Phase change mass transfer rate calculation method and device, electronic equipment and storage medium

Abstract

The application discloses a phase change mass transfer rate calculation method and device, electronic equipment and a storage medium, and relates to the technical field of engineering, and is used to solve the problem that the output phase change mass transfer rate cannot accurately reflect the difference between the actual condensation amount or evaporation amount of each component, and the simulation result deviates from the actual situation in the related art. The method comprises the following steps: obtaining the partial pressure values of each component in the gas phase of a gas-liquid mixture and the first proportion parameters of each component in the liquid phase; determining the target vapor pressure of each component under the gas-liquid equilibrium state according to the partial pressure values and the first proportion parameters; calculating the target temperature of each component based on the target vapor pressure of each component and the preset characteristic relationship corresponding to each component; and calculating the phase change mass transfer rate of each component according to the target temperature and the actual temperature of the gas-liquid mixture through a preset phase change mass transfer rate model.

Description

Technical Field

[0001] This application relates to the field of engineering technology, and in particular to a method, apparatus, electronic device and storage medium for calculating phase change mass transfer rate. Background Technology

[0002] With the advancement of computer technology and the rapid development of computational fluid dynamics (CFD) and numerical heat transfer, numerical simulation has become an important tool for studying phase change processes in multi-component fluids. CFD technology allows for a relatively clear understanding of the operational status of computational models under various conditions. In fields such as chemical distillation, brewing, and energy, the condensation and evaporation phase change processes of multi-component mixtures such as water-ethanol are widespread, and their numerical simulation has significant engineering value for equipment optimization and energy consumption control.

[0003] In related technologies, the Lee model is the main phase transition model used in CFD simulation studies of evaporation and condensation. However, in multi-component systems, the volatility and condensation characteristics of different components vary, leading to different migration rates and directions of each component between the gas and liquid phases during the phase transition process, exhibiting selective condensation or evaporation behavior. The traditional Lee model treats each component as a single medium, failing to independently describe the phase transition characteristics of different components. This makes it difficult to accurately capture the selective phase transition behavior in multi-component systems, and the output phase transition mass transfer rate cannot accurately reflect the differences in the actual condensation or evaporation rates of each component, resulting in discrepancies between the simulation results and actual conditions. Summary of the Invention

[0004] This application provides a method, apparatus, electronic device, and storage medium for calculating phase change mass transfer rate, which can solve the problem in related technologies that the output phase change mass transfer rate cannot accurately reflect the differences in the actual condensation or evaporation of each component, and the simulation results deviate from the actual situation.

[0005] In a first aspect, this application provides a method for calculating the phase change mass transfer rate, the method comprising: The partial pressure values ​​of each component in the gas phase of the gas-liquid mixture and the first proportion parameter of each component in the liquid phase are obtained. Based on the partial pressure values ​​and the first proportion parameters, the target vapor pressure of each component under gas-liquid equilibrium state is determined; Based on the target vapor pressures and the preset characteristic relationships corresponding to each component, the target temperatures of each component are calculated; wherein, the preset characteristic relationships are used to characterize the correspondence between the vapor pressure and temperature of a single component; Using a preset phase change mass transfer rate model, the phase change mass transfer rate of each component is calculated based on the target temperature and the actual temperature of the gas-liquid mixture. The phase change mass transfer rate model is used to determine the mass transfer rate during the gas-liquid phase change process.

[0006] In some embodiments, obtaining the partial pressure values ​​of each component in the gas phase of the gas-liquid mixture includes: Obtain the total gas phase pressure in the gas-liquid mixture, and the second proportion parameter of each component in the gas phase; Each of the second percentage parameters is multiplied by the total gas phase pressure to obtain the partial pressure value.

[0007] In some embodiments, determining the target vapor pressure of each component under gas-liquid equilibrium state based on each of the partial pressure values ​​and each of the first proportion parameters includes: Obtain the theoretical vapor pressure of each component in its pure state; Based on each of the first proportion parameters and the corresponding theoretical vapor pressure, the theoretical vapor pressure of each component in the liquid phase is calculated; Using a pre-defined gas-liquid equilibrium correlation model, the target vapor pressure of each component is calculated based on its partial pressure and theoretical vapor partial pressure. The gas-liquid equilibrium correlation model uses the constraint equation that the partial pressure of each component in the gas phase at gas-liquid equilibrium is equal to its theoretical vapor partial pressure in the liquid phase.

[0008] In some embodiments, before determining the target vapor pressure of each component under gas-liquid equilibrium based on each of the partial pressure values ​​and each of the first proportion parameters, the method further includes: Obtain the liquid phase content of the gas-liquid mixture; When the liquid phase content is greater than or equal to a preset threshold and the gas-liquid mixture is a non-pure liquid phase, the step of determining the target vapor pressure of each component under gas-liquid equilibrium state based on each partial pressure value and each first proportion parameter is performed. When the liquid phase content is less than the preset threshold, the target temperature of each component is calculated based on the partial pressure value of each component and the corresponding preset characteristic relationship, and the phase change mass transfer rate is calculated based on the target temperature and the actual temperature using the phase change mass transfer rate model.

[0009] In some embodiments, after obtaining the liquid phase content of the gas-liquid mixture, the method further includes: When the liquid phase content is within a preset range, each partial pressure value is used as the first vapor pressure of each component, and the second vapor pressure of each component under the gas-liquid equilibrium state is calculated based on each partial pressure value and each first proportion parameter, wherein the preset threshold is within the preset range; Obtain a first weight for the first vapor pressure and a second weight for the second vapor pressure, wherein the first weight is negatively correlated with the liquid phase content and the second weight is positively correlated with the liquid phase content; The first vapor pressure and the second vapor pressure are weighted and calculated according to the first weight and the second weight to obtain the target vapor pressure.

