An automated simulation method, system, and readable storage medium for condensation in fresh air conditioning systems.

Abstract

This application discloses an automated simulation method, system, and storage medium for condensation in fresh air conditioning systems. The method includes: automatically identifying the air duct, wall, air outlet, and computational domain after importing a simplified geometric model; automatically generating a mesh and refining it at least at the boundary layer of the condensation risk zone; automatically loading a preset parameter set containing low-temperature fresh air, indoor temperature and humidity, wall liquid film, condensation phase change, boundary conditions, and transient control; triggering a one-click calculation to perform fully coupled transient calculations of the flow field, temperature, phase field, and liquid film field, tracking in real time the wall's position below the dew point, liquid film formation, thickness changes, and flow convergence; and automatically outputting a temperature cloud map of the condensation area, a liquid film thickness distribution map, and a full-process evolution animation upon completion. This application automates the entire simulation process, enabling structural engineers to operate independently without CAE knowledge, directly obtaining key condensation information, lowering the barrier to entry, and accelerating optimization.

Description

Technical Field

[0001] This invention belongs to the field of computer-aided engineering (CAE) simulation technology, and particularly relates to an automated simulation method, system and readable storage medium for condensation in fresh air conditioning systems. Background Technology

[0002] While introducing fresh outdoor air to improve indoor air quality, fresh air conditioners face a significant technical challenge: in extremely cold winter environments (such as -20°C to -30°C), the low-temperature fresh air flowing through the indoor unit significantly lowers the local wall temperature. When the wall temperature falls below the dew point temperature of the indoor air, water vapor condenses, forming a liquid film on the wall. Over time, this liquid film grows, migrates, and accumulates, eventually forming visible water droplets that drip down, severely impacting product reliability and user experience. To predict and address this issue during the design phase, the industry has attempted to introduce CAE (Computer-Aided Engineering) simulation technology. For example, Chinese patent CN103851767A proposes a method to analyze the flow field by establishing a three-dimensional model and performing CFD (Computational Fluid Dynamics) numerical simulation, thereby assisting in the design of anti-condensation vents. Furthermore, some studies have utilized Eulerian Wall Film (EWF) models to simulate and analyze condensation on specific components (such as air guides). However, these existing simulation methods generally have significant limitations: they rely heavily on manual operation by professional CAE engineers, the process is cumbersome and time-consuming, and the lack of uniformity in simulation standards makes the results difficult to reproduce and compare. More importantly, the post-processing analysis of these methods is not focused enough, and they cannot automatically output key information directly needed by structural engineers, such as condensation thickness, regional distribution, and dynamic evolution, which seriously restricts the rapid iteration and optimization of anti-condensation structures in product development. Summary of the Invention

[0003] (a) Purpose of the invention To overcome the above shortcomings, the present invention aims to provide an automated simulation method, system and readable storage medium for condensation in fresh air conditioning systems, in order to solve the problems of high operation threshold, cumbersome process, inconsistent standards and inability to automatically output key results required for engineering in existing air conditioning condensation simulation technologies, which make it difficult to meet the needs of efficient product development.

[0004] (II) Technical Solution To achieve the above objectives, this application provides the following technical solution: An automated simulation method for condensation in a fresh air conditioning system includes the following steps: Step S1: In response to the simplified geometric model imported by the user, automatically identify the preset key areas in the simplified geometric model. The preset key areas include the air duct area, wall area, air outlet area and calculation domain area. Step S2: Automatically perform mesh generation for each identified preset key area, and perform boundary layer mesh refinement at least in the condensation risk area; Step S3: Automatically load the preset multiphysics simulation parameter set, which includes: low temperature fresh air condition parameters, indoor temperature and humidity parameters, wall liquid film model, condensation phase change model, boundary conditions and transient solution control parameters; Step S4: In response to the user's one-click calculation command, automatically perform fully coupled transient calculations of the flow field, temperature field, phase field and liquid film field, and track in real time the location where the wall temperature is below the dew point threshold, the time of liquid film formation, the change of liquid film thickness, and the flow and convergence process of the liquid film during the calculation process. Step S5: After the calculation is completed, the simulation results will be automatically output, including at least the temperature cloud map of the condensation area, the liquid film thickness distribution map of the wall, and the dynamic evolution animation of the entire condensation process.

