Heat transfer simulation method, system, device and medium for material freezing process

Abstract

The present invention discloses a heat transfer simulation method for a material freezing process, comprising: step 1, obtaining a liquid phase volume fraction V before the material is frozen according to various physical property parameters of the material before freezing; L , the volume fraction V of the porous matrix before freezing SL , effective physical property parameters of the liquid phase before freezing the material and effective physical property parameters of the porous matrix before freezing the material; Step 2, according to the physical property parameters of the material after freezing, obtain the frozen phase volume fraction V of the material after freezing F , the volume fraction V of the porous matrix after freezing SF , effective physical property parameters of the frozen phase after the material is frozen and effective physical property parameters of the porous matrix after the material is frozen; step three, construct a heat transfer model of the material freezing process according to the parameters in step one and step two. The present invention can accurately predict the freezing process temperature, phase change and freezing end point, etc., and realize the standardization of freeze-drying production of materials (especially agricultural products).

Description

Technical Field

[0001] The present invention relates to the technical field of material freezing, and more specifically, to a heat transfer simulation method, system, device and medium for material freezing process. Background Art

[0002] Materials with high water content, especially agricultural products, are very prone to rot and deterioration when stored at room temperature. Freeze drying is one of the effective methods to extend the shelf life and increase the added value of materials (especially agricultural products). The freeze drying process includes three stages, namely the freezing stage, the sublimation stage and the desorption drying stage. Freezing refers to the use of cold air flow or cooling medium to contact the material, and remove heat from the material by heat conduction or heat convection. During the freezing process, the material is cooled below the freezing point, and the water in the material gradually turns into ice crystals and releases latent heat. During this stage, the temperature of the material will not drop temporarily. When the water in the material is completely solidified into ice crystals, the temperature of the material begins to drop until it approaches the freezing temperature end point. According to the phase equilibrium diagram, the freezing point of pure water is 0°C at normal pressure. However, agricultural products contain a variety of solutes that can lower the freezing point of the solution and make the freezing point of agricultural products below 0°C. Freezing, as the first key step in the freeze drying process, has an important impact on the texture of the freeze-dried product and the energy consumption of the freeze drying process.

[0003] At present, most companies rely on the experience of production operators to judge the freezing endpoint. This method is highly subjective and difficult to ensure consistency. In the freezing production process, different agricultural products and even different batches of the same product have very different freezing characteristics and freezing endpoints. Therefore, it is difficult to ensure production standardization simply by judging by experience. It is easy to be affected by factors such as the operator's experience level and the source of the product, and it is difficult to ensure production standardization. Installing temperature detection equipment during the freezing process to monitor the internal temperature of the product to determine the freezing endpoint is a common method for detecting the freezing endpoint of materials. Due to the small number of temperature sensor detection points and the heterogeneity of agricultural products, the temperature monitoring results are not universal. In addition, the temperature sensor detection process is invasive, which will destroy the original appearance structure of the material and affect the consistency of the frozen product. It can be seen that the judgment of the freezing endpoint of agricultural products lacks a scientific and standardized method, which greatly affects the stability of the freeze-drying production cycle and quality. Therefore, in the future, it is necessary to combine the characteristics of agricultural products and operating parameters to develop a more convenient, accurate and reliable freezing endpoint prediction method to accurately control the freezing cycle, achieve more energy-saving and green freezing production, and ultimately improve the standardization of freeze-drying production.

[0004] Simulation can be used to perform mathematical modeling based on actual production parameters and material properties, accurately predict physical and chemical changes during processing, and optimize processing technology. Agricultural products, such as fruits and vegetables, are mainly rich in water, soluble solids, and crude fiber. Applying mathematical simulation to the freezing processing of agricultural products, coupling the properties of agricultural products and freezing parameters, is conducive to the actual production process to predict the freezing process temperature, phase change, and freezing end point in advance according to the physical property differences of agricultural products and freezing conditions, avoid excessive freezing or insufficient freezing, and ensure the standardization of freezing production and quality consistency. At present, no one has proposed a corresponding heat transfer simulation method for the freezing process of materials to predict the freezing process temperature, phase change, and freezing end point, etc., to achieve the standardization of freeze-drying production of materials (especially agricultural products). Summary of the invention

[0005] An object of the present invention is to solve at least the above problems and to provide at least the advantages which will be described hereinafter.

[0006] Another object of the present invention is to provide a heat transfer simulation method for a material freezing process, which can accurately predict the freezing process temperature, phase change and freezing end point, etc., to achieve standardization of freeze-drying production of materials (especially agricultural products).