[0010] In some embodiments, the method further includes: When the gas-liquid mixture is a pure liquid phase, the theoretical vapor pressure of each component in its pure substance state is obtained; Based on the theoretical vapor pressures and the corresponding preset characteristic relationships, the target temperatures of each component are calculated. Using the phase change mass transfer rate model, the phase change mass transfer rate of each component is calculated based on the target temperature and the actual temperature.

[0011] In some embodiments, the method further includes: The physical state parameters of the gas-liquid mixture are updated based on the phase change mass transfer rate of each component using a preset gas-liquid two-phase flow model. Based on the updated physical state parameters, the phase transition mass transfer rate of each component is iteratively calculated until the preset convergence condition is met, and the converged physical state parameters are output.

[0012] Secondly, this application provides a phase change mass transfer rate calculation device, the device comprising: The acquisition module is used to acquire the partial pressure values ​​of each component in the gas phase of the gas-liquid mixture, and the first proportion parameter of each component in the liquid phase; The determining module is used to determine the target vapor pressure of each component under gas-liquid equilibrium state based on each of the partial pressure values ​​and each of the first proportion parameters; The temperature calculation module is used to calculate the target temperature of each component based on the target vapor pressure and the preset characteristic relationship corresponding to each component; wherein, the preset characteristic relationship is used to characterize the correspondence between the vapor pressure and temperature of a single component; The mass transfer rate calculation module is used to calculate the phase change mass transfer rate of each component based on the target temperature and the actual temperature of the gas-liquid mixture using a preset phase change mass transfer rate model. The phase change mass transfer rate model is used to determine the mass transfer rate during the gas-liquid phase change process.

[0013] Thirdly, this application provides an electronic device, comprising: Memory, used to store computer programs; When the processor executes the computer program stored in the memory, it implements the phase change mass transfer rate calculation method of the first aspect described above.

[0014] Fourthly, this application provides a computer-readable storage medium storing a computer program, which, when executed by a processor, implements the phase transition mass transfer rate calculation method of the first aspect described above.

[0015] Fifthly, this application provides a computer program product comprising: computer program code, which, when run on a computer, causes the computer to execute the phase change mass transfer rate calculation method of the first aspect described above.

[0016] In the aforementioned method, apparatus, electronic equipment, and storage medium for calculating phase change mass transfer rate, the target vapor pressure of each component under gas-liquid equilibrium is accurately derived by combining gas phase partial pressure and liquid phase composition data. The target vapor pressure is then converted into target temperature using the physical property relationships of the pure components, thereby quantifying the complex phase equilibrium problem into an intuitive deviation between the target temperature and the actual temperature. Then, based on this temperature deviation, the phase change mass transfer rate model can be driven to quantitatively calculate the actual mass transfer rate of each component during the gas-liquid phase change process. This enables differentiated rate calculation of the selective condensation or evaporation behavior of each component, significantly improving the accuracy and reliability of CFD simulation in predicting the difference between actual condensation and evaporation rates. Attached Figure Description

[0017] Figure 1 A flowchart illustrating a method for calculating phase change mass transfer rate provided in an embodiment of this application; Figure 2 This is a schematic diagram of the structure of a phase change mass transfer rate calculation device provided in an embodiment of this application; Figure 3 This is a schematic diagram of an electronic device structure provided in an embodiment of this application. Detailed Implementation

[0018] To make the objectives, technical solutions, and advantages of this application clearer, the application will be further described in detail below with reference to the accompanying drawings. The specific operational methods in the method embodiments can also be applied to the device embodiments or system embodiments. It should be noted that in the description of this application, "multiple" is understood as "at least two". "And / or" describes the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing together, or B existing alone. A connected to B can represent: A and B directly connected, or A and B connected through C. Furthermore, in the description of this application, terms such as "first" and "second" are used only for distinguishing the purpose of description and should not be construed as indicating or implying relative importance or order.

[0019] The technical solution provided in this application will be described in detail below with reference to the accompanying drawings and specific embodiments.

[0020] Figure 1 A flowchart illustrating a method for calculating phase change mass transfer rate provided in this application embodiment includes the following steps: S101, obtain the partial pressure values ​​of each component in the gas phase of the gas-liquid mixture, and the first proportion parameter of each component in the liquid phase; S102, determine the target vapor pressure of each component under gas-liquid equilibrium state based on each partial pressure value and each first proportion parameter; S103, calculate the target temperature of each component based on the target vapor pressure and the preset characteristic relationship of each component; S104 calculates the phase change mass transfer rate of each component based on the target temperature and the actual temperature of the gas-liquid mixture using a preset phase change mass transfer rate model.

[0021] Here, a gas-liquid mixture refers to a two-phase system comprising at least two condensable components, such as a water-ethanol binary mixture, a methanol-water binary mixture, or an acetone-water binary mixture. The specific application scenario depends on the operating conditions and is not limited here. In the numerical simulation, the gas-liquid mixture is discretized into several computational grid cells. A component refers to the types of substances that coexist in both the gas and liquid phases, such as water and ethanol in a water-ethanol binary mixture.

[0022] For example, firstly, the partial pressure values ​​of each component in the gas phase of the gas-liquid mixture are obtained using Dalton's law of partial pressures. Simultaneously, the first proportion parameter of each component in the liquid phase is obtained, whereby the first proportion parameter is used to characterize the relative content of each component in the liquid phase, and can be mole fraction, mass fraction, or volume fraction, depending on the modeling requirements, and is not limited here.

[0023] Mole fraction is the dimensionless ratio of the amount of a component to the total amount of substance in the liquid phase. In ideal solutions, mole fraction is the standard input parameter in Raoult's law calculations. In numerical simulations, the mole fraction of each component in the liquid phase is obtained directly by the CFD solver through solving the component transport equations, or it can be converted from the mass fraction.

