Energy-saving building design method based on digital simulation

Abstract

The invention relates to the technical field of computer aided design, in particular to an energy-saving building design method based on digital simulation, which comprises the following steps: analyzing air velocity, temperature gradient, density and pressure distribution based on indoor aerodynamic parameters, identifying air vortex structure characteristics, and generating an energy-saving building environment data set. According to the method, aerodynamic characteristics in a building are accurately recognized, the vortex structure analysis capacity is improved, the air flowing path is optimized, aerodynamic parameters are combined, thermal resistance and heat conduction materials are matched, the building envelope layer is adjusted, heat flow transmission is guided, heat loss is reduced, the heat energy utilization rate is increased, and the spectral characteristics of the materials are adjusted according to illumination redundancy; the lighting efficiency is optimized, the heat load is reduced, outer wall heat transfer is optimized in combination with airflow characteristics, the ventilation rate is dynamically regulated and controlled, airflow short circuit is avoided, heat flow, illumination and ventilation parameters are integrated, precise optimization of building energy consumption is achieved, and the energy efficiency regulation and control level is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of computer-aided design, and particularly to an energy-saving building design method based on digital simulation. Background Art

[0002] The technical field of computer-aided design includes various methods and tools for design, analysis, and optimization using computer technology. This technical field involves using computers for geometric modeling, graphic rendering, engineering analysis, and data processing to improve design accuracy, reduce human errors, and accelerate the product development cycle. Computer-aided design is widely applied in multiple fields such as mechanical manufacturing, construction engineering, and electronic circuit design. In the field of construction engineering, computer-aided design can be used for building structure modeling, construction planning, energy consumption simulation, and optimization analysis, etc. This technology relies on means such as digital modeling, parametric design, and computer simulation to make the design process more efficient and contribute to achieving the goals of building energy conservation and environmental protection.

[0003] Among them, the energy-saving building design method based on digital simulation refers to a method of simulating and calculating building energy consumption by establishing a building digital model and combining factors such as environmental parameters, material properties, and climate data. This method covers key technical contents such as building geometric structure modeling, thermal performance calculation, daylighting simulation, and ventilation optimization, and relies on computer software for energy consumption calculation and analysis. This method uses building information modeling technology for spatial and structural modeling, analyzes the energy transfer characteristics of the envelope structure through heat flow calculation methods, simulates the indoor light environment under different daylighting conditions in combination with the lighting calculation model, and optimizes the building ventilation design based on the aerodynamic simulation method.

[0004] In the existing technology, the analysis accuracy of the air flow state in building energy consumption simulation is limited. A relatively simplified flow path calculation method is adopted, resulting in insufficient recognition ability for local vortices and recirculation regions, making it difficult to achieve the optimized ventilation and air change effect. Heat retention or ventilation short circuits are formed in some areas, reducing the building energy-saving effect. In terms of heat flow analysis, the heat resistance matching method of the envelope structure material is relatively fixed, and the dynamic influence of aerodynamic factors is not fully considered, resulting in the heat flow direction not reaching the optimal configuration during the energy consumption optimization process, and some high heat loss areas cannot be effectively alleviated. At the level of daylighting optimization, the existing technology mainly relies on static parameters to adjust the building daylighting design, lacking the ability to dynamically adjust under different daylighting conditions, resulting in redundant daylighting in some areas and insufficient daylighting in some areas, making the indoor light environment unbalanced, affecting comfort, and increasing unnecessary lighting energy consumption. In the existing methods during the energy consumption optimization process, the synergistic relationship between multiple key parameters has not been fully utilized, making it difficult to achieve refined dynamic control of the overall building environment, resulting in limited space for energy-saving optimization. Summary of the Invention

[0005] The object of the present invention is to solve the disadvantages existing in the prior art, and a method for designing an energy-saving building based on digital simulation is proposed.

[0006] In order to achieve the above object, the present invention adopts the following technical solutions: A method for designing an energy-saving building based on digital simulation, comprising the following steps:

[0007] S1: Based on indoor aerodynamic parameters, analyze air velocity, temperature gradient, density, pressure distribution, identify the characteristics of air vortex structures, and generate an energy-saving building environment data set;

[0008] S2: Based on the energy-saving building environment data set, call indoor aerodynamic parameters, analyze the air flow path, screen areas with abnormal heat exchange rates, adjust the material layers of the envelope structure, optimize the heat conduction direction, adjust the wall heat transfer coefficient, optimize the thickness of the insulation layer, and obtain building hierarchical modeling parameters;

[0009] S3: Based on the building hierarchical modeling parameters, analyze indoor and outdoor light redundancy, match variable spectral material parameters, adjust spectral transmittance and reflectance, and obtain energy-saving building light environment regulation data;

[0010] S4: According to the energy-saving building light environment regulation data, call the characteristics of air vortex structures, analyze the air recirculation area, adjust the external wall heat transfer data, identify the ventilation rate and optimize the air flow path, and generate a building ventilation energy consumption assessment result;

[0011] S5: Based on the building ventilation energy consumption assessment result, call the energy-saving building hierarchical modeling data, analyze heat flow, light, and ventilation parameters, optimize the building energy consumption configuration, and obtain an energy-saving building dynamic simulation design scheme.

[0012] As a further solution of the present invention, the energy-saving building environment data set includes air velocity data, temperature gradient data, air density distribution, pressure distribution data, building lighting parameters, and air vortex structure characteristics. The building hierarchical modeling parameters include air flow path data, heat exchange rate distribution, thermal resistance material parameters, thermal conductivity material parameters, envelope structure material layer parameters, heat conduction direction parameters, wall heat transfer coefficient parameters, and insulation layer thickness parameters. The energy-saving building light environment regulation data includes light redundancy data, variable spectral material parameters, spectral transmittance parameters, and spectral reflectance parameters. The building ventilation energy consumption assessment result includes external wall heat transfer data, air recirculation area data, ventilation rate parameters, and air flow path parameters. The energy-saving building dynamic simulation design scheme includes a heat flow parameter set, a light parameter set, a ventilation parameter set, and building energy consumption configuration parameters.

