A heat-moisture decoupled regularized modeling method

Abstract

The application provides a heat-moisture decoupling regularization modeling method, comprising the following steps: step one, based on an energy conservation modeling method, a first model is established, the first model is a regularization temperature model of a dehumidification process; step two, based on the first model, a second model is established, the second model is a heat resistance and moisture resistance model; step three, based on a heat flow method, the first model and the second model are combined to establish a third model, the third model is a global regularization model of a solution dehumidification process; step four, system calculation is carried out by using the third model, and finally a general regularization global modeling method which can comprehensively evaluate various solution dehumidification processes is obtained. The application extends the recently developed heat flow method to analyze the universal solution dehumidification process; a new regularization temperature is introduced, including a heat-moisture decoupling strategy driven by a heat flow topology, and the heat flow model is reconstructed by defining heat resistance and moisture resistance; and the solution dehumidification system performance can be further optimized.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of energy utilization, and in particular, relates to a heat-humidity decoupling regularized modeling method. BACKGROUND

[0002] In industrial and domestic applications, cooling and heating are a large part of energy consumption. Traditional air conditioning systems often result in a large amount of energy waste due to their temperature-humidity coupled control method, which requires the cold source temperature to meet both the latent load and the sensible load at the same time. In addition, humidity control is often neglected in favor of temperature control, leading to a decrease in air quality.

[0003] Liquid desiccant systems are a technology used to control air humidity. It removes moisture from the air by exposing it to a liquid desiccant, such as saltwater or other hygroscopic solutions. This system utilizes the affinity of the desiccant for humidity, adsorbing it into the solution, making the air drier. In this process, the desiccant is hygroscopic, while the air becomes drier. Through this method, the humidity in the air can be adjusted and controlled, providing a suitable humidity level for specific environments, such as industrial processes or comfortable indoor spaces. This system is commonly used to control environmental conditions, ensuring that the humidity in the air is maintained at the desired level.

[0004] It can independently control temperature and humidity by handling latent heat and a portion of the sensible heat load of the air. This makes it a promising solution. It has been widely used in industrial deep dehumidification, renewable energy utilization, comfortable air conditioning, waste heat recovery, laboratory environment creation, shipping industry, and other application fields.

[0005] Regarding the modeling of liquid desiccant systems, there are generally five model types: experimental models, finite difference models, ε-NTU models, empirical simplified models, and computational fluid dynamics models, which are suitable for describing the thermodynamic and dynamic processes within liquid desiccant systems. However, when faced with complex, multi-parameter, time-varying, highly lagging, and nonlinear liquid desiccant processes, existing models still have limitations in reducing nonlinear constraints and solving nonlinear problems. For some simplified models, the introduction of too many characteristic parameters may affect the accuracy and convergence of the algorithm.

[0006] Performance evaluation of liquid desiccant systems mainly focuses on entropy generation evaluation, loss, single-parameter analysis, and multi-objective optimization. However, in most system modeling processes, subsystems are modeled separately. On the one hand, this introduces too many intermediate variables, and on the other hand, it disrupts the strong coupling between parameters and subsystem components. This may lead to a lack of globally optimal operating parameter combinations during single-parameter analysis. Although people widely adopt entropy generation and Loss minimization is the objective to evaluate the performance of liquid desiccant systems, but the entropy generation evaluation, The correspondence between loss rate and system performance has not been fully established. Therefore, there is still a need for new methods and theories to model liquid desiccant systems across scales, regularization, and optimization analysis.

