A rapid CFD simulation method and system for livestock and poultry houses for non-experts

Abstract

This application discloses a rapid CFD simulation method and system for livestock and poultry houses for non-experts, relating to the field of computational fluid dynamics simulation technology. It includes constructing standardized templates by identifying typical ventilation patterns in the livestock and poultry industry and the entities or equipment present in the houses. Through parameter extraction and simplified abstraction of these templates, users only need to input a few key parameters to automatically complete the core process from modeling to result output and directly view the simulation results. This application uses the above method to enable non-expert users to quickly complete the entire CFD simulation process for livestock and poultry buildings, balancing simulation efficiency and result reliability.

Description

Technical Field

[0001] This application relates to the field of computational fluid dynamics simulation technology, and in particular to a rapid CFD simulation method and system for livestock and poultry houses for non-experts. Background Technology

[0002] In centralized, large-scale production, the creation and maintenance of a microclimate environment are crucial factors affecting production efficiency and quality. Economic losses caused by environmental factors are very common in the livestock and poultry farming sector. Most livestock and poultry farms require precise sensing of environmental parameters within the farm throughout their entire lifecycle, including design, operation, and renovation, to support the design of environmental control strategies, equipment selection, assessment of animal thermophysiological status, and prediction of gas emissions. Environmental simulation and modeling have become core tools for meeting this need.

[0003] Computational Fluid Dynamics (CFD) simulations have mature workflows and are more economical and convenient than experimental testing. They can quickly simulate the aerodynamic environment of an object and report complete flow field distribution details. However, the application of CFD technology in livestock and poultry farming still faces significant bottlenecks: On the one hand, CFD preprocessing requires precise construction of the computational domain and boundary conditions, completing a series of operations such as boundary setting, sub-model matching, and solution control parameter setting, as well as simplifying complex livestock and poultry housing scenarios and modeling and evaluating animal physiology. This process is often extremely labor-intensive and highly dependent on the operator's understanding of the physics problem and long-term technical experience. On the other hand, the high licensing fees of commercial software and the high operational barriers of open-source software together constitute significant obstacles to its use.

[0004] For non-professional users in the livestock and poultry farming sector, their core need is not to master the intrinsic computer principles of airflow fields, but to obtain simulation results with reference value to help judge the feasibility of design or modification schemes.

[0005] In summary, how to deeply integrate and encapsulate the professional knowledge in the field of livestock and poultry farming with the best practices of CFD modeling and solving, so that agricultural engineers who are not CFD experts can also conduct high-confidence simulations, remains an urgent problem to be solved. Summary of the Invention

[0006] To address the aforementioned issues, this application proposes a rapid CFD simulation method and system for livestock and poultry houses for non-experts. It aims to solve the problems of high barriers to entry, low efficiency, complex parameter configuration, and uncontrollable accuracy in existing livestock and poultry CFD simulation technologies. The specific details are as follows: On the one hand, this application proposes a rapid CFD simulation method for livestock and poultry houses for non-experts. The method adopts a design concept that combines template-based and wizard-based approaches. The core is to hide the complexity of the underlying CFD configuration and expose key parameters related to engineering decisions. This avoids users directly accessing the underlying CFD configuration details such as mesh generation, turbulence model selection, and numerical format settings. Only a few input parameters highly relevant to engineering decisions are used to drive the entire CFD simulation process to run efficiently, including the following steps: S1. Construct a livestock and poultry house building database based on the structure and heat transfer properties of livestock and poultry houses under different ventilation modes; Based on the components present in livestock and poultry houses, component structure, component location, and component ventilation conditions are extracted to construct a component template library, wherein the components include physical objects or equipment; The aforementioned livestock and poultry housing component template library includes simplified templates for solid structures and porous media for different types of animal activity areas; Ventilation modes include typical ventilation modes such as tunnel ventilation, ceiling air intake, side wall window air intake, precision duct air supply, and semi-enclosed natural ventilation; Livestock and poultry housing components include livestock and poultry, livestock and poultry activity areas, wet curtains, fans, small windows, ventilation openings, manure ditches, and enclosure walls, which are typical entities or equipment that have a significant impact on airflow and the thermal and humid environment.

[0007] Understandably, the construction of CFD simulation templates follows the principle of balancing universality and representativeness. Specifically, it includes templates for ventilation modes of different livestock and poultry buildings and templates for livestock and poultry house components for different animal categories, covering mainstream application scenarios in the livestock and poultry field and meeting the simulation needs of different breeding types and different building structures.

[0008] Specifically, the database of livestock and poultry house buildings (including various ventilation modes such as tunnel ventilation, ceiling air intake, side wall small window air intake, precision duct air supply, and semi-enclosed natural ventilation) and the component template library (various physical equipment structures such as chicken cages, wind deflectors, small windows, fans, and wet curtains, as well as abstract areas such as animal activity areas).

[0009] This application targets parametric modeling of livestock and poultry houses, generating an initial mesh based on the minimum feature size of the components and a preset basic size; for naturally ventilated livestock and poultry houses, it establishes a cylindrical outer domain and divides the mesh according to preset rules, which adopt existing rules.

[0010] This application abstracts the fan-evaporative cooling pad system of mechanically ventilated livestock and poultry houses into a standardized CFD physical model, which includes five major modules: evaporative cooling pads, ventilation windows, wind deflectors, animal activity areas, and fans. The modeling rules are as follows: The evaporative cooling pad is simplified to a total pressure inlet and a porous media area; The fan is simplified to a pressure outlet and an internal momentum setting surface; The ventilation window uses a total pressure inlet; The animal activity area is simplified into a porous media region; The deflector and the low wall are simplified into a non-slip solid wall.

[0011] The parameters of the above components are all based on industry-standard data, and the resistance coefficient is automatically calculated using a resistance calculator.

[0012] S2. Input building data and component data for the specific simulation object; Based on the building data, the corresponding template data is input into the livestock and poultry house building database to generate the main geometry of the livestock and poultry building; Based on the component data, the corresponding template data is input into the component template library to predefine the simulated reusable components, that is, to realize the parameterized predefinition of components such as fans, wet curtains, air guide windows, livestock and poultry breeding units, and enclosure structures, which supports subsequent batch assembly and rapid configuration under multiple working conditions. The initial CFD geometric model is formed by assembling reusable components (fans, wet curtains, livestock and poultry breeding units, etc.) in the main geometry of the livestock and poultry building by calling the simulation of reusable components. Based on the component parameters, the corresponding template data is extracted from the component template library to predefine the specific content of the simulated reusable component, including: (physical animal model, equipment abstract model, construction abstract model, area simplification model, etc.).