[0005] This application encapsulates model import, region identification, mesh generation, multiphysics loading, coupled calculation, and result output into a complete automated execution chain, enabling structural engineers to independently complete condensation simulations without CAE expertise. The automatic region identification function eliminates the tedious manual labeling of different component regions in traditional simulations, while boundary layer mesh refinement effectively improves the solution accuracy for condensation risk areas without increasing the overall mesh count. Fully coupled transient calculations realistically reflect the complete physical process of wall temperature drop, water vapor phase change condensation, liquid film formation, and gradual thickening after the low-temperature fresh air meets the indoor hot and humid air. Real-time tracking ensures accurate capture of the condensation initiation time, liquid film thickness evolution, and flow accumulation trends. The final automatically output temperature cloud map, liquid film thickness distribution map, and dynamic evolution animation allow engineers to intuitively understand the specific location, severity, and time-varying trend of condensation without any additional post-processing, directly supporting subsequent structural optimization decisions.

[0006] In some embodiments, the automatic mesh generation in step S2 further includes: after the mesh generation is completed, automatically performing mesh quality checks and repairs. The mesh quality checks include at least: mesh distortion checks, mesh orthogonality checks, and mesh aspect ratio checks. When it is detected that the mesh quality does not meet the preset quality standards, the mesh areas that do not meet the quality requirements are automatically re-divided or the node positions are adjusted until all meshes meet the preset quality standards.

[0007] In traditional simulation operations, after mesh generation, CAE engineers must manually check each quality indicator one by one using software tools. If unqualified areas are found, mesh parameters must be repeatedly adjusted and the mesh re-divided, a lengthy process reliant on experience. This embodiment achieves automatic closed-loop control of mesh quality by pre-fixing the judgment criteria and repair logic of mesh quality checks into built-in program rules. This mechanism ensures that, without any additional manual intervention, each mesh generated by the program meets the geometric accuracy and numerical stability requirements of subsequent solutions, thereby avoiding computational divergence or result distortion caused by poor mesh quality, providing a fundamental guarantee for the reliability and repeatability of the simulation.

[0008] In some embodiments, the automatic mesh generation in step S2 further includes: after completing the mesh generation, automatically performing mesh independence verification. Mesh independence verification includes: performing trial calculations based on at least two sets of computational meshes with different mesh densities, comparing the deviations of key physical quantities in the condensation risk area under each set of meshes, and determining that the mesh density meets the computational accuracy requirements when the deviation is less than a preset threshold; otherwise, automatically triggering mesh adaptive densification and re-performing the verification.

[0009] In traditional CAE simulation workflows, mesh independence verification requires engineers to manually generate multiple meshes of different densities, submit calculations one by one, and manually compare the results. This process is extremely labor-intensive and time-consuming, and is therefore often omitted or simplified in practical engineering, making it difficult to guarantee the reliability of simulation results. This embodiment incorporates mesh independence verification into an automated execution chain, automatically quantifying the impact of mesh density on calculation results without requiring any additional user intervention. When calculation results exhibit unacceptable deviations due to insufficient mesh density, the program automatically densifies the mesh and re-verifies until the results stabilize. This mechanism fundamentally eliminates computational errors introduced by improper mesh generation, ensuring consistent reliability of simulation results obtained by different engineers at different times, thus providing a reliable data foundation for structural optimization decisions based on simulation results.

[0010] In some embodiments, the preset multiphysics simulation parameter set in step S3 further includes: a three-dimensional transient turbulence model, an Eulerian multiphase flow model, and a solid-liquid conjugate heat transfer model; and, the evaporation mode is turned off by default in step S3 to adapt to the unidirectional condensation characteristics of the low-temperature wall.

[0011] The combination of the above physical models comprehensively covers multiple physical processes involved in condensation phenomena, including fluid flow, gas-liquid two-phase distribution, and heat transfer between the gas phase and the solid wall. The three-dimensional transient turbulence model describes the unsteady flow characteristics of indoor hot and humid air after being disturbed by low-temperature fresh air. The Eulerian multiphase flow model accurately describes the coexistence of gaseous air and liquid water vapor and their condensed droplets. The solid-liquid conjugate heat transfer model depicts the heat transfer paths between the low-temperature airflow and the solid structure of the wall, as well as between the wall and the indoor air. The coupled solution of each model ensures that the simulation can realistically reflect the complete physical chain of airflow, wall cooling, water vapor phase change, and liquid film formation. The default setting of disabling evaporation eliminates the reverse physical processes that should be ignored in the low-temperature unidirectional condensation scenario, avoiding unnecessary computational costs and eliminating potential numerical oscillations.

[0012] In some embodiments, In step S3: the low-temperature fresh air condition parameters are -20℃ fresh air inlet temperature, and the indoor temperature and humidity parameters are 25℃ indoor temperature and corresponding humidity parameters; the dew point threshold is automatically calculated from the indoor temperature and humidity parameters. In step S2, the parameters for mesh refinement of the boundary layer in the condensation risk area are: first layer mesh thickness 0.1 mm, number of refinement layers 5.