[0024] Mass fraction refers to the ratio of the mass of a component to the total mass of the liquid phase, and it is dimensionless. In numerical simulations, the mass fraction of each component in the liquid phase is directly obtained by the CFD solver by solving the component transport equations.

[0025] Volume fraction refers to the ratio of the volume of a component to the total volume of the liquid phase, and it is dimensionless. In numerical simulations, the volume fraction of each component in the liquid phase is calculated by the CFD solver based on the mass fraction and density of each component.

[0026] In this embodiment, the first proportion parameter is illustrated using mole fraction as an example, but it should not be construed as limiting the scope of protection of this application. In practical applications, if the CFD solver directly outputs the mass fraction, the mass fraction must first be converted into mole fraction before being substituted into Raoult's law for calculation.

[0027] Therefore, based on Raoult's law, the target vapor pressure of each component under gas-liquid equilibrium is determined according to the partial pressure values ​​and the first proportion parameters. The target vapor pressure refers to the saturated vapor pressure that each component should have on the liquid phase surface under gas-liquid equilibrium.

[0028] Then, based on the target vapor pressures and the corresponding preset characteristic relationships of each component, the target temperatures of each component are calculated. The preset characteristic relationships characterize the correspondence between the vapor pressure and temperature of a single component. The vapor pressure and temperature referred to in this application, when applied to a single component, essentially refer to the saturated vapor pressure and saturated temperature of that component. This is because the preset characteristic relationships are essentially characteristic curves between saturated vapor pressure and saturated temperature, which are determined by the intrinsic properties of the substance and represent a one-to-one correspondence.

[0029] Finally, using a preset phase change mass transfer rate model, the phase change mass transfer rate of each component is calculated based on the target temperature and the actual temperature of the gas-liquid mixture. The phase change mass transfer rate model is used to determine the amount of mass transferred per unit time and per unit volume of each component during the gas-liquid phase change process. The phase change mass transfer rate model can be the Lee model, Tanasawa model, Schrage model, etc., depending on the application scenario and accuracy requirements, and is not limited here.

[0030] The target temperature is used to determine whether a phase transition process exists within the current computational cell. Within the current computational grid cell, if the actual temperature is higher than the target temperature of a component, that component is in an evaporation process; if the actual temperature is lower than the target temperature, that component is in a condensation process; if the two are equal, the system is in gas-liquid equilibrium and there is no phase transition. Since different components each have independent target temperatures, at the same actual temperature, one component may evaporate while another may condense, thus demonstrating the selective phase transition characteristics of multi-component systems. For example, in the condensation process of a water-ethanol binary mixture, at the same actual temperature, the target temperature of water may be higher than the actual temperature (water condenses), while the target temperature of ethanol may be lower than the actual temperature (ethanol does not condense or may even evaporate), thus achieving selective separation of water and ethanol.

[0031] The following example uses the Lee phase transition model and the presupposed characteristic relationship, the Antoine formula. The Antoine formula is a semi-empirical vapor pressure equation used to describe the functional relationship between the saturated vapor pressure of a pure substance and its saturation temperature. Its expression is: Where P is the saturated vapor pressure (usually in mmHg or kPa); T is the saturation temperature (usually in °C); and A, B, and C are the Antoine constants of the substance, the values ​​of which depend on the chosen temperature range and pressure unit. For example, for water, with a vapor pressure in mmHg and a temperature range of 1–100 °C, A = 8.07131, B = 1730.63, and C = 233.426; for ethanol, with a vapor pressure in mmHg and a temperature range below the normal boiling point (e.g., 78.32 °C), A = 8.20417, B = 1642.89, and C = 230.300.

[0032] The Antoine formula can also be expressed in natural logarithmic form; the two forms are mathematically equivalent, requiring only adjustments based on the chosen constant system. The solution of this invention does not depend on the specific formula form chosen, as long as it can characterize the mapping relationship between saturated vapor pressure and saturated temperature.

[0033] Therefore, for any component, once its saturated vapor pressure is known, substituting the saturated vapor pressure into the inverse function form of the Antoine formula allows us to calculate the saturation temperature corresponding to that saturated vapor pressure, which can be expressed as: .

[0034] Then the condensation mass transfer rate ,in, The condensation relaxation coefficient is... It is the liquid volume fraction. The density of the liquid phase is... The actual temperature of the gas-liquid mixture; evaporation mass transfer rate. ,in, This is the evaporation relaxation coefficient. It is the liquid volume fraction. Wherein, is the liquid phase density. , The phase transition mass transfer coefficient is an empirical adjustment parameter in the Lee model used to control the phase transition rate. Its specific value needs to be determined based on physical experiments or literature calibration, and it usually ranges from 0.1 to 1.0.

[0035] By substituting the saturation temperature of each component and the actual temperature of the gas-liquid mixture into the Lee model, the phase change mass transfer rate of each component can be obtained.

[0036] Using the above method, based on the coupling of Dalton's law of partial pressures and Raoult's law, and utilizing the grid-level total vapor pressure, component proportion, and liquid mole fraction provided by the CFD solver, the target vapor pressure that each component should have under gas-liquid equilibrium is accurately obtained. Then, relying on the intrinsic property relationship of the Antoine formula, the independent target temperature of each component is calculated, establishing a personalized phase transition criterion for each component in the multi-component system. On this basis, the target temperatures are compared with the actual temperatures, and the Lee phase transition model is driven to calculate the mass transfer rate of each component. This allows for the accurate differentiation of the phase transition direction and intensity of different components at the same actual temperature, truly reflecting the selective separation behavior of the multi-component system. Thus, when performing numerical simulations based on the Lee model, the physical realism and quantitative accuracy of evaporation-condensation CFD simulations are significantly improved.

[0037] In some embodiments, exemplarily illustrated, obtaining the partial pressure values ​​of each component in the gas phase of a gas-liquid mixture includes, but is not limited to: The total pressure of the gas phase in the gas-liquid mixture and the second proportion parameter of each component in the gas phase are obtained. The second proportion parameter is multiplied by the total pressure of the gas phase to obtain the partial pressure value of each component.

