Indoor temperature simulation method and device, and storage medium

Abstract

The embodiment of the application provides a kind of indoor temperature simulation method, device and storage medium, the method comprises: the conversion relationship between Boltzmann space and real physical space physical quantity is established;Load house geometric model and carry out space discretization to obtain multiple lattices and classification, set the physical attribute parameters of each type of lattice and the initial state of each lattice;Wherein, state includes temperature and speed;The following cycle is executed until the set termination condition is reached: for the lattice affected by air convection, update the state of the lattice by collision and flow process in air convection;For the lattice affected by temperature diffusion, update the state of the lattice by collision and flow process in temperature diffusion;According to the conversion relationship and the state of the lattice, obtain the preset physical quantity of real physical space;Pre-set physical quantity includes temperature.The embodiment of the application realizes the temperature simulation in room using lattice Boltzmann method, improves the simplicity and accuracy of temperature simulation.

Description

Technical Field

[0001] The embodiments of the present invention relate to the field of computer technology, and in particular to an indoor temperature simulation method, device, and storage medium. Background Art

[0002] With the improvement of living standards, people have put forward higher requirements for living comfort. Temperature control equipment such as air conditioners can effectively adjust the room temperature through cooling and heating, making people's living more comfortable.

[0003] The placement of temperature control devices, such as air conditioners, in indoor spaces can have a significant impact on the indoor temperature regulation. In real life, because simulation results for temperature control devices in different locations are unavailable, people often randomly select a location for their installation. This hinders optimal performance and energy conservation. Therefore, simulating indoor temperatures at different temperature control device locations is a pressing need. Summary of the Invention

[0004] In view of the defects in the prior art, embodiments of the present invention provide an indoor temperature simulation method, device and storage medium.

[0005] An embodiment of the present invention provides an indoor temperature simulation method, including: establishing a conversion relationship between Boltzmann space and physical quantities in real physical space; loading a house geometric model, spatially discretizing the house geometric model to obtain multiple grids, classifying the multiple grids, and setting physical property parameters of each type of grid and the initial state of each grid; wherein the state includes temperature and speed; executing the following loop until a set termination condition is reached: for the grid affected by air convection, updating at least one of the states of the grid through collision and flow processes in air convection; for the grid affected by temperature diffusion, updating at least one of the states of the grid through collision and flow processes in temperature diffusion; obtaining a preset physical quantity of the real physical space based on the conversion relationship and the state of the grid; wherein the preset physical quantity includes temperature.

[0006] An embodiment of the present invention also provides an indoor temperature simulation device, including: a conversion relationship establishment module, used to establish a conversion relationship between the Boltzmann space and the physical quantities of the real physical space; a discretization processing module, used to load a house geometric model, spatially discretize the house geometric model to obtain multiple grids, classify the multiple grids, and set the physical property parameters and initial states of each type of grid; wherein the states include temperature and speed; a loop simulation module, used to execute the following loop until the set termination condition is reached: for the grid affected by air convection, update at least one of the states of the grid through the collision and flow process in the air convection; for the grid affected by temperature diffusion, update at least one of the states of the grid through the collision and flow process in the temperature diffusion; obtain the preset physical quantity of the real physical space according to the conversion relationship and the state of the grid; wherein the preset physical quantity includes temperature.

[0007] An embodiment of the present invention further provides an electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the program, the steps of any of the above-described indoor temperature simulation methods are implemented.

[0008] An embodiment of the present invention further provides a non-transitory computer-readable storage medium having a computer program stored thereon. When the computer program is executed by a processor, the steps of any of the above-mentioned indoor temperature simulation methods are implemented.

[0009] An embodiment of the present invention further provides a computer program product, including a computer program, which implements the steps of any of the above-mentioned indoor temperature simulation methods when executed by a processor.