[0013] Based on user needs or simulation resource limitations, physical animal models will be equipped in key observation areas and animal activity areas in small-scale simulations. In non-focused areas or large-scale simulations, complex and computationally intensive entities such as animal activity areas and slatted floors are simplified into porous media regions and the drag coefficient of complex modeled objects is calculated. Understandably, the parameterized implementation of the template is as follows: By parametrically disassembling various ventilation system components, a component template database is formed; Users can predefine components by inputting specific parameters into the component template database, mainly defining their structural and ventilation characteristic parameters, including: Fan structural parameters include diameter and thickness, while ventilation characteristic parameters include rated air volume or fan performance curve; The structural parameters of the evaporative cooling pad include length, width, height, ventilation characteristics, resistance characteristics, and cooling characteristics; The structural parameters of the animal activity area include length, width and height, and the ventilation characteristics include the number of animals, heat production per animal, and resistance characteristics. In real-world case modeling, template components from the database are directly called for component assembly to quickly generate a complete CFD simulation model without having to build from scratch. The component equipment has its installation parameters set, including installation location, quantity, and installation indirection.

[0014] S3. Semi-automatic mesh generation is achieved by dividing the mesh according to the dimensional characteristics of the livestock and poultry house structure and component structure; S4. Automatically configure boundary conditions for livestock and poultry house building parameters (ventilation template attribute parameters) and external environmental parameters (temperature, humidity, natural ventilation including wind speed and wind direction) based on the initial CFD geometric model; Based on the component parameters (attribute parameters) of the initial CFD geometric model and the preset empirical parameters, the coupling characteristics of ventilation, heat and humidity environment and airflow resistance in the grid area are set (i.e., the momentum, cooling and resistance characteristics of the fan-wet curtain system and the heat and humidity generation parameters of the livestock activity area are automatically set), and the turbulence parameters are automatically estimated by combining empirical formula parameters to complete the CFD preprocessing. This application categorizes boundary conditions into four types: inlet, outlet, solid wall, and symmetry plane. Inlet and outlet are both subject to total pressure boundary, building walls are subject to thermal conductivity boundary, ventilation components are subject to non-slip boundary, and symmetry planes are subject to symmetry boundary.

[0015] Users only need to input three parameters: ambient temperature, humidity, and wind direction, and the system will automatically complete all boundary settings.

[0016] The inlet temperature is calculated based on dry-bulb temperature, relative humidity, and the cooling coefficient of the wet curtain. Turbulence parameters are automatically estimated using CFD empirical formulas. Natural ventilation uses atmospheric boundary layer conditions and a semi-cylindrical inlet.

[0017] This application simplifies the fan, wet curtain, and animal activity area into a grid influence area and automatically adds momentum source terms and energy source terms: the resistance effect adopts the porous medium momentum source term, the driving effect adopts velocity-pressure interpolation, and the heat exchange effect calculates the heat source intensity per unit volume according to the component properties.

[0018] S5. With preset solver parameters, it automatically completes steady-state calculation and multi-physics coupling solution to obtain the first set of results. Subsequently, it can semi-automatically perform adaptive mesh refinement based on the flow field velocity gradient and solve to obtain the second set of mesh and results. Then, it can semi-automatically perform multiple sets of gradient mesh refinement and solve to obtain the corresponding mesh and results. This application has the manually configured parameters built into a script. With mesh adaptation and empirical parameters, users can automatically run multiple iterations with one click. The results can be used to complete mesh independence verification. The parameters of the boundary and region can be automatically iterated and updated during multiple calculations. The robust computational setup employed in this application uses a k-epsilon or k-omega two-equation turbulence model, supports first- / second-order schemes for the convection term, has a pressure field relaxation factor of 0.7, and other fields range from 0.2 to 0.4. The convergence criterion is 10. -4 The minimum iteration is 3000 steps, and the air age is calculated simultaneously to assess the air quality inside the building.

[0019] This application proposes an automated grid independence analysis method using multiple gradient grids. Group 1 generates the basic grid and performs initial calculations; Group 2 uses a three-level adaptive refinement based on the velocity gradient field; Groups 3 through n refine the grid according to the growth rate of the number of grids, and adjust the refinement threshold to ensure regional stability. Simultaneously, based on the iterative results, the cooling efficiency of the evaporative cooling pad and the inlet and outlet turbulence parameters are dynamically adjusted to improve the simulation stability and accuracy.

[0020] S6. Based on any solution result, output flow field detection point data, slice cloud map and vector map and inlet and outlet streamline map, automatically calculate temperature and humidity index (THI), ambient temperature index (ETI), air age core evaluation index, automatically output the operating status of core equipment such as wet curtain fans, and complete the livestock and poultry environment simulation assessment.

[0021] This application performs post-processing to simultaneously calculate and visualize the Temperature and Humidity Index (THI) and the Environmental Temperature Index (ETI). The output slice cloud map includes velocity, temperature, pressure, air age, THI, and ETI cloud maps. The vector map is mainly a velocity vector map, and the streamline map consists of inlet and outlet streamlines. It automatically outputs the operating status of core equipment such as evaporative cooling pads and fans, mainly including fan operating pressure, wind speed, rotational speed, and energy consumption (attribute parameters under different fan performance curves), for the assessment of heat stress and environmental comfort in livestock and poultry.

[0022] Preferably, the specific content of parameterizing and encapsulating the structure and heat transfer properties of livestock and poultry houses under different ventilation modes is as follows: Structural parameters are obtained by parametric extraction of livestock and poultry house structures; The heat transfer properties of livestock and poultry houses under different ventilation modes were parameterized and extracted to obtain heat transfer attribute parameters; The livestock and poultry house building database includes structural parameters and heat transfer attribute parameters; The heat transfer property parameters are used to automatically match and set the boundary conditions required for CFD simulation, so as to realize the linkage between parameters and simulation settings. Preferably, the component template library includes component structural parameters, component location parameters, component ventilation attribute parameters, and drag coefficient; The component structure parameters, component location parameters, and component ventilation attribute parameters are obtained by extracting parameters for the component structure, component location, and component ventilation status, respectively. The drag coefficient was calculated using a drag calculator; The component location parameters are used to install components in batches in the livestock and poultry house model, along with structural parameters to assist in automatic mesh generation.

[0023] Preferably, the grid division adopts a semi-automatic setting method, specifically including: Based on the classification and definition of poultry house building structures and components in the livestock and poultry house building database and component template library, combined with the maintenance structures and location parameters of the livestock and poultry house, and relying on the preset background grid size, the entire simulation model is automatically meshed.

[0024] Preferably, the boundary conditions and the initial conditions of the grid region are set in a semi-automatic manner. The automatic configuration of boundary conditions based on the livestock and poultry house building parameters and external environmental parameters of the initial CFD geometric model specifically includes: The boundary conditions between the interior and exterior of the building are all configured as walls or pressure inlets and outlets, and the heat exchange between the building structure and the outside world is configured by the heat transfer coefficient of the building structure material properties.