[0038] The total gas phase pressure of the current computational grid cell is obtained through a CFD solver. Each computational grid cell stores physical quantities such as temperature, pressure, volume fraction, and mass fraction of each component. The second proportion parameter is used to characterize the relative content of each component in the gas phase, and can be mole fraction, volume fraction, or mass fraction. For multi-component systems, the sum of the mole fractions of each component in the gas phase is 1.

[0039] Using the above method, the total vapor pressure and the second proportion parameters of each component are obtained in real time within the computational grid cell. Based on Dalton's law of partial pressures, the partial pressure values ​​of each component are obtained by direct multiplication, providing accurate vapor pressure input for subsequent calculation of the target vapor pressure using Raoult's law.

[0040] In some embodiments, it is exemplarily illustrated that the target vapor pressure of each component under vapor-liquid equilibrium is determined based on each partial pressure value and each first proportion parameter, including but not limited to: First, obtain the theoretical vapor pressure of each component in its pure state. The theoretical vapor pressure refers to the saturated vapor pressure of each component in its pure state at the current temperature, which is determined by the intrinsic properties of the substance.

[0041] For example, for component i, its theoretical vapor pressure P in its pure substance state ip * It can be calculated using the Antoine formula. That is, obtain the actual temperature of the current computational grid cell, substitute the actual temperature into the Antoine formula, and you can obtain P at that actual temperature. ip * .

[0042] Then, based on each first proportion parameter and its corresponding theoretical vapor pressure, the theoretical vapor partial pressure of each component in the liquid phase is calculated.

[0043] According to Raoult's law, in an ideal solution, the saturated vapor pressure of a component is equal to the saturated vapor pressure of the pure component at the same temperature multiplied by the mole fraction of that component in the liquid phase: P i * =x i，l P ip * , where P i * P is the saturated vapor pressure (i.e., theoretical vapor partial pressure) of component i in the liquid phase, in Pa. ip * x is the saturated vapor pressure (i.e., target vapor pressure) of pure component i at the same temperature, in Pa; i，l Let i be the mole fraction of component i in the liquid phase.

[0044] Finally, using a pre-defined gas-liquid equilibrium correlation model, the target vapor pressure of each component is calculated based on its partial pressure and theoretical vapor partial pressure. The gas-liquid equilibrium correlation model uses the fact that the partial pressure of each component in the gas phase at gas-liquid equilibrium is equal to its theoretical vapor partial pressure in the liquid phase as the constraint equation.

[0045] For example, when the gas and liquid phases reach equilibrium, for component i, its partial pressure P in the gas phase is... i It is equal to its theoretical vapor pressure P in the liquid phase i * That is, P i =P i * By combining the equations, we can obtain: ,in, The total pressure of the gas phase. Let be the mole fraction of component i in the gas phase. Then the gas-liquid equilibrium correlation model is: .

[0046] The calculation method based on Raoult's law described above applies to scenarios where the liquid phase satisfies the ideal solution assumption, such as binary ideal solution systems like water-ethanol and methanol-water under low pressure conditions. For liquid mixtures with stronger non-ideal properties, a modified Raoult's law can be used (i.e., introducing the activity coefficient γ of component i). i , The correction can be made using either the state equation method or the state equation method, depending on the application scenario and accuracy requirements, and is not limited here.

[0047] Using the above method, based on the Antoine formula and utilizing the actual temperature of the current grid provided by the CFD solver, the theoretical saturated vapor pressure of each component in its pure state is accurately calculated. Then, combined with the liquid phase mole fraction, the theoretical vapor partial pressure of that component in the liquid phase is obtained through Raoult's law, establishing a reasonable vapor pressure calibration bridge between the intrinsic properties of pure substances and the actual mixed system of multiple components. On this basis, taking the equalization of the vapor phase partial pressure and the theoretical vapor partial pressure of the liquid phase at gas-liquid equilibrium as a physical constraint, the target vapor pressure of each component is derived through a pre-set gas-liquid equilibrium correlation model. This ensures that the solution process for the target vapor pressure strictly follows the thermodynamic consistency condition, avoiding the physical distortion caused by directly using the vapor pressure of pure substances to replace the vapor pressure of the mixed system. Thus, an accurate thermodynamic starting point is provided for the subsequent independent target temperature back-calculation of each component and the prediction of selective phase transition behavior.

[0048] In some embodiments, exemplarily illustrated, before determining the target vapor pressure of each component under vapor-liquid equilibrium based on each partial pressure value and each first proportion parameter, the method further includes: First, the liquid phase content of the gas-liquid mixture is obtained, where the liquid phase content refers to the volume fraction of the liquid phase within the current computational grid cell.

[0049] In the Volume of Fluid (VOF) gas-liquid two-phase flow model, the liquid phase content within the computational grid cell is characterized by a volume fraction α, where α=1 represents a pure liquid phase, α=0 represents a pure gas phase, and 0<α<1 represents a gas-liquid mixture. This liquid phase content is directly obtained by the CFD solver at each time step by solving the phase fraction transport equation and is one of the standard output variables of the VOF model.

[0050] Then, determine whether α is less than the preset threshold α. th , where α th It is a critical value used to determine whether the liquid phase content of the current grid cell is sufficient. When α is lower than α th When the liquid phase content is extremely low, directly using calculation methods based on Raoult's law will lead to numerical anomalies (such as the denominator approaching zero and unstable property calculations); when α reaches or exceeds α th At this point, the liquid phase is sufficient to form a continuous phase, and calculations based on Raoult's law can be used. α thThe value range is 1×10 -5 Up to 1×10 -4 For example, 0.00075. The specific value needs to be determined through sensitivity analysis, that is, for specific working conditions, test the impact of different thresholds on the calculation results, and select the smallest threshold that is stable and physically reasonable for the calculation results.

