050] Optionally, a proportional three-dimensional adsorption tube model is constructed based on COMSOL Multiphysic software: a proportional three-dimensional adsorption tube model containing an aluminum tube, heat flow in the tube, adsorbent (MOFs) and adsorbate (ethanol) is constructed; a proportional two-dimensional axisymmetric geometric model is constructed by using the geometric module built in COMSOL.

[0051] Specifically, the two-dimensional axisymmetric model drawing includes: Open the COMSOL Multiphysic software, select the "two-dimensional axisymmetric" spatial dimension, and create a new project; in the geometric module, use the rectangular tool to draw three regions: Heat flow channel: coordinate range (r: 0-10mm, z: 0-1000mm), named "region 1"; Aluminum tube: coordinate range (r: 10-11mm, z: 0-1000mm), named "region 2"; Adsorbent layer: coordinate range (r: 11-13mm, z: 0-1000mm), named "region 3".

[0052] It can be understood that material parameter assignment is performed: in the material module, four materials of heat flow (water), aluminum tube, metal organic framework material and ethanol vapor are newly created, and are assigned based on the previous molecular simulation results and experimental data.

[0053] In some embodiments, aluminum tube size parameters, heat flow channel size parameters and metal organic framework material size parameters input by a user are obtained; a metal organic framework material model is constructed based on the aluminum tube size parameters, the heat flow channel size parameters and the metal organic framework material size parameters. The metal organic framework material model adopts a three-dimensional adsorption tube model, and the three-dimensional adsorption tube model includes an aluminum tube, heat flow in the tube, an adsorbent and an adsorbate, and the adsorbent adopts a metal organic framework material.

[0054] Further, the type of heat flow in the tube is determined, heat flow material parameters corresponding to the type of heat flow in the tube are obtained; aluminum tube material parameters are obtained; the constant pressure heat capacity of the metal organic framework material is obtained, and the metal organic framework material parameters are constructed through the constant pressure heat capacity, the density of the metal organic framework material, the thermal conductivity coefficient of the metal organic framework material and the permeability equation of the metal organic framework material; the type of working fluid is determined, and fluid material parameters corresponding to the type of working fluid are obtained; the heat flow material parameters, the aluminum tube material parameters, the metal organic framework material parameters and the fluid material parameters are applied through the three-dimensional adsorption tube model.

[0055] Optionally, multi-physical field coupling settings and boundary condition settings are performed; mesh division settings are performed; solver settings are performed.

[0056] In the embodiment, a plurality of metal organic framework material models are constructed, parameter settings of the metal organic framework material models are performed through balance adsorption isotherm, adsorption enthalpy, diffusion coefficient, thermal conductivity coefficient and permeability equation, and cross-scale correlation and quantitative analysis from “molecular adsorption mechanism → channel mass transfer behavior → macroscopic system performance” are realized.

[0057] In step S105, a plurality of parameter files of metal organic framework materials are input into corresponding metal organic framework material models, real-time data output by the metal organic framework material models is called, and refrigeration performance coefficient and specific refrigerating capacity are calculated based on the real-time data.

[0058] Specifically, the real-time data include temperature field distribution in the adsorption bed, ethanol concentration field change, adsorption rate dynamic curve and instantaneous adsorption amount data.

[0059] In some embodiments, parameterized scanning is set: in the research module, parameterized scanning is added, a specified combined scanning type is selected, parameter files (including adsorption isotherm parameters, adsorption enthalpy and diffusion coefficient) of 455 MOFs are imported, scanning parameters are set as MOF numbers (1-455), and it is ensured that each number corresponds to a complete set of parameters.

[0060] Further, by clicking to run the parameterized scanning, the system automatically calls the 455 MOFs in sequence, researches, calculates and outputs temperature field distribution in the adsorption bed, ethanol concentration field change, adsorption rate dynamic curve and instantaneous adsorption amount data, and calculates COP and SCP through derived values.

[0061] In the embodiment, a plurality of parameter files of metal organic framework materials are input into corresponding metal organic framework material models, real-time data output by the metal organic framework material models is called, and refrigeration performance coefficient and specific refrigerating capacity are calculated based on the real-time data, cross-scale correlation and quantitative analysis from “molecular adsorption mechanism → channel mass transfer behavior → macroscopic system performance” are realized, which is conducive to rapid evaluation and accurate prediction of adsorption performance of large-scale metal organic framework materials, and is conducive to efficient screening of MOF materials.

[0062] The steps S101 to S105 shown in the embodiments of the present application obtain core structure parameters of a plurality of metal organic framework materials based on a metal organic framework material database through molecular simulation; predict the equilibrium adsorption isotherm and the adsorption enthalpy of each metal organic framework material through Monte Carlo simulation; perform molecular dynamics simulation based on the restricted pore diameter to obtain the diffusion coefficient, the thermal conductivity coefficient and the permeability equation of each metal organic framework material; construct a plurality of metal organic framework material models, and perform parameter setting of the metal organic framework material models through the equilibrium adsorption isotherm, the adsorption enthalpy, the diffusion coefficient, the thermal conductivity coefficient and the permeability equation; input the parameter files of the plurality of metal organic framework materials into the corresponding metal organic framework material models, call the metal organic framework material models to output real-time data, calculate the coefficient of performance and the specific refrigeration capacity based on the real-time data, and realize rapid evaluation and accurate prediction of the adsorption performance of the large-scale metal organic framework material. Through the collaborative calculation of the multi-scale models, the real-time data of the adsorbent adsorption process can be effectively obtained, the core performance indicators such as the coefficient of performance and the specific refrigeration capacity of the adsorption heat pump are processed to obtain, and efficient screening of the metal organic framework material is realized.