[0013] As a further solution of the present invention, the steps for obtaining the energy-saving building environment data set are specifically as follows:

[0014] S111: Extract air velocity, temperature gradient, density, and pressure distribution data based on indoor aerodynamic parameters, analyze the variation range of air velocity, screen the areas where the air velocity is within the critical velocity range, and identify the pressure gradient of the areas to obtain the air velocity and pressure gradient data set.

[0015] S112: Call the air velocity and pressure gradient data set, identify the areas affected by light intensity, analyze the air density and velocity according to the light intensity change rate, adjust the aerodynamic parameters, and use the formula:

[0016] ;

[0017] Calculate the air velocity correction amount, adjust the velocity parameter, and obtain the air velocity correction data set.

[0018] Wherein, represents the air velocity correction amount, represents the air velocity at the position, represents the air velocity at the position, represents the pressure at the position, represents the air density at the position, represents the light intensity change rate at the position, represents the total number of data points of the aerodynamic parameters;

[0019] S113: Call the air velocity correction data set, identify the characteristics of the air vortex structure, analyze the co-variation of the air velocity and pressure distribution, screen the vortex core area, extract the aerodynamic parameters, and form an energy-saving building environment data set.

[0020] As a further solution of the present invention, the steps for obtaining the building hierarchical modeling parameters are specifically as follows:

[0021] S211: Based on the energy-saving building environment data set, call the indoor aerodynamic parameters, analyze the air flow path, screen the areas with abnormal heat exchange rates, and obtain the air flow deviation interval.

[0022] S212: Call the air flow deviation interval, match the thermal resistance and heat-conducting materials, analyze the change of the thermal resistance value and the thermal conductivity gradient, and use the formula:

[0023] ;

[0024] Calculate the average value of the thermal resistance gradient, and adjust the material layer of the enclosure structure according to the average value to obtain the optimized material layer data.

[0025] Among them, represents the average value of the thermal resistance gradient, represents the number of layers in the analysis area, represents the thermal resistance value of the material of the th layer, and

[0026] S213: Based on the material layer optimization data, adjust the heat transfer coefficient of the wall, optimize the thickness of the insulation layer, identify the heat transfer coefficient of the optimized material for each layer, and obtain the building hierarchical modeling parameters.

[0027] As a further solution of the present invention, the steps for obtaining the energy-saving building light environment regulation data are specifically as follows:

[0028] S311: Based on the building hierarchical modeling parameters, call the indoor and outdoor lighting parameters, analyze the lighting distribution in each area, screen the areas where the lighting intensity exceeds the set threshold, and obtain the lighting redundancy interval;

[0029] S312: Call the lighting redundancy interval, match the variable spectral material parameters, identify the spectral transmittance and reflectance of the differential material under the target lighting conditions, and use the formula:

[0030] ;

[0031] Calculate the matching value of the spectral transmittance and reflectance, adjust the material layer, and establish the spectral matching data;

[0032] Among them, represents the matching value of the spectral transmittance and reflectance, represents the number of material layers, represents the spectral reflectance, represents the thickness, represents the spectral transmittance, represents the spectral refractive index, represents the spectral refractive index of the adjacent layer, represents the accumulation;

[0033] S313: Based on the spectral matching data, adjust the spectral transmittance and reflectance, identify the building overall light environment regulation parameters, and obtain the energy-saving building light environment regulation data.

[0034] As a further solution of the present invention, the steps for obtaining the building ventilation energy consumption evaluation result are specifically as follows:

[0035] S411: According to the energy-saving building light environment regulation data, call the air vortex structure characteristics, analyze the flow velocity gradient and pressure distribution in the vortex core area, and obtain the air flow recirculation distribution parameters;

[0036] S412: Call the air flow recirculation distribution parameter, adjust the heat transfer data of the exterior wall, identify the heat transfer gradient in the vortex core region, analyze the energy exchange in the air flow circulation region, and obtain the heat transfer coefficient of the exterior wall;

[0037] S413: Based on the heat transfer coefficient of the exterior wall, identify the ventilation rate, optimize the air flow path, and use the formula:

[0038] ;

[0039] Calculate the ventilation energy consumption value per unit volume of the building space, and obtain the building ventilation energy consumption evaluation result;

[0040] where, represents the ventilation energy consumption value per unit volume of the building space, represents the temperature gradient of the th exterior wall unit, represents the th surface area of the exterior wall unit, represents the th gas density corresponding to the exterior wall unit, represents the specific heat capacity of air, represents the th air flow velocity at the exterior wall unit, represents the total number of exterior wall units.

[0041] As a further solution of the present invention, the steps for obtaining the energy-saving building dynamic simulation design solution are specifically as follows:

[0042] S511: Based on the building ventilation energy consumption evaluation result, call the hierarchical modeling data, extract the heat flow, light, and ventilation parameters, and obtain the regional heat energy accumulation parameter;

[0043] S512: Based on the regional heat energy accumulation parameter, identify the heat flow exchange situation in the building functional area, and use the formula:

[0044] ;

[0045] Calculate the heat flow balance coefficient, call the ventilation rate parameter, analyze the influence amount of air circulation, and adjust the building energy consumption parameter in combination with the heat flow balance coefficient to obtain the energy consumption optimization adjustment parameter;

[0046] where, represents the heat flow balance coefficient, represents the temperature in the high-temperature area, represents the temperature in the low-temperature area, represents the ventilation influence factor, represents the indoor heat loss amount, represents the window transmission heat loss, Represents the thermal resistance parameter of the building envelope;

[0047] S513: Based on the energy consumption optimization adjustment parameters, the regional ventilation mode and lighting mode are adjusted, the optimal building energy consumption configuration is screened, and a dynamic simulation design scheme for an energy-saving building is obtained.