[0025] Preferably, the boundary conditions and initial conditions of the grid region also include other in-cell equipment, specifically including: The fan sets the internal fan grid domain velocity-momentum source term or dynamic velocity-pressure change boundary according to the predefined rated air volume or fan performance curve; The evaporative cooling pad sets the resistance coefficient and negative heat source coefficient of the internal evaporative cooling pad grid domain according to the predefined evaporative cooling pad resistance characteristics and cooling characteristics; The animal activity area automatically sets the animal heat and humidity production rates based on the input number of animals and the current ambient temperature and humidity.

[0026] Preferably, in S5, the iterative process generates different numbers of grids at a grid number growth rate of 1.5 times based on the discrete distribution of the computational domain space in the grid adaptive optimization, and automatically completes the grid independence analysis.

[0027] Preferably, during the S5 iteration process, the current dynamic boundary and grid region conditions are automatically determined based on the previous solution, the simulation accuracy is optimized, and multiple iterative solutions for grid independence verification and adaptive boundary and grid region conditions are achieved.

[0028] The dynamic boundary and grid region conditions specifically include: inlet and outlet turbulence parameter conditions; and the negative heat source coefficient of the internal wet curtain grid domain.

[0029] On the other hand, this application proposes a rapid CFD simulation system for livestock and poultry houses for non-experts. The rapid CFD simulation system for livestock and poultry houses is equipped with a porous media resistance calculator, which is used to calculate the resistance coefficient of the animal activity area and complex structures with fine features in the livestock and poultry house.

[0030] Preferably, the CFD rapid simulation system for livestock and poultry houses for non-experts includes: CFD Parametric Modeling Unit: Based on the structure and heat transfer properties of livestock and poultry houses under different ventilation modes, a livestock and poultry house building database is constructed. Based on the components present in the livestock and poultry houses, the component structure, component location, and component ventilation status are extracted to construct a component template library. The components include entities or equipment. The livestock and poultry house component template library contains simplified templates for the entity structure and porous media of different types of animal activity areas. For specific simulation objects, building data and component data are input. Based on the building data, the corresponding template data is extracted from the livestock and poultry house building database to generate the main geometry of the livestock and poultry house. Based on the component data, the corresponding template data is extracted from the component template library to predefine simulated reusable components. The simulated reusable components of the livestock and poultry house are called to perform batch assembly of components in the main geometry of the livestock and poultry house to form an initial CFD geometric model. Automated mesh generation: Semi-automated mesh generation is achieved by dividing the mesh based on the dimensional characteristics of the livestock and poultry house structure and component structure; Intelligent boundary condition configuration: Based on the parameters of the livestock and poultry house building database and the external environment parameters, the boundary conditions are automatically configured. Based on the parameters of the component template library and the preset empirical parameters, the coupling characteristics of ventilation, heat and humidity environment and airflow resistance in the grid area are set. Combined with empirical formula parameters, the turbulence parameters are automatically estimated to complete the CFD preprocessing. Adaptive Iterative Calculation: With preset solver parameters, it automatically completes steady-state calculation and multi-physics coupled solution to obtain the first set of results. Subsequently, it can semi-automatically perform adaptive mesh refinement based on the flow field velocity gradient and solve to obtain the second set of mesh and results. Then, it can semi-automatically perform multiple sets of gradient mesh refinement and solution to obtain the corresponding mesh and results. The results of multiple iterations can be used to complete mesh independence verification, and the parameters of the boundary and region can be automatically iterated and updated during multiple calculations. Simple post-processing: Based on any solution result, output flow field detection point data, slice cloud map and inlet / outlet streamline map, automatically calculate temperature and humidity index (THI), ambient temperature index (ETI), air age core evaluation index, automatically output the operating status of core equipment such as wet curtain fans, and complete the simulation evaluation of livestock and poultry environment.

[0031] In summary, the rapid CFD simulation method for livestock and poultry houses proposed in this application, designed for non-experts, has the following advantages compared to traditional technologies: 1. Adopting a design concept that combines templates and wizards, the complexity of the underlying CFD configuration is hidden, while key parameters related to engineering decisions are exposed. This avoids users directly contacting the underlying CFD configuration such as mesh generation details, turbulence model selection, and numerical format settings. Only a few input parameters that are highly relevant to engineering decisions are used to drive the entire CFD simulation process to run efficiently. Non-expert users only need to input a few engineering parameters to complete the entire simulation process, which greatly reduces the operating threshold. 2. Construct a dedicated parametric component library for livestock and poultry, enabling batch assembly of geometric models and improving modeling efficiency; fully automated configuration of boundary conditions, porous media parameters, and mesh generation eliminates manual configuration errors and improves simulation consistency; integrates multi-level mesh automated independence verification and boundary dynamic iteration mechanism, balancing computational efficiency and simulation accuracy; integrates modeling, solving, and post-processing in one system, automatically outputting core evaluation indicators of livestock and poultry heat stress, adapting to the rapid application needs of livestock and poultry breeding engineering.

[0032] The technical methods of this application will be further described in detail below with reference to the accompanying drawings and embodiments. Attached Figure Description

[0033] Figure 1 This is a step-by-step diagram of a rapid CFD simulation method for livestock and poultry houses for non-experts, as described in this application. Figure 2 This is a schematic diagram of the fan-cooled curtain boundary system of this application; Figure 3 This is an interface display diagram showing the dimensions of the wall-mounted fan in this application; Figure 4 This is a simulation model diagram of the wet curtain room in the tunnel-ventilated chicken house used for testing in this application; Figure 5 This is a simulation model diagram of the evaporative cooling pad air intake window in the tunnel-ventilated chicken coop used in this application for testing. Figure 6 This is a simulation model diagram of a stacked caged chicken flock in a tunnel-ventilated chicken house used for testing in this application; Figure 7 This is a geometric model diagram of the tunnel-ventilated chicken coop used for testing in this application.

[0034] Figure Labels 1-1. Wet curtain thickness; 1-2. Inner height of the wet curtain compartment; 1-3. Wet curtain height; 1-4. Wet curtain width; 1-5. Height of the wet curtain from the ground; 1-6. Wet curtain length; 1-7. Length of the wet curtain compartment; 1-8. Outer height of the wet curtain compartment; 2-1. Angle of the guide plate; 2-2. Number of guide plates; 2-3. Width of the guide plate; 2-4. Height of the guide plate; 3-1. Length of the chicken cage; 3-2. Number of chicken cage layers; 3-3. Ground level; 3-4. Height of the bottom of the chicken cage from the ground; 3-5. Spacing between chicken cages; 3-6. Height of the actual animal activity area in the chicken cage; 3-7. Height of the chicken cage; 3-8. Width of the chicken cage. Detailed Implementation

[0035] The technical methods of this application will be further described below with reference to the accompanying drawings and embodiments. It should be noted that, unless otherwise specifically stated, the relative arrangement, numerical expressions, and values ​​of the components and steps described in these embodiments do not limit the scope of this application.