[0063] Please refer to Figure 2 In some embodiments, the adsorption refrigeration performance evaluation method provided by the embodiments of the present application further includes a model setting step, which can include but is not limited to steps S201 to S203: Step S201, multi-physical field coupling setting and boundary condition setting.

[0064] In step S201 of some embodiments, the multi-physical field setting includes porous medium heat transfer, coefficient form partial differential equation, Darcy's law and fluid / solid heat transfer.

[0065] Among them, the fluid heat transfer interface is set; the solid heat transfer interface is set; the porous medium heat transfer interface is set; the Darcy's law interface is set; and the coefficient form partial differential equation interface is set.

[0066] Step S202, mesh division setting.

[0067] In step S202 of some embodiments, in the mesh module of the metal organic framework material model, a free triangular mesh is selected; a coarse mesh, a fine mesh and an extremely fine mesh are generated through the free triangular mesh; transient calculation is performed on the same metal organic framework material through the coarse mesh, the fine mesh and the extremely fine mesh respectively to obtain transient calculation results; and the target mesh of the free triangular mesh is determined based on the transient calculation results.

[0068] Specifically, in the mesh module, a free triangular mesh is selected, the unit size is set to fine, and after the mesh is generated, the number of meshes is about 120,000; to verify the independence of the mesh, three kinds of meshes, namely, coarse, fine and very fine meshes, are generated, and transient calculation is performed on the same MOFs, and the COP calculation results of the three kinds of meshes are compared.

[0069] For example, the difference between the calculation results of the fine and coarse meshes is less than 0.05, and the difference between the calculation results of the fine and very fine meshes is less than 0.01, so the fine mesh is used to reduce the running time.

[0070] Step S203, solver setting.

[0071] In step S203 of some embodiments, a transient study is added in the solver, the solver is used to perform the transient study, the transient study is used to call the metal organic framework material model to output real-time data; the time range, output time step, relative tolerance and absolute tolerance of the transient study are set.

[0072] Specifically, the transient study 1 is added, the time unit is set to s, the output time step range (0, 1, 500) is set, the tolerance is set, and the fluid heat transfer, solid heat transfer, porous medium heat transfer, Darcy's law, and coefficient form partial differential equation physical field are enabled, and the transient study calculation button is clicked.

[0073] Further, in the study part, a parameterized scan is added, the scan type is specified as a specified combination, the parameters of the equilibrium adsorption curve are scanned, and each parameter has 455 values. Real-time data such as heat flow temperature and adsorption capacity, as well as performance parameters such as COP and SCP, are output.

[0074] Please refer to Figure 3 In some embodiments, step S104 can include but is not limited to steps S301 to S307: Step S301, obtaining the aluminum pipe size parameters, heat flow channel size parameters and metal organic framework material size parameters input by the user.

[0075] Optionally, the size parameters can adopt default values or be input by the user.

[0076] For example, the area size parameters are as follows: Aluminum pipe: inner diameter r1 = 20 mm, wall thickness 1 mm, axial length z = 1000 mm; Heat flow channel: located inside the aluminum pipe (r < 20 mm, 0 < z < 1000 mm), which is a hot water flow area, used to provide low-grade heat energy during the desorption stage; Metal-organic framework: coated on the outer wall of the aluminum tube (24 mm < r < 26 mm, 0 < z < 1000 mm), thickness 2 mm, MOFs particle accumulation area (particle size 3.5e-4 m, porosity ε = 0.4, obtained by literature data).

[0077] Step S302, based on the aluminum tube size parameters, the heat flow channel size parameters and the metal-organic framework size parameters, a metal-organic framework model is constructed.

[0078] Specifically, the metal-organic framework model adopts a three-dimensional adsorption tube model, which includes an aluminum tube, a heat flow in the tube, an adsorbent and an adsorbate, and the adsorbent adopts a metal-organic framework.

[0079] In some embodiments, an equal-proportion three-dimensional adsorption tube model containing an aluminum tube, a heat flow in the tube, an adsorbent (MOFs) and an adsorbate (ethanol) is constructed; an equal-proportion two-dimensional axisymmetric geometric model is constructed by using the built-in geometric module of COMSOL.

[0080] Step S303, the type of heat flow in the tube is determined, and the heat flow material parameters corresponding to the type of heat flow in the tube are obtained.

[0081] Optionally, the type of heat flow in the tube is selected by a user or a default type is adopted, and the corresponding material parameters are automatically obtained by software.

[0082] Exemplarily, the type of heat flow in the tube is water, and the constant-pressure heat capacity, density, thermal conductivity and dynamic viscosity are defined by the built-in material of the software.

[0083] Step S304, aluminum tube material parameters are obtained.

[0084] Among them, the constant-pressure heat capacity, density and thermal conductivity of the aluminum tube are defined by the built-in material of the software.

[0085] Step S305, the constant-pressure heat capacity of the metal-organic framework is obtained, and the metal-organic framework parameters are constructed by the constant-pressure heat capacity, the density of the metal-organic framework, the thermal conductivity of the metal-organic framework and the permeability equation of the metal-organic framework.

[0086] Optionally, the constant-pressure heat capacity is obtained by public literature query or input by a user.