[0007] In order to achieve these purposes and other advantages according to the present invention, a heat transfer simulation method for a material freezing process is provided, comprising:

[0008] Step 1: According to the physical properties of the material before freezing, obtain the liquid phase volume fraction V of the material before freezing L , the volume fraction V of the porous matrix before freezing SL , the effective physical property parameters of the liquid phase before freezing the material and the effective physical property parameters of the porous matrix before freezing the material, wherein the effective physical property parameters of the liquid phase before freezing the material include: the effective density of the liquid phase ρ L , Liquid effective specific heat capacity Cp L And the liquid phase effective thermal conductivity γ L , the effective physical properties of the porous matrix before freezing include: the effective density of the porous matrix ρ SL , effective specific heat capacity of porous matrix Cp SL and the effective thermal conductivity γ of the porous matrix SL ;

[0009] Step 2: According to the physical properties of the material after freezing, obtain the frozen phase volume fraction V of the material after freezing F , the volume fraction V of the porous matrix after freezing SF , the effective physical property parameters of the frozen phase after the material is frozen and the effective physical property parameters of the porous matrix after the material is frozen, wherein the effective physical property parameters of the frozen phase after the material is frozen include: the effective density ρ of the frozen phase F , effective specific heat capacity of frozen phase CpF and the effective thermal conductivity γ of the frozen phase F The effective physical properties of the porous matrix after freezing include the effective density of the porous matrix ρ SF , effective specific heat capacity of porous matrix Cp SF and the effective thermal conductivity γ of the porous matrix SF ;

[0010] Step 3: Based on the parameters in steps 1 and 2, the heat transfer model of the material freezing process is constructed as follows:

[0011]

[0012] Where ΔH L→F represents the latent heat of phase change from liquid phase to frozen phase, J;

[0013] ρ eff Indicates the effective density of the material, kg / m 3 ;

[0014] Cp eff Indicates the effective specific heat capacity of the material, J / kg / K;

[0015] γ eff Indicates the effective thermal conductivity of the material, W / m·K;

[0016] Q1 represents the heat radiated from the environment to the material, J;

[0017] Q2 represents the heat released by the material to the shelf, J;

[0018] T i Indicates the temperature at any time point during the freezing process of the material, K;

[0019] a represents the ratio of thermal diffusivity between the liquid phase and the frozen phase;

[0020] θ L and θ F represent the saturation fractions of liquid phase and frozen phase respectively, %;

[0021] ε represents the surface radiation factor, 0.74;

[0022] σ denotes the Stefan-Boltzmann constant;

[0023] h p Represents the heat transfer coefficient of the refrigerant medium, 62.3 W / (m 2 K);

[0024] T a represents the ambient temperature of the freezing chamber, K;

[0025] T p represents the freezing shelf temperature, K.

[0026] Preferably, the liquid volume fraction V of the material before freezing in step 1 is L and the volume fraction V of the porous matrix before freezing SL The method of obtaining is as follows:

[0027] Before freezing:

[0028] Liquid volume fraction V L ,%,V L =(X w / ρ w +X c / ρ c ) / (X w / ρ w +X f / ρ f +X c / ρ c );

[0029] The volume fraction of the porous matrix V SL ,%,V SL =X f / ρ f / (X w / ρ w +X f / ρ f +X c / ρ c );

[0030] The method for obtaining the effective physical property parameters of the liquid phase before freezing the material in step 1 is as follows:

[0031] Liquid effective density ρ L ,kg / m 3 , ρ L = 1 / (X w / ρ w +X c / ρ c );

[0032] Liquid effective specific heat capacity Cp L , J / kg / K, Cp L = Cp w ×X w +Cp c ×X c ;

[0033] Liquid phase effective thermal conductivity γ L , W / m·K, γ L = γ w × (X w / ρ w / (X w / ρw +Xc / ρ c )) +γc×(X c / ρ c / (X w / ρ w +X c / ρ c ));

[0034] The method for obtaining the effective physical property parameters of the porous matrix before freezing the material in step 1 is as follows:

[0035] Porous matrix effective density ρ SL ,kg / m 3 , ρ SL = 1 / (X c / ρ c );

[0036] Porous matrix effective specific heat capacity Cp SL , J / kg / K, Cp SL = Cp f ×X f ;

[0037] Effective thermal conductivity of porous matrix γ SL , W / m·K, γ SL =γ f ×X f / ρ f ;

[0038] Among them, X w Indicates the mass fraction of moisture in the material, %;

[0039] X c Indicates the mass fraction of soluble solids in the material, %;

[0040] X f Indicates the mass fraction of crude fiber in the material, %;

[0041] ρ w Indicates the moisture density of the material before freezing ρ w ,kg / m 3 ;

[0042] ρ c Indicates the soluble solid density of the material before freezing, kg / m 3 ;

[0043] ρ f Indicates the crude fiber density of the material before freezing, kg / m 3 ;

[0044] Cp w Indicates the specific heat capacity of water before freezing of the material, J / kg / K;

[0045] Cp c It indicates the specific heat capacity of soluble solids before freezing of the material, J / kg / K;

[0046] Cp f It indicates the specific heat capacity of crude fiber before freezing of the material, J / kg / K;

[0047] γ w Indicates the moisture thermal conductivity of the material before freezing, W / m·K;

[0048] γ c Indicates the thermal conductivity of soluble solids before freezing of the material, W / m·K;

[0049] γ f It indicates the thermal conductivity of crude fiber before freezing of the material, W / m·K.