[0051] To elaborate, in α≥α th If the gas-liquid mixture is a non-pure liquid phase (i.e., α < 1), it indicates that there is a sufficient amount of liquid phase within the current grid cell to satisfy the applicable conditions of Raoult's law. At this point, the step of determining the target vapor pressure of each component under gas-liquid equilibrium state based on each partial pressure value and each first proportion parameter is performed, that is, considering the mixing effect between components, the target vapor pressure of each component is accurately calculated.

[0052] In 0≤α<α th In this case, the liquid phase content within the current grid cell is extremely low. If Raoult's law is applied for calculation under these circumstances, numerical anomalies will occur. Therefore, a simplified approach is adopted using the partial pressure law of a single component, i.e., ignoring the mixing effect between components. Based on the partial pressure values ​​of each component and their corresponding preset characteristic relationships, the target temperature of each component is calculated. Then, using a phase change mass transfer rate model, the phase change mass transfer rate of each component is calculated based on the target temperature and the actual temperature.

[0053] Using the above method, a liquid phase content threshold judgment mechanism is introduced before the target vapor pressure calculation. Utilizing the liquid phase volume fraction α provided by the CFD solver in the VOF model for each mesh element, it accurately identifies whether the current mesh meets the applicable conditions of Raoult's law; when α ≥ α th When 0 ≤ α < α, it indicates that the liquid phase is sufficient to form a continuous phase. At this point, an accurate mixing model based on Raoult's law is executed to fully consider the mixing effects between components and obtain a highly accurate target vapor pressure. However, when 0 ≤ α < α... th When the liquid phase volume fraction approaches zero, the algorithm intelligently switches to the single-component partial pressure law for simplification, effectively avoiding numerical instability issues such as denominator anomalies and property calculation divergences caused by the liquid phase volume fraction approaching zero. This not only ensures the numerical robustness and computational continuity of multi-component phase change simulation across the entire liquid phase content range, but also preserves the accurate characterization of mixing effects in regions with sufficient liquid phase and reduces unnecessary computational overhead in regions with scarce liquid phase, achieving a synergistic optimization of computational accuracy and numerical stability.

[0054] In some embodiments, exemplarily illustrated, after obtaining the liquid phase content of the gas-liquid mixture, the method further includes: When α is within a preset range, each partial pressure value is used as the first vapor pressure of each component. The first vapor pressure corresponds to the calculation result of the simplified model, that is, based on the single-component partial pressure law, the gas phase partial pressure value is directly used as the equilibrium vapor pressure. Then, based on each partial pressure value and each first proportion parameter, the second vapor pressure of each component under gas-liquid equilibrium is calculated, where α... th Located within a preset interval, such as [α] th -Δα,α th +Δα], where Δα can be 2.5 × 10 -4 The specific value needs to be determined based on the actual working conditions and sensitivity analysis results, and is not limited here.

[0055] Then, obtain the first weight w1 of the first vapor pressure and the second weight w2 of the second vapor pressure, wherein w1 is negatively correlated with α, that is, within the preset interval, as α increases, w1 gradually decreases (from 1→0); w2 is positively correlated with α, that is, within the preset interval, as α increases, w2 gradually increases (from 0→1); w1+w2=1.

[0056] Finally, the first vapor pressure and the second vapor pressure are weighted and calculated based on w1 and w2 to obtain the target vapor pressure.

[0057] Using the above method, when α is within a preset range, a weighted mixing strategy is introduced to fuse the first vapor pressure based on the single-component partial pressure law and the second vapor pressure based on Raoult's law according to dynamic weights. The weights are negatively or positively correlated with α and satisfy normalization constraints. This achieves a smooth switching between the two calculation modes in the transition region near the gas-liquid interface, rather than a hard cutoff at the threshold. This effectively avoids the problem of numerical jumps and physical oscillations in the target vapor pressure caused by small fluctuations in liquid content, ensures the continuity and differentiability of the phase change driving force in space and time, and enhances the convergence stability of the numerical solution.

[0058] In some embodiments, the phase change mass transfer rate calculation method is illustrated by way of example: When the gas-liquid mixture is a pure liquid phase (i.e., α=1), the theoretical vapor pressure of each component in its pure substance state is obtained. Based on the theoretical vapor pressure and the corresponding preset characteristic relationship, the target temperature of each component is calculated. Furthermore, using a phase change mass transfer rate model, the phase change mass transfer rate of each component is calculated based on the target temperature and the actual temperature. For specific details, please refer to the aforementioned embodiments, which will not be repeated here.

[0059] Under pure liquid phase conditions, if the actual temperature is higher than the target temperature, the liquid phase tends to evaporate, and the mass transfer rate is positive; if the actual temperature is lower than the target temperature, no evaporation occurs, and the mass transfer rate is zero or takes a minimum value according to the model settings.

[0060] Using the above method, a phase change mass transfer processing path based on the intrinsic properties of pure substances was constructed separately for specific working conditions where the gas-liquid mixture is in the pure liquid phase. That is, the theoretical vapor pressure of each component in the pure substance state is directly obtained, the target temperature of each component is calculated by relying on the Antoine formula, and then the Lee model is driven to calculate the mass transfer rate. This completes the full working condition coverage of multi-component phase change simulation in the full liquid content range, and ensures that the phase change mass transfer rate of each component can be calculated stably and reasonably under different phase conditions.

[0061] In some embodiments, the phase change mass transfer rate calculation method is illustrated by way of example: First, the physical state parameters of the gas-liquid mixture are updated based on the phase change mass transfer rate of each component using a pre-defined gas-liquid two-phase flow model. Then, based on the updated physical state parameters, the phase change mass transfer rate of each component is iteratively calculated until the pre-defined convergence condition is met, and the converged physical state parameters are output. The gas-liquid two-phase flow model is used to describe the mass conservation, momentum conservation, and energy conservation relationships of the gas and liquid phases. The physical state parameters include, but are not limited to, the temperature field, component concentration field, and phase content distribution.