[0087] Exemplarily, the constant-pressure heat capacity, density, thermal conductivity and permeability equation of the metal-organic framework are defined according to the molecular simulation results.

[0088] Step S306, the type of working fluid is determined, and the fluid material parameters corresponding to the type of working fluid are obtained.

[0089] Optionally, the working fluid type is selected by the user or a default type is adopted, and the corresponding material parameters are automatically obtained by the software.

[0090] Exemplarily, the working fluid type is ethanol vapor, and the constant pressure heat capacity, density, thermal conductivity coefficient, and dynamic viscosity are defined by the built-in material of the software.

[0091] In step S307 of some embodiments, the material parameters are applied by the three-dimensional adsorption tube model of the software.

[0092] In step S307 of some embodiments, the material parameters are applied by the three-dimensional adsorption tube model of the software.

[0093] Please refer to Figure 4 In some embodiments, step S201 can include but is not limited to steps S401 to S405: In step S401, a fluid heat transfer interface is set, and region 1 (heat flow channel) is enabled.

[0094] In step S401 of some embodiments, setting the fluid heat transfer interface includes the following steps: 1: Fluid heat transfer selects the heat flow region, the velocity field is set to z-axis -0.05 m / s, r-axis 0 m / s, the inner wall of the aluminum pipe is added as heat flux, and other parameters are default values; 2: The initial value of fluid heat transfer is set to 353K; 3: The inflow temperature is set to 353K.

[0095] It can be understood that the above 0.05 m / s, 0 m / s and 353K are only examples, and the above parameters are variable parameters supporting user customization.

[0096] In step S402, a solid heat transfer interface is set, and region 2 (aluminum pipe) is enabled.

[0097] In step S402 of some embodiments, setting the solid heat transfer interface includes the following steps: 1: Solid heat transfer selects the aluminum pipe region, adds the inner wall of the aluminum pipe as heat flux 1, adds the outer wall of the aluminum pipe as heat flux 2, and other parameters are default values; 2: The initial value of fluid heat transfer is set to 303K.

[0098] It can be understood that the above 303K is only an example, and the above parameters are variable parameters supporting user customization.

[0099] In step S403, a porous medium heat transfer interface is set, and region 3 (metal organic framework material) is enabled.

[0100] In step S403 of some embodiments, setting the porous medium heat transfer interface includes the following steps: 1: Porous medium heat transfer adsorbent domain, add aluminum tube outer wall as heat flux, other parameters are default values; 2: The velocity field of the porous medium part of the fluid is set to the total Darcy velocity field, the pressure is set to the absolute pressure calculated by the Darcy law, the thermal conductivity is user-defined as isotropic kv, the fluid type is gas / liquid, the density is set to rhov, the constant-pressure heat capacity is set to Cv, and other parameters are default values; 3: The porous medium part of the solid, the solid type is solid phase attribute, the thermal conductivity is user-defined as isotropic ks, the density is set to rhov, and other parameters are default values; 4: The initial value of the porous medium heat transfer is set to 303K; 5: The heat source is designed as a generalized heat source, and its value is defined as an adsorption heat formula.

[0101] Step S404, set the Darcy law interface, enable region 3 (metal-organic framework material).

[0102] In step S404 of some embodiments, setting the Darcy law interface includes the following steps: 1: Darcy law selects porous medium, porous medium heat transfer selects adsorbent domain, and other parameters are default values; 2: The porous medium flow model selects Darcy flow, and the water storage model comes from density and porosity, and other parameters are default values; 3: The temperature of the fluid part of the porous medium is set to Ts, the fluid type is set to ideal gas, the gas constant type is average molar mass, which is user-defined as 46 g / mol, the dynamic viscosity is user-defined as 0.46e-3 Pas, the porosity of the porous matrix is set to ε, and the permeability is set to κ, and other parameters are default values; 4: The initial value of the pressure of the porous medium is set to 10400 Pa; 5: The mass source is set to -(1-ε)*ρs*dX / dt; 6: The three sides of the porous medium in contact with the environment are set to pressure outlets, and the outlet pressure is set to 10400 Pa.

[0103] Step S405, set the coefficient form partial differential equation interface, enable region 3 (metal-organic framework material).

[0104] In step S405 of some embodiments, setting the coefficient form partial differential equation interface includes the following steps: 1: The absorption coefficient is set to KLDF; 2: The initial value of the coefficient form partial differential equation is set to Weq0.

[0105] Figure 5 is a specific implementation flowchart of the adsorption refrigeration performance evaluation method provided by the embodiments of the present application when applied to evaluate the multi-scale coupled system of MOFs working pair heat pump performance, Figure 5 The method in the method can include but is not limited to including the following steps: Step 1, molecular simulation.

[0106] In some embodiments, the structural characteristics, adsorption isotherm, diffusion coefficient of MOFs are obtained by molecular simulation, and relevant thermodynamic parameters are provided for multi-physical field simulation.

[0107] Specifically, the CoRE MOF database consists of 2932 structures used in this study, of which 2476 structures cannot obtain reasonable adsorption performance, thermophysical properties or dynamic transport diffusion performance before screening. Therefore, finally, the core structure parameters include density, specific surface area, effective pore volume, maximum pore diameter and restricted pore diameter.

[0108] Among them, the density will be used as the input of the metal organic framework material in the COMSOL modeling part, in addition to the density, the restricted pore diameter is used to judge whether the adsorption can be carried out, which is used in the molecular simulation. The specific surface area and other parameters calculated are the adsorbent characteristic parameters, which are not used in the subsequent simulation.