[0050] Preferably, the physical property parameters of the material before freezing are obtained by coupling with the temperature, as follows:

[0051] Moisture density of material before freezing ρ w = 997.18+0.0031439×T1-0.0037574×T1 2 ;

[0052] Soluble solid density ρ before freezing c = 1599.1-0.31046×T1;

[0053] Crude fiber density ρ before freezing f = 1311.5-0.36589×T1;

[0054] Specific heat capacity of water before freezing of materials Cp w =4176.2-0.090864×T-0.0054731×T1 2 ;

[0055] Specific heat capacity of soluble solids before freezing Cp c =1548.8+1.9625×T1×-0.0059399×T1 2 ;

[0056] Crude fiber specific heat capacity Cp before material freezing f = 1845.9+1.8306×T1×-0.0046509×T1 2 ;

[0057] Thermal conductivity of moisture before freezing of the material γ w =0.57109+0.0017625×T1-6.7036×10 -6×T1 2 ;

[0058] Thermal conductivity of soluble solids before freezing γ c =0.20141+0.0013874×T1-4.3312×10 -6 ×T1 2 ;

[0059] Thermal conductivity of crude fiber before freezing γ f =0.18331+0.0012497×T1-3.1683×10 -6 ×T1 2 ;

[0060] Where T1 represents the initial temperature of the material, K.

[0061] Preferably, the frozen phase volume fraction V F , the volume fraction V of the porous matrix after freezing SF The method to obtain is as follows:

[0062] After freezing:

[0063] Frozen phase volume fraction V F ,%,V F =(X w / ρ i / +X c / ρ ci ) / (X w / ρ i +X f / ρ fi +X c / ρ ci );

[0064] The volume fraction of the porous matrix V SF ,%,V SF =X f / ρfi / (X w / ρ i +X f / ρ fi +X c / ρ ci );

[0065] The method for obtaining the effective physical property parameters of the frozen phase after the material is frozen in step 2 is as follows:

[0066] Frozen phase effective density ρ F ,kg / m 3 , ρ F = 1 / (X w / ρ i +X c / ρci );

[0067] Effective specific heat capacity of frozen phase Cp F , J / kg / K, Cp F = Cp i ×X w +Cp ci ×X c ;

[0068] Effective thermal conductivity of frozen phase γ F , W / m·K, γ F = γ i × (Xw / ρ i / (Xw / ρ i +Xc / ρ ci )) +γci×(Xc / ρ ci / (Xw / ρi+Xc / ρ ci ));

[0069] The method for obtaining the effective physical property parameters of the porous matrix after the material is frozen in step 2 is as follows:

[0070] Porous matrix effective density ρ SF ,kg / m 3 , ρ SF = 1 / (X c / ρ ci );

[0071] Porous matrix effective specific heat capacity Cp SF , J / kg / K, Cp SF = Cp fi ×X f ;

[0072] Effective thermal conductivity of porous matrix γ SF , W / m·K, γ SF =γ fi ×X f / ρ fi ;

[0073] Among them, ρ i Indicates the ice density of the material after freezing, kg / m 3 ;

[0074] ρ ci Indicates the soluble solid density of the material after freezing;

[0075] ρ fi Indicates the crude fiber density of the material after freezing, kg / m 3 ;

[0076] Cp iIt indicates the specific heat capacity of ice after freezing the material, J / kg / K;

[0077] Cp ci It indicates the specific heat capacity of soluble solids after freezing of the material, J / kg / K;

[0078] Cp fi It indicates the specific heat capacity of crude fiber after freezing of the material, J / kg / K;

[0079] γ i Indicates the thermal conductivity of moisture after freezing of the material, W / m·K;

[0080] γ ci Indicates the thermal conductivity of soluble solids after freezing of the material;

[0081] γ fi It indicates the thermal conductivity of crude fiber after freezing of the material, W / m·K.

[0082] Preferably, the physical property parameters of the material after freezing are obtained by coupling with the temperature, as follows:

[0083] Ice density of frozen material ρ i = 916.89-0.1307×T i ;

[0084] Soluble solid density of the material after freezing ρ ci = 1599.1-0.31046×T i ;

[0085] Crude fiber density ρ after freezing of the material fi = 1311.5-0.36589×T i ;

[0086] Specific heat capacity of ice after freezing of material Cp i =2062.3+6.0769×T i ;

[0087] Specific heat capacity of soluble solids after freezing of materials Cp ci =1548.8+1.9625×T i ×-0.0059399×T i 2 ;

[0088] Crude fiber specific heat capacity Cp after material freezing fi = 1845.9+1.8306×T i ×-0.0046509×T i 2 ;

[0089] Thermal conductivity of moisture after freezing of material γ i =2.2196-6.2489×10 -3 ×T i +1.0154×10 -4 ×T i 2 ;

[0090] Thermal conductivity of soluble solids after freezing of the material γ ci =0.20141+0.0013874×T i -4.3312×10 -6 ×T i 2 ;

[0091] Thermal conductivity of crude fiber after freezing of material γ fi =0.18331+0.0012497×T i -3.1683×10 -6 ×T i 2 ;

[0092] Among them, T i Indicates the temperature of the material at any point in time during the freezing process, K.