[0062] For example, the VOF model is used as a gas-liquid two-phase flow model. In the VOF model, the phase change mass transfer rate of each component is introduced into the transport equation in the form of mass source terms and energy source terms to describe the heat and mass transfer behavior during condensation or evaporation phase change processes. Specifically, for the condensation process (gas phase to liquid phase transfer), the gas phase acts as a mass sink, and its mass source term is taken as... The liquid phase is used as the mass source, and its mass source term is taken as follows: For the evaporation process (transfer from liquid to gas phase), the liquid phase acts as a mass sink, and its mass source term is taken as... As a gas phase mass source, its mass source term is taken as follows: The energy source term is determined based on the latent heat of phase change, and its sign is consistent with that of the mass source term.

[0063] Based on the calculation of phase change mass transfer rate and definition of source terms, the defined VOF model and Lee model are embedded into the CFD solution environment for numerical simulation. For example, a user-defined function (UDF) is written to embed the liquid phase content threshold determination, regional phase equilibrium calculation, and phase state transition smoothing mechanism into the CFD simulation software, achieving organic coupling with the VOF model and the Lee model with the target temperature as input. Simultaneously, the computational domain is meshed and mesh independence is verified. Boundary conditions are set: the inlet is a velocity inlet, the wall is an isothermal condensation surface, and the outlet is a pressure outlet. An unsteady-state solver is used for numerical calculation; the pressure equation is discretized using the standard scheme, and the momentum equation is discretized using the first-order upwind scheme.

[0064] Within each time step of the unsteady-state solution, the solver reads the temperature, pressure, and component concentration fields of the current grid cell and substitutes them into the Lee model with the target temperature as input to calculate the phase change mass transfer rate of each component. Subsequently, the calculated phase change mass transfer rate is substituted into the VOF model in the form of mass source terms and energy source terms to obtain the updated temperature field, component concentration field, and liquid phase content distribution. The updated physical state parameters serve as the initial conditions for the next time step and participate in the next round of iterative calculations. This process is repeated cyclically to achieve dynamic capture of the evolution of each physical field during condensation or evaporation.

[0065] The preset convergence conditions include, but are not limited to: the residuals of each conservation equation are less than the preset values, and the key monitoring variables (such as outlet temperature, total condensate volume, etc.) no longer change significantly over time.

[0066] After obtaining the convergence results, key data such as the temperature field, component concentration field, wall heat flux, and component ratio of condensate (or evaporation) during the simulation process were extracted to verify the mass conservation of the numerical calculation. Based on this, the heat and mass transfer characteristics of a multi-component ideal solution in the condensation or evaporation process, based on the Lee model with the target temperature as input, were analyzed under different inlet component concentrations, flow rates, and temperatures, providing data support for engineering applications.

[0067] Using the methods described above, the adaptive determination of liquid content threshold, regional phase equilibrium calculation, weighted smoothing transition mechanism, and Lee model based on independent target temperature are fully embedded into the CFD solution environment in the form of UDF. This is tightly coupled and integrated with the VOF gas-liquid two-phase flow model. In each time step of the unsteady-state iteration, the phase change mass transfer rate of each component is introduced into the transport equation in the form of mass source terms and energy source terms, dynamically updating the temperature field, component concentration field, and liquid content distribution. This constructs a fully coupled numerical simulation framework from the calculation of local thermodynamic driving force to the evolution of macroscopic two-phase flow heat and mass transfer. On this basis, through the dual convergence criteria of preset residual threshold and key monitoring variables, it is ensured that the iterative solution reaches a physically self-consistent steady-state or dynamic equilibrium state. After convergence, key data such as temperature field, component distribution, wall heat flux, and condensate / evaporate component ratio are extracted to verify mass conservation. The heat and mass transfer laws of multi-component ideal solutions under different operating conditions are systematically analyzed, providing quantitative data support for engineering optimization.

[0068] Optionally, this application also addresses different α th The calculation results were verified. For example, in α th =1×10 -5 5×10 -5 1×10 -4Under three different threshold values, the temperature distribution, ethanol gas phase concentration distribution, and ethanol liquid phase concentration distribution within the computational grid cells were compared. The results show that the distribution curves of each key variable exhibit consistent trends under the three threshold conditions, with the maximum relative deviation being less than the set value (e.g., 5%, which can be determined based on actual operating conditions and is not limited here), indicating that α... th The value of has reasonable physical consistency and numerical stability, which verifies the effectiveness of the threshold determination strategy.

[0069] It should be understood that, although Figure 1 The steps in the flowchart are shown sequentially as indicated by the arrows, but these steps are not necessarily executed in the order indicated by the arrows. Unless otherwise specified herein, there is no strict order in which these steps are executed, and they can be performed in other orders. Figure 1 At least some of the steps in the process may include multiple sub-steps or multiple stages. These sub-steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these sub-steps or stages is not necessarily sequential, but can be executed in turn or alternately with other steps or at least some of the sub-steps or stages of other steps.

[0070] In some embodiments, such as Figure 2 As shown, a phase change mass transfer rate calculation device is provided, including: an acquisition module 201, a determination module 202, a temperature calculation module 203, and a mass transfer rate calculation module 204, wherein: The acquisition module 201 is used to acquire the partial pressure values ​​of each component in the gas phase of the gas-liquid mixture and the first proportion parameter of each component in the liquid phase. The determination module 202 is used to determine the target vapor pressure of each component under gas-liquid equilibrium state based on each partial pressure value and each first proportion parameter; The temperature calculation module 203 is used to calculate the target temperature of each component based on the target vapor pressure and the preset characteristic relationship corresponding to each component; wherein, the preset characteristic relationship is used to characterize the correspondence between the vapor pressure and temperature of a single component; The mass transfer rate calculation module 204 is used to calculate the phase change mass transfer rate of each component based on the target temperature and the actual temperature of the gas-liquid mixture using a preset phase change mass transfer rate model. The phase change mass transfer rate model is used to determine the mass transfer rate during the gas-liquid phase change process.