[0007] Currently, modeling based on heat flow method is mainly achieved by extending the standard heat flow model of two heat flows in heat exchangers. When modeling and optimizing evaporative cooling and ventilation systems, the extension of the standard heat flow model is based on the saturated air line of the wet type. In contrast, when dealing with the solution desiccant process, the extension of the standard heat flow model needs to be consistent with the unsaturated relative humidity line. Therefore, the current model cannot be directly applied, and the standard heat flow model needs to be extended to include the solution desiccant process. Therefore, the present application can realize the simulation and optimization of the solution desiccant process by driving the heat flow topology structure to decouple the heat and mass, defining the regularization temperature, and reconstructing the thermal and moisture resistance. SUMMARY

[0008] According to the technical problems proposed above, a heat-humidity decoupling regularization modeling method is provided. The present application first analyzes the solution desiccant process using the heat flow method and establishes a model of a typical solution desiccant system. Subsequently, the heat flow topology structure is used to drive the heat and mass decoupling, and the global constraints of the solution desiccant system are obtained from the heat flow model and verified with previous research. Then, based on orthogonal experimental design and correlation analysis, significant influencing factors are selected, and single-variable decision variable analysis and double-variable decision variable analysis are performed. Finally, the system uses NSGA-II for three-objective optimization analysis, demonstrating the application and advantages of the newly proposed modeling method.

[0009] The technical means adopted by the present application are as follows:

[0010] A heat-humidity decoupling regularization modeling method, comprising the following steps:

[0011] Step one, based on the energy conservation modeling method, a first model is established, and the first model is a regularization temperature model of the desiccant process;

[0012] Step two, a second model is established based on the first model, and the second model is a thermal and moisture resistance model;

[0013] Step three, based on the heat flow method, a third model is established combining the first model and the second model, and the third model is a global regularization model of the established typical solution desiccant process;

[0014] Step four, the third model is used for system calculation, and finally a universal regularization global modeling method that can comprehensively evaluate various solution desiccant processes is obtained.

[0015] Further, in the step two, the heat and mass decoupling strategy driven by heat flow topology is used to redefine the heat and mass resistance based on the first model, and the heat and mass resistance model is obtained.

[0016] The definition of the normalization temperature and the heat and mass resistance includes the graphical deconstruction of the solution dehumidification process and the definition of the normalization temperature, and the reconstruction of the heat and mass resistance model by the heat and mass decoupling driven by the heat flow topology.

[0017] Further, in the step four, the system calculation includes the system model verification, the orthogonal test analysis, the evaluation index setting, and the single variable and multi-variable optimization; the heat and mass coupling energy transfer law in the solution dehumidification process is revealed by the global normalization model of the typical solution dehumidification process.

[0018] Further, for the definition of the normalization temperature, it is assumed that there is a linear relationship between the equivalent water content of the solution and the temperature in the micro-interval, and the symbol κ represents the relative position relationship between the air inlet parameter and the solution inlet parameter on the humidity chart; when the relative humidity of the inlet air is higher than the relative humidity of the solution , κ>0, and vice versa; no matter the inlet air state, the intersection of the constant humidity line and the relative humidity line can be used as the reference point of the normalization temperature t a,e .

[0019] Further, the heat and mass decoupling strategy driven by the heat flow topology is: by describing the differential equations of heat and mass transfer and energy conservation in the solution dehumidification process, the change of the water content in the air is accurately analyzed and processed; the process is understood as the heat transfer problem of the equivalent three fluids by using the heat and mass decoupling strategy driven by the heat flow topology based on the heat flow method.

[0020] Further, by listing the mass conservation equations, the heat conservation equations of the equivalent three fluids, and introducing the normalization temperature, the heat and mass resistance equations are redefined, and the heat and mass resistance model is obtained.

[0021] Further, in the step four, first, the significant influencing factors of the solution dehumidification system are identified by the orthogonal test analysis, then the performance indicators are evaluated by the single decision variable analysis and the double decision variable analysis, and finally the optimal solution of the solution dehumidification system is obtained according to the evaluation indicators and by applying the multi-objective optimization method.

[0022] Further, in the orthogonal test analysis, the solution dehumidification system orthogonal test design 10 parameters, including the total heat conduction coefficient of the system, the solution mass flow, the inlet air water content, the inlet air temperature, the dehumidifier air / solution flow ratio, the regenerator air / solution flow ratio, the dehumidifier solution inlet temperature, the regenerator solution inlet temperature, the cold source temperature and the heat source temperature.