[0013] The above operating parameters are typical values ​​for actual operation of fresh air conditioning systems in extremely cold winter environments. The program presets these as default values, avoiding the need for engineers to repeatedly input them each time. The automatic calculation function of the dew point threshold eliminates the need for engineers to consult dew point temperature tables or use external tools for calculation, reducing the introduction of human error. The specific values ​​of the boundary layer densification parameters are specifically configured. The initial layer thickness of 0.1mm effectively captures the drastic gradient changes in temperature and water vapor concentration near the wall. The five densification layers ensure accuracy while taking into account the overall mesh size, allowing the calculation to achieve engineering-usable accuracy within an acceptable timeframe. The pre-configuration of these parameters eliminates the need for engineers to concern themselves with the physical meaning and reasonable values ​​of the simulation parameters, further lowering the barrier to entry. Another aspect of this application provides an automated simulation system for condensation in a fresh air conditioning system, comprising: Model Import and Recognition Module: Configured to respond to simplified geometric models imported by users, automatically identify preset key areas in the simplified geometric models. The preset key areas include air duct areas, wall areas, air outlet areas, and computational domain areas. Automated Mesh Generation Module: Configured to automatically perform mesh generation for each identified preset key region, and perform boundary layer mesh refinement at least in condensation risk areas; after completing mesh generation, the automated mesh generation module automatically performs mesh quality checks and repairs, as well as mesh independence verification. Mesh quality checks include at least mesh distortion checks, mesh orthogonality checks, and mesh aspect ratio checks. When the mesh quality is detected to be inconsistent with the preset quality standards, local re-meshing or node position adjustment is automatically triggered. Mesh independence verification is performed on at least two sets of computational meshes with different mesh densities, and the deviations of key physical quantities in condensation risk areas are compared. Standardized simulation process module: Configured to automatically load preset multiphysics simulation parameter sets, which include: low temperature fresh air condition parameters, indoor temperature and humidity parameters, wall liquid film model, condensation phase change model, boundary conditions and transient solution control parameters; One-click calculation and solution module: Configured to respond to the user's one-click calculation command, automatically perform fully coupled transient calculations of flow field, temperature field, phase field and liquid film field, and track in real time the location where the wall temperature is below the dew point threshold, the time of liquid film formation, the change of liquid film thickness and the flow and convergence process of liquid film during the calculation process. Automatic post-processing and output module: Configured to automatically output simulation results, including at least the temperature cloud map of the condensation area, the liquid film thickness distribution map on the wall, and the dynamic evolution animation of the entire condensation process, after the calculation is completed.

[0014] The system provided in this application implements all the core functions of the methods described in Embodiments 1 to 3 in a modular manner. The model import and recognition module solves the problem of manually selecting and marking different component regions in traditional simulations, enabling non-professional users to correctly configure the model. The automated mesh generation module integrates mesh generation, quality control, and accuracy verification, ensuring that the mesh quality meets the solution requirements without manual intervention. The standardized simulation process module, by pre-configuring the physical model and operating parameters, not only eliminates the impact of differences in user operations on the consistency of results but also makes the simulation process reproducible and traceable. The one-click calculation and solution module completely hides the highly complex calculation process of multiphysics coupling from the user, allowing the user to trigger the complete calculation process with just one click. The automatic post-processing and output module eliminates the tedious operations of manually capturing cloud images, extracting data, and creating animations required in traditional simulations, directly producing visualized results that can be directly used for engineering judgment and structural optimization. Through the collaborative work of the above five modules, the system achieves full automation and standardization from model import to result output.

[0015] In some embodiments, the multiphysics simulation parameter set preset in the standardized simulation process module further includes: a three-dimensional transient turbulence model, an Eulerian multiphase flow model, and a solid-liquid conjugate heat transfer model; and the standardized simulation process module disables the evaporation mode by default to adapt to the unidirectional condensation characteristics of low-temperature walls.

[0016] In some embodiments, the low-temperature fresh air condition parameters are -20℃ fresh air inlet temperature and 25℃ indoor temperature and humidity parameters; the dew point threshold is automatically calculated from the indoor temperature and humidity parameters; the parameters for densifying the boundary layer mesh of the condensation risk area are: first layer mesh thickness 0.1mm and 5 densification layers.

[0017] In some embodiments, the automatic post-processing and output module is further configured to: output a distribution map of condensation risk levels and a report of key data for structural optimization; and output an animation of the dynamic evolution of the entire condensation process in AVI or MP4 format, the output of which includes at least the time-series evolution of the entire process from condensation generation, liquid film flow to liquid film accumulation.