[0109] Step 2, Monte Carlo simulation.

[0110] In some embodiments, the Monte Carlo simulation predicts the equilibrium adsorption isotherm, such as the adsorption amount and the adsorption enthalpy. Specifically, the interaction between MOFs and ethanol molecules is described by Lennard-Jones potential and Coulomb potential. For MOF framework atoms, the Universal Force Field (UFF) is used for force field parameterization, and the atomic charge is calculated by combining the density-derived electrostatic chemical (DDEC) charge method; for ethanol molecules, the TraPPE force field based on the united atom model defines it as a flexible molecule. This study performs grand canonical Monte Carlo simulation through RASPA 2.0 software, a total of 4×105 cycles, including translation, rotation, reinsertion and exchange of molecular movement: The first 2×105 cycles are used for system initialization to eliminate the influence of the initial state, and the remaining cycles are used as production cycles for the statistics and estimation of adsorption performance (such as equilibrium adsorption amount, adsorption enthalpy).

[0111] Step 3, molecular dynamics simulation.

[0112] In some embodiments, the transport diffusion properties of MOFs for ethanol are evaluated by molecular dynamics simulation. The diffusion coefficient KLDF of ethanol in the pore of MOFs, and the "degree of change of concentration distribution" in the molecular diffusion process are calculated. As the input of Darcy's law.

[0113] Wherein, the thermal conductivity of the MOFs is calculated by molecular dynamics simulation.

[0114] Step 4, COMSOL modeling.

[0115] Exemplarily, a schematic diagram of the MOFs working fluid pair heat pump is as shown in Figure 6

[0116] In some embodiments, based on the COMSOL Multiphysics software, considering the axisymmetric structure of the adsorption tube (with the tube axis as the rotation axis, the radial parameters are symmetrically distributed), in order to improve the calculation efficiency, a two-dimensional axisymmetric adsorption tube model (instead of a three-dimensional model) is constructed, which includes three core areas of aluminum tube, heat flow channel and adsorbent layer (MOFs).

[0117] Optionally, an equal-proportion three-dimensional adsorption tube model is constructed based on the COMSOL Multiphysics software: an equal-proportion three-dimensional adsorption tube model is constructed, which includes aluminum tube, heat flow in the tube, adsorbent (MOFs) and adsorbate (ethanol); an equal-proportion two-dimensional axisymmetric geometric model is constructed by using the built-in geometric module of COMSOL (coordinate system: r-z axis, r is the radial coordinate and z is the axial coordinate), and the size parameters of each area are as follows: Aluminum tube: inner diameter r1 = 20 mm, wall thickness 1 mm, axial length z = 1000 mm; Heat flow channel: located inside the aluminum tube (r < 20 mm, 0 < z < 1000 mm), which is a hot water flow area, used to provide low-grade heat energy in the desorption stage; Metal organic framework material: coated on the outer wall of the aluminum tube (24 mm < r < 26 mm, 0 < z < 1000 mm), thickness 2 mm, which is a MOFs particle accumulation area (particle size 3.5e-4 m, porosity ε = 0.4, obtained from literature data).

[0118] It can be understood that the above area size parameters are only examples and can be dynamically set.

[0119] Further, according to the molecular simulation results and public literature data, the material parameters of each area are set as follows: Heat flow (water): constant pressure heat capacity, density, thermal conductivity, dynamic viscosity are defined by the built-in material of the software; Aluminum tube: constant pressure heat capacity, density, thermal conductivity are defined by the built-in material of the software; Metal organic framework material (MOFs): constant pressure heat capacity, density, thermal conductivity, permeability equation are defined according to the molecular simulation results; Working fluid (ethanol vapor): constant pressure heat capacity, density, thermal conductivity, dynamic viscosity are defined by the built-in material of the software; ​In some embodiments, a multi-physics setup is performed, including porous media heat transfer, coefficient form partial differential equation, Darcy's law, fluid / solid heat transfer.

[0120] Specifically, the fluid heat transfer interface is set to include: 1) Applicable domain: hot stream channel (0 mm < r < 10 mm, 0 < z < 1000 mm); 2) Velocity field setup: z-axis direction velocity -0.05 m / s (negative sign indicates that the hot water flow direction is opposite to the positive direction of the z-axis), r-axis direction velocity 0 m / s; 3) Initial condition: initial temperature 353 K; 4) Boundary condition: aluminum tube inner wall (r = 10 mm): set as heat flux, the heat flux value is calculated by the temperature difference between the hot stream and the aluminum tube; hot stream inlet (z = 1000 mm): set as inlet, taking the value 353 K; hot stream outlet (z = 0 mm): set as outlet.

[0121] Optionally, the solid heat transfer interface is set to include: 1) Applicable domain: aluminum tube (10 mm < r < 11 mm, 0 < z < 1000 mm); 2) Initial condition: initial temperature 303 K; 3) Boundary condition: aluminum tube inner wall (r = 10 mm): set as heat flux, coupled with the fluid heat transfer interface; aluminum tube outer wall (r = 11 mm): set as heat flux, the heat flux value is calculated by the temperature difference between the aluminum tube and the adsorbent layer.