[0023] The evaluation indicators include the dehumidification rate, the loss, efficiency, exergy dissipation and exergy efficiency.

[0024] Further, 10 parameters in orthogonal test analysis are analyzed, and 4 most significant factors of the solution dehumidification system are obtained, which are total heat transfer coefficient, solution mass flow, air / solution flow ratio of the dehumidifier and heat source temperature.

[0025] Further, multi-objective optimization shows that there is a trade-off relationship between the dehumidification rate, efficiency, exergy efficiency, and the optimal solution values are 3.25 g / s, 65.92% and 12.01% respectively.

[0026] Compared with the prior art, the present application has the following advantages:

[0027] 1. The present application extends the recently developed heat flow method to analyze the general solution dehumidification process.

[0028] 2. The heat flow modeling of the present application introduces a new normalized temperature, which includes the use of heat flow topology driven heat-mass decoupling strategy, and reconstructs the heat flow model by defining heat resistance and humidity resistance.

[0029] 3. The present application extends the application of the heat flow method and analyzes the heat-mass coupled energy transfer mechanism, which has a positive effect.

[0030] 4. The present application can further optimize the performance of the solution dehumidification system, and the significant factors affecting the performance indicators of the solution dehumidification system are total heat transfer coefficient, solution mass flow, air / solution mass flow ratio and heat source temperature.

[0031] 5. Multi-objective optimization of the present application shows that there is a trade-off relationship between the dehumidification rate, efficiency and exergy efficiency.

[0032] Based on the above reasons, the present application can be widely popularized in the field of dehumidification. BRIEF DESCRIPTION OF DRAWINGS

[0033] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the drawings needed to be used in the embodiments or prior art description will be briefly introduced as follows. Obviously, the drawings in the following description are some embodiments of the present application, and other drawings can also be obtained by those skilled in the art without creative labor.

[0034] Figure 1 It is a schematic diagram of the heat-humidity decoupling normalized modeling method of the present application.

[0035] Figure 2 It is a graphical deconstruction of the solution dehumidification process model of the present application.

[0036] Figure 3 A schematic of the definition of the conditioning temperature for the present invention, where (a) is the definition of the conditioning temperature, (b) is the coupling of the heat and mass transfer processes.

[0037] Figure 4 A schematic of the reconstructed thermal and moisture resistance model for the present invention.

[0038] Figure 5 A flow chart of the solution dehumidification modeling optimization for the present invention.

[0039] Figure 6 A typical solution dehumidification system case for the present invention. DETAILED DESCRIPTION

[0040] It should be noted that the embodiments in the present application and the features in the embodiments can be combined with each other without conflict. The present application will be described in detail below with reference to the accompanying drawings and in combination with the embodiments.

[0041] In order to make the purpose, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be described clearly and completely below in combination with the drawings of the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all the embodiments. The description of the at least one exemplary embodiment is actually only illustrative, but not as any limitation on the present application and its application or use. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor fall within the scope of protection of the present application.

[0042] It should be noted that the terms used herein are only for describing specific embodiments, and are not intended to limit the exemplary embodiments according to the present application. As used herein, the singular form is intended to include the plural form unless the context clearly indicates otherwise, and it should also be understood that when the terms "comprise" and / or "include" are used in the specification, there is a presence of the features, steps, operations, devices, components and / or combinations thereof.

[0043] The relative arrangement of parts and steps, numerical expressions, and numerical values set forth in the examples herein are not intended to limit the scope of the application unless specifically so stated. It is to be understood that the drawings are not necessarily to scale as the dimensions of the parts shown are for the purpose of illustration and description only and not limitation of the scope of the application. Techniques, methods, and apparatus known to those of ordinary skill in the relevant art can not be discussed in detail but are intended to be understood as a part of the specification when appropriate. In all examples shown and discussed herein, any specific values should be interpreted as merely illustrative and not as a limitation on the scope of the exemplary embodiments. Thus, other examples of the exemplary embodiments can have different values. It is noted that like numbers and letters refer to like elements throughout the several views of the drawings and, as such, no further discussion with regard thereto is needed.