[0036] The following description of at least one exemplary embodiment is merely illustrative and is in no way intended to limit the scope of this application and its application or use.

[0037] Techniques, systems, and equipment known to those skilled in the art may not be discussed in detail, but where appropriate, they should be considered part of the instruction manual.

[0038] In all the examples shown and discussed herein, any specific values ​​should be interpreted as merely exemplary and not as limitations. Therefore, other examples of exemplary embodiments may have different values.

[0039] Unless otherwise defined, the technical or scientific terms used in this application shall have the ordinary meaning as understood by a person of ordinary skill in the art to which this application pertains.

[0040] This application presents a unified, end-to-end rapid CFD simulation technology solution for the livestock and poultry industry, designed for non-expert users. It integrates standardized modeling of livestock and poultry structures, intelligent parameter configuration, automated mesh generation, adaptive boundary matching, intelligent solving, and visualization post-processing technologies across the entire chain. The specific content includes: This application summarizes various ventilation modes in the field of livestock and poultry farming, and standardizes and encapsulates the building structure and ventilation system component installation logic of each ventilation mode to form a simulation model database, including two levels: different ventilation modes and ventilation system components.

[0041] Building structures mainly include structural parameters and property parameters, while ventilation system components mainly include three parts: structural parameters, installation parameters, and property parameters.

[0042] The predefined modeling of ventilation system components is based on the ventilation system component templates contained in the ventilation system database. Users can input relevant parameters according to the schematic diagram to build special components for different cases. After this defined modeling, subsequent manual geometric modeling can directly use these predefined component models for assembly.

[0043] Existing manual geometric modeling uses a top-down workflow. This application adopts a batch assembly-style modeling approach for mechanical products, treating ventilation system components as parts and the main building structure as the assembly body, and dividing it into three steps: component preparation, main body creation, and component installation. (1) Ventilation system component preparation stage: Set specific parameter templates for each component type, add parameterized components in the database according to the templates, and input structural parameters and attribute parameters; (2) Initialization and creation stage of building main structure: Select ventilation mode, set building geometry and physical parameters, and generate livestock and poultry house building structure; (3) Ventilation system component installation stage: replicate the components in the array and install them in batches, set the installation parameters, and update the model data synchronously when the parameters are modified.

[0044] Example 1 This embodiment uses a tunnel-ventilated, multi-layered caged laying hen house as the engineering implementation object, and fully implements the rapid CFD simulation method for livestock and poultry fields described in this application, which is geared towards non-experts. The implementation object includes five core physical objects: the main enclosure structure of the livestock and poultry house, the wall-mounted negative pressure ventilation fan, the evaporative cooling wet curtain room, the wet curtain air inlet guide window, and the multi-layered caged livestock and poultry activity area. The entire process adopts the standardized template system, parametric component definition, automated mesh generation, adaptive boundary configuration, and multi-round iterative solution technology of this application to complete the numerical simulation. The specific implementation process is as follows.

[0045] 1. Construction of parametric simulation geometric model: For layered cage chicken houses using tunnel ventilation, the ventilation system is a longitudinal tunnel ventilation. The main building structure is typically a long, narrow, enclosed structure, formed by two side walls, two end walls, a gable roof, and the ground, creating a longitudinally continuous, narrow computational domain. Layered cage areas are arranged longitudinally within the house, with exhaust fans installed at one end wall and evaporative cooling pads installed at the corresponding end / side walls, forming a unidirectional airflow channel along the length of the house. This is the most commonly used high-density mechanical ventilation house structure in the livestock and poultry industry. Figure 1 As shown. This embodiment adopts a batch assembly parametric modeling method, which abstracts the ventilation system components into standardized parametric units and the main body of the livestock and poultry house into an assembly base. Referring to the batch manufacturing logic of mechanical products, the entire computational domain geometric model is automatically constructed in three steps: component parametric definition, livestock and poultry house main body parametric modeling, and component batch assembly, without the need for manual modeling of each component.

[0046] 1.1 Ventilation Mode and Parametric Definition of System Components of Ventilation System: The main structure of the egg-laying hen house with tunnel ventilation mode includes two side walls, two end walls, a roof and a ground. It can be quickly modeled using four structural parameters: length, width, side wall height, and ridge height. Its heat transfer characteristics only need to be defined by maintaining the thermal resistance of each part.

[0047] The core components of its ventilation system, after simplification, can be categorized as follows: wall-mounted negative pressure fans, evaporative cooling pads, airflow guide windows, and stacked caged chicken flocks (cages, chicken flocks, transmission equipment, and other main structural components within the house are uniformly integrated). Each component is refined into three core parameter systems: structural parameters, installation parameters, and attribute parameters. The specific definitions of structural and attribute parameters are as follows: (1) Wall-mounted negative pressure fan components: two structural parameters, fan diameter and axial installation thickness; defining aerodynamic physical property parameters such as pressure-airflow performance curve and pressure-power performance curve. Figure 3As shown.

[0048] (2) Components of the evaporative cooling pad compartment: installation structural parameters such as evaporative cooling pad installation height, segment width, installation depth, body thickness, and width and height of the evaporative cooling pad compartment; defining physical property parameters of heat and mass transfer such as the evaporative cooling pad speed-pressure drop resistance characteristic curve and the speed-evaporative cooling efficiency characteristic curve, such as... Figure 2 and Figure 4 As shown.

[0049] (3) Evaporative cooling pad air inlet guide window component: Define structural parameters such as the effective width and height of the air inlet, the number of layers of the guide structure, and the air delivery angle of the guide plate, which are used for geometric constraints and flow direction control of the airflow organization, such as... Figure 5 As shown.

[0050] (4) Components of the stacked caged livestock and poultry activity area: Define geometric structural parameters such as single cage length, width, cage height, effective height of porous media area, and number of cage layers; define multi-physical field attribute parameters such as porous media viscous resistance coefficient, inertial resistance coefficient, total number of livestock and poultry, steady-state heat production power per animal, and steady-state moisture production rate per animal, to couple and quantitatively characterize the flow resistance, heat source term, and moisture source term characteristics of the animal activity area, such as... Figure 6 As shown.

[0051] This embodiment constructs a dedicated standardized parameter template for each type of ventilation system component. Based on engineering measurement data and equipment nominal parameters, it completes the parameterization assignment of components. By inputting structural dimension parameters and physical property parameters, it forms a reusable and batch-callable predefined parameter component for the ventilation system.