[0048] Compared with the prior art, the advantages and positive effects of the present invention are:

[0049] In the present invention, by analyzing parameters such as air velocity, temperature gradient, density, and pressure distribution, the aerodynamic characteristics of the interior of the building can be accurately identified, so that the study of air flow state has a more detailed vortex structure analysis capability, and can effectively identify the airflow recirculation area and the abnormal heat exchange area, improve the optimization accuracy of the air flow path, and through the screening of aerodynamic parameters, match the thermal resistance and thermal conductive materials in the heat flow transfer process, and make reasonable adjustments to the levels of the enclosure structure materials, so that the heat flow guidance of the building is more in line with the energy-saving needs, reduce unnecessary heat loss, and improve the overall thermal energy utilization rate. Combined with indoor and outdoor light data, According to the redundancy of light, the spectral transmittance and reflectivity of materials are adjusted to further improve the lighting efficiency while reducing unnecessary heat load. The linkage optimization of building heat flow and light can reduce energy consumption while maintaining comfort. Combined with the airflow characteristics, the heat transfer parameters of the exterior wall are optimized to achieve dynamic regulation of the ventilation rate, avoid the occurrence of air short-circuiting and stagnation areas, and make the ventilation path more in line with the energy consumption optimization goal. Based on the coordinated analysis of the overall energy consumption parameters, the three major factors of heat flow, light and ventilation are integrated to accurately optimize the building energy consumption configuration, realize the precise dynamic simulation of energy-saving buildings, and improve the overall energy efficiency regulation level of the building environment. BRIEF DESCRIPTION OF THE DRAWINGS

[0050] Figure 1 It is a schematic diagram of the main steps of the present invention;

[0051] Figure 2 A flowchart for obtaining an energy-saving building environment data set in the present invention;

[0052] Figure 3 A flowchart for obtaining building layered modeling parameters in the present invention;

[0053] Figure 4 This is a flow chart for obtaining the light environment control data of the energy-saving building in the present invention;

[0054] Figure 5 A flowchart for obtaining building ventilation energy consumption evaluation results in the present invention;

[0055] Figure 6 The figure is a flow chart for obtaining the dynamic simulation design scheme of energy-saving buildings in the present invention. Detailed Implementation Manner

[0056] In order to make the objectives, technical solutions, and advantages of the present invention clearer and more understandable, the present invention will be further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0057] In the description of the present invention, it should be understood that the orientation or positional relationship indicated by the terms "length", "width", "upper", "lower", "front", "rear", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outer", etc. is based on the orientation or positional relationship shown in the accompanying drawings. It is only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and thus should not be construed as a limitation to the present invention. In addition, in the description of the present invention, the meaning of "a plurality of" is two or more, unless otherwise specifically defined.

[0058] Embodiment 1

[0059] Please refer to Figure 1 , the present invention provides a technical solution: an energy-saving building design method based on digital simulation, including the following steps:

[0060] S1: Based on indoor aerodynamic parameters, analyze air velocity, temperature gradient, density, and pressure distribution, extract building lighting parameters, identify the characteristics of air vortex structures, and generate an energy-saving building environment dataset;

[0061] S2: Based on the energy-saving building environment dataset, call indoor aerodynamic parameters, analyze the air flow path, screen areas with abnormal heat exchange rates, match thermal resistance and heat-conducting materials, adjust the material layers of the enclosure structure, optimize the heat transfer direction, adjust the wall heat transfer coefficient, and optimize the thickness of the insulation layer to obtain building hierarchical modeling parameters;

[0062] S3: Based on the building hierarchical modeling parameters, call indoor and outdoor lighting parameters, analyze lighting redundancy, match variable spectral material parameters, and adjust spectral transmittance and reflectance to obtain energy-saving building light environment regulation data;

[0063] S4: According to the energy-saving building light environment regulation data, call the characteristics of air vortex structures, analyze the air recirculation area, adjust the external wall heat transfer data, identify the ventilation rate and optimize the air flow path to generate a building ventilation energy consumption assessment result;

[0064] S5: Based on the building ventilation energy consumption assessment result, call the energy-saving building hierarchical modeling data, analyze heat flow, lighting, and ventilation parameters, optimize the building energy consumption configuration, and obtain an energy-saving building dynamic simulation design scheme.

[0065] The energy-saving building environment dataset includes air velocity data, temperature gradient data, air density distribution, pressure distribution data, building lighting parameters, and air vortex structure characteristics. The building hierarchical modeling parameters include air flow path data, heat exchange rate distribution, thermal resistance material parameters, heat conduction material parameters, enclosure structure material layer parameters, heat transfer direction parameters, wall heat transfer coefficient parameters, and insulation layer thickness parameters. The energy-saving building light environment regulation data includes lighting redundancy data, variable spectral material parameters, spectral transmittance parameters, and spectral reflectance parameters. The building ventilation energy consumption assessment results include exterior wall heat transfer data, air flow recirculation area data, ventilation rate parameters, and air flow path parameters. The energy-saving building dynamic simulation design scheme includes heat flow parameter sets, lighting parameter sets, ventilation parameter sets, and building energy consumption configuration parameters.

[0066] Please refer to Figure 2 , and the steps for obtaining the energy-saving building environment dataset are specifically as follows:

[0067] S111: Based on indoor aerodynamic parameters, extract air velocity, temperature gradient, density, and pressure distribution data, analyze the variation range of air velocity, screen the areas where the air velocity is within the critical velocity range, and identify the pressure gradient of the areas to obtain the air velocity and pressure gradient dataset;

[0068] In the indoor environment, through the real-time monitoring of air velocity, temperature gradient, density, and pressure distribution, the energy consumption of the air conditioning system can be effectively controlled and optimized. For example, in a typical office, sensors are used to obtain air velocity and temperature gradient data, and then the air conditioning output is adjusted to reduce energy consumption and improve comfort. By calculating the variation range of air velocity at different spatial positions, the efficient areas and areas that need improvement in air flow can be identified. For example, the air velocity in the corner of the meeting room is relatively low, indicating that the air flow path needs to be optimized or auxiliary ventilation equipment needs to be added. Screen the areas where the velocity is within the critical velocity range, and by monitoring the pressure gradient of the areas, the ventilation strategy can be further adjusted to achieve the best energy efficiency. By calculating the density change rate corresponding to the temperature gradient and combining the pressure distribution data to calculate the influence of the density gradient on the pressure gradient, the response sensitivity and accuracy of the air conditioning system are improved, and the air velocity and pressure gradient dataset is obtained, which provides an experimental basis and theoretical support for the energy-saving design of the building.