[0044] As shown in Figure 1 , the present application provides a heat-moisture decoupling regularization modeling method, including regularization temperature, definition of thermal resistance / moisture resistance, modeling process and evaluation optimization, including the following steps:

[0045] Step one, based on the energy conservation modeling method, define the regularization temperature of the dehumidification process, and on this basis, redefine the thermal resistance and moisture resistance by using the heat flow topology driven heat-mass decoupling strategy;

[0046] Step two, based on the heat flow method and the definition of regularization temperature, thermal resistance and moisture resistance in step one, establish the global regularization model construction of typical solution dehumidification process;

[0047] Step three, system calculation, system model verification, orthogonal test analysis, evaluation index setting and single variable and multi-variable optimization, finally comprehensive evaluation of the general solution dehumidification process of the universal regularization global modeling method.

[0048] The definition of regularization temperature, thermal resistance and moisture resistance in step one includes: graphical deconstruction of solution dehumidification process and definition process of regularization temperature, and redefinition of thermal resistance and moisture resistance by using heat flow topology driven heat-mass decoupling.

[0049] Solution dehumidification process is to realize water transfer by using the difference between the water vapor pressure of wet air and the liquid desiccant. The surface vapor pressure of the liquid desiccant is approximately equal to the water vapor pressure. When the liquid desiccant is in contact with the air and reaches equilibrium, their temperature and water vapor pressure are equal. The water content of the liquid desiccant is equal to the water content of the wet air in equilibrium. Figure 2The present invention is a graphical deconstruction of the solution dehumidification process model. The water transfer between the liquid desiccant and the humid air is represented by introducing an equivalent surface. When the effect of water absorption or release on the solution flow rate is neglected in a micro-interval, it can be inferred that the change of solution concentration along the path can also be neglected. Therefore, there is an approximate linear relationship between the enthalpy of the solution and its equivalent humidity and temperature.

[0050] The heat resistance and the moisture resistance are redefined by the heat flux topology driven heat-mass decoupling. Figure 3 The definition of the normalized temperature is illustrated, assuming a linear relationship between the equivalent water content of the solution and the temperature in the micro-interval. Let the symbol κ represent the relative position relationship between the air inlet parameter and the solution inlet parameter on the humidity chart. When the relative humidity of the inlet air is higher than the relative humidity of the solution , κ > 0, and vice versa. Regardless of the inlet air state, the intersection of the constant humidity line and the relative humidity line can be used as a reference point for the normalized temperature (t a,e ).

[0051] Heat flux topology driven heat-mass decoupling strategy based on heat flux method: In order to accurately analyze the water content change of the air, it is necessary to describe the energy-saving differential equation of the liquid desiccant dehumidification process, that is, the heat and mass transfer and energy conservation differential equation in the solution dehumidification process. By using the heat flux topology driven heat-mass decoupling strategy based on the heat flux method, the process can be understood as a heat transfer problem of three equivalent (equivalent) fluids. By listing the mass conservation equations and heat conservation equations of the equivalent three fluids and introducing the concept of the defined normalized temperature, the heat resistance and moisture resistance equations are redefined.

[0052] Global normalized model construction of typical solution dehumidification process: On the basis of the traditional energy conservation modeling method, the defined normalized temperature, heat resistance and moisture resistance are added to construct the global normalized model of the typical solution dehumidification process relying on the heat flux method. This model can reveal the heat-mass coupled energy transfer law in the solution dehumidification process.