[0018] The condensation risk level distribution map uses a visually intuitive color-coded grading system to indicate the severity of condensation in different areas of the wall, enabling engineers to quickly pinpoint problem areas and assess their risk levels. The key data report for structural optimization extracts crucial quantitative indicators such as condensation initiation time, maximum liquid film thickness and location, and liquid film coverage area, providing directly applicable data support for structural improvements. The dynamic evolution animation records the entire process of wall condensation from initial liquid film formation, gradual thickening, flow along the wall, to accumulation in specific areas, allowing engineers to fully understand the dynamic development of condensation and subsequently optimize and adjust the structure to alter airflow paths or wall temperature distribution. These outputs comprehensively support structural optimization decisions from three levels: qualitative judgment, quantitative analysis, and dynamic patterns.

[0019] This application also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of any of the above methods. Attached Figure Description

[0020] Figure 1 This is a flowchart of the automated simulation method for condensation in fresh air conditioning systems according to the present invention. Detailed Implementation

[0021] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to specific embodiments and the accompanying drawings. It should be understood that these descriptions are merely exemplary and not intended to limit the scope of the invention. Furthermore, descriptions of well-known structures and techniques are omitted in the following description to avoid unnecessarily obscuring the concept of the invention.

[0022] This invention provides an automated simulation method for condensation in a fresh air conditioning system. The user first imports a simplified geometric model of the indoor air conditioning unit and the fresh air module into the program. This simplified model is a geometric file after removing minor structural features such as bolts, clips, and reinforcing ribs; its format can be a common 3D drawing format such as STEP, IGS, or STL. Upon receiving the user's import operation, the program automatically identifies the duct area, wall area, air outlet area, and computational domain area in the simplified geometric model. Specifically, the program uses a pre-defined geometric recognition algorithm to automatically distinguish these different areas based on the model's topology and surface normal information, eliminating the need for the user to manually select or label each area on the interface. Subsequently, the program automatically performs mesh generation on each identified area, preferably using a polyhedral mesh type, which has better adaptability and lower numerical diffusion in complex geometric regions.

[0023] Specifically, the program will perform boundary layer mesh refinement at least in the condensation risk area—namely, the wall area directly impacted by the fresh airflow and the low-temperature area downstream of the air outlet—to ensure the accuracy of the velocity gradient, temperature gradient, and concentration gradient solutions in this area. Based on this, the program automatically loads a pre-configured multiphysics simulation parameter set. This parameter set is pre-configured for the low-temperature condensation scenario of the fresh air conditioning system and includes low-temperature fresh air operating parameters, indoor temperature and humidity parameters, wall liquid film model, condensation phase change model, boundary conditions, and transient solution control parameters. Users do not need to manually input any values ​​or select any models during this process.

[0024] Furthermore, while loading the aforementioned parameter set, the program automatically binds the geometric surfaces of each preset key region to the corresponding boundary condition types based on the regions automatically identified in step S1: the surface where the fresh air inlet is located is automatically bound as the velocity inlet boundary, the surface where the indoor air outlet is located is automatically bound as the pressure outlet boundary, and all wall surfaces are automatically bound as non-slip wall boundaries, and liquid film adhesion boundary conditions are automatically activated on the wall regions. Simultaneously, based on the currently loaded low-temperature fresh air operating parameters and the overall size of the computational domain, the program automatically configures an appropriate time step, maximum number of iterations per step, and convergence residual threshold for the transient calculation. The specific values ​​of the aforementioned boundary condition types and transient parameters are all pre-defined in the program as engineering default values, eliminating the need for users to manually specify or input any parameters. In this way, users do not need to perform any boundary condition selection, annotation, or parameter trial and error after the model is imported. The program completes the automated configuration of all boundary settings and solution control simultaneously with loading the physical field parameter set, further reducing manual intervention and making the closed-loop automation of the entire process more complete.

[0025] Furthermore, users only need to click the "Start Calculation" command on the program interface, and the program will automatically perform fully coupled transient calculations of the flow field, temperature field, phase field, and liquid film field.

[0026] Throughout the calculation process, the program tracks in real time the location where the wall temperature is below the dew point threshold, the moment when the liquid film first appears, the rate at which the liquid film thickness increases over time, and the flow direction and convergence location of the liquid film on the wall under the influence of gravity and airflow shear force.