[0069] S112: Call the air velocity and pressure gradient dataset, identify the areas affected by light intensity, analyze the air density and velocity based on the light intensity change rate, adjust the aerodynamic parameters, and use the formula:

[0070] ;

[0071] Calculate the air velocity correction amount, adjust the velocity parameters, and obtain the air velocity correction dataset;

[0072] Among them, represents the air velocity correction amount, represents the air velocity at the th position, represents the air velocity at the th position, represents the pressure at the th position, represents the light intensity change rate at the

[0073] In the lighting optimization design of office buildings, considering the influence of light intensity on air velocity and temperature, by calculating the change rate of light intensity and its correction value for aerodynamic parameters, assuming that in five different monitored areas, the air velocity is successively 0.5 m / s, 0.7 m / s, 0.8 m / s, 0.65 m / s, 0.6 m / s;

[0074] The corresponding pressure is 101 kPa, 102 kPa, 100 kPa, 101.5 kPa, 101 kPa;

[0075] And the air density common value is about 1.225 ;

[0076] The light intensity change rate is assumed to be 20%, 25%, 22%, 18%, 21% in the areas respectively;

[0077] Using the data, calculate the air velocity correction rate ;

[0078] The specific calculation steps are as follows: Default to 0.5 m / s (initial velocity), then , m / s, m / s, m / s, m / s;

[0079] Use the formula to calculate the correction rate of each item:

[0080] ;

[0081] ;

[0082] ;

[0083] ;

[0084] ;

[0085] Total correction rate ;

[0086] The results show that, by synthesizing the light change rate and the change of aerodynamic parameters in each region, the overall air velocity correction rate is 0.1072. This indicates that after considering the influence of light intensity, the adjustment range of air velocity needs to be increased by about 10.72% to adapt to the influence brought by light changes, so as to optimize the environmental quality of the office.

[0087] S113: Call the air velocity correction data set, identify the characteristics of the air vortex structure, analyze the co-variation of air velocity and pressure distribution, screen the core region of the vortex, extract aerodynamic parameters, and form an energy-saving building environment data set;

[0088] Through real-time data monitoring and control systems, key areas affecting air quality and energy efficiency are identified. For example, by identifying the characteristics of the vortex structure, the output of the HVAC system can be precisely adjusted to match the actual demand, reducing energy waste. Calculate the co-variation coefficient of air velocity and pressure distribution to help engineers optimize the layout and angle of the air conditioner outlets. Screen out the areas that meet the vortex formation conditions, and special attention needs to be paid to these areas to avoid local overheating or overcooling phenomena. Calculate the spatial distribution of the vortex structure in this area to provide a basis for the optimization of the HVAC system. Further screen the core region of the vortex, extract relevant aerodynamic parameters, and form an energy-saving building environment data set. The data set provides a basis for building managers to adjust and optimize the building environment in real time to achieve the goal of energy conservation and emission reduction.

[0089] Please refer to Figure 3 , and the specific steps for obtaining the building hierarchical modeling parameters are as follows:

[0090] S211: Based on the energy-saving building environment data set, call the indoor aerodynamic parameters, analyze the air flow path, screen the areas with abnormal heat exchange rates, and obtain the air flow deviation interval;

[0091] First, call the indoor aerodynamic parameters. This operation involves extracting the measured air velocity and direction data from the database. For example, in a specific energy-efficient building, data is collected by sensors installed in the corners of different rooms. Subsequently, analyze the air flow path. This analysis not only focuses on the path itself but also monitors more deeply any deviations that occur in the path. For example, by comparing the data at consecutive time points, identify the areas where the flow rate suddenly changes. These areas have abnormal flow due to obstacles or design defects. Then, use advanced data processing software to draw a spatial distribution map of the heat exchange rate. By setting a heat exchange rate threshold, for example, setting the threshold to 0.5 kilowatts per second, the areas exceeding this value are marked as abnormal. The threshold is determined based on the dataset previously collected in similar buildings, thereby obtaining the air flow deviation interval. The result provides key data for subsequent steps. For example, when selecting wall materials or making design adjustments, it can be carried out according to the specific location of the deviation interval, indicating the areas that need to be focused on and processed to ensure the optimization of the air flow inside the building.

[0092] S212: Call the air flow deviation interval, match the thermal resistance with the heat-conducting material, analyze the changes in the thermal resistance value and the thermal conductivity gradient, and use the formula:

[0093] ;

[0094] Calculate the average value of the thermal resistance gradient, adjust the material layers of the building envelope according to the average value, and obtain the optimized data of the material layers;

[0095] Among them, represents the average value of the thermal resistance gradient, represents the number of layers in the analysis area, represents the thermal resistance value of the material of the and represent the thermal conductivity coefficients of adjacent layers;

[0096] After obtaining the air flow deviation interval, use this data as the basis for material matching operations, select suitable thermal resistance and heat-conducting materials to optimize the heat conduction performance in the areas with large air flow deviations, and calculate the thermal resistance values and thermal conductivities of each area in detail to identify the changes in the thermal characteristics of the materials within the area;

[0097] Suppose the exterior wall of a certain building is composed of three different materials:

[0098] The first layer of material (insulation layer): m²·K / W, W / mK;

[0099] The second layer of material (brick wall): m²·K / W, W / mK;

[0100] The third layer of material (interior layer): m²·K / W, W / mK.