[0093] In the above technical scheme, according to the heat transfer model of the freezing process of the material, considering that the mass fraction of soluble solids in the material has a great influence on the critical temperature point of liquid water turning into solid ice, under ideal conditions (the crude fiber content in the material is 0), the mass fraction of soluble solids in the material is set gradually (0, 5%, 10%, 20%, 40%, 60%), and the critical temperature point T of liquid water turning into solid ice in the material is obtained experimentally. L→F , and the critical temperature point T at which liquid water in the material turns into solid ice is obtained L→F The fitting equation for the mass fraction of soluble solids in the material is: L→F = 65.861 Xc 3 -104.88 Xc 2 + 5.5201 Xc + 0.7869 (R 2 =0.9991). In the heat transfer model of the material freezing process, when T>T L→F When θ F =0; when T=T L→F When 0<θ F <1; when T <T L→F When θ F =1, so as to set θ F Boundary conditions. The empirical formula for the critical temperature point where liquid water turns into solid ice is: T L→F= −1.86 ×X w , the critical temperature T at which liquid water in the material provided by the present invention is transformed into solid ice L→F It is more in line with the actual conditions of materials (especially agricultural products) and can better fit the heat transfer model of the material freezing process provided by the present invention.

[0094] Preferably, the heat transfer simulation method for the material freezing process also includes the step of further coupling the heat transfer model of the material freezing process obtained in step three with the material shape to construct a heat transfer model for the freezing process of materials of different shapes, specifically: using COMSOL Multiphysics software to obtain the material size, constructing a geometric model of the material and refining the mesh, and solving the heat transfer model of the material freezing process constructed in step three under the boundary conditions constrained by the geometric model of the material.

[0095] The present invention further claims a heat transfer simulation system for a material freezing process, comprising:

[0096] The input module is used to input at least the mass fraction X of moisture in the material. w , the mass fraction of soluble solids in the material X c , the mass fraction of crude fiber in the material X f , represents the initial temperature of the material T1, the ambient temperature of the freezing chamber T a , Freezing shelf temperature T p And the material's dimensional data;

[0097] COMSOL Multiphysics software is used to encapsulate the coded software based on Windows and Linux environments, giving the visualization software the ability to run across platforms and offline without installing professional software, such as Figure 1 As shown, the parameter input bar options of the visualization software include the coding setting freezing mode option, adding a function list option to it, giving two freezing mode functions: shelf freezing and cold air freezing. The refrigerant heat transfer coefficient of the cold air freezing setting is 0.42h p . Program the demoulding option for the freezing process, and assign two functions: demoulding and non-demolding freezing. The surface radiation factor of non-demolding freezing is set to 0.35ε. Set function options for material shape, and assign five functions: cuboid, cylinder, cone, truncated table, terrace and hemisphere. Figure 2 As shown, add the input windows of the initial temperature of the material, the ambient temperature of the freezing chamber, the temperature of the freezing shelf, the length, width and height of the material, the radius of the material, the moisture content of the material (the mass fraction of moisture in the material), the soluble solid content of the material (the mass fraction of soluble solids in the material) and the crude fiber content of the material (the mass fraction of crude fiber in the material);

[0098] The analysis module is used to calculate at least the physical parameters of the material coupled with the temperature before freezing, the liquid phase volume fraction V before freezing L , the volume fraction V of the porous matrix before freezing SL , effective physical parameters of the liquid phase before freezing, effective physical parameters of the porous matrix before freezing, physical parameters of the material coupled with temperature after freezing, volume fraction V of the frozen phase after freezing F , the volume fraction V of the porous matrix after freezing SF , the effective physical property parameters of the frozen phase after the material is frozen and the effective physical property parameters of the porous matrix after the material is frozen, and the heat transfer model of the material freezing process is solved;

[0099] Among them, the material size input by the user is obtained, the physical model of the corresponding material is constructed and the mesh is refined. Material models of different geometric shapes are as follows Figure 3 As shown;

[0100] A storage module, used for storing data of the input module and the analysis module;

[0101] An output module, which is used at least to output a material freezing curve, a freezing temperature historical distribution diagram, a material phase field historical distribution diagram, and predict the material ice crystal growth start time and the material freezing end point;

[0102] The graphic output window of the visualization software is designed as follows: the material freezing curve, the freezing temperature historical distribution diagram, and the material phase field historical distribution diagram are output as results, and a resolution adaptive function is set for the window.

[0103] The present invention further claims protection for a heat transfer simulation device for a material freezing process, which comprises: a memory and a processor, wherein the memory is used to store information including program instructions, the processor is used to control the execution of the program instructions, and the program instructions are loaded and executed by the processor to implement the heat transfer simulation method for the material freezing process.

[0104] The present invention further claims protection for a computer-readable storage medium storing a computer program, wherein the computer program, when executed by a processor, can implement the heat transfer simulation method for the material freezing process.

[0105] The present invention has at least the following beneficial effects:

[0106] First, the heat transfer simulation method of the material freezing process provided by the present invention fills the gap in the simulation of the material freezing process and solves the precise control of the material freezing process;

[0107] Secondly, in the heat transfer simulation method of the freezing process of materials provided by the present invention, the mass fraction of water in the material, the mass fraction of soluble solids in the material and the mass fraction of crude fiber in the material can accurately and reliably predict the freezing end point of the material without destroying the original appearance structure of the material, accurately control the freezing cycle of the material, realize green and energy-saving freeze-drying of the material, and finally realize the standardization of freeze-drying production of the material;

[0108] Thirdly, the heat transfer simulation method of the material freezing process provided by the present invention is also coupled with the external dimensions of the material, thereby improving the accuracy of the heat transfer simulation of the material freezing process, and facilitating the prediction of the freezing process temperature, phase change and freezing end point in advance according to the differences in material properties and external shapes, thereby avoiding over-freezing or insufficient freezing, and ensuring the standardization of material freezing production and the consistency of material freezing product quality;

[0109] Fourthly, the heat transfer simulation method for the material freezing process provided by the present invention solves the problem of temperature monitoring during the freezing process of materials (especially agricultural products), the problem of difficulty in predicting the end point of material freezing, and the problem of difficulty in tracking the changes in the freezing phase field of materials.