[0027] After the calculation is completed, the program automatically outputs a temperature cloud map of the condensation area, a liquid film thickness distribution map of the wall, and a dynamic evolution animation of the entire condensation process. This dynamic evolution animation, with time as the horizontal axis, presents the complete evolution trajectory of condensation from nothing to something, from thin to thick, and from dispersion to accumulation, in a sequence of image frames. In this way, users do not need any professional background in computational fluid dynamics or numerical simulation, nor do they need to perform any post-processing operations, to directly obtain all the key information supporting structural optimization decisions.

[0028] Specifically, the automatic mesh generation in step S2 further includes automatic mesh quality checking and repair functions. Specifically, after the mesh is generated, the program immediately initiates the mesh quality check process. This check includes at least three dimensions: One is the mesh distortion check, which assesses the degree to which each mesh cell deviates from the ideal shape; The second is the grid orthogonality check, which assesses the degree of orthogonality between the edges of grid cells; Thirdly, the aspect ratio of the grid is checked, which evaluates the proportional relationship between the longest and shortest edges of the grid cells.

[0029] The three quality indicators mentioned above collectively determine the stability and accuracy of subsequent numerical solutions. When the program detects that the quality of a certain region or some mesh cells does not meet the preset quality standards, it will not simply report an error to the user or ask the user to manually correct it. Instead, it will automatically perform local mesh re-mapping or node repositioning operations for that region. This operation is iterative, meaning that the program will re-check the quality after each correction until all meshes meet the preset quality standards.

[0030] Preferably, the preset quality standard can be configured with different tolerances for different analysis regions. For example, a stricter quality standard can be used in areas with condensation risk, while a more lenient standard can be used in mainstream areas far from the wall. In this way, the mechanism ensures that each automatically generated mesh has good numerical solution quality, effectively avoiding common engineering problems such as computational divergence, numerical oscillation, or result distortion caused by poor mesh quality. It also provides a reliable mesh foundation for the stable convergence of subsequent multiphysics coupling calculations.

[0031] Specifically, the automatic mesh generation in step S2 further includes a mesh independence verification function. The specific implementation of this verification mechanism is as follows: After completing the initial mesh generation, the program will generate at least one set of comparison meshes with different densities based on the density of the initial mesh, that is, at least two sets of computational meshes with different mesh densities.

[0032] Then, the program performs trial calculations based on each set of meshes, focusing on comparing the deviations between the calculated results of key physical quantities within the condensation risk area. These key physical quantities may include indicators such as the minimum wall temperature, the maximum liquid film thickness, and its location. When the deviation is less than a preset threshold, the program determines that the current mesh density meets the computational accuracy requirements and no further refinement is needed. Conversely, when the deviation exceeds the preset threshold, it indicates that the current mesh density is insufficient to obtain a mesh-independent solution, and the program automatically triggers an adaptive mesh refinement operation—that is, prioritizing the refinement of regions with drastic changes in physical quantity gradients—and re-executes the above verification process.

[0033] Preferably, the trial calculations for verification can use fewer iterations or larger time steps to save computational resources, with the full transient settings only used in the final formal calculation. In this way, the mechanism fundamentally eliminates computational errors introduced by inappropriate mesh size without increasing the user's operational burden. This ensures that the results obtained by different engineers when simulating different machine models or operating conditions have consistent reliability and comparability, thus providing a reliable data foundation for structural optimization decisions.

[0034] Specifically, the multiphysics simulation parameter set preset in step S3 also includes a three-dimensional transient turbulence model, an Eulerian multiphase flow model, and a solid-liquid conjugate heat transfer model.

[0035] Specifically, the three-dimensional transient turbulence model is used to describe the unsteady turbulent flow characteristics formed by indoor hot and humid air after being impacted by a low-temperature fresh air jet. The preferred model is the SST k-ω turbulence model, which combines the computational accuracy of the near-wall region with the numerical stability of the mainstream region.

[0036] The Euler multiphase flow model is used to describe both the gas phase (air) and the liquid phase (condensed water) simultaneously. This model treats air as a continuous phase and water vapor and the tiny droplets formed by condensation as dispersed phases, thus achieving an accurate simulation of the coexistence of the gas and liquid phases.

[0037] The solid-liquid conjugate heat transfer model is used to couple and solve the bidirectional heat transfer process between the low-temperature airflow and the solid wall structure, as well as between the inside of the solid wall structure and the indoor air. It is worth noting that since this application addresses the physical scenario of unidirectional condensation at a low-temperature wall—that is, water vapor only changes from a gaseous to a liquid state at the low-temperature wall surface, without involving the reverse process of liquid water re-evaporating back to a gaseous state at room temperature—the program disables the evaporation function by default. This setting avoids unnecessary gas-liquid phase change mass transfer calculations, saving approximately 20% to 30% of computation time; it also eliminates potential numerical oscillations or non-physical solutions introduced by the evaporation model in the low-temperature unidirectional condensation scenario.