[0101] Calculate according to the formula:

[0102] ;

[0103] Calculate the difference in thermal conductivity: , ;

[0104] Calculate the square root: , ;

[0105] Calculate the product: , ;

[0106] Calculate the sum: ;

[0107] Calculate the final mean value: ;

[0108] Calculate the average value of the thermal resistance gradient , and this value is relatively low, indicating that there is a large difference in thermal conductivity between different layers of the wall, resulting in a relatively high thermal bridge effect. It is necessary to further optimize the material layers based on the calculation results. For example: increase the thickness of the insulation layer to improve to reduce heat flow loss, select more uniform thermal conductivity materials to reduce the difference in thermal conductivity between adjacent materials, use thermal conductive filling materials to fill the wall gaps to reduce the thermal bridge phenomenon, adjust the material layers of the enclosure structure according to the calculated average value of the thermal resistance gradient, and establish data for optimizing the material layers. This data includes the combined materials of each layer after optimization, the thermal resistance value after optimization, and the adjusted thermal conductivity coefficient to ensure the improvement of the overall thermal performance of the building.

[0109] S213: Based on the data for optimizing the material layers, adjust the heat transfer coefficient of the wall, optimize the thickness of the insulation layer, identify the heat transfer coefficient of the optimized material for each layer, and obtain the building hierarchical modeling parameters;

[0110] First, recalculate the heat transfer coefficient of each layer of material to ensure that each calculated value is accurate. For example, conduct on-site tests with a thermal imager to obtain the thermal conductivity of the actual material. Then, combined with the optimized thickness of the insulation layer, simulate the heat conduction behavior after the combination of each layer through advanced simulation software. The software will automatically calculate the total heat transfer coefficient of the wall according to the input material properties and structural configuration. Then, based on the analysis of the coefficient and the heat transfer direction, comprehensively evaluate the thermal efficiency of the building. Through precise calculations, obtain the building's hierarchical modeling parameters, which not only provide detailed guidance for construction but also ensure the maximization of the building's energy efficiency. The parameters include the total thermal resistance of the wall, the thermal conductivity of each layer of material, and the optimized thickness of the insulation layer, making the thermal environment control of the entire building more precise and efficient, providing a clear and practically calculated operation framework for the building design and construction teams.

[0111] Please refer to Figure 4 , and the steps for obtaining the data for the light environment control of energy-saving buildings are specifically as follows:

[0112] S311: Based on the building's hierarchical modeling parameters, call the indoor and outdoor lighting parameters, analyze the lighting distribution in each area, screen the areas where the lighting intensity exceeds the set threshold, and obtain the lighting redundancy interval;

[0113] Obtain the indoor and outdoor lighting parameters of each area inside the building. The parameters are measured by lighting sensors. For example, sensors installed at different positions in the building can measure the intensities of direct light, scattered light, and reflected light respectively, and collect stratified data according to the different external obstructions, window angles, and glass materials of the building, and then calculate the lighting distribution in each area. Conduct time series analysis on the lighting data to divide the lighting changes in different periods of the day to obtain the stable lighting areas and lighting fluctuation areas in each period. On this basis, compare the lighting intensities in each area, select the maximum and minimum lighting values in each space inside the building, and calculate their average lighting intensity. Screen the areas where the lighting intensity exceeds the set threshold through the set lighting threshold. For example, if the set lighting threshold is 800 lux, when the lighting intensity in a certain area reaches 1000 lux, then this area is determined as a lighting redundancy area. Combine the surface light reflection characteristics of the building walls, floors, and furniture to further calculate the lighting redundancy. This calculation involves the analysis of light reflectivity, surface absorptivity, and material transmittance. For example, for a wall with a light reflectivity of 0.6, calculate its lighting contribution to the surrounding space, and finally obtain the lighting redundancy interval.

[0114] S312: Call the lighting redundancy interval, match the variable spectral material parameters, identify the spectral transmittance and reflectance of the differential materials under the target lighting conditions, and use the formula:

[0115] ;

[0116] Calculate the matching value of the spectral transmittance and reflectance, adjust the material layers, and establish spectral matching data;

[0117] Among them, represents the matching value of the spectral transmittance and reflectance, represents the number of material layers, represents the spectral reflectance, represents the thickness, represents the spectral transmittance, represents the spectral refractive index, represents the spectral refractive index of the adjacent layer, represents the accumulation;

[0118] Identify that the adaptability of the lighting environment in different regions to the spectral materials affects the building energy-saving effect. Therefore, it is necessary to calculate the spectral transmittance and reflectance of different materials under specific lighting conditions, represents the matching value of the spectral transmittance and reflectance, represents the calculated number of material layers, represents the spectral reflectance of the material of the layer, represents the thickness of this layer of material, represents the spectral transmittance of this layer of material, represents the spectral refractive index of this layer of material, represents the spectral refractive index of the adjacent layer of material,

[0119] Assume that the building wall in a certain area is composed of three layers of materials:

[0120] The first layer of material (outer wall coating): , m, , ;

[0121] The second layer of material (glass): , m, , ;

[0122] The third layer of material (curtain): , m, , ;

[0123] Calculate according to the formula:

[0124] ;

[0125] Calculate the product of the spectral reflectance and the thickness: , , ;

[0126] Calculate the absolute value of the spectral refractive index difference: , ;

[0127] Calculate the product of spectral transmittances: , ;

[0128] Calculate the final matching value: ;

[0129] Calculate the matching value of spectral transmittance and reflectance , which reflects the regulation ability of different spectral material combinations to the lighting environment. If this value is too high, it means that the reflectance of the current material combination is large, resulting in light pollution. It is necessary to adjust the transmittance or increase light-absorbing materials. According to the calculation results, adjust the material layer to optimize the spectral matching characteristics of the building surface, and finally obtain the spectral matching data.