[0110] Other advantages, objectives and features of the present invention will be embodied in part through the following description, and in part will be understood by those skilled in the art through study and practice of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0111] Figure 1 The visualization software function bar described in one technical solution of the present invention;

[0112] Figure 2 It is the visualization software parameter input bar described in another technical solution of the present invention;

[0113] Figure 3 Different geometric models of materials in another technical solution of the present invention;

[0114] Figure 4 The geometric model of the material of Example 1 of the present invention;

[0115] Figure 5 It is the grid model of the material of Example 1 of the present invention;

[0116] Figure 6 The material freezing curve of Example 1 of the present invention;

[0117] Figure 7 This is a historical distribution diagram of material freezing temperature in Example 1 of the present invention;

[0118] Figure 8 This is a historical distribution diagram of the material phase field of Example 1 of the present invention;

[0119] Fig. 9 The material freezing curve of Example 2 of the present invention;

[0120] Fig.10 This is a historical distribution diagram of material freezing temperature in Example 2 of the present invention;

[0121] Fig.11 This is a material phase field history distribution diagram of Example 2 of the present invention;

[0122] Fig.12 The material freezing curve of Example 3 of the present invention;

[0123] Fig.13 This is a historical distribution diagram of material freezing temperature in Example 3 of the present invention;

[0124] Fig.14 This is a material phase field history distribution diagram of Example 3 of the present invention;

[0125] Fig.15 The geometric model of the material of Example 4 of the present invention;

[0126] Fig.16 It is the grid model of the material of Example 4 of the present invention;

[0127] Fig.17 The material freezing curve of Example 4 of the present invention;

[0128] Fig.18 This is a historical distribution diagram of material freezing temperature in Example 4 of the present invention;

[0129] Fig.19 This is the material phase field historical distribution diagram of Example 4 of the present invention. DETAILED DESCRIPTION

[0130] The present invention is further described in detail below in conjunction with specific embodiments so that those skilled in the art can implement the invention with reference to the description.

[0131] It should be understood that the terms such as “having”, “including” and “comprising” used herein do not exclude the existence or addition of one or more other elements or combinations thereof.

[0132] Example 1

[0133] Heat transfer simulation method for freezing process of cylindrical material (radius 17mm, height 10mm):

[0134] Step 1. Select the freezing method: freeze on the shelf, freeze without demoulding;

[0135] Step 2: The initial temperature of the material is measured to be 298.15K, the mass fraction of water in the material is 89%, the mass fraction of soluble solids in the material is 10%, and the mass fraction of crude fiber in the material is 1%. The ambient temperature of the freezing chamber is set to 285.15K and the freezing shelf temperature is set to 233.15K;

[0136] Step 3: Figure 4 As shown, COMSOL Multiphysics software is used to generate the material geometry; the mesh size is set to Fine, and the geometric mesh of the synthesized material is as follows Figure 5 As shown;

[0137] Step 4: Solve the constructed heat transfer model of the material freezing process under the boundary conditions constrained by the material geometric model to obtain the freezing curve as shown in Figure 6 As shown;

[0138] Step 5: Set the material temperature history time to 30 minutes and obtain the material temperature history distribution diagram as shown below: Figure 7 As shown;

[0139] Step 6: Set the phase field history time to 30 minutes and obtain the material phase field history distribution diagram as shown below: Figure 8 As shown;

[0140] Step 7: According to Figures 6-8 The results show that the ice crystal growth time of the material is predicted to be 30.3 minutes and the freezing end point is 100 minutes, which is consistent with the actual situation.

[0141] Example 2

[0142] Heat transfer simulation method for freezing process of cylindrical material (radius 17mm, height 10mm):

[0143] Step 1. Select the freezing method: cold air freezing, demoulding freezing;

[0144] Step 2: The initial temperature of the material is measured to be 298.15K, the mass fraction of water in the material is 89%, the mass fraction of soluble solids in the material is 10%, and the mass fraction of crude fiber in the material is 1%. The ambient temperature of the freezing chamber is set to 285.15K and the freezing shelf temperature is set to 233.15K;

[0145] Step 3: Generate the geometric shape of the material using COMSOL Multiphysics software; set the mesh size to Fine and synthesize the geometric mesh of the material;

[0146] Step 4: Solve the constructed heat transfer model of the material freezing process under the boundary conditions constrained by the material geometric model to obtain the freezing curve as shown in Fig. 9 As shown;

[0147] Step 5: Set the material temperature history time to 30 minutes and obtain the material temperature history distribution diagram as shown below: Fig.10 As shown;

[0148] Step 6: Set the phase field history time to 30 minutes and obtain the material phase field history distribution diagram as shown below: Fig.11 As shown;

[0149] Step 7: According to Figures 9-11 The results show that the ice crystal growth time of the material is predicted to be 38.4 minutes and the freezing end point is 120 minutes, which is consistent with the actual situation.