[0038] Furthermore, the coupling solution sequence between the above physical models is as follows: within each time step, first solve the turbulent flow field to obtain the velocity field and pressure field, then solve the energy equation to obtain the temperature field distribution, then solve the phase field to obtain the water vapor concentration distribution and condensation location, and finally solve the liquid film model to obtain the liquid film thickness, velocity and flow direction.

[0039] Specifically, the low-temperature fresh air condition parameters in step S3 are a fresh air inlet temperature of -20℃, and the indoor temperature and humidity parameters are an indoor air temperature of 25℃ and its corresponding humidity. These parameters represent typical boundary conditions for the actual operation of a fresh air conditioning system in extremely cold winter regions. After loading the above indoor temperature and humidity parameters, the program will automatically calculate the corresponding dew point temperature threshold based on the thermodynamic properties of the air. This calculation is automatically completed based on the physical relationship between dry-bulb temperature, relative humidity, and atmospheric pressure, without requiring the user to consult a dew point temperature table or use external calculation tools.

[0040] Furthermore, in step S2, the boundary layer mesh refinement parameters for the condensation risk region are specifically configured as follows: the initial mesh thickness is 0.1 mm, and the number of refinement layers is 5. This parameter combination is an optimal value determined after extensive condensation simulation verification: the initial layer thickness of 0.1 mm ensures that the region with the most severe temperature and water vapor concentration gradients near the wall is covered by a sufficiently fine mesh, while the number of refinement layers of 5 ensures the solution accuracy in this region while preventing the overall mesh size from becoming too large. Preferably, when the model scale changes significantly, the initial mesh thickness can be adjusted accordingly within the range of 0.05 mm to 0.15 mm, and the number of refinement layers can be increased to 6 layers to ensure a reasonable balance between computational accuracy and computational resources.

[0041] This application also provides an automated simulation system for condensation in a fresh air conditioning system. The system includes a model import and recognition module, an automated mesh generation module, a standardized simulation process module, a one-click calculation and solution module, and an automatic post-processing and output module.

[0042] The model import and recognition module is configured to automatically identify air duct regions, wall regions, air outlet regions, and computational domain regions in response to simplified geometric models imported by the user. This module employs a region segmentation algorithm based on curvature analysis and normal vector clustering, enabling automatic classification and labeling of regions in any imported simplified model.

[0043] The automated mesh generation module is configured to automatically perform mesh generation for each identified region, and at least perform boundary layer mesh refinement in condensation risk areas. After mesh generation, the module also automatically performs mesh quality checks and repairs, as well as mesh independence verification. The mesh quality check includes at least distortion checks, orthogonality checks, and aspect ratio checks. When a non-compliant mesh is detected, local re-meshing or node position adjustment is automatically triggered. The mesh independence verification is performed by comparing the deviations of key physical quantities based on at least two sets of computational meshes with different densities.

[0044] The standardized simulation process module is configured to automatically load a preset multiphysics simulation parameter set, which includes parameters for low-temperature fresh air conditions, indoor temperature and humidity parameters, wall liquid film model, condensation phase change model, boundary conditions, and transient solution control parameters.

[0045] The one-click calculation and solution module is configured to respond to a single click by the user, automatically perform fully coupled transient calculations of the flow field, temperature field, phase field, and liquid film field, and track in real time the location where the wall temperature is below the dew point threshold, the time of liquid film formation, thickness changes, and its flow and convergence process.

[0046] The automatic post-processing and output module is configured to automatically output the temperature cloud map of the condensation area, the wall liquid film thickness distribution map, and the dynamic evolution animation of the entire condensation process after the calculation is completed. The above five modules are connected in sequence to form a complete automated simulation pipeline from model input to result output. The entire operation of this pipeline does not require the user to perform any intermediate operations or parameter adjustments.

[0047] Specifically, the pre-set multiphysics simulation parameter set in the standardized simulation workflow module further includes a three-dimensional transient turbulence model, an Eulerian multiphase flow model, and a solid-liquid conjugate heat transfer model. The selection and configuration of these models have been pre-completed and embedded in this module. Simultaneously, the module disables the evaporation process by default to accommodate the physical characteristics of unidirectional condensation on low-temperature walls. The rationale for this setting is that, under conditions of continuous fresh air supply in extremely cold winters, the wall temperature remains consistently below the dew point temperature of the indoor air, resulting in continuous condensation while evaporation is negligible. Therefore, disabling the evaporation model aligns with physical reality and effectively reduces computational resource consumption.