[0122] Specifically, the porous media heat transfer interface is set to include: 1) Applicable domain: metal organic framework material (11 mm < r < 13 mm, 0 < z < 1000 mm); 2) Initial condition: initial temperature 303 K; 3) Fluid phase parameters: Velocity field: set as total Darcy velocity field, coupled with the Darcy's law interface; Pressure: set as the absolute pressure calculated by Darcy's law; Thermal conductivity: self-defined isotropic; Fluid type: gas; Density: calculated by the ideal gas equation of state; Constant pressure heat capacity: constant pressure heat capacity of ethanol; 3) Solid phase parameters: Solid type: solid phase attribute; Thermal conductivity: self-defined isotropic; 4) Heat source setup: add a generalized heat source, the heat source intensity is defined as the adsorption heat formula (Q = ΔHads (1 - ε) ρs dX / dt, where X is the adsorption amount and dX / dt is the adsorption rate.

[0123] Specifically, setting the Darcy's law interface specifically includes: 1) Applicable domain: metal organic framework (11 mm < r < 13 mm, 0 < z < 1000 mm); 2) Model settings: Flow model: Darcy flow (applicable to low-speed flow in porous media); Water storage model: from density and porosity (considering the influence of ethanol vapor density change on mass transfer); 3) Fluid parameters: Temperature: set to Ts (adsorbent layer temperature, coupled with the porous media heat transfer interface); Fluid type: ideal gas; Gas constant type: average molar mass (46 g / mol); Dynamic viscosity: custom 0.46 x 10-3Pa s; Permeability: kappa (formula); 4) Initial conditions: initial pressure 10400 Pa (saturation vapor pressure of ethanol at 303 K); 5) Mass source settings: add mass source term -(1 - ε) ρs dX / dt; 6) Boundary conditions: adsorbent layer outer boundary (r = 13 mm, z = 0, z = 1000 mm) is set to pressure outlet, and the outlet pressure is 10400 Pa.

[0124] Specifically, setting the coefficient form partial differential equation interface specifically includes: 1) Applicable domain: metal organic framework (11 mm < r < 13 mm, 0 < z < 1000 mm); 2) Set the absorption coefficient to KLDF; 3) Set the initial value of the coefficient form partial differential equation to Weq0.

[0125] In some embodiments, mesh partitioning settings are made, and mesh independence verification is performed. Exemplarily, the specific mesh partitioning shape of the free triangle network is as shown in Figure 3 .

[0126] In the grid module, select the free triangle grid, set the cell size to fine, and output about 120,000 grids after generating the grid. To verify the grid independence, generate three kinds of grids, namely, coarse, fine, and very fine. Perform transient calculation on the same MOFs, and compare the COP calculation results of the three kinds of grids. For example, the COP difference between the fine and coarse calculation results is less than 0.05, and the COP difference between the fine and very fine calculation results is less than 0.01, so the fine grid is used to reduce the running time.

[0127] Further, the solver settings are performed, the separation solver is set to use the tolerance as the parameter to control the equation termination, and the transient calculation is performed.

[0128] 1) Add transient study 1, set the time unit to s, output the time step range (0, 1, 500), set the tolerance, and enable fluid heat transfer, solid heat transfer, porous medium heat transfer, Darcy's law, and coefficient form partial differential equation physical field. Click the transient study calculation button.

[0129] 2) Add a parameterized scan in the study section, specify the scan type as specified combination, and scan the parameters of the equilibrium adsorption curve. Each parameter has 455 values. Output real-time data such as heat flow temperature, adsorption capacity, and COP, SCP performance parameters.

[0130] Among them, the solver settings and transient calculation include: in the study module, add a transient study, set the time range to 0-500s, and output the time step as range (0, 1, 500); set the relative tolerance to 1e-6 and the absolute tolerance to 1e-8; click run. The transient calculation of a single MOF takes about 5 minutes.

[0131] Step 5, changes in temperature, adsorption capacity, and pressure in the adsorption bed.

[0132] It should be noted that the parameterized scan setting specifically includes: In the study module, add a parameterized scan, select the specified combination scan type, import the parameter files of 455 MOFs (including adsorption isotherm parameters, adsorption enthalpy, and diffusion coefficient), set the scan parameter to MOF number (1-455), and ensure that each number corresponds to a complete set of parameters.

[0133] Further, batch calculation and data output specifically include: Click Run Parameterized Scan, and the system automatically calls 455 MOFs in sequence, calculates and outputs the temperature field distribution in the adsorption bed, the change of ethanol concentration field, the adsorption rate dynamic curve, and the instantaneous adsorption capacity data, and calculates COP and SCP through derived value calculation.

[0134] It should be noted that the application establishes a multi-scale calculation framework covering "adsorption equilibrium-mass transfer kinetics-macroscopic system performance" through the cooperation of Monte Carlo simulation, molecular dynamics simulation and COMSOL multi-physical field coupling simulation, and the specific implementation path is as follows: 1. Monte Carlo simulation: obtain the equilibrium adsorption isotherms of 455 MOFs through Monte Carlo simulation to provide adsorption performance parameters (such as adsorption capacity and adsorption enthalpy) for subsequent calculation; 2. Molecular dynamics simulation: obtain the gas diffusion coefficient (such as gas diffusion constant) based on molecular dynamics simulation; 3. COMSOL calculation: import the adsorption parameters obtained by Monte Carlo simulation as the input parameters of the adsorption kinetics equation, and the gas diffusion coefficient obtained by molecular dynamics simulation as the parameters of the mass transfer equation into the COMSOL multi-physical field simulation platform, construct the mathematical model of "heat transfer-mass transfer-adsorption reaction" coupling in the adsorption bed, solve the nonlinear transient coupled equation set by the finite element method, simulate the dynamic distribution of the temperature field and concentration field in the adsorption bed under different operating conditions, and finally evaluate and calculate the actual heat pump performance COP and SCP of the MOFs / ethanol working pair, realizing the direct correlation from molecular parameters to macroscopic performance.