[0010] The indoor temperature simulation method, device and storage medium provided by the embodiments of the present invention establish a conversion relationship between the Boltzmann space and the physical quantities of the real physical space, spatially discretize the house geometric model to obtain multiple grids, classify the multiple grids, and set the physical property parameters of each type of grid and the initial state of each grid. For the grids affected by air convection, at least one state of the grid is updated through the collision and flow process in the air convection. For the grids affected by temperature diffusion, at least one state of the grid is updated through the collision and flow process in the temperature diffusion. According to the conversion relationship and the state of the grid, the preset physical quantities including temperature of the real physical space are obtained, thereby realizing the use of the lattice Boltzmann method to perform indoor temperature simulation, and improving the simplicity and accuracy of the temperature simulation. BRIEF DESCRIPTION OF THE DRAWINGS

[0011] In order to more clearly illustrate the technical solution of the present invention, the following is a brief introduction to the drawings required for use in the description of the embodiments. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0012] Figure 1 1 is a flow chart of an indoor temperature simulation method provided by an embodiment of the present invention;

[0013] Figure 2 Schematic diagram of spatial discretization results in the indoor temperature simulation method provided by an embodiment of the present invention;

[0014] Figure 3 Schematic diagram of the collision process in the indoor temperature simulation method provided by an embodiment of the present invention;

[0015] Figure 4 Schematic diagram of the flow process in the indoor temperature simulation method provided by an embodiment of the present invention;

[0016] Figure 5 Schematic diagram of the position of particle flow in the indoor temperature simulation method provided by an embodiment of the present invention;

[0017] Figure 6 Schematic diagram of the motion trajectory of particle flow in the indoor temperature simulation method provided by an embodiment of the present invention;

[0018] Figure 7 1 is a schematic structural diagram of an indoor temperature simulation device provided by an embodiment of the present invention;

[0019] Figure 8 It is a structural diagram of an electronic device provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0020] To make the objectives, technical solutions, and advantages of the present invention more clear, the technical solutions of the present invention will be clearly and completely described below in conjunction with the accompanying drawings. Obviously, the embodiments described are only some of the embodiments of the present invention, not all of them. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts shall fall within the scope of protection of the present invention.

[0021] The physical simulation of the lattice Boltzmann method is part of computational fluid dynamics. In terms of scale, the lattice Boltzmann method lies between microscopic molecular models and macroscopic continuum models, and is referred to as a mesoscopic kinetic model. Compared to microscopic molecular models, the lattice Boltzmann method describes fluid motion using the statistical behavior of molecules, rather than calculating the individual behavior of a large number of molecules (on the order of 10^23). Furthermore, unlike the macroscopic continuum model, the kinetic model underlying the lattice Boltzmann method does not make the continuity assumption of the fluid.

[0022] Based on the continuum assumption, the fluid model is the Navier-Stokes equations, which satisfy the conservation of mass, momentum, and energy. When the Knudsen number is small, the fluid can be considered continuous; otherwise, the continuum model is no longer applicable. The molecular model is primarily based on the classical Newton's second law, and the macroscopic variables of the fluid can be derived from the physical quantities of the molecules at each moment.

[0023] Kinetic models use coarse-grained distribution functions to describe discrete systems composed of large numbers of particles. Specifically, they describe the percentage of molecules at a given location within a range of speeds at a given moment. Fluid molecules can collide with each other over a wide range of velocities, with high-speed molecules transferring kinetic energy to lower-speed molecules, and the collisions obey the law of conservation of momentum. This distribution is known as the Maxwell-Boltzmann distribution. The differential of this distribution with respect to time t is the Boltzmann equation. Under conditions of a small Knudsen number, the Boltzmann equation can be derived from the Navier-Stokes equation. Kinetic theory has a wider range of applicability than macroscopic continuum models and can be considered a bridge between microscopic molecular and macroscopic continuum models of fluids.

[0024] Numerical methods based on continuous models, that is, traditional methods, take the NS equations as the starting point, and generally use numerical solution formats such as finite difference method, finite volume method, and finite element method to discretize the differential equations, obtain the corresponding algebraic equation system, and solve it using standard numerical methods. This type of method requires solving a huge nonlinear algebraic equation system, and the computational complexity is high. In addition, it is difficult to realize the automated construction of algebraic equations for arbitrary geometric bodies, such as various boundaries. When faced with complex indoor geometric scene problems, this type of method is not competent. The molecular model is too large, and the physical properties of the molecule are generally simulated in the form of smooth particles, and the particle properties are interpolated using smooth kernel functions. It is generally used to describe visible fluids such as liquids.

[0025] The lattice Boltzmann method is finally used to implement the indoor physical simulation, mainly because of its wider application range, low implementation complexity, ability to handle a large number of complex geometries, and good parallelism.