[0053] The following equations describe the heat-mass coupled transfer mechanism:

[0054]

[0055]

[0056]

[0057] wherein, m represents the mass flow rate of the fluid, h represents the specific enthalpy, γ0 is the latent heat of vaporization of water vapor, h s represents the specific enthalpy of the solution, ω e and ω a represent the water content in the solution and the air, respectively, α and αm represent the heat and mass transfer coefficients, respectively, t is the temperature, H is the length of the dehumidifier, A is the heat transfer area, and the subscripts a and s refer to air and solution, respectively.

[0058] Assuming that the moisture content and the corresponding normalized temperature are approximately linearly related by the following equation:

[0059] ω a = at a,e +b (4)

[0060] where a and b are linear coefficients and t is the normalized temperature. a,e

[0061] Assuming that the dimensionless Le number in the liquid desiccant dehumidification process is equal to 1:

[0062] Le = a / (a m c p,a ) = 1 (5)

[0063] Equations (1) to (5) can be collectively derived as:

[0064]

[0065]

[0066]

[0067] where c p,a is the specific heat at constant pressure of the moist air and c p,s is the specific heat at constant pressure of the solution.

[0068] Based on the extended thermal and moisture resistances obtained from the heat flow method, the heat and mass transfer resistances can be obtained by integrating the dehumidifier along the length H in a counterflow configuration, assuming that the solution spray rate is infinite, i.e., the solution temperature does not change along the length:

[0069]

[0070]

[0071]

[0072]

[0073]

[0074]

[0075] where G c1 and G c2 are the equivalent heat capacity flow rate and the equivalent mass transfer heat capacity flow rate, respectively, and G​s is the equivalent heat capacity flow rate of the solution, (kA) h and (kA) m represent the overall heat transfer conductance and the overall equivalent mass transfer conductance, respectively. NTU e and NTU m represent the number of heat transfer units and the number of mass transfer units, respectively.

[0076] After the combined solution, the general heat and moisture resistances of the solution dehumidification are obtained as follows:

[0077]

[0078]

[0079] where R h and R m represent the heat and moisture resistances, respectively, in K / W.

[0080] Figure 4 The heat and moisture model containing heat and moisture resistances derived from the heat and mass decoupling strategy driven by the heat flow topology structure is illustrated.

[0081] In step three, the significant influencing factors of the solution dehumidification system are first identified by orthogonal test analysis, and then the performance indicators are evaluated by single decision variable analysis and double variable decision variable analysis. Finally, the optimal solution of the solution dehumidification system is found by applying multi-objective optimization method according to the evaluation indicators.

[0082] where the influence of each factor on the objective function is determined by orthogonal test design. The orthogonal test analysis design of the solution dehumidification system has 10 parameters. The main factors include overall conductance (αA, i.e. the total conductance of the system), solution mass flow rate (G air inlet moisture content (ω a , i.e. the moisture content of the inlet air), inlet air temperature (t a,in ), dehumidifier air / solution flow ratio (R A / S,D ), regenerator air / solution flow ratio (R A / S,R ), dehumidifier solution inlet temperature (t s,D,in ), regenerator solution inlet temperature (t s,R,in ), cold source temperature (t C ), and heat source temperature (t H ). The four most significant influencing factors of the general solution dehumidification system obtained by analyzing the 10 orthogonal test parameters are the total conductance of the system, the solution mass flow rate, the dehumidifier air / solution flow ratio, and the heat source temperature, in order.

[0083] The objective functions (evaluation indicators) include: dehumidification rate (MRR), loss (Ex loss ), Efficiency (η ex ), exergy destruction (En dis ), and exergy efficiency (η en ).

[0084] Dehumidification rate formula:

[0085]

[0086] where, is the mass flow rate of air at the air side of the dehumidifier, ω a is the moisture content in the air, and subscripts in and out represent the inlet and outlet.

[0087] Loss is:

[0088] Ex = m x [(h - ho) - To (s - so)] (18)

[0089] where ho, To, so represent the specific enthalpy, temperature, and entropy of the environment, respectively, in the dead state.