[0071] Specific limitations regarding the phase change mass transfer rate calculation device can be found in the limitations of the phase change mass transfer rate calculation method above, and will not be repeated here. Each module in the aforementioned phase change mass transfer rate calculation device can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in hardware or independently of the processor in a computer device, or stored in software in the memory of a computer device, so that the processor can call and execute the operations corresponding to each module.

[0072] In some embodiments, an electronic device is provided that can perform the functions of the aforementioned phase change mass transfer rate calculation device, with reference to... Figure 3 Electronic devices include: At least one processor 301 and a memory 302 connected to at least one processor 301. In this embodiment, the specific connection medium between the processor 301 and the memory 302 is not limited. Figure 3 The example shown is the connection between processor 301 and memory 302 via bus 300. Bus 300 is... Figure 3 The connections between other components are indicated by thick lines and are for illustrative purposes only, not as limiting information. Bus 300 can be divided into address bus, data bus, control bus, etc., for ease of representation. Figure 3 The term 301 is represented by a single thick line, but this does not imply that there is only one bus or one type of bus. Alternatively, the processor 301 can also be called a controller; there is no restriction on the name.

[0073] In this embodiment, memory 302 stores instructions executable by at least one processor 301. By executing the instructions stored in memory 302, at least one processor 301 can perform the phase transition mass transfer rate calculation method discussed above. Processor 301 can implement... Figure 2 The functions of each module in the device shown.

[0074] The processor 301 is the control center of the device. It can connect to various parts of the control device through various interfaces and lines. By running or executing instructions stored in memory 302 and calling data stored in memory 302, the processor can perform various functions and process data, thereby monitoring the device as a whole.

[0075] In some embodiments, processor 301 may include one or more processing units. Processor 301 may integrate an application processor and a modem processor, wherein the application processor mainly handles the operating system, user interface, and applications, and the modem processor mainly handles wireless communication. It is understood that the modem processor may not be integrated into processor 301. In some embodiments, processor 301 and memory 302 may be implemented on the same chip; in some embodiments, they may be implemented separately on independent chips.

[0076] Processor 301 can be a general-purpose processor, such as a central processing unit (CPU), digital signal processor, application-specific integrated circuit, field-programmable gate array or other programmable logic device, discrete gate or transistor logic device, or discrete hardware component, capable of implementing or executing the methods, steps, and logic block diagrams disclosed in the embodiments of this application. The general-purpose processor can be a microprocessor or any conventional processor. The steps of the phase transition mass transfer rate calculation method disclosed in the embodiments of this application can be directly implemented by a hardware processor, or implemented by a combination of hardware and software modules within the processor.

[0077] Memory 302, as a non-volatile computer-readable storage medium, can be used to store non-volatile software programs, non-volatile computer-executable programs, and modules. Memory 302 may include at least one type of storage medium, such as flash memory, hard disk, multimedia card, card-type memory, random access memory (RAM), static random access memory (SRAM), programmable read-only memory (PROM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), magnetic storage, magnetic disk, optical disk, etc. Memory 302 can be any other medium capable of carrying or storing desired program code in the form of instructions or data structures that can be accessed by a computer, but is not limited thereto. In the embodiments of this application, memory 302 may also be a circuit or any other device capable of implementing storage functions for storing program instructions and / or data.

[0078] By designing and programming the processor 301, the code corresponding to the phase transition mass transfer rate calculation method described in the foregoing embodiments can be embedded into the chip, thereby enabling the chip to execute the code during operation. Figure 1The steps of the phase change mass transfer rate calculation method in the illustrated embodiment are as follows. How to design and program the processor 301 is a technique well-known to those skilled in the art and will not be described further here.

[0079] In some embodiments, a computer storage medium is provided, comprising: computer program code, which, when executed on a computer, causes the computer to perform any of the phase change mass transfer rate calculation methods discussed above. Since the principle by which the computer storage medium solves the problem is similar to that of the phase change mass transfer rate calculation method, the implementation of the computer storage medium can be found in the implementation of the method, and repetitions will not be repeated.

[0080] In specific implementation, computer storage media can include: Universal Serial Bus Flash Drive (USB), portable hard drive, Read-Only Memory (ROM), Random Access Memory (RAM), magnetic disk or optical disk, and other storage media that can store program code.

[0081] In some embodiments, a computer program product is also provided, comprising: computer program code, which, when executed on a computer, causes the computer to perform any of the phase change mass transfer rate calculation methods described above. Since the principle by which the above-described computer program product solves the problem is similar to that of a phase change mass transfer rate calculation method, the implementation of the above-described computer program product can be found in the implementation of the method, and repeated details will not be elaborated further.

[0082] Computer program products may employ any combination of one or more readable media. A readable medium may be a readable signal medium or a readable storage medium. A readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples of readable storage media (a non-exhaustive list) include: electrical connections having one or more wires, portable disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof.

[0083] The methods in this application can be implemented, in whole or in part, by software, hardware, firmware, or any combination thereof. When implemented in software, they can be implemented, in whole or in part, as a computer program product. A computer program product includes one or more computer programs or instructions. When the computer program or instructions are loaded and executed on a computer, the processes or functions of this application are performed, in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, network equipment, user equipment, core network equipment, OAM, or other programmable device.