[0026] Figure 1 FIG. 1 is a flow chart of an indoor temperature simulation method provided by an embodiment of the present invention. Figure 1 As shown, the method includes:

[0027] Step S1: establishing a conversion relationship between physical quantities in the Boltzmann space and the real physical space;

[0028] In order to convert physical quantities between the Boltzmann space and the real physical space, it is first necessary to establish a conversion relationship between the physical quantities in the Boltzmann space and the real physical space.

[0029] Step S2: Loading a house geometric model, spatially discretizing the house geometric model to obtain a plurality of grids, classifying the plurality of grids, and setting physical property parameters of each type of grid and an initial state of each grid; wherein the state includes temperature and speed;

[0030] After establishing the conversion relationship between the Boltzmann space and physical quantities in the real world, since this embodiment of the present invention utilizes the lattice Boltzmann method for temperature simulation, the model to be simulated must first be spatially discretized. The geometric model of the house to be simulated for indoor temperature is loaded and spatially discretized into multiple grids (also known as voxels) with the same discrete step length. The house geometric model includes the apartment model and furniture and appliance models.

[0031] Indoor scenes are discretized using a discrete occupancy approach. This involves categorizing grids based on their corresponding objects to clearly identify which objects are associated with each grid. For example, grids for tables, grids for walls, grids for air conditioners, and so on. The loaded house geometry can be configured with the locations of temperature control devices such as air conditioners to simulate the indoor temperature conditions when these devices are placed in those locations.

[0032] In addition, set the physical property parameters of each grid as needed, and set the initial state of each grid. The state of the grid includes temperature and speed.

[0033] Figure 2 FIG. 1 is a schematic diagram of the spatial discretization results in the indoor temperature simulation method provided by an embodiment of the present invention. Figure 2 As shown, the three-dimensional model of the house is spatially discretized to obtain multiple grids, and different categories of grids can be distinguished by different colors.

[0034] Step S3: Execute the following loop until the set termination condition is reached:

[0035] For the grid affected by air convection, updating at least one state of the grid through collision and flow processes in the air convection;

[0036] For the lattice affected by temperature diffusion, updating at least one state of the lattice through collision and flow processes in temperature diffusion;

[0037] A preset physical quantity of the real physical space is obtained according to the conversion relationship and the state of the grid; wherein the preset physical quantity includes temperature.

[0038] The simulation operation is performed in the main loop. As for the change of indoor temperature, the embodiment of the present invention couples the two processes of air convection and temperature diffusion.

[0039] For grids affected by air convection, at least one grid state is updated through the collision and flow processes involved in air convection. For grids affected by temperature diffusion, at least one grid state is updated through the collision and flow processes involved in temperature diffusion. The grids affected by air convection and temperature diffusion can intersect. For example, the grids affected by air convection can be only those containing air in the indoor space, while grids containing solid objects such as furniture and walls are unaffected by air convection. Since solid objects like walls can also conduct heat, the grids affected by temperature diffusion can be all grids obtained by spatially discretizing the geometric model of the house.

[0040] In each loop, after updating the states of the grids affected by air convection and those affected by temperature diffusion, the preset physical quantities of the real physical space can be derived based on the calculated physical quantities in the Boltzmann space and the conversion relationship between the physical quantities in the Boltzmann space and the real physical space. These preset physical quantities include temperature, but can also include other physical quantities such as velocity and heat flux, as long as they can be calculated from physical parameters.

[0041] Since the temperature is available for every grid in the house geometry, the temperature of each grid can be displayed in different colors. For example, if you want a lower temperature at the sofa, you can simulate the temperature of the sofa when the thermostat is placed in different positions to determine the optimal location for the thermostat.

[0042] The indoor temperature simulation method provided by an embodiment of the present invention establishes a conversion relationship between the Boltzmann space and the physical quantities of the real physical space, spatially discretizes the house geometric model to obtain multiple grids, classifies the multiple grids, and sets the physical property parameters of each type of grid and the initial state of each grid. For grids affected by air convection, at least one state of the grid is updated through the collision and flow process in the air convection. For grids affected by temperature diffusion, at least one state of the grid is updated through the collision and flow process in the temperature diffusion. Preset physical quantities including temperature in the real physical space are obtained based on the conversion relationship and the state of the grid, thereby realizing indoor temperature simulation using the lattice Boltzmann method and improving the simplicity and accuracy of temperature simulation.