[0052] 1.2 Parametric Modeling of the Chicken Coop Building: Based on the aforementioned standardized tunnel ventilation template, the main body model can be automatically completed by inputting the geometric parameters of the livestock and poultry house's main structure and the physical properties of its enclosure structure. The geometric parameters include the total length, total width, vertical height of the side walls, and height of the roof ridge; the physical properties are the thermal conductivity of each enclosure wall. Based on these input parameters, the main geometric model of the livestock and poultry house's closed fluid computational domain is automatically generated.

[0053] 1.3 Mass spatial assembly of ventilation system components: After completing the parametric modeling of the main body of the livestock and poultry house, the predefined standardized ventilation system components in the component database are called up. By inputting the installation and positioning parameters, various components are assembled in batches to the designated positions of the main geometric model, realizing the automated assembly of the entire model.

[0054] In this embodiment, the assembly of components for the tunnel-ventilated layer hen house relies on the building's main enclosure surface. Installation parameters first require defining the enclosure surface type to which the components are compatible, and then defining the array layout parameters based on the wall's two-dimensional coordinate system: viewing the target enclosure surface from an outdoor perspective, with the lower left corner of the wall as the origin, the horizontal direction as the X-axis, and the vertical direction as the Y-axis. Precise component positioning is achieved through coordinates and array parameters. The assembly constraints and installation parameters for various components are defined as follows: (1) Wall-mounted negative pressure fan: The installation surface is suitable for double side walls and two end walls; the installation parameters include the reference installation coordinates (X, Y), the number of horizontal arrays, the number of vertical arrays, the horizontal adjacent spacing, and the vertical adjacent spacing.

[0055] (2) Wet curtain room: The suitable installation surface is the double side wall and the two end wall; the installation parameters include the reference installation coordinates (X, Y), the number of horizontal arrays, the number of vertical arrays, the horizontal adjacent spacing, and the vertical adjacent spacing.

[0056] (3) Evaporative air inlet guide window: The suitable installation surface is the double side wall and the two end walls; the installation parameters include the reference installation coordinates (X, Y), the number of horizontal arrays, the number of vertical arrays, the horizontal adjacent spacing, and the vertical adjacent spacing.

[0057] (4) Stacked caged livestock and poultry activity area: The suitable installation surface is the floor inside the house; this component uses the end wall as the 2D coordinate system; the installation parameters include the reference installation coordinates (X, Y), the number of horizontal arrays, the number of vertical arrays, the horizontal adjacent spacing, and the vertical adjacent spacing.

[0058] After inputting the above installation and positioning parameters, the system automatically completes the batch array assembly of all ventilation system components. When component parameters are modified, the geometric topology and physical properties of the simulation model will be updated synchronously, ultimately generating a complete, closed, and geometrically interference-free CFD simulation geometric model of the livestock and poultry house, such as... Figure 7 As shown.

[0059] 2. Automated mesh generation and adaptive encryption: This embodiment focuses on the automated generation of meshes in a multi-layered cage-raised laying hen house with tunnel ventilation mode. The entire mesh generation process is implemented using the OpenFOAM open-source numerical simulation platform. The core tool used is blockMesh to construct the structured background mesh, and snappyHexMesh to refine and densify the mesh, generate the boundary layer, and divide the mesh region. The entire process does not require manual adjustment of mesh size, boundary layer parameters, and densification rules.

[0060] Since the simulation object is a forced mechanical ventilation poultry house, only the internal fluid computational domain needs to be meshed, and the external atmospheric computational domain is not constructed. First, a standardized cubic background mesh that completely surrounds the chicken house model is generated using blockMesh, and the three-dimensional geometric dimensions of the mesh are all set to integer multiples of the user-preset base mesh size. Combining the symmetrical structural characteristics of the chicken house computational domain, a symmetrical plane is set along the Y-axis, and symmetrical boundary conditions are used to reduce the size of the computational domain, effectively reducing the numerical computation cost.

[0061] Based on the initial background mesh, the basic mesh refinement, boundary layer addition, and automated generation of mesh sets are completed using snappyHexMesh. The basic mesh refinement uses a preset basic mesh size as the core benchmark, automatically extracting the dimensional parameters and installation gap parameters of each ventilation component during the geometric modeling stage. It then filters out the minimum feature dimensions of components such as fan thickness and guide window thickness. The ratio of the minimum feature dimension to the preset basic mesh size is used as the basis for determining the encryption level: a ratio > 10 uses Level 1 encryption, a ratio of 4-10 uses Level 2 encryption, a ratio of 2-4 uses Level 3 encryption, and a ratio < 2 uses Level 4 encryption. Adaptive surface encryption is then performed on the structural surfaces of each component according to the rule of decreasing the feature encryption level by one. Mesh generation is automatically completed based on the pre-defined component-specific tags in the geometric modeling stage. SnappyHexMesh can generate corresponding faceZone and cellZone regions for fan surfaces, wet curtain surfaces, and porous media areas for livestock and poultry activities, providing standardized region indexes for subsequent automatic assignment of boundary conditions, definition of porous media properties, and addition of heat and moisture source items.

[0062] 3. Automated configuration of boundary conditions and grid region conditions: 3.1 Standardized physical modeling of the fan-evaporative cooling pad system: For layered cage chicken houses with tunnel ventilation mode, the core fan-evaporative cooling system is abstracted into a standardized CFD physical model. The model includes four core components: evaporative cooling unit, evaporative cooling air inlet and guide unit, porous media unit for layered caged livestock and poultry activities, and wall-mounted negative pressure exhaust fan unit. Based on the physical characteristics of each component, unified modeling and boundary assignment rules are established. The component parameters all adopt industry-standardized equipment data and empirical formulas, and the built-in porous media resistance calculator completes the automatic solution.

[0063] The evaporative cooling pad unit is simplified as a composite structure of a pressure inlet boundary and an internal porous media surface, with the internal surface set as a porous baffle boundary. The resistance characteristics are defined by the Darcy-Forchheimer equation. The wall-mounted negative pressure fan unit is simplified as a composite structure of a pressure outlet boundary and an internal fan surface, with the internal surface set as a fan momentum boundary. The ventilation performance is defined by linear fitting of the equipment pressure-airflow performance curve. The side wall windows in the tunnel ventilation mode adopt a pressure inlet boundary and have no porous media resistance structure. The activity area for stacked caged livestock and poultry is simplified as a porous media area. The influence of the laying hen population on the indoor environment is characterized by the coupling of the resistance coefficient with the heat and moisture sources. The auxiliary structures of the laying hen house, such as the wind deflector and the manure conveyor belt for stacked caged housing, are simplified as non-slip solid wall boundaries to characterize the airflow obstruction and guiding effects.