[0084] Computer programs or instructions can be stored in or transferred from one computer-readable storage medium to another. For example, a computer program or instructions can be transferred from one website, computer, server, or data center to another via wired or wireless means. A computer-readable storage medium can be any usable medium that a computer can access, or a data storage device such as a server or data center that integrates one or more usable media. Usable media can be magnetic media, such as floppy disks, hard disks, and magnetic tapes; optical media, such as digital video discs; or semiconductor media, such as solid-state drives. The computer-readable storage medium can be volatile or non-volatile, or may include both types.

[0085] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage and optical storage) containing computer-usable program code.

[0086] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 Devices that specify the functions in one or more boxes.

[0087] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including an instruction device, which is implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0088] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0089] Obviously, those skilled in the art can make various modifications and variations to this invention without departing from its spirit and scope. Therefore, if these modifications and variations fall within the scope of the claims of this invention and their equivalents, this invention also intends to include these modifications and variations.

Claims

1. A method for calculating phase change mass transfer rate, characterized in that, The method includes: The partial pressure values ​​of each component in the gas phase of the gas-liquid mixture and the first proportion parameter of each component in the liquid phase are obtained. Based on the partial pressure values ​​and the first proportion parameters, the target vapor pressure of each component under gas-liquid equilibrium state is determined; Based on the target vapor pressures and the preset characteristic relationships corresponding to each component, the target temperatures of each component are calculated; wherein, the preset characteristic relationships are used to characterize the correspondence between the vapor pressure and temperature of a single component; Using a preset phase change mass transfer rate model, the phase change mass transfer rate of each component is calculated based on the target temperature and the actual temperature of the gas-liquid mixture. The phase change mass transfer rate model is used to determine the mass transfer rate during the gas-liquid phase change process.

2. The method according to claim 1, characterized in that, The method of obtaining the partial pressure values ​​of each component in the gas phase of the gas-liquid mixture includes: Obtain the total gas phase pressure in the gas-liquid mixture, and the second proportion parameter of each component in the gas phase; Each of the second percentage parameters is multiplied by the total gas phase pressure to obtain the partial pressure value.

3. The method according to claim 1, characterized in that, The step of determining the target vapor pressure of each component under gas-liquid equilibrium state based on each partial pressure value and each of the first proportion parameters includes: Obtain the theoretical vapor pressure of each component in its pure state; Based on each of the first proportion parameters and the corresponding theoretical vapor pressure, the theoretical vapor pressure of each component in the liquid phase is calculated; Using a pre-defined gas-liquid equilibrium correlation model, the target vapor pressure of each component is calculated based on its partial pressure and theoretical vapor partial pressure. The gas-liquid equilibrium correlation model uses the constraint equation that the partial pressure of each component in the gas phase at gas-liquid equilibrium is equal to its theoretical vapor partial pressure in the liquid phase.

4. The method according to claim 1, characterized in that, Before determining the target vapor pressure of each component under gas-liquid equilibrium state based on each of the partial pressure values ​​and each of the first proportion parameters, the method further includes: Obtain the liquid phase content of the gas-liquid mixture; When the liquid phase content is greater than or equal to a preset threshold and the gas-liquid mixture is a non-pure liquid phase, the step of determining the target vapor pressure of each component under gas-liquid equilibrium state based on each partial pressure value and each first proportion parameter is performed. When the liquid phase content is less than the preset threshold, the target temperature of each component is calculated based on the partial pressure value of each component and the corresponding preset characteristic relationship, and the phase change mass transfer rate is calculated based on the target temperature and the actual temperature using the phase change mass transfer rate model.

5. The method according to claim 4, characterized in that, After obtaining the liquid phase content of the gas-liquid mixture, the method further includes: When the liquid phase content is within a preset range, each partial pressure value is used as the first vapor pressure of each component, and the second vapor pressure of each component under the gas-liquid equilibrium state is calculated based on each partial pressure value and each first proportion parameter, wherein the preset threshold is within the preset range; Obtain a first weight for the first vapor pressure and a second weight for the second vapor pressure, wherein the first weight is negatively correlated with the liquid phase content and the second weight is positively correlated with the liquid phase content; The first vapor pressure and the second vapor pressure are weighted and calculated according to the first weight and the second weight to obtain the target vapor pressure.

6. The method according to claim 1, characterized in that, The method further includes: When the gas-liquid mixture is a pure liquid phase, the theoretical vapor pressure of each component in its pure substance state is obtained; Based on the theoretical vapor pressures and the corresponding preset characteristic relationships, the target temperatures of each component are calculated; Using the phase change mass transfer rate model, the phase change mass transfer rate of each component is calculated based on the target temperature and the actual temperature.

7. The method according to claim 1, characterized in that, The method further includes: The physical state parameters of the gas-liquid mixture are updated based on the phase change mass transfer rate of each component using a preset gas-liquid two-phase flow model. Based on the updated physical state parameters, the phase change mass transfer rate of each component is calculated iteratively until the preset convergence condition is met, and the converged physical state parameters are output.

8. A device for calculating phase change mass transfer rate, characterized in that, The device includes: The acquisition module is used to acquire the partial pressure values ​​of each component in the gas phase of the gas-liquid mixture, and the first proportion parameter of each component in the liquid phase; The determining module is used to determine the target vapor pressure of each component under gas-liquid equilibrium state based on each of the partial pressure values ​​and each of the first proportion parameters; The temperature calculation module is used to calculate the target temperature of each component based on the target vapor pressure and the preset characteristic relationship corresponding to each component; wherein, the preset characteristic relationship is used to characterize the correspondence between the vapor pressure and temperature of a single component; The mass transfer rate calculation module is used to calculate the phase change mass transfer rate of each component based on the target temperature and the actual temperature of the gas-liquid mixture using a preset phase change mass transfer rate model. The phase change mass transfer rate model is used to determine the mass transfer rate during the gas-liquid phase change process.

9. An electronic device, characterized in that, include: Memory, used to store computer programs; A processor, when executing a computer program stored in the memory, implements the method as described in any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program that, when executed by a processor, implements the method as described in any one of claims 1 to 7.

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