[0135] Specifically, based on the multi-scale model (integrating Monte Carlo simulation, molecular dynamics simulation and COMSOL nonlinear equation solving), the application simulates and calculates the full-cycle dynamic adsorption process of the MOFs / ethanol working pair in the adsorption heat pump. The equilibrium adsorption isotherms of 455 MOFs are obtained through Monte Carlo simulation; the gas diffusion coefficient is obtained through molecular dynamics simulation; and the two types of micro parameters are input to build and solve the distributed parameter model on the COMSOL platform, realizing the cross-scale correlation and quantitative analysis from "molecular adsorption mechanism → pore mass transfer behavior → macroscopic system performance". The purpose of the method is to quickly evaluate and accurately predict the adsorption performance of large-scale MOFs materials. Through the cooperative calculation of the multi-scale model, real-time data of the adsorption process of the adsorbent can be effectively obtained, including the temperature field distribution in the adsorption bed, the change of the ethanol concentration field, the adsorption rate dynamic curve and the instantaneous adsorption capacity; and through post-processing, the core performance indicators of the adsorption heat pump such as the coefficient of performance and the specific cooling capacity are obtained, realizing the efficient screening of MOFs materials.

[0136] Please refer to Figure 7 The application embodiment further provides an adsorption refrigeration performance evaluation device, which can realize the above-mentioned method, and the device comprises: The parameter acquisition module 701 is configured to obtain core structure parameters of a plurality of metal organic framework materials based on a metal organic framework material database through molecular simulation, wherein the core structure parameters include density and restricted pore diameter; The Monte Carlo simulation module 702 is configured to predict the equilibrium adsorption isotherms and adsorption enthalpy of each of the metal organic framework materials through Monte Carlo simulation; a molecular dynamics simulation module 703, configured to perform a molecular dynamics simulation based on the restricted pore diameter to obtain a diffusion coefficient, a thermal conductivity coefficient, and a permeability equation of each of the metal-organic frameworks; a model construction module 704, configured to construct a plurality of metal-organic framework models, and perform parameter setting of the metal-organic framework models by using the equilibrium adsorption isotherm, the adsorption enthalpy, the diffusion coefficient, the thermal conductivity coefficient, and the permeability equation; an evaluation module 705, configured to input a parameter file of each of the metal-organic frameworks into a corresponding metal-organic framework model, call the metal-organic framework model to output real-time data, and calculate a coefficient of performance and a specific refrigeration capacity based on the real-time data, the real-time data including a temperature field distribution in an adsorption bed, an ethanol concentration field change, an adsorption rate dynamic curve, and instantaneous adsorption amount data.

[0137] It can be understood that the contents in the above method embodiments are all applicable to the device embodiments, the device embodiments specifically implement the functions of the above method embodiments, and achieve the same beneficial effects as the above method embodiments.

[0138] The embodiments of the present application further provide an electronic device, which includes a memory and a processor, the memory stores a computer program, and the processor implements the above method when executing the computer program. The electronic device can be any intelligent terminal including a tablet computer, a vehicle-mounted computer, etc.

[0139] It can be understood that the contents in the above method embodiments are all applicable to the device embodiments, the device embodiments specifically implement the functions of the above method embodiments, and achieve the same beneficial effects as the above method embodiments.

[0140] Please refer to Figure 8 , Figure 8 The hardware structure of the electronic device of another embodiment is illustrated, and the electronic device includes: The processor 801 can be implemented in a general-purpose CPU (Central Processing Unit), a microprocessor, an ASIC (Application Specific Integrated Circuit), or one or more integrated circuits, etc., and is used to execute related programs to implement the technical solutions provided by the embodiments of the present application. The memory 802 can be implemented in the form of Read Only Memory (ROM), static storage device, dynamic storage device or Random Access Memory (RAM), etc. The memory 802 can store an operating system and other application programs, and when the technical solutions provided by the embodiments of the present specification are implemented by software or firmware, the related program codes are stored in the memory 802 and are called and executed by the processor 801 to implement the above-mentioned method of the embodiments of the present application; The input / output interface 803 is configured to realize information input and output. The communication interface 804 is configured to realize the communication interaction between the device and other devices, and the communication can be realized by wired mode (for example, USB, network cable, etc.) or wireless mode (for example, mobile network, WIFI, Bluetooth, etc.). The bus 805 is configured to transmit information between various components (for example, the processor 801, the memory 802, the input / output interface 803 and the communication interface 804) of the device. The processor 801, the memory 802, the input / output interface 803 and the communication interface 804 are connected to each other through the bus 805 to realize the communication connection between them in the device.

[0141] The embodiments of the present application also provide a computer readable storage medium, which stores a computer program, and the computer program is executed by a processor to realize the above-mentioned method.

[0142] It can be understood that the contents in the above-mentioned method embodiments are all applicable to the present storage medium embodiments, the functions specifically realized by the present storage medium embodiments are the same as those of the above-mentioned method embodiments, and the beneficial effects achieved by the present storage medium embodiments are also the same as those achieved by the above-mentioned method embodiments.

[0143] The embodiments of the present application also provide a computer program product, which includes a computer program, and the computer program is executed by a processor to realize the above-mentioned method.