[0064] 3.2 Automated assignment of boundary conditions across the entire computational domain: This embodiment simplifies the aforementioned fan-evaporative cooling pad system, categorizing the boundary conditions for CFD simulation of a multi-layered caged laying hen house with tunnel ventilation into four standardized types: Inlet, Outlet, Wall, and Symmetry. Inlets and outlets are all set as pressure boundary conditions. The Wall is divided into building structure and ventilation system components (same as during modeling). The building structure primarily uses thermal conductivity boundary conditions, setting the wall thermal conductivity coefficient. All ventilation system components are set as no-slip boundary conditions; additional conditions are added if there is a gas or heat source. All Symmetry surfaces are set as symmetric boundary conditions. This embodiment significantly simplifies the boundary condition setting process, requiring only two parameters (ambient temperature and humidity) and automatically completing all boundary condition settings by combining the ventilation system component and building structure attribute parameters input during modeling.

[0065] The inlet temperature and the initial temperature of the computational domain are calculated based on outdoor meteorological parameters: firstly, based on the outdoor dry-bulb temperature. With relative humidity The wet-bulb temperature was calculated using the empirical formula proposed by Stull (2011). Then, combining the cooling coefficient of the evaporative cooling pad, the temperature entering the building through the evaporative cooling pad, i.e., the inlet boundary temperature, is calculated. The calculation formula is as follows: ; ; in, Wet-bulb temperature, ; The ambient temperature, ; , is the initial temperature at the inlet boundary. ; The relative humidity of the outside environment is %; This is the cooling parameter for the evaporative cooling pads; the default value is 80%.

[0066] Turbulent parameters at the inlet and outlet, such as turbulent kinetic energy ( ), Turbulent dissipation rate ( ) and turbulent specific dissipation rate ( All estimates are based on CFD empirical formulas. The formulas for calculating turbulence parameters are as follows: ; ; ; in, The average flow velocity, The default value is calculated based on the fan flow rate and size at 50Pa. Turbulence intensity, default 5%. The length scale for turbulence is taken as 7% of the hydraulic diameter; The turbulence model constant is set to 0.09.

[0067] 3.3 Automated configuration of source term conditions for grid regions: Based on the fan-evaporative cooling pad system, this embodiment simplifies all the components of the ventilation system, including the fan, evaporative cooling pad, animal activity area, etc., into grid influence regions (cellZone). Momentum source terms and energy source terms are added to these grid regions to simulate their driving effect, obstruction effect, and heating and heat absorption phenomena on the airflow field.

[0068] The drag effect is abstracted through porous media, and the source term of the momentum equation is added as follows: ; in, The viscous drag coefficient in the i-direction and ; The inertial drag coefficient in the i-direction ; Let be the velocity component in the i-direction, in m / s.

[0069] The driving force is added through discrete velocity-pressure scatter interpolation, or as a function of velocity and pressure: ; Where u is the velocity, in m / s; The pressure change is expressed in Pa.

[0070] The heat absorption and release phenomena are calculated using the component property parameters of the ventilation system: ; Where q represents the unit of heat source efficiency, W / m3 Q is the efficiency of a single heat source, in W; n is the number of heat sources; a, b, and c are the length, width, and height of the heat sources, in m, respectively.

[0071] 4. Steady-state CFD calculation and multi-round adaptive iterative solution: 4.1 Automated configuration of basic solution parameters: Steady-state numerical calculations were employed, using the energy equation to solve for the temperature field distribution. The k-omega SST two-equation turbulence model was selected, with a second-order upwind scheme for the convection term discretization. The relaxation factor was set to 0.7 for the pressure field and 0.2 for the other physical fields. The convergence residuals for all physical fields were controlled within 10. -4 The minimum number of iterations is no less than 3000.

[0072] The calculation process additionally solves the air age scalar transport equation to quantitatively assess the air freshness and pollutant retention characteristics in the barn. The higher the air age value, the longer the harmful gas stays, and the greater the impact on livestock health and production performance.

[0073] 4.2 Automated Independence Verification of Multiple Gradient Mesh Sets: For layered cage chicken houses with tunnel ventilation mode, an automated analysis method based on flow field adaptive densification and multi-group gradient grid independence is carried out based on the open-source simulation platform OpenFOAM. In this embodiment, five groups of experiments are conducted, which are denoted as Group 1 to Group 5, with the number of grids increasing step by step. The entire process is automated to improve the reliability of the simulation results.

[0074] The Group 1 mesh is generated based solely on geometric features and is not coupled with the actual flow field distribution. Therefore, in Group 2, adaptive refinement is performed based on the Group 1 mesh and the velocity gradient field of the corresponding calculation results to optimize the mesh spatial density distribution. Adaptive refinement requires a pre-set velocity gradient threshold (20). The specific implementation process is as follows: First, a background mesh is generated using blockMesh, and only the mesh splitting function of snappyHexMesh is enabled to generate a hexahedral mesh that adapts to the geometric features, ensuring that the mesh topology can support the stable operation of the OpenFOAM adaptive refinement function; second, the simulation results of Group 1 are mapped to the Group 2 hexahedral mesh using the OpenFOAM mapFields program, and the adaptive refinement reference field refVal is obtained through post-processing calculation; then, the gradient change of the refVal field is solved by combining the preset velocity gradient threshold and the current basic mesh size; finally, the mesh exceeding the threshold in the refVal field is refined to achieve accurate refinement of the large velocity gradient region. In actual execution, the process of mapping the field to adaptive mesh refinement involves three rounds of iteration. Within each round, the `maxRefinement` parameter of the `dynamicRefineFvMesh` program is set to 1, 2, and 3 sequentially, progressively refining the first, second, and third levels of adaptive mesh. Because `dynamicRefineFvMesh` is based on a dynamic mesh mechanism, it requires calling the transient solver in OpenFOAM that supports dynamic meshes to perform single-step iterations and complete mesh reconstruction. After the three rounds of refinement are completed, the Group 2 adaptive refinement process ends, and the process reverts to the conventional simulation flow. Mesh fitting and boundary layer generation are then performed using `snappyHexMesh`, and numerical computation begins.

[0075] The mesh generation for Groups 3 to 5 uses the expected mesh quantity growth rate (50%) as the core control parameter, replacing the basic mesh size. This avoids the problem of excessive mesh quantity surge caused by an excessively small basic mesh size, improving the ease of use of the method. The adaptive densification logic of these three mesh groups is basically the same as that of Group 2, with only two differences: First, constrained by the global mesh quantity growth rate, the background mesh size of each group decreases progressively compared to the previous group; second, the refVal densification threshold needs to be corrected according to the ratio of the background mesh size of the current group to that of Group 1, ensuring that the adaptive densification area remains stable under different basic mesh sizes, and ensuring the consistency and comparability of the mesh irrelevance analysis of the tunnel ventilation mode stacked cage-rearing chicken house.