[0090] The following equation represents Efficiency:

[0091] η ex = E x,out / E x,in (19)

[0092] Exergy loss (exergy destruction) is:

[0093]

[0094]

[0095]

[0096] where, and are the exergy destruction numbers for air and solution, respectively, is the exergy destruction loss of the system.

[0097] Exergy efficiency is:

[0098]

[0099] Example 1

[0100] This is for a typical system configuration as Figure 6An example analysis is performed. The system shown is intended to provide dry air for the cabins of an ocean-going ship operating under high temperature and high humidity conditions. Inside the dehumidification exchanger (DEH), a low temperature lithium chloride dilute solution is used as the liquid desiccant for spray dehumidification. Air and liquid desiccant flow in a cross-flow manner. The surface vapor pressure of the dilute solution is lower than the partial pressure of water vapor in fresh air, allowing the liquid desiccant to effectively absorb moisture in the air. After the dehumidification process is completed, the dry air is further cooled. The lithium chloride liquid desiccant, which is slightly higher in temperature and slightly lower in concentration, flows to the dilute solution tank and exchanges heat with the lithium chloride liquid desiccant in the concentrated solution tank through an intermediate heat exchanger. In order to maintain quality preservation, the lithium chloride liquid desiccant must undergo a regeneration process after absorbing water to continue working. This process will be carried out in the regenerator. The diluted lithium chloride solution is heated when passing through the regeneration exchanger (REH). The heat exchanger uses the waste heat from the main engine cylinder liner cooling water as the heat source. At high temperatures, the surface vapor pressure of the solution exceeds the partial pressure of water vapor in fresh air. Therefore, the water in the regenerated liquid desiccant is taken out of the cabin and pre-cooled by the concentrated solution tank into the intermediate heat exchanger. Finally, cooling is carried out in the cooler to prepare for the next round of dehumidification process.

[0101] Based on the heat and mass decoupling strategy driven by the heat flow topology, the solution dehumidification system is modeled using extended thermal and moisture resistances. Due to the limited flow rate of the sprayed solution, its temperature changes constantly during the process. By applying the principles of calculus, the dehumidifier / regenerator is divided into N equal intervals. Within each micro-interval, the linear relationship between the solution's equivalent water content and temperature remains unchanged, and the solution temperature can still be considered constant. Therefore, the thermal resistance model in each micro-interval can be shown as Figure 4 The temperature change between two nodes of the same fluid is described by the heat dynamics.

[0102] The equation for the additional heat dynamics potential of the dehumidifier is:

[0103] ε D,a,i = Q D,h,i / G D,a (i = 1 ~ N) (24)

[0104] ε D,a,e,i = Q D,m,i / G D,a,e,i (i = 1 ~ N) (25)

[0105] ε D,s,i = (Q D,h,i + Q D,m,i ) / G D,s,i (i = 1 ~ N) (26)

[0106] The equation for the additional heat dynamics potential of the regenerator is:

[0107] ε R,a,i = Q R,h,i / G R,a (i = 1 ~ N) (27)

[0108] ε R,a,e,i = Q R,m,i / G R,a,e,i (i = 1 ~ N) (28)

[0109] ε R,s,i = (Q R,h,i + Q R,m,i ) / G R,s,i (i = 1 ~ N) (29)

[0110] The equation of the additional thermodynamic potential of the intermediate heat exchanger is:

[0111] ε D,IHEX = Q IHEX / G D,s,out (30)

[0112] ε R,IHEX = Q IHEX / G R,s,out (31)

[0113] where ε is the thermodynamic potential, Q is the heat transfer rate, G is the heat capacity rate, the subscripts D, R and IHEX represent the dehumidifier, regenerator and intermediate heat exchanger, respectively, i and out represent the inlet and outlet, a and s represent air and solution, respectively, h, e and m represent heat source, equivalent and average, respectively.