[0048] Preferably, the module also reserves an interface for enabling evaporation conditions. When users need to simulate non-low temperature or variable temperature conditions, they can restart the evaporation model through advanced settings options. However, this option is kept hidden in the default interface to maintain the simplicity of the operation interface.

[0049] Specifically, the low-temperature fresh air operating parameters are preset to a fresh air inlet temperature of -20℃, and the indoor temperature and humidity parameters are preset to an indoor temperature of 25℃ and its corresponding humidity parameters. The dew point threshold is automatically calculated by the system based on the indoor temperature and humidity parameters, and the specific calculation method is as follows: First, the partial pressure of water vapor in the air is calculated based on the indoor dry-bulb temperature and relative humidity. Then, the corresponding saturation temperature, which is the dew point temperature, is calculated in reverse based on this partial pressure. In addition, the boundary layer mesh refinement parameters for the condensation risk area are preset to an initial mesh thickness of 0.1 mm and a refinement layer count of 5 layers.

[0050] The above operating parameters and mesh parameters are all system default values. Users can modify them through the advanced settings interface. However, in normal use cases, users do not need to pay attention to the specific values ​​of these parameters and can directly use the default values ​​to obtain simulation results that are usable in engineering.

[0051] Specifically, the automatic post-processing and output module is also configured to output a condensation risk level distribution map and a key data report for structural optimization. The condensation risk level distribution map is a visualization result obtained by comparing the liquid film thickness of each area of ​​the wall with a preset risk threshold and rendering it in different colors. For example, green represents safe areas, yellow represents areas requiring attention, and red represents high-risk condensation areas, enabling engineers to quickly locate problem areas. The key data report for structural optimization summarizes key quantitative indicators such as condensation start time, maximum liquid film thickness and its coordinate position on the wall, and the change curve of liquid film coverage area over time, and presents them in the form of tables or graphs.

[0052] Furthermore, the dynamic evolution animation of the entire condensation process can be output in AVI or MP4 format, both of which are supported by mainstream video playback software. The animation content includes at least the entire temporal evolution of condensation from its initial formation on the wall surface, its gradual thickening, its flow along the wall surface under the action of gravity and airflow shear force, and its final accumulation at a specific geometric structure. Engineers can intuitively observe the complete dynamic behavior of condensation by playing the animation, thereby more accurately determining the direction of structural adjustments.

[0053] This application also provides a computer-readable storage medium. This storage medium can be any medium capable of storing program code, such as a read-only memory, random access memory, USB flash drive, portable hard drive, magnetic disk, or optical disk. The storage medium stores a computer program, which, when executed by a processor, can implement all the steps of the automated simulation method for condensation control in a fresh air conditioning system as described in any of the preceding claims. In this way, the method of this application can be deployed as standalone software on a local computer, integrated into a cloud simulation platform as an online service, or burned into the firmware of a dedicated simulation device as an embedded function, offering broad application and deployment flexibility.

[0054] It should be understood that the specific embodiments described above are merely illustrative or explanatory of the principles of the invention and do not constitute a limitation thereof. Therefore, any modifications, equivalent substitutions, improvements, etc., made without departing from the spirit and scope of the invention should be included within the protection scope of the invention. Furthermore, the appended claims are intended to cover all variations and modifications falling within the scope and boundaries of the appended claims, or equivalent forms of such scope and boundaries.

Claims

1. An automated simulation method for condensation in a fresh air conditioning system, characterized in that, Includes the following steps: Step S1: In response to the simplified geometric model imported by the user, automatically identify the preset key regions in the simplified geometric model. The preset key regions include the air duct region, the wall region, the air outlet region, and the computational domain region. Step S2: Automatically perform mesh generation for each of the identified preset key regions, and perform boundary layer mesh refinement at least in the condensation risk areas; Step S3: Automatically load the preset multiphysics simulation parameter set, which includes: low temperature fresh air condition parameters, indoor temperature and humidity parameters, wall liquid film model, condensation phase change model, boundary conditions and transient solution control parameters; Step S4: In response to the user's one-click calculation command, automatically perform fully coupled transient calculations of the flow field, temperature field, phase field and liquid film field, and track in real time the location where the wall temperature is below the dew point threshold, the time of liquid film formation, the change of liquid film thickness, and the flow and convergence process of the liquid film during the calculation process. Step S5: After the calculation is completed, the simulation results will be automatically output, including at least the temperature cloud map of the condensation area, the liquid film thickness distribution map of the wall, and the dynamic evolution animation of the entire condensation process.