[0076] Throughout the process, the parameters required to generate Group 1 to Group 5 meshes include the initial base mesh size of Group 1, the velocity gradient threshold of Group 2, and the expected mesh number growth rate and gradient threshold of Groups 3-5. These parameters all have default values ​​available, as detailed above.

[0077] 4.3 Dynamic boundary condition iterative update: Dynamic boundary parameters such as inlet and outlet turbulence parameters, evaporative cooling efficiency, and livestock heat and moisture production rates cannot be accurately predicted initially. Direct dynamic assignment can easily lead to computational divergence. This application adopts a multi-round iterative solution strategy to achieve dynamic optimization of boundary parameters. Using the average cross-curtain wind speed at the inlet surface calculated in the previous round as input, the inlet and outlet turbulence parameters, evaporative cooling efficiency, and livestock heat and moisture production rates are automatically updated. The inlet temperature and humidity boundary parameters and source term parameters of the animal activity area are iteratively corrected to eliminate computational instability caused by dynamic boundaries and improve the accuracy and convergence of simulation results.

[0078] ; ; ; in, It is the cooling efficiency, and u is the curtain velocity, which is the average wind speed at the inlet surface. The wind speed in the animal activity area is the average value of this area, and T is the temperature in the animal activity area; f refers to different correlations.

[0079] 5. Post-processing: For layered cage houses with tunnel ventilation mode, semi-automatic post-processing is performed after CFD calculation convergence. The core output is the flow field distribution information in the house and the simplified operating status parameters of the ventilation equipment. In order to meet the needs of rapid quantitative assessment of the layer chicken breeding environment, an automatic calculation module for temperature and humidity index (THI) and ambient temperature index (ETI) is specially integrated in the post-processing stage to realize the intuitive quantitative characterization of the heat stress level of layer chickens in the house.

[0080] The Temperature-Humidity Index (THI) is a core indicator for determining the heat stress status of laying hens in tunnel-ventilated, multi-layered cage houses. It is used to accurately identify heat stress risk areas within the house. This index couples dry-bulb temperature and relative humidity to comprehensively reflect the thermal perception status of the space in which the laying hens are located. The higher the THI value, the stronger the degree of heat stress in a local area of ​​the house, and the higher the risk of heat stress for the laying hens. It can provide direct data support for ventilation control and local environmental optimization in chicken houses.

[0081] ; In the formula T dDry bulb temperature (°C); RH is relative humidity (%).

[0082] The Environmental Temperature Index (ETI) is a comprehensive evaluation index of the thermal comfort status of laying hens in a tunnel-ventilated, multi-layered cage house. It can further couple information from multiple physical fields such as airflow velocity, wet-bulb temperature, and humidity to fully characterize the actual thermal comfort level inside the house.

[0083] ; In the formula, T w , where is the wet-bulb temperature, in °C.

[0084] The post-processing system can output characteristic cross-sectional cloud maps and vector maps of different heights and longitudinal sections inside the house, which can intuitively show the spatial distribution patterns of pressure field, velocity field, temperature field, temperature and humidity index (THI), and ambient temperature index (ETI) in the stacked cage laying hen house of the tunnel ventilation mode. This can be used to quantitatively evaluate the uniformity of airflow organization and the overall environmental control effect of the chicken house.

[0085] After the relevant parameters are calculated, the detection points and detection lines can be set according to user needs, and the data can be sliced ​​to extract the values ​​of specified variables at different spatial locations, XY numerical maps, cloud maps, and vector maps.

[0086] To simplify the verification and parameter output of ventilation equipment operation status, this embodiment extracts and verifies key operating parameters for the core ventilation equipment (wall-mounted negative pressure fan and evaporative cooling pad) in a tunnel ventilation mode layered cage-raised layer hen house: (1) Wall-mounted negative pressure fan: Extract the pressure difference on both sides of the simplified internal surface of the fan and the average airflow velocity of the internal surface. First, check the matching degree between the actual calculation results and the fan pressure-velocity performance curve input by the boundary conditions to verify the accuracy of the fan simulation model. Then, output the static pressure, operating wind speed and actual operating power of the fans at different installation positions in the building, and quantitatively evaluate the actual operating status of the fan unit.

[0087] (2) Evaporative cooling wet curtain: Extract the pressure difference on both sides of the simplified inner surface of the wet curtain and the average wind speed through the inner surface. First, check the matching degree between the actual calculation results and the wet curtain resistance characteristic curve input by the boundary conditions to verify the accuracy of the wet curtain simulation model. Then, output the local resistance, wind speed through the curtain and the actual evaporative cooling efficiency calculated based on the wind speed of the wet curtain at different positions in the building to quantitatively evaluate the cooling operation effect of the wet curtain group.

[0088] Finally, it should be noted that the above embodiments are only used to illustrate the technical methods of this application and not to limit them. Although this application has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can still be made to the technical methods of this application, and these modifications or equivalent substitutions cannot cause the modified technical methods to deviate from the spirit and scope of the technical methods of this application.

Claims

1. A rapid CFD simulation method for livestock and poultry houses for non-experts, characterized in that, Includes the following steps: S1. Construct a livestock and poultry house building database based on the structure and heat transfer properties of livestock and poultry houses under different ventilation modes; Based on the components present in livestock and poultry houses, component structure, component location, and component ventilation conditions are extracted to construct a component template library, wherein the components include physical objects or equipment; The aforementioned livestock and poultry housing component template library includes simplified templates for solid structures and porous media for different types of animal activity areas; S2. Input building data and component data for the specific simulation object; Based on the building data, the corresponding template data is input into the livestock and poultry house building database to generate the main geometry of the livestock and poultry building; Based on the component data, simulated reusable components are obtained by inputting the corresponding template data into the component template library and predefining them. The reusable components of the livestock and poultry house simulation are called to form an initial CFD geometric model by batch assembly of the components in the main geometry of the livestock and poultry building. Based on component parameters, the corresponding template data is extracted from the component template library to predefine the specific content of the simulated reusable component, including: Based on user needs or simulation resource limitations, physical animal models will be equipped in key observation areas and animal activity areas in small-scale simulations. In non-focused areas or large-scale simulations, complex and computationally intensive entities such as animal activity areas and slatted floors are simplified into porous media regions and the drag coefficient of complex modeled objects is calculated. S3. Semi-automatic mesh generation is achieved by dividing the mesh according to the dimensional characteristics of the livestock and poultry house structure and component structure; S4. Automatically configure boundary conditions for livestock and poultry house building parameters and external environmental parameters based on the initial CFD geometric model; The component parameters and preset empirical parameters of the initial CFD geometric model are used to set the coupling characteristics of ventilation, heat and humidity environment and airflow resistance in the grid region. The turbulence parameters are automatically estimated by combining empirical formula parameters to complete the CFD preprocessing. S5. With preset solver parameters, it automatically completes steady-state calculation and multi-physics coupling solution to obtain the first set of results. Then, it can semi-automatically perform adaptive mesh refinement based on the flow field velocity gradient and solve to obtain the second set of mesh and results. Subsequently, it can semi-automatically perform multiple sets of gradient mesh refinement and solve to obtain the corresponding mesh and results. The results of multiple iterations can be used to verify mesh independence, and the parameters for boundary and region settings can be automatically updated iteratively during multiple calculations; S6. Based on any solution result, output flow field detection point data, slice cloud map and inlet / outlet streamline map, automatically calculate temperature and humidity index (THI), ambient temperature index (ETI), air age core evaluation index, automatically output the operating status of core equipment such as wet curtain fans, and complete the livestock and poultry environment simulation assessment.