[0043] According to an indoor temperature simulation method provided by an embodiment of the present invention, in the cycle, before updating at least one of the states of the grid affected by air convection through the collision and flow process in the air convection, the method further includes: modifying the state of at least one of the grids at the boundary; wherein the grid at the boundary is the union of the boundary grids among the grids affected by air convection and the boundary grids among the grids affected by temperature diffusion.

[0044] The boundaries of cells affected by air convection and those affected by temperature diffusion are different, but they can intersect. For example, the boundaries of cells affected by air convection include cells with interior walls, while the boundaries of cells affected by temperature diffusion include cells with exterior walls. Generally speaking, cells at the boundary are the union of the boundary cells of cells affected by air convection and those of cells affected by temperature diffusion.

[0045] Since the grids at the boundary will be affected by various factors such as disturbances, before each cycle starts, the state of the grids at the boundary can be modified in advance according to the actual scenario to further improve the accuracy of the simulation.

[0046] Idealized modeling can be performed for various boundaries according to the Boltzmann method's boundary requirements. For example, if the influence of window ventilation is not considered, the boundary grids corresponding to the windows can be set to a closed state, and geometric models can be constructed for the boundary grids corresponding to the air conditioning outlet and return air.

[0047] The indoor temperature simulation method provided by the embodiment of the present invention further improves the accuracy of the simulation by modifying the state of at least one grid at the boundary.

[0048] According to an indoor temperature simulation method provided by an embodiment of the present invention, the establishment of a conversion relationship between the Boltzmann space and the physical quantities of the real physical space includes: setting the spatial step for spatial discretization, the time step for time discretization and the density of various substances in the house geometric model in the real physical space; obtaining the spatial step, time step and density of the Boltzmann space; and establishing a conversion relationship between the physical quantities of the Boltzmann space and the real physical space based on the conversion relationship between the spatial step, the time step and the density in the real physical space and the Boltzmann space.

[0049] The dimensions of any mechanical quantity are a combination of length, time, and mass. In the International System of Units, length is meters, time is seconds, and mass is kilograms. Therefore, it is necessary to determine the step size Δx for spatial discretization, the step size Δt for temporal discretization, and the density ρ, where the density ρ includes the densities of various substances in the geometric model of the house. The scale of the corresponding lattice space (Boltzmann space) is generally:

[0050] Δx*=1

[0051] Δt*=1

[0052] ρ * =1

[0053] Among them, Δx* represents the spatial step of the Boltzmann space, Δt* represents the time step of the Boltzmann space, and ρ * represents the density of the Boltzmann space.

[0054] The relationship between the physical quantities of Boltzmann space and real physical space can be uniquely established through the conversion relationship between length, time and density.

[0055] The simulation algorithm is as follows:

[0056]

[0057] The coupling of convection and diffusion processes means that there is a transfer of values ​​between the convection process and the diffusion process, wherein the velocity of the convection process is transferred to the diffusion process, and the temperature of the diffusion process is transferred to the convection process.

[0058] The indoor temperature simulation method provided by the embodiment of the present invention improves the speed and accuracy of establishing the conversion relationship between the Boltzmann space and the physical quantities of the real physical space by uniquely establishing the conversion relationship between the Boltzmann space and the physical quantities of the real physical space based on the conversion relationship between length, time, and density.

[0059] According to an indoor temperature simulation method provided by an embodiment of the present invention, the physical property parameters of the grid include a relaxation factor; the updating of at least one state of the grid through the collision and flow process in the air convection includes: for the grid at each position, according to the probability of the speed of the grid in the discrete direction i at the current time, the probability of the speed of the grid in the discrete direction i at the current time being in equilibrium, and the relaxation factor of the grid with respect to air convection, obtaining the value of the first collision operator of the grid in the discrete direction i at the current time; according to the value of the first collision operator of the adjacent grid, the value of the atmospheric buoyancy in the discrete direction i at the current time, the probability of the speed in the discrete direction i at the current time, and the time step for time discretization, obtaining the probability of the speed of the grid in the discrete direction i at the next moment; according to the probability of the speed of the grid in the discrete direction i at the next moment, the density of the grid at the next moment, and the discrete speed of the discrete direction i.

[0060] The derivation of the first collision operator takes into account the collision process in air convection, and the derivation of the probability of the velocity magnitude of the grid in the discrete direction i at the next moment takes into account the collision and flow processes in air convection.