[0130] S313: Based on the spectral matching data, adjust the spectral transmittance and reflectance, identify the building's overall light environment regulation parameters, and obtain the energy-saving building light environment regulation data;

[0131] First, further measure the light environment of each area of the building, use a spectral analyzer to record the optical properties of the adjusted materials, and verify the accuracy of the spectral matching data. During the adjustment process, introduce the spectral adaptability parameters of building materials, which are jointly determined by the incident angle dependence, surface microstructure, and coating reflectance of the materials. For example, in the area of the glass curtain wall, introduce low-emissivity glass to reduce the amount of solar radiation transmitted, thereby improving the indoor light environment. Compare the changes in the light intensity of each area before and after adjustment, calculate the final light environment regulation parameters, including spectral reflectance distribution, transmittance equilibrium value, and environmental brightness adjustment coefficient, and optimize the overall light environment in combination with the building layout and window orientation to finally obtain the energy-saving building light environment regulation data.

[0132] Please refer to Figure 5 , and the specific steps for obtaining the building ventilation energy consumption assessment results are as follows:

[0133] S411: According to the energy-saving building light environment regulation data, call the air vortex structure characteristics, analyze the velocity gradient and pressure distribution in the core area of the vortex, and obtain the air flow recirculation distribution parameters;

[0134] First, it is necessary to obtain the distribution of light intensity inside the building, which can be achieved by installing light sensors at different positions within the building. For example, place one sensor at each of the four corners and the center of the room to record the light intensity values at each point. Suppose at a certain moment, the readings of the sensors are 300 lux, 320 lux, 310 lux, 305 lux, and 315 lux respectively. To invoke the characteristics of the air vortex structure, it is necessary to introduce aerodynamic analysis into the ventilation system of the building to determine the air flow pattern and vortex regions, which can be realized through computational fluid dynamics (CFD) simulation. For example, use CFD software to simulate the air flow in the room and identify a counterclockwise vortex near the window. Calculate the velocity gradient and pressure distribution in the core region of the vortex. Velocity and pressure sensors can be arranged in the core region of the vortex to measure the flow velocity and pressure at different positions. For example, at the four measurement points in the core of the vortex, the flow velocities are 1.2 m / s, 1.5 m / s, 1.3 m / s, and 1.4 m / s respectively, and the pressures are 101325 Pa, 101320 Pa, 101330 Pa, and 101328 Pa respectively. Through the data, the velocity gradient and pressure distribution can be calculated, and its impact on the air flow recirculation region can be identified. This requires analyzing the interaction between the vortex region and the surrounding air flow to determine which regions of the air are affected by the vortex and form recirculation. For example, it is found that the vortex causes the air flow velocity in the corners of the room to decrease, forming an air flow recirculation region, and obtaining the distribution parameters of the air flow recirculation.

[0135] S412: Invoke the distribution parameters of the air flow recirculation, adjust the heat transfer data of the exterior wall, identify the heat transfer gradient in the core region of the vortex, analyze the energy exchange within the air flow circulation region, and obtain the heat transfer coefficient of the exterior wall;

[0136] First, it is necessary to analyze the influence of the parameters on the heat transfer of the exterior wall. For example, the air flow recirculation region causes the heat conduction efficiency of some parts of the exterior wall to decrease. Adjust the heat transfer data of the exterior wall by installing temperature sensors at different positions on the exterior wall to monitor the temperature difference between the inside and outside of the wall in real time. For example, at the upper, middle, and lower positions of the exterior wall, the temperature differences measured by the temperature sensors are 5 °C, 4 °C, and 6 °C respectively. Calculate the heat transfer gradient in the core region of the air vortex, which requires combining the distribution parameters of the air flow recirculation and the heat transfer data of the exterior wall to determine the temperature change rate within the vortex region. For example, using the above temperature difference data and air flow velocity data, calculate the heat transfer gradient in the core region of the vortex to be 0.5 °C / m. Analyze the characteristics of the energy exchange within the air flow recirculation region, which includes evaluating the influence of air flow on heat transfer. For example, it is found that the air flow recirculation causes heat to accumulate in the room, affecting the overall temperature distribution, and obtaining the heat transfer coefficient of the exterior wall.

[0137] S413: Based on the heat transfer coefficient of the exterior wall, identify the ventilation rate, optimize the air flow path, and use the formula:

[0138] ;

[0139] Calculate the ventilation energy consumption value per unit volume of building space to obtain the building ventilation energy consumption assessment result;

[0140] Among them, represents the ventilation energy consumption value per unit volume of building space, represents the temperature gradient of the th external wall unit, represents the surface area of the th external wall unit, represents the gas density corresponding to the th external wall unit, represents the specific heat capacity of air, represents the air flow velocity at the th external wall unit, represents the total number of external wall units;

[0141] First, it is necessary to measure the heat transfer of the building exterior wall to calculate the building air change rate. The temperature gradient is obtained through methods such as infrared thermal imaging and heat flux sensors. For example, the measured temperature gradients of a certain building exterior wall are respectively K / m, K / m, K / m, K / m, and the corresponding external wall unit areas are respectively , , , . According to the data, the heat transfer contribution of the external wall unit during the air change process can be calculated. It is necessary to measure the air density and the air flow velocity to calculate the ventilation energy consumption of the building. Set the air density , , , , the air specific heat capacity J / (kg·K), and the wind speeds are respectively m / s, m / s, m / s, m / s;

[0142] Substitute the values for calculation:

[0143] ;

[0144] ;

[0145] ;

[0146] This calculation shows that the ventilation energy consumption value per unit volume of building space is 0.65, indicating that during the ventilation and air change process of the building, the energy consumption required for air exchange per unit volume is relatively low, which is conducive to energy-saving design. Obtaining the evaluation results of building ventilation energy consumption, the results can be used to evaluate the energy consumption performance of different ventilation paths and adjust the air flow path to optimize the overall ventilation energy consumption of the building.