2. The rapid CFD simulation method for livestock and poultry houses for non-experts as described in claim 1, characterized in that, The specific content of parameterizing and encapsulating the structure and heat transfer properties of livestock and poultry houses under different ventilation modes is as follows: Structural parameters are obtained by parametric extraction of livestock and poultry house structures; The heat transfer properties of livestock and poultry houses under different ventilation modes were parameterized and extracted to obtain heat transfer attribute parameters; The livestock and poultry house building database includes structural parameters and heat transfer attribute parameters; The heat transfer property parameters are used to automatically match and set the boundary conditions required for CFD simulation, thereby achieving linkage between parameters and simulation settings.

3. The rapid CFD simulation method for livestock and poultry houses for non-experts as described in claim 1, characterized in that, The component template library includes component structural parameters, component location parameters, component ventilation attribute parameters, and drag coefficients; The component structure parameters, component location parameters, and component ventilation attribute parameters are obtained by extracting parameters for the component structure, component location, and component ventilation status, respectively. The drag coefficient was calculated using a drag calculator; The component location parameters are used to install components in batches in the livestock and poultry house model, along with structural parameters to assist in automatic mesh generation.

4. The rapid CFD simulation method for livestock and poultry houses for non-experts as described in claim 1, characterized in that, The grid division adopts a semi-automatic setting method, specifically including: Based on the classification and definition of poultry house building structures and components in the livestock and poultry house building database and component template library, combined with the maintenance structures and location parameters of the livestock and poultry house, and relying on the preset background grid size, the entire simulation model is automatically meshed.

5. The rapid CFD simulation method for livestock and poultry houses for non-experts as described in claim 1, characterized in that, The boundary conditions and initial conditions of the grid region are set semi-automatically. The automatic configuration of boundary conditions based on the livestock and poultry house building parameters and external environmental parameters of the initial CFD geometric model specifically includes: The boundary conditions between the interior and exterior of the building are all configured as walls or pressure inlets and outlets, and the heat exchange between the building structure and the outside world is configured by the heat transfer coefficient of the building structure material properties.

6. The rapid CFD simulation method for livestock and poultry houses for non-experts according to claim 1, characterized in that, The boundary conditions and initial conditions for the grid region also include other in-cell equipment, specifically including: The fan sets the internal fan grid domain velocity-momentum source term or dynamic velocity-pressure change boundary according to the predefined rated air volume or fan performance curve; The evaporative cooling pad sets the resistance coefficient and negative heat source coefficient of the internal evaporative cooling pad grid domain according to the predefined evaporative cooling pad resistance characteristics and cooling characteristics; The animal activity area automatically sets the animal heat and humidity production rates based on the input number of animals and the current ambient temperature and humidity.

7. The rapid CFD simulation method for livestock and poultry houses for non-experts according to claim 1, characterized in that, In S5, the iterative process generates different numbers of grids at a rate of 1.5 times the grid number growth rate based on the discrete distribution of the computational domain space in the grid adaptive optimization, and automatically completes the grid independence analysis.

8. The rapid CFD simulation method for livestock and poultry houses for non-experts according to claim 1, characterized in that, During the S5 iteration process, the current dynamic boundary and grid region conditions are automatically determined based on the previous solution, and the simulation accuracy is optimized to achieve adaptive multiple iterations of boundary conditions and grid region conditions. The dynamic boundary and grid region conditions specifically include: inlet and outlet turbulence parameter conditions; and the negative heat source coefficient of the internal wet curtain grid domain.

9. A rapid CFD simulation system for livestock and poultry houses for non-experts, characterized in that, The livestock and poultry house CFD rapid simulation system is equipped with a porous media resistance calculator, which is used to calculate the resistance coefficient of the animal activity area and complex structures with fine features in the livestock and poultry house.

10. A rapid CFD simulation system for livestock and poultry houses for non-experts according to claim 9, characterized in that, include: CFD Parametric Modeling Unit: Based on the structure and heat transfer properties of livestock and poultry houses under different ventilation modes, a livestock and poultry house building database is constructed. Based on the components present in the livestock and poultry houses, the component structure, component location, and component ventilation status are extracted to construct a component template library. The components include entities or equipment. The livestock and poultry house component template library contains simplified templates for the entity structure and porous media of different types of animal activity areas. For specific simulation objects, building data and component data are input. Based on the building data, the corresponding template data is extracted from the livestock and poultry house building database to generate the main geometry of the livestock and poultry house. Based on the component data, the corresponding template data is extracted from the component template library to predefine simulated reusable components. The simulated reusable components of the livestock and poultry house are called to perform batch assembly of components in the main geometry of the livestock and poultry house to form an initial CFD geometric model. Automated mesh generation: Semi-automated mesh generation is achieved by dividing the mesh based on the dimensional characteristics of the livestock and poultry house structure and component structure; Intelligent boundary condition configuration: Based on the building parameters of the livestock and poultry house and the external environment parameters of the initial CFD geometric model, the boundary conditions are automatically configured. Based on the component parameters of the initial CFD geometric model and the preset empirical parameters, the coupling characteristics of ventilation, heat and humidity environment and airflow resistance in the grid area are set. The turbulence parameters are automatically estimated by combining empirical formula parameters, thereby completing the CFD preprocessing. Adaptive Iterative Calculation: With preset solver parameters, it automatically completes steady-state calculation and multi-physics coupled solution to obtain the first set of results. Subsequently, it can semi-automatically perform adaptive mesh refinement based on the flow field velocity gradient and solve to obtain the second set of mesh and results. Then, it can semi-automatically perform multiple sets of gradient mesh refinement and solution to obtain the corresponding mesh and results. The results of multiple iterations can be used to complete mesh independence verification, and the parameters of the boundary and region can be automatically iterated and updated during multiple calculations. Simple post-processing: Based on any solution result, output flow field detection point data, slice cloud map and inlet / outlet streamline map, automatically calculate temperature and humidity index (THI), ambient temperature index (ETI), air age core evaluation index, automatically output the operating status of core equipment such as wet curtain fans, and complete the simulation evaluation of livestock and poultry environment.

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