[0114] In the cross-flow configuration, the thermal resistance equation of the liquid desiccant system needs to introduce a cross-flow configuration heat exchanger correction factor φ cr , so for the counter-flow heat exchanger, the unit thermal resistance and humidity resistance can be rewritten as follows:

[0115]

[0116]

[0117] where NTU is the number of heat transfer units.

[0118] As Figure 5 described above, the equations of the total model in the liquid desiccant system are as follows:

[0119]

[0120]

[0121]

[0122]

[0123]

[0124]

[0125] T C1 +Q C R C -ε D,SHEX =T s,D2 (40)

[0126] T E1 -Q REH R REH +ε R,SHEX -Q SHEX R SHEX =T s,D2 (41)

[0127] T E1 -Q REH R REH +ε R,SHEX =T s,R2 (42)

[0128] where T is temperature, and N is assigned a value of 100.

[0129] The accuracy of the model was evaluated using the average absolute deviation (AAD). Validation indices included air temperature, air humidity, solution temperature, and mass concentration. The maximum deviation of these indices did not exceed 15.0%, indicating that the model had high accuracy.

[0130]

[0131] The effects of various factors on the objective function were further determined using an orthogonal test design. The main factors included overall thermal conductance (αA), solution mass flow rate (G Air inlet water content (ω a ), inlet air temperature (t a,in ), dehumidifier air / solution flow ratio (R A / S,D ), regenerator air / solution flow ratio (R A / S,R ), dehumidifier solution inlet temperature (t s,D,in ), regenerator solution inlet temperature (t s,R,in ), cold source temperature (t C ), and heat source temperature (t H ).

[0132] The objective function included: dehumidification rate (MRR), exergy loss (Ex loss ), efficiency (η ex ), and exergy consumption (En dis) and fire accumulation efficiency (η en ).

[0133] Dehumidification rate formula:

[0134]

[0135] where, is the mass flow rate of the air side of the dehumidifier, ω a moisture content in the air, subscripts in and out represent the inlet and outlet, Loss is:

[0136] Ex = m x [(h - h0) - T0(s - s0)] (18)

[0137] where h0, T0, s0 represent the specific enthalpy, temperature and entropy of the environment, respectively, in the death state. The following formula represents Efficiency:

[0138] η ex = E x,out / E x,in (19)

[0139] η ex = E x,out / E x,in (18)

[0140] Fire accumulation loss:

[0141]

[0142]

[0143]

[0144] where, and are the fire accumulation dissipation numbers of air and solution, respectively, is the fire accumulation dissipation loss of the system.

[0145] Fire accumulation efficiency:

[0146]

[0147] Obtain the relevant results: first, through orthogonal test analysis and correlation analysis to identify the significant influence factors overall heat transfer coefficient αA, dehumidifier air / solution flow ratio R A / S,D , solution mass flow rate m s and heat source temperature t HThen, the univariate decision variable analysis and bivariate decision variable analysis are performed to evaluate the performance indicators. Finally, the multi-objective optimization method is applied to find the optimal solution of the system. The multi-objective optimization shows that there is a trade-off relationship between the dehumidification rate, efficiency, exergy efficiency, and the optimal solution values are 3.25 g / s, 65.92%, and 12.01%, respectively.

[0148] End.

[0149] Finally, it should be noted that: the above embodiments are only used to illustrate the technical solutions of the present application, but not to limit them; although the present application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that: it can still modify the technical solutions recorded in the foregoing embodiments, or make equivalent replacement for part or all of the technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the scope of the technical solutions of the embodiments of the present application.