[0144] It can be understood that the contents in the above-mentioned method embodiments are all applicable to the present program product embodiments, the functions specifically realized by the present program product embodiments are the same as those of the above-mentioned method embodiments, and the beneficial effects achieved by the present program product embodiments are also the same as those achieved by the above-mentioned method embodiments.

[0145] The memory, as a non-transitory computer-readable storage medium, can be used to store non-transitory software programs and non-transitory computer-executable programs. In addition, the memory can include a high-speed random access memory, and can also include a non-transitory memory, such as at least one magnetic disk storage device, a flash memory device, or other non-transitory solid-state memory device. In some embodiments, the memory can optionally include a memory disposed remotely relative to the processor, which can be connected to the processor through a network. Examples of the above network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0146] The adsorption refrigeration performance evaluation method and device, the electronic device, the storage medium and the program product provided by the embodiments of the present application obtain the core structure parameters of a plurality of metal organic framework materials based on a metal organic framework material database through molecular simulation; predict the equilibrium adsorption isotherm and the adsorption enthalpy of each metal organic framework material through Monte Carlo simulation; perform molecular dynamics simulation based on the restricted pore diameter to obtain the diffusion coefficient, the thermal conductivity coefficient and the permeability equation of each metal organic framework material; construct a plurality of metal organic framework material models, and set the parameters of the metal organic framework material models through the equilibrium adsorption isotherm, the adsorption enthalpy, the diffusion coefficient, the thermal conductivity coefficient and the permeability equation; input the parameter files of the plurality of metal organic framework materials into the corresponding metal organic framework material models, call the metal organic framework material models to output real-time data, calculate the refrigeration performance coefficient and the specific refrigeration capacity based on the real-time data, and realize rapid evaluation and accurate prediction of the adsorption performance of a large-scale metal organic framework material. Through the cooperative calculation of the multi-scale models, the real-time data of the adsorption process of the adsorbent can be effectively obtained, the core performance indicators such as the refrigeration performance coefficient and the specific refrigeration capacity of the adsorption heat pump are processed, and efficient screening of the metal organic framework material is realized.

[0147] The embodiments described in the embodiments of the present application are used to more clearly illustrate the technical solutions of the embodiments of the present application, and do not constitute a limitation on the technical solutions provided by the embodiments of the present application. Those skilled in the art can know that, with the evolution of technology and the appearance of new application scenarios, the technical solutions provided by the embodiments of the present application are also applicable to similar technical problems.

[0148] Those skilled in the art can understand that the technical solutions shown in the figures do not constitute a limitation on the embodiments of the present application, and can include more or fewer steps than shown in the figures, or combine certain steps or different steps.

[0149] The device embodiments described above are only schematic, and the units described as separate components can or can not be physically separate, that is, can be located in one place, or can be distributed on multiple network units. Part or all of the modules can be selected according to actual needs to achieve the purpose of the embodiments of the present application.

[0150] Those skilled in the art can understand that all or some of the steps in the method disclosed above, the function modules / units in the system and the device can be implemented as software, firmware, hardware and appropriate combinations thereof.

[0151] The terms "first", "second", "third", "fourth" and the like in the description of the application and in the claims hereof, if any, are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It is to be understood that the use of the terms so termed is interchangeable under appropriate circumstances such that the embodiments of the application described herein are, for example, capable of orderly or chronological permutations. Moreover, the terms "comprise", "have" and any variations thereof are intended to cover a non-exclusive inclusion, for example, a process, method, article, or apparatus that comprises a list of steps or units can not necessarily be limited to those steps or units, but can include additional steps or units not expressly listed or inherent to such process, method, article, or apparatus.

[0152] It should be understood that, in the present application, "at least one" means one or more, and "multiple" means two or more. "And / or" is used to describe the relationship between associated objects, which means that there can be three relationships, for example, "A and / or B" can mean that there are three cases: only A, only B, and A and B at the same time, where A and B can be singular or plural. The character " / " generally represents an "or" relationship between the associated objects. "At least one of the following" or similar expressions means any combination of these items, including any combination of single or multiple items. For example, at least one of a, b or c can mean a, b, c, "a and b", "a and c", "b and c", or "a and b and c", where a, b, and c can be single or multiple.

[0153] In several embodiments provided in the present application, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic. For example, the division of the above-mentioned units is only a logical function division, and actual implementation can have another division manner, for example, a plurality of units or components can be combined or integrated into another system, or some features can be omitted or not executed. In addition, the coupling or direct coupling or communication connection between the displayed or discussed objects can be indirect coupling or communication connection through some interfaces, devices or units, which can be electrical, mechanical or other forms.

[0154] The units described as separate components above can or can not be physically separate, and the components shown as units can or can not be physical units, that is, can be located in one place, or can be distributed to multiple network units. Part or all of the units can be selected according to actual needs to achieve the purpose of the embodiment scheme.

[0155] In addition, each functional unit in each embodiment of the present application can be integrated in one processing unit, or each unit can be physically present alone, or two or more units can be integrated in one unit. The integrated unit can be realized in the form of hardware or in the form of a software functional unit.

[0156] If the integrated unit is realized in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer readable storage medium. Based on this understanding, the technical solutions of the present application essentially or the part that contributes to the prior art or the whole or part of the technical solutions can be embodied in the form of a software product. The computer software product is stored in a storage medium, including a plurality of 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 method of each embodiment of the present application. The foregoing storage medium includes: a U disk, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk, and various program storage media.