[0147] Please refer to Figure 6 , and the specific steps for obtaining the dynamic simulation design scheme of energy-saving buildings are as follows:

[0148] S511: Based on the evaluation results of building ventilation energy consumption, call the hierarchical modeling data, extract heat flow, lighting, and ventilation parameters, and obtain the regional thermal energy accumulation parameters;

[0149] Extract the initial heat flow, lighting, and ventilation parameters. In an example of an office building, the heat flow parameters include the heat loss of the exterior wall and windows, the lighting parameters involve the sunshine duration and lighting intensity, and the ventilation parameters are based on the statistical data of the air circulation volume of each floor and space. Use these parameters to perform a preliminary calculation of the energy consumption of the office building, identify the key areas of thermal energy loss, and calculate the regional thermal energy accumulation parameters. The data used in this process are all based on the actual measurement results of the previous year. By comparing the current data with the historical data, the energy efficiency improvement points of each area can be judged, providing a basis for the next step of energy consumption optimization.

[0150] S512: Based on the regional thermal energy accumulation parameters, identify the heat flow exchange situation in the building functional areas, and use the formula:

[0151] ;

[0152] Calculate the heat flow balance coefficient, call the ventilation rate parameters, analyze the influence of air circulation, and adjust the building energy consumption parameters in combination with the heat flow balance coefficient to obtain the energy consumption optimization adjustment parameters;

[0153] Among them, represents the heat flow balance coefficient, represents the temperature in the high-temperature area, represents the temperature in the low-temperature area, represents the ventilation and air change influence factor, represents the indoor heat loss, represents the heat loss through window transmission, represents the thermal resistance parameter of the building envelope;

[0154] Calculate the heat flow exchange situation in each functional area of the building. Select a high-rise office building as the implementation object. Assume that the building is located in the hot summer and cold winter region, and the external environmental temperature fluctuates greatly. To quantify the heat flow exchange situation, it is necessary to introduce parameters such as the indoor-outdoor temperature difference, ventilation influence factor, indoor heat loss, window transmission heat loss, and thermal resistance of the building envelope. Collect the temperature data of the building at different time periods. Assume that the highest indoor temperature in the high-rise office area of the building is 28°C, and the lowest indoor temperature is 22°C, then the temperature difference between the two is . Based on the building design standard, the ventilation influence factor of this floor is 0.8 (a dimensionless parameter calculated according to the ventilation system design). The indoor heat loss is detected by measuring equipment and assumed to be 1500 W. The window transmission heat loss is calculated based on the glass material and orientation and assumed to be 1200 W. The thermal resistance parameter of the building envelope is calculated from the material thickness and thermal conductivity and assumed to be 2.5 . Substitute the data into the formula:

[0155] ;

[0156] ;

[0157] ;

[0158] ;

[0159] The calculated heat flow balance coefficient , the value represents the degree of heat flow exchange inside the building, that is, the heat flow fluctuation caused by the change of indoor temperature. A higher value means stronger heat flow exchange in the building, indicating a greater demand for energy consumption optimization. Based on this calculation result, further call the ventilation rate parameter to calculate the influence amount of building air circulation. Assume that the ventilation rate of this office building is 5 times per hour. Then the air exchange amount directly affects the adjustment of the heat flow balance coefficient, and combined with the optimization calculation of building energy consumption parameters, finally obtain the energy consumption optimization adjustment parameter. This parameter will be used in the subsequent steps for building energy consumption dynamic simulation and configuration optimization.

[0160] S513: Based on the energy consumption optimization adjustment parameter, adjust the regional ventilation mode and lighting method, screen the optimal building energy consumption configuration, and obtain the dynamic simulation design scheme of the energy-saving building;

[0161] Call the energy consumption optimization adjustment parameters to further adjust the heat flow exchange situation in each functional area of the building. A teaching building in a school was selected as an example. According to the energy consumption optimization adjustment parameters, the ventilation modes and lighting adjustment methods of each classroom and office area were adjusted. Through dynamic simulation tests, the best building energy consumption configuration plan was screened out. Especially for the special needs of large lecture halls and laboratories, a customized energy consumption management plan was implemented. Finally, a series of dynamic simulations were carried out in combination with the regional climate conditions, and a dynamic simulation design plan for an energy-saving building was successfully obtained.

[0162] The above are only the preferred embodiments of the present invention, and do not limit the present invention in other forms. Any person skilled in the art may use the disclosed technical content to make changes or modifications into equivalent embodiments with equivalent changes and apply them to other fields. However, as long as the technical solution content of the present invention is not departed from, any simple modification, equivalent change and modification made to the above embodiments according to the technical essence of the present invention still belong to the protection scope of the technical solution of the present invention.

Claims

1. An energy-saving building design method based on digital simulation, characterized in that: The following steps are involved: S1: Based on indoor aerodynamic parameters, analyze air velocity, temperature gradient, density, and pressure distribution, identify air vortex structure characteristics, and generate energy-saving building environment data sets; S2: Based on the energy-saving building environment dataset, call the indoor aerodynamic parameters, analyze the air flow path, screen the abnormal heat exchange rate area, adjust the envelope material layer, optimize the heat flow conduction direction, adjust the wall heat transfer coefficient, optimize the insulation layer thickness, and obtain the building layered modeling parameters; S3: Based on the building hierarchical modeling parameters, analyze the indoor and outdoor lighting redundancy, match the variable spectrum material parameters, adjust the spectral transmittance and reflectance, and obtain the energy-saving building light environment control data; S4: Based on the light environment control data of the energy-saving building, call the air vortex structure characteristics, analyze the airflow recirculation area, adjust the exterior wall heat transfer data, identify the ventilation rate and optimize the airflow path, and generate the building ventilation energy consumption evaluation result; S5: Based on the building ventilation energy consumption assessment result, call the energy-saving building hierarchical modeling data, analyze the heat flow, light, and ventilation parameters, optimize the building energy consumption configuration, and obtain a dynamic simulation design plan for the energy-saving building.