Claims

1. A normalized modeling method for thermal-humidity decoupling, characterized in that, Includes the following steps: Step 1: Based on the energy conservation modeling method, establish the first model, which is the normalized temperature model of the dehumidification process; Step 2: Establish a second model based on the first model. The second model is a thermal resistance and moisture resistance model. Step 3: Based on the heat flow method, a third model is established by combining the first and second models. The third model is a global normalization model of the solution dehumidification process. Step 4: Use the third model to perform system calculations, and finally obtain a generalized global modeling method that can comprehensively evaluate various solution dehumidification processes; In step two, based on the first model, thermal resistance and humidity resistance are redefined using a thermal-fluid topology-driven thermal-mass decoupling strategy to obtain thermal resistance and humidity resistance models. The definitions of normalization temperature and thermal and moisture resistance include: the graphical deconstruction of the solution dehumidification process and the definition process of normalization temperature, as well as the reconstruction of thermal and moisture resistance models using heat flux topology-driven thermo-mass decoupling. The heat-fluidity topology-driven heat-mass decoupling strategy is as follows: by describing the differential equations of heat and mass transfer and energy conservation in the solution dehumidification process, the change in moisture content in the air is accurately analyzed; using the heat-fluidity topology-driven heat-mass decoupling strategy based on the heat flow method, the process is understood as an equivalent heat transfer problem of three fluids. By listing the mass conservation equations and heat conservation equations for the three equivalent fluids and introducing the normalized temperature, the thermal resistance and moisture resistance equations are redefined, resulting in thermal resistance and moisture resistance models.

2. The normalized modeling method for thermal-humidity decoupling according to claim 1, characterized in that, In step four, the system calculation includes system model verification, orthogonal experimental analysis, evaluation index setting, and univariate and multivariate optimization; the heat-mass coupling energy transfer law in the solution dehumidification process is revealed through a global normalization model of the solution dehumidification process.

3. The normalized modeling method for thermal-humidity decoupling according to claim 1, characterized in that, For the definition of normalized temperature, it is assumed that there is a linear relationship between the equivalent water content of the solution and the temperature in the micro-interval. Let the symbol κ represent the relative positional relationship between the air inlet parameter and the solution inlet parameter on the humidity map. When the relative humidity of the inlet air is higher than that of the solution... φ e When κ > 0, the opposite is also true; Regardless of the intake conditions, the intersection of the constant humidity line and the relative humidity line can be used as the normalized temperature t. a,e Reference point.

4. The normalized modeling method for thermal-humidity decoupling according to claim 2, characterized in that, In step four, firstly, orthogonal experimental analysis is used to identify significant influencing factors of the solution dehumidification system. Then, single-decision variable analysis and bivariate decision variable analysis are performed to evaluate the evaluation indicators. Finally, based on the evaluation indicators, a multi-objective optimization method is applied to obtain the optimal solution of the solution dehumidification system.

5. The normalized modeling method for thermal-humidity decoupling according to claim 4, characterized in that, In the orthogonal experimental analysis, the orthogonal experimental design of the solution dehumidification system includes 10 parameters, including the overall thermal conductivity of the system, solution mass flow rate, inlet air moisture content, inlet air temperature, dehumidifier air / solution flow ratio, regenerator air / solution flow ratio, dehumidifier solution inlet temperature, regenerator solution inlet temperature, cold source temperature, and heat source temperature. Evaluation indicators include dehumidification rate, heat loss, heat efficiency, heat dissipation, and heat efficiency.

6. The normalized modeling method for thermal-humidity decoupling according to claim 5, characterized in that, Analysis of 10 parameters in the orthogonal experimental design revealed the four most significant influencing factors of the solution dehumidification system, which are, in order, the overall thermal conductivity of the system, the mass flow rate of the solution, the air / solution flow ratio of the dehumidifier, and the temperature of the heat source.

7. The normalized modeling method for thermal-humidity decoupling according to claim 5, characterized in that, Multi-objective optimization shows that there is a trade-off between dehumidification rate, heat efficiency, and heat accumulation efficiency among the performance evaluation indicators of the solution dehumidification system, and the optimal solution values ​​are 3.25 g / s, 65.92%, and 12.01%, respectively.

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