[0157] The preferred embodiments of the embodiments of the present application are described above with reference to the accompanying drawings, and are not limited to the scope of the embodiments of the present application. Any modifications, equivalent replacements and improvements made by those skilled in the art without departing from the scope and essence of the embodiments of the present application shall be within the scope of the embodiments of the present application.

Claims

1. A method for evaluating adsorption refrigeration performance, characterized in that, The method includes the following steps: Several core structural parameters of metal-organic framework materials were obtained by molecular simulation based on a metal-organic framework material database. These core structural parameters include density and confined pore diameter. The equilibrium adsorption isotherm and adsorption enthalpy of each of the metal-organic framework materials were predicted using Monte Carlo simulations. Molecular dynamics simulations were performed based on the confined pore diameter to obtain the diffusion coefficient, thermal conductivity, and permeability equations for each metal-organic framework material. Several metal-organic framework material models are constructed, and the parameters of the metal-organic framework material models are set by the equilibrium adsorption isotherm, the adsorption enthalpy, the diffusion coefficient, the thermal conductivity and the permeability equation. The parameter files of several metal-organic framework materials are input into the corresponding metal-organic framework material model. The metal-organic framework material model is called to output real-time data. The refrigeration performance coefficient and specific refrigeration capacity are calculated based on the real-time data. The real-time data includes the temperature field distribution in the adsorption bed, the change in the ethanol concentration field, the dynamic curve of the adsorption rate, and the instantaneous adsorption capacity data.

2. The method according to claim 1, characterized in that, The method further includes: Perform multiphysics coupling settings and boundary condition settings; Configure the grid division settings; Configure the solver.

3. The method according to claim 2, characterized in that, The process of setting up the grid division includes: In the mesh module of the metal-organic framework material model, a free triangle mesh is selected; Coarser, finer, and extremely finer meshes are generated using the free triangular mesh. Transient calculations were performed on the same metal-organic framework material using the coarser grid, the finer grid, and the ultrafiner grid, respectively, to obtain transient calculation results. The target mesh of the free triangular mesh is determined based on the transient calculation results.

4. The method according to claim 1, characterized in that, The construction of several metal-organic framework material models, and the parameter settings of the metal-organic framework material models using the equilibrium adsorption isotherm, the adsorption enthalpy, the diffusion coefficient, the thermal conductivity, and the permeability equation, include: Obtain the user-input aluminum tube size parameters, heat flow channel size parameters, and metal-organic framework material size parameters; A metal-organic framework (MOF) material model is constructed based on the aluminum tube size parameters, the heat flow channel size parameters, and the metal-organic framework material size parameters. The MOF material model adopts a three-dimensional adsorption tube model, which includes an aluminum tube, internal heat flow, adsorbent, and adsorbate. The adsorbent is the metal-organic framework material.

5. The method according to claim 4, characterized in that, The construction of several metal-organic framework material models, and the parameter setting of the metal-organic framework material models through the equilibrium adsorption isotherm, the adsorption enthalpy, the diffusion coefficient, the thermal conductivity, and the permeability equation, further includes: Determine the type of heat flow inside the pipe and obtain the heat flow material parameters corresponding to the type of heat flow inside the pipe; Obtain aluminum tube material parameters; Obtain the constant-pressure heat capacity of the metal-organic framework material, and construct the parameters of the metal-organic framework material through the constant-pressure heat capacity, the density of the metal-organic framework material, the thermal conductivity of the metal-organic framework material, and the permeability equation of the metal-organic framework material; Determine the type of working fluid and obtain the fluid material parameters corresponding to the type of working fluid; The heat flow material parameters, the aluminum tube material parameters, the metal-organic framework material parameters, and the fluid material parameters are applied through the three-dimensional adsorption tube model.

6. The method according to claim 2, characterized in that, The process of setting up the solver includes: Add a transient study to the solver, the solver is used to execute the transient study, and the transient study is used to call the metal-organic framework material model to output real-time data; Set the time range, output time step, relative tolerance, and absolute tolerance for the transient study.

7. An adsorption refrigeration performance evaluation device, characterized in that, The device includes: The parameter acquisition module is used to obtain the core structural parameters of several metal-organic framework materials through molecular simulation based on a metal-organic framework material database. The core structural parameters include density and confined pore diameter. Monte Carlo simulation module for predicting the equilibrium adsorption isotherm and adsorption enthalpy for each of the metal-organic framework materials using Monte Carlo simulation; The molecular dynamics simulation module is used to perform molecular dynamics simulations based on the confined pore diameter to obtain the diffusion coefficient, thermal conductivity, and permeability equations for each metal-organic framework material. The model building module is used to build several metal-organic framework material models. The parameters of the metal-organic framework material models are set by the equilibrium adsorption isotherm, the adsorption enthalpy, the diffusion coefficient, the thermal conductivity and the permeability equation. The evaluation module is used to input parameter files of several metal-organic framework materials into the corresponding metal-organic framework material model, call the metal-organic framework material model to output real-time data, and calculate the coefficient of performance and specific cooling capacity based on the real-time data. The real-time data includes the temperature field distribution in the adsorption bed, the change in the ethanol concentration field, the dynamic curve of the adsorption rate, and the instantaneous adsorption amount data.

8. An electronic device, characterized in that, The electronic device includes a memory and a processor, the memory storing a computer program, and the processor executing the computer program to implement the method according to any one of claims 1 to 6.

9. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by a processor, it implements the method of any one of claims 1 to 6.

10. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by a processor, it implements the method of any one of claims 1 to 6.

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