2. The energy-saving building design method based on digital simulation according to claim 1 is characterized in that: The energy-saving building environment data set includes air flow rate data, temperature gradient data, air density distribution, pressure distribution data, building lighting parameters, and air vortex structure characteristics. The building layered modeling parameters include air flow path data, heat exchange rate distribution, thermal resistance material parameters, thermal conductivity material parameters, enclosure structure material layer parameters, heat flow conduction direction parameters, wall heat transfer coefficient parameters, and insulation layer thickness parameters. The energy-saving building light environment control data includes lighting redundancy data, variable spectrum material parameters, spectral transmittance parameters, and spectral reflectance parameters. The building ventilation energy consumption assessment results include exterior wall heat transfer data, airflow recirculation area data, ventilation rate parameters, and airflow path parameters. The energy-saving building dynamic simulation design scheme includes a heat flow parameter set, a lighting parameter set, a ventilation parameter set, and a building energy consumption configuration parameter.

3. The energy-saving building design method based on digital simulation according to claim 1 is characterized in that: The steps for obtaining the energy-saving building environment data set are specifically as follows: S111: Based on indoor aerodynamic parameters, extract air velocity, temperature gradient, density and pressure distribution data, analyze the air velocity change range, screen the area where the air velocity is within the critical velocity range, and identify the pressure gradient of the area to obtain the air velocity and pressure gradient data set; S112: Call the air velocity and pressure gradient data set, identify the area affected by the light intensity, analyze the air density and velocity according to the light intensity change rate, adjust the aerodynamic parameters, and use the formula: ； Calculate the air velocity correction amount, adjust the velocity parameters, and obtain the air velocity correction data set; in, Represents the air velocity correction, Representative Air velocity at the location, Representative Air velocity at the location, Representative Position pressure, Representative The air density at the location, Representative The rate of change of light intensity at a location, The total number of data points representing aerodynamic parameters; S113: calling the air velocity correction data set, identifying the air vortex structure characteristics, analyzing the coordinated changes of air velocity and pressure distribution, screening the vortex core area, extracting aerodynamic parameters, and forming an energy-saving building environment data set.

4. The energy-saving building design method based on digital simulation according to claim 2 is characterized in that: The steps for obtaining the building layered modeling parameters are specifically as follows: S211: Based on the energy-saving building environment data set, call indoor aerodynamic parameters, analyze the air flow path, screen the abnormal heat exchange rate area, and obtain the air flow deviation interval; S212: calling the air flow offset interval, matching the thermal resistance and the thermal conductive material, analyzing the thermal resistance value and the thermal conductivity gradient change, and using the formula: ； Calculate the mean value of thermal resistance gradient, adjust the material level of the enclosure structure according to the mean value, and obtain the material level optimization data; in, represents the mean value of thermal resistance gradient, Represents the number of analysis area layers, Representative Thermal resistance of the layer material, and represents the thermal conductivity of the adjacent layers; S213: Based on the material level optimization data, adjust the wall heat transfer coefficient, optimize the thickness of the insulation layer, identify the heat transfer coefficient of each layer of optimized material, and obtain building layered modeling parameters.

5. The energy-saving building design method based on digital simulation according to claim 3 is characterized in that: The steps for acquiring the energy-saving building light environment control data are specifically as follows: S311: Based on the building hierarchical modeling parameters, call indoor and outdoor lighting parameters, analyze the lighting distribution of each area, screen areas where the lighting intensity exceeds a set threshold, and obtain a lighting redundancy interval; S312: calling the illumination redundancy interval, matching the variable spectrum material parameters, identifying the spectral transmittance and reflectance of the differentiated material under the target illumination conditions, using the formula: ； Calculate the spectral transmittance and reflectance matching values, adjust the material level, and establish spectral matching data; in, Represents the spectral transmittance and reflectance matching value, Represents the number of material layers, represents the spectral reflectance, Represents thickness, represents the spectral transmittance, represents the spectral refractive index, represents the spectral refractive index of the adjacent layers, represents accumulation; S313: Based on the spectral matching data, adjust the spectral transmittance and reflectance, identify the overall light environment control parameters of the building, and obtain energy-saving building light environment control data.

6. The energy-saving building design method based on digital simulation according to claim 4 is characterized in that: The steps for obtaining the building ventilation energy consumption assessment results are specifically as follows: S411: According to the energy-saving building light environment control data, call the air vortex structure characteristics, analyze the velocity gradient and pressure distribution in the vortex core area, and obtain the airflow recirculation distribution parameters; S412: calling the airflow recirculation distribution parameter, adjusting the external wall heat transfer data, identifying the heat transfer gradient in the vortex core area, analyzing the energy exchange in the airflow circulation area, and obtaining the external wall heat transfer coefficient; S413: Based on the external wall heat transfer coefficient, identify the ventilation rate and optimize the airflow path, using the formula: ； Calculate the ventilation energy consumption per unit volume of building space and obtain the building ventilation energy consumption assessment results; in, Represents the ventilation energy consumption per unit volume of building space. Representative The temperature gradient of each exterior wall unit, Representative The surface area of ​​each exterior wall unit, Representative The gas density corresponds to each exterior wall unit. represents the specific heat capacity of air, Representative Airflow velocity at each exterior wall unit, Represents the total number of exterior wall units.

7. The energy-saving building design method based on digital simulation according to claim 5 is characterized in that: The steps for obtaining the energy-saving building dynamic simulation design scheme are specifically as follows: S511: Based on the building ventilation energy consumption assessment result, calling the hierarchical modeling data, extracting the heat flow, light, and ventilation parameters, and obtaining the regional heat energy accumulation parameters; S512: Based on the regional heat energy accumulation parameter, identify the heat flow exchange of the building functional area, using the formula: ； Calculate the heat flow balance coefficient, call the ventilation rate parameter, analyze the air circulation impact, adjust the building energy consumption parameters based on the heat flow balance coefficient, and obtain the energy consumption optimization adjustment parameters; in, represents the heat flow balance coefficient, Represents the temperature of the high temperature zone, Represents the low temperature zone temperature, represents the ventilation influencing factor, Represents the indoor heat loss, represents the window transmission heat loss, Represents the thermal resistance parameter of the building envelope; S513: Based on the energy consumption optimization adjustment parameters, the regional ventilation mode and lighting mode are adjusted, the optimal building energy consumption configuration is screened, and a dynamic simulation design scheme for an energy-saving building is obtained.

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