[0150] Example 3

[0151] Heat transfer simulation method for freezing process of cylindrical material (radius 17mm, height 10mm):

[0152] Step 1. Select the freezing method: freeze on the shelf, freeze without demoulding;

[0153] Step 2: The initial temperature of the material is measured to be 298.15K, the mass fraction of water in the material is 49%, the mass fraction of soluble solids in the material is 41%, and the mass fraction of crude fiber in the material is 10%. The ambient temperature of the freezing chamber is set to 285.15K and the freezing shelf temperature is set to 233.15K;

[0154] Step 3: Generate the geometric shape of the material using COMSOL Multiphysics software; set the mesh size to Fine and synthesize the geometric mesh of the material;

[0155] Step 4: Solve the constructed heat transfer model of the material freezing process under the boundary conditions constrained by the material geometric model to obtain the freezing curve as shown in Fig.12 As shown;

[0156] Step 5: Set the material temperature history time to 20 minutes and obtain the material temperature history distribution diagram as shown below: Fig.13 As shown;

[0157] Step 6: Set the phase field history time to 20 minutes and obtain the material phase field history distribution diagram as shown below: Fig.14 As shown;

[0158] Step 7: According to Figures 12-14 The results show that the ice crystal growth time of the material is predicted to be 20 minutes and the freezing end point is 80 minutes, which is consistent with the actual situation.

[0159] Example 4

[0160] Heat transfer simulation method for the freezing process of rectangular materials (length 10mm, width 10mm):

[0161] Step 1. Select the freezing method: freeze on the shelf, freeze without demoulding;

[0162] Step 2: The initial temperature of the material is measured to be 298.15K, the mass fraction of water in the material is 89%, the mass fraction of soluble solids in the material is 10%, and the mass fraction of crude fiber in the material is 1%. The ambient temperature of the freezing chamber is set to 285.15K and the freezing shelf temperature is set to 233.15K;

[0163] Step 3: Use COMSOL Multiphysics software to generate the material geometry as follows Fig.15 As shown; set the grid size to Fine, the geometric grid of the composite material is as follows Fig.16 As shown;

[0164] Step 4: Solve the constructed heat transfer model of the material freezing process under the boundary conditions constrained by the material geometric model to obtain the freezing curve as shown in Fig.17 As shown;

[0165] Step 5: Set the material temperature history time to 30 minutes and obtain the material temperature history distribution diagram as shown below: Fig.18 As shown;

[0166] Step 6: Set the phase field history time to 30 minutes and obtain the material phase field history distribution diagram as shown below: Fig.19 As shown;

[0167] Step 7: According to Figures 17 to 19 The results show that the ice crystal growth time of the material is predicted to be 26.6 minutes and the freezing end point is 80 minutes, which is consistent with the actual situation.

[0168] By comparing the data results of Examples 1 to 4, it can be clearly found that the ice crystal growth time and the freezing end point during the freezing process of the material are affected by the material's external dimensions, freezing method, and the proportion of each component in the material.

[0169] The number of equipment and processing scale described here are used to simplify the description of the present invention. The application, modification and variation of the heat transfer simulation method, system, device and medium for material freezing process of the present invention will be obvious to those skilled in the art.

[0170] Although the embodiments of the present invention have been disclosed as above, they are not limited to the applications listed in the specification and the implementation modes, and they can be fully applied to various fields suitable for the present invention. For those familiar with the art, additional modifications can be easily implemented. Therefore, without departing from the general concept defined by the claims and the scope of equivalents, the present invention is not limited to the specific details and the illustrations shown and described herein.

Claims

1. A heat transfer simulation method for a material freezing process, characterized in that: include: Step 1: According to the physical properties of the material before freezing, obtain the liquid phase volume fraction V of the material before freezing L , the volume fraction V of the porous matrix before freezing SL , the effective physical property parameters of the liquid phase before freezing the material and the effective physical property parameters of the porous matrix before freezing the material, wherein the effective physical property parameters of the liquid phase before freezing the material include: the effective density of the liquid phase ρ L , Liquid effective specific heat capacity Cp L And the liquid phase effective thermal conductivity γ L , the effective physical properties of the porous matrix before freezing include: the effective density of the porous matrix ρ SL , effective specific heat capacity of porous matrix Cp SL and the effective thermal conductivity γ of the porous matrix SL ; Step 2: According to the physical properties of the material after freezing, obtain the frozen phase volume fraction V of the material after freezing F , the volume fraction V of the porous matrix after freezing SF , the effective physical property parameters of the frozen phase after the material is frozen and the effective physical property parameters of the porous matrix after the material is frozen, wherein the effective physical property parameters of the frozen phase after the material is frozen include: the effective density ρ of the frozen phase F , effective specific heat capacity of frozen phase Cp F and the effective thermal conductivity γ of the frozen phase F The effective physical properties of the porous matrix after freezing include the effective density of the porous matrix ρ SF , effective specific heat capacity of porous matrix Cp SF and the effective thermal conductivity γ of the porous matrix SF ; Step 3: Based on the parameters in steps 1 and 2, the heat transfer model of the material freezing process is constructed as follows: Where ΔH L→F represents the latent heat of phase change from liquid phase to frozen phase, J; ρ eff Indicates the effective density of the material, kg / m 3 ; Cp eff Indicates the effective specific heat capacity of the material, J / kg / K; γ eff Indicates the effective thermal conductivity of the material, W / m·K; Q1 represents the heat radiated from the environment to the material, J; Q2 represents the heat released by the material to the shelf, J; T i Indicates the temperature at any time point during the freezing process of the material, K; a represents the ratio of thermal diffusivity between the liquid phase and the frozen phase; θ L and θ F represent the saturation fractions of liquid phase and frozen phase respectively, %; ε represents the surface radiation factor, 0.74; σ denotes the Stefan-Boltzmann constant; h p Represents the heat transfer coefficient of the refrigerant medium, 62.3 W / (m 2 K); T a represents the ambient temperature of the freezing chamber, K; T p represents the freezing shelf temperature, K.