[0061] The indoor temperature simulation method provided by the embodiment of the present invention provides a method for updating the speed of grids affected by air convection through the collision and flow process in air convection.

[0062] According to an embodiment of the present invention, a method for simulating indoor temperature is provided. Before obtaining the value of the first collision operator of the grid in the discrete direction i at the current time based on the probability of the speed of the grid in the discrete direction i at the current time, the probability of the speed of the grid in the equilibrium state in the discrete direction i at the current time, and the relaxation factor of the grid with respect to air convection, the method further includes: obtaining the probability of the speed of the grid in the discrete direction i at the current time based on the density of the grid at the current time; obtaining the probability of the speed of the grid in the equilibrium state in the discrete direction i at the current time based on the density and speed of the grid at the current time, the weight of the discrete direction i, the discrete speed of the discrete direction i, and the speed of sound; before obtaining the speed of the grid at the next moment based on the probability of the speed of the grid in the discrete direction i at the next moment, the density of the grid at the next moment, and the discrete speed of the discrete direction i, the method further includes: obtaining the density of the grid at the next moment based on the probability of the speed of the grid in the discrete direction i at the next moment.

[0063] The updating of at least one state of the grid through the collision and flow process in the air convection includes: for the grid at each position, obtaining the probability of the speed of the grid in the discrete direction i at the current time according to the density of the grid at the current time; obtaining the probability of the speed of the grid in the discrete direction i at the current time being in equilibrium according to the density and speed of the grid at the current time, the weight of the discrete direction i, the discrete speed of the discrete direction i and the speed of sound; obtaining the speed of the grid in the discrete direction i at the current time according to the probability of the speed of the grid at the current time, the probability of the speed of the grid in the discrete direction i at the current time being in equilibrium and the relaxation factor of the grid with respect to air convection. The value of the first collision operator in direction i; obtaining the value of the atmospheric buoyancy in the discrete direction i that the grid is subjected to at the current time; obtaining the probability of the speed of the grid in the discrete direction i at the next moment based on the value of the first collision operator of the adjacent grid, the value of the atmospheric buoyancy in the discrete direction i at the current time, the probability of the speed in the discrete direction i at the current time and the time step for time discretization; obtaining the density of the grid at the next moment based on the probability of the speed in the discrete direction i at the next moment; obtaining the speed of the grid at the next moment based on the probability of the speed in the discrete direction i at the next moment, the density of the grid at the next moment and the discrete speed of the discrete direction i.

[0064] Figure 3 It is a schematic diagram of the collision process in the indoor temperature simulation method provided by an embodiment of the present invention. Figure 4 This is a schematic diagram of the flow process in the indoor temperature simulation method provided by an embodiment of the present invention. Collision calculates the current equilibrium distribution. Flow converts the collision results in each direction into a flow.

[0065] The directional discretization of the lattice Boltzmann method is usually expressed in the form of DdQq, where d represents the spatial dimension and q represents the discrete direction. Common examples include D2Q9 (e.g. Figure 3 、 Figure 4 2D scene examples are shown), D3Q7, D3Q19, D3Q27, etc.

[0066] The indoor temperature simulation method provided by the embodiment of the present invention provides a method for updating the speed of grids affected by air convection through the collision and flow process in air convection.

[0067] According to an indoor temperature simulation method provided by an embodiment of the present invention, the probability of obtaining the speed of the grid in a discrete direction i at the current time according to the density of the grid at the current time is expressed as:

[0068]

[0069] Wherein, x represents the spatial coordinate of the grid, t represents the current time, ρ(x,t) represents the density of the grid with spatial coordinate x at the current time, i represents the discrete direction, and f i (x, t) represents the probability of the velocity of the grid with spatial coordinate x in the discrete direction i at the current time;

[0070] The probability of the velocity of the grid being in equilibrium in the discrete direction i at the current time is obtained based on the density and velocity of the grid at the current time, the weight of the discrete direction i, the discrete velocity of the discrete direction i, and the speed of sound, and is expressed as:

[0071]

[0072] Among them, f i eq (ρ(x,t),u(x,t))=f i eq (x, t) represents the probability that the grid with spatial coordinate x is in equilibrium in the discrete direction i at the current time, ω i represents the weight of the discrete direction i, u(x,t) represents the speed of the grid with spatial coordinate x at the current time, c i represents the discrete velocity in discrete direction i, c s represents the speed of sound;