2. The method according to claim 1, characterized in that, The automatic mesh generation in step S2 also includes: after completing the mesh generation, automatically performing mesh quality checks and repairs. The mesh quality checks include at least: mesh distortion checks, mesh orthogonality checks, and mesh aspect ratio checks. When it is detected that the mesh quality does not meet the preset quality standards, the mesh areas that do not meet the quality requirements are automatically re-divided or the node positions are adjusted until all meshes meet the preset quality standards.

3. The method according to claim 1, characterized in that, The automatic mesh generation in step S2 further includes: after completing the mesh generation, automatically performing mesh independence verification. The mesh independence verification includes: performing trial calculations based on at least two sets of computational meshes with different mesh densities, comparing the deviations of key physical quantities in the condensation risk area under each set of meshes, and determining that the mesh density meets the computational accuracy requirements when the deviation is less than a preset threshold; otherwise, automatically triggering mesh adaptive densification and re-performing the verification.

4. The method according to claim 1, characterized in that, The multiphysics simulation parameter set preset in step S3 also includes: a three-dimensional transient turbulence model, an Eulerian multiphase flow model, and a solid-liquid conjugate heat transfer model; and, the evaporation mode is turned off by default in step S3 to adapt to the unidirectional condensation characteristics of the low-temperature wall.

5. The method according to claim 1, characterized in that, In step S3: the low-temperature fresh air condition parameter is the -20℃ fresh air inlet temperature, and the indoor temperature and humidity parameter is the 25℃ indoor temperature and the corresponding humidity parameter; the dew point threshold is automatically calculated from the indoor temperature and humidity parameter. In step S2, the parameters for densifying the boundary layer mesh of the condensation risk area are: the thickness of the first layer mesh is 0.1 mm, and the number of densification layers is 5.

6. An automated simulation system for condensation in a fresh air conditioning system, characterized in that, include: Model import and recognition module: Configured to automatically recognize preset key regions in the simplified geometric model in response to user-imported simplified geometric model. The preset key regions include air duct region, wall region, air outlet region and computing domain region. Automated mesh generation module: Configured to automatically perform mesh generation on each of the identified preset key regions, and to perform boundary layer mesh refinement at least in condensation risk areas; After the mesh generation is completed, the automated mesh generation module automatically performs mesh quality checks and repairs as well as mesh independence verification. The mesh quality checks include at least mesh distortion checks, mesh orthogonality checks, and mesh aspect ratio checks. When the mesh quality is detected to be not in line with the preset quality standards, local re-meshing or node position adjustment is automatically triggered. The mesh independence verification is based on at least two sets of computational meshes with different mesh densities, and the key physical quantity deviations in the condensation risk area are compared. Standardized simulation process module: Configured to automatically load a preset multiphysics simulation parameter set, which includes: low temperature fresh air condition parameters, indoor temperature and humidity parameters, wall liquid film model, condensation phase change model, boundary conditions and transient solution control parameters; One-click calculation and solution module: Configured to respond to the user's one-click calculation command, automatically perform fully coupled transient calculations of flow field, temperature field, phase field and liquid film field, and track in real time the location where the wall temperature is below the dew point threshold, the time of liquid film formation, the change of liquid film thickness and the flow and convergence process of liquid film during the calculation process. Automatic post-processing and output module: Configured to automatically output simulation results, including at least the temperature cloud map of the condensation area, the liquid film thickness distribution map on the wall, and the dynamic evolution animation of the entire condensation process, after the calculation is completed.

7. The system according to claim 6, characterized in that, The multiphysics simulation parameter set preset in the standardized simulation process module also includes: a three-dimensional transient turbulence model, an Eulerian multiphase flow model, and a solid-liquid conjugate heat transfer model; and the standardized simulation process module disables the evaporation mode by default to adapt to the unidirectional condensation characteristics of low-temperature walls.

8. The system according to claim 6, characterized in that, The low-temperature fresh air operating condition parameters are -20℃ fresh air inlet temperature, and the indoor temperature and humidity parameters are 25℃ indoor temperature and corresponding humidity parameters; the dew point threshold is automatically calculated from the indoor temperature and humidity parameters; the parameters for the densification of the boundary layer grid of the condensation risk area are: first layer grid thickness 0.1mm, and 5 densification layers.

9. The system according to claim 6, characterized in that, The automatic post-processing and output module is also configured to: output a distribution map of condensation risk levels and a key data report on structural optimization; the dynamic evolution animation of the entire condensation process is in AVI or MP4 format, and its output content includes at least the entire time-series evolution from condensation generation, liquid film flow to liquid film accumulation.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the steps of the method as described in any one of claims 1 to 5.

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