2. The heat transfer simulation method for material freezing process according to claim 1, characterized in that: The liquid volume fraction V before freezing of the material in step 1 L and the volume fraction V of the porous matrix before freezing SL The method of obtaining is as follows: Before freezing: Liquid volume fraction V L ,%,V L =(X w / ρ w +X c / ρ c ) / (X w / ρ w +X f / ρ f +X c / ρ c ); The volume fraction of the porous matrix V SL ,%,V SL =X f / ρ f / (X w / ρ w +X f / ρ f +X c / ρ c ); The method for obtaining the effective physical property parameters of the liquid phase before freezing the material in step 1 is as follows: Liquid effective density ρ L ,kg / m 3 , ρ L = 1 / (X w / ρ w +X c / ρ c ); Liquid effective specific heat capacity Cp L , J / kg / K, Cp L = Cp w ×X w +Cp c ×X c ; Liquid phase effective thermal conductivity γ L , W / m·K, γ L = γ w × (X w / ρ w / (X w / ρ w +Xc / ρ c )) +γc×(X c / ρ c / (X w / ρ w +X c / ρ c )); The method for obtaining the effective physical property parameters of the porous matrix before freezing the material in step 1 is as follows: Porous matrix effective density ρ SL ,kg / m 3 , ρ SL = 1 / (X c / ρ c ); Porous matrix effective specific heat capacity Cp SL , J / kg / K, Cp SL = Cp f ×X f ; Effective thermal conductivity of porous matrix γ SL , W / m·K, γ SL =γ f ×X f / ρ f ; Among them, X w Indicates the mass fraction of moisture in the material, %; X c Indicates the mass fraction of soluble solids in the material, %; X f Indicates the mass fraction of crude fiber in the material, %; ρ w Indicates the moisture density of the material before freezing ρ w ,kg / m 3 ; ρ c Indicates the soluble solid density of the material before freezing, kg / m 3 ; ρ f Indicates the crude fiber density of the material before freezing, kg / m 3 ; Cp w Indicates the specific heat capacity of water before freezing of the material, J / kg / K; Cp c It indicates the specific heat capacity of soluble solids before freezing of the material, J / kg / K; Cp f It indicates the specific heat capacity of crude fiber before freezing of the material, J / kg / K; γ w Indicates the moisture thermal conductivity of the material before freezing, W / m·K; γ c Indicates the thermal conductivity of soluble solids before freezing of the material, W / m·K; γ f It indicates the thermal conductivity of crude fiber before freezing of the material, W / m·K.

3. The heat transfer simulation method for material freezing process according to claim 2, characterized in that: The physical properties of the material before freezing are obtained by coupling with the temperature, as follows: Moisture density of the material before freezing ρ w = 997.18+0.0031439×T1-0.0037574×T1 2 ; Soluble solid density ρ before freezing c = 1599.1-0.31046×T1; Crude fiber density ρ before freezing f = 1311.5-0.36589×T1; Specific heat capacity of water before freezing of materials Cp w =4176.2-0.090864×T-0.0054731×T1 2 ; Specific heat capacity of soluble solids before freezing Cp c =1548.8+1.9625×T1×-0.0059399×T1 2 ; Crude fiber specific heat capacity Cp before material freezing f = 1845.9+1.8306×T1×-0.0046509×T1 2 ; Thermal conductivity of moisture before freezing of the material γ w =0.57109+0.0017625×T1-6.7036×10 -6 ×T1 2 ; Thermal conductivity of soluble solids before freezing γ c =0.20141+0.0013874×T1-4.3312×10 -6 ×T1 2 ; Thermal conductivity of crude fiber before freezing γ f =0.18331+0.0012497×T1-3.1683×10 -6 ×T1 2 ; Where T1 represents the initial temperature of the material, K.

4. The heat transfer simulation method for material freezing process according to claim 3, characterized in that: The frozen phase volume fraction V after freezing of the material in step 2 F , the volume fraction V of the porous matrix after freezing SF The method to obtain is as follows: After freezing: Frozen phase volume fraction V F ,%,V F =(X w / ρ i / +X c / ρ ci ) / (X w / ρ i +X f / ρ fi +X c / ρ ci ); The volume fraction of the porous matrix V SF ,%,V SF =X f / ρfi / (X w / ρ i +X f / ρ fi +X c / ρ ci ); The method for obtaining the effective physical property parameters of the frozen phase after the material is frozen in step 2 is as follows: Frozen phase effective density ρ F ,kg / m 3 , ρ F = 1 / (X w / ρ i +X c / ρ ci ); Effective specific heat capacity of frozen phase Cp F , J / kg / K, Cp F = Cp i ×X w +Cp ci ×X c ; Effective thermal conductivity of frozen phase γ F , W / m·K, γ F = γ i × (Xw / ρ i / (Xw / ρ i +Xc / ρ ci )) +γci×(Xc / ρ ci / (Xw / ρi+Xc / ρ ci )); The method for obtaining the effective physical property parameters of the porous matrix after the material is frozen in step 2 is as follows: Porous matrix effective density ρ SF ,kg / m 3 , ρ SF = 1 / (X c / ρ ci ); Porous matrix effective specific heat capacity Cp SF , J / kg / K, Cp SF = Cp fi ×X f ; Effective thermal conductivity of porous matrix γ SF , W / m·K, γ SF =γ fi ×X f / ρ fi ; Among them, ρ i Indicates the ice density of the material after freezing, kg / m 3 ; ρ ci Indicates the soluble solid density of the material after freezing; ρ fi Indicates the crude fiber density of the material after freezing, kg / m 3 ; Cp i It indicates the specific heat capacity of ice after freezing the material, J / kg / K; Cp ci It indicates the specific heat capacity of soluble solids after freezing of the material, J / kg / K; Cp fi It indicates the specific heat capacity of crude fiber after freezing of the material, J / kg / K; γ i Indicates the thermal conductivity of moisture after freezing of the material, W / m·K; γ ci Indicates the thermal conductivity of soluble solids after freezing of the material; γ fi It indicates the thermal conductivity of crude fiber after freezing of the material, W / m·K.

5. The heat transfer simulation method for material freezing process according to claim 4, characterized in that: The physical properties of the material after freezing are obtained by coupling with the temperature, as follows: Ice density of frozen material ρ i = 916.89-0.1307×T i ; Soluble solid density of the material after freezing ρ ci = 1599.1-0.31046×T i ; Crude fiber density ρ after freezing of the material fi = 1311.5-0.36589×T i ; Specific heat capacity of ice after freezing of material Cp i =2062.3+6.0769×T i ; Specific heat capacity of soluble solids after freezing of materials Cp ci =1548.8+1.9625×T i ×-0.0059399×T i 2 ; Crude fiber specific heat capacity Cp after material freezing fi = 1845.9+1.8306×T i ×-0.0046509×T i 2 ; Thermal conductivity of moisture after freezing of material γ i =2.2196-6.2489×10 -3 ×T i +1.0154×10 -4 ×T i 2 ; Thermal conductivity of soluble solids after freezing of the material γ ci =0.20141+0.0013874×T i -4.3312×10 -6 ×T i 2 ; Thermal conductivity of crude fiber after freezing of material γ fi =0.18331+0.0012497×T i -3.1683×10 -6 ×T i 2 ; Among them, T i Indicates the temperature of the material at any point in time during the freezing process, K.

6. The heat transfer simulation method for material freezing process according to claim 5, characterized in that: The method also includes the step of further coupling the heat transfer model of the material freezing process obtained in step three with the material shape to construct a heat transfer model of the freezing process of materials with different shapes. Specifically, the method comprises: obtaining the material size using COMSOL Multiphysics software, constructing a geometric model of the material and performing mesh refinement, and solving the heat transfer model of the material freezing process constructed in step three under the boundary conditions constrained by the geometric model of the material.

7. A heat transfer simulation system based on the heat transfer simulation method of the material freezing process according to claim 6, characterized in that: include: The input module is used to input at least the mass fraction X of moisture in the material. w , the mass fraction of soluble solids in the material X c , the mass fraction of crude fiber in the material X f , represents the initial temperature of the material T1, the ambient temperature of the freezing chamber T a , Freezing shelf temperature T p And the material's dimensional data; The analysis module is used to calculate at least the physical parameters of the material coupled with the temperature before freezing, the liquid phase volume fraction V before freezing L , the volume fraction V of the porous matrix before freezing SL , effective physical parameters of the liquid phase before freezing, effective physical parameters of the porous matrix before freezing, physical parameters of the material coupled with temperature after freezing, volume fraction V of the frozen phase after freezing F , the volume fraction V of the porous matrix after freezing SF , the effective physical property parameters of the frozen phase after the material is frozen and the effective physical property parameters of the porous matrix after the material is frozen, and the heat transfer model of the material freezing process is solved; A storage module, used for storing data of the input module and the analysis module; The output module is used at least to output the material freezing curve, the freezing temperature historical distribution diagram, the material phase field historical distribution diagram, and predict the material ice crystal start growth time and material freezing end point.

8. Heat transfer simulation device for material freezing process, characterized in that: include: A memory and a processor, wherein the memory is used to store information including program instructions, and the processor is used to control the execution of the program instructions, and the program instructions are loaded and executed by the processor to implement the heat transfer simulation method for the material freezing process described in 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 can implement the heat transfer simulation method for the material freezing process described in any one of claims 1 to 6.

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