[0073] The value of the first collision operator of the grid in the discrete direction i at the current time is obtained according to the probability of the speed of the grid in the discrete direction i at the current time, the probability of the speed of the grid in the equilibrium state in the discrete direction i at the current time, and the relaxation factor of the grid with respect to air convection, and is expressed as:

[0074]

[0075] Among them, Ω f,i (x, t) represents the first collision operator of the grid with spatial coordinate x in the discrete direction i at the current time, τ f The relaxation factor of the grid with spatial coordinate x with respect to air convection;

[0076] The value of the atmospheric buoyancy of the grid at the current time in the discrete direction i is obtained as:

[0077] F i (x,t)=-ρ0βg(T i (x,t)-T 0i )

[0078] Among them, Fi (x, t) represents the value of the atmospheric buoyancy in the discrete direction i at the current time of the grid with spatial coordinate x, ρ0 represents the initial density of the grid with spatial coordinate x, β represents the fluid thermal diffusion coefficient, g represents the acceleration of gravity, T i (x, t) represents the temperature of the grid with spatial coordinate x in discrete direction i at the current time, and T0 is the reference temperature of discrete direction i;

[0079] The probability of the velocity of the grid in the discrete direction i at the next moment is obtained based on the value of the first collision operator of the adjacent grid, the value of the atmospheric buoyancy in the discrete direction i at the current time, the probability of the velocity in the discrete direction i at the current time, and the time step of the time discretization, and is expressed as:

[0080] f i (x+c i Δt,t+Δt)-f i (x,t)=Δt(Ω f,i (x,t)+F i (x,t))

[0081] Among them, f i (x+c i Δt, t+Δt) represents the probability of the velocity of the grid adjacent to the grid with spatial coordinate x in the discrete direction i at the next moment; Δt represents the time step of the time discretization, and t+Δt represents the next moment;

[0082] The density of the grid at the next moment is obtained according to the probability of the speed of the grid in the discrete direction i at the next moment, which is expressed as:

[0083]

[0084] Among them, ρ(x+c i Δt,t+Δt) represents the density of the grids adjacent to the grid with spatial coordinate x at the next moment;

[0085] The speed of the grid at the next moment is obtained according to the probability of the speed of the grid in the discrete direction i at the next moment, the density of the grid at the next moment and the discrete speed of the discrete direction i, which is expressed as:

[0086]

[0087] Among them, u(x+c i Δt,t+Δt) represents the velocity of the grid adjacent to the grid with spatial coordinate x at the next moment.

[0088] The relationship between fluid viscosity and relaxation factor is as follows:

[0089]

[0090] Here, ν represents the viscosity of the fluid.

[0091] The initial velocity and temperature of the grid are set in the initial state. The velocity and temperature of the next moment can be obtained by calculating the collision and flow process, and the calculation is repeated.

[0092] The indoor temperature simulation method provided by the embodiment of the present invention provides a specific formula for updating the speed of grids affected by air convection through the collision and flow process in air convection.

[0093] According to an indoor temperature simulation method provided by an embodiment of the present invention, the physical property parameters of the grid also include the specific heat capacity parameters of the material in the grid; the state also includes enthalpy; the updating of at least one of the states of the grid through the collision and flow process in temperature diffusion includes: for the grid at each position, according to the probability of the temperature of the grid in the discrete direction i at the current time, the probability of the temperature of the grid in the discrete direction i at the current time being in equilibrium, and the relaxation factor of the grid with respect to thermal diffusion, obtaining the value of the second collision operator of the grid in the discrete direction i at the current time; according to the value of the second collision operator of the adjacent grid, the probability of the temperature in the discrete direction i at the current time, and the time step for time discretization, obtaining the probability of the temperature of the grid in the discrete direction i at the next moment; according to the probability of the temperature of the grid in the discrete direction i at the next moment, obtaining the temperature of the grid at the next moment.

[0094] The second collision operator is derived by taking into account the collision process in temperature diffusion. The probability of the temperature magnitude in the next discrete direction i of the grid is derived by taking into account the convection and collision process in temperature diffusion.

[0095] The indoor temperature simulation method provided by the embodiment of the present invention provides a method for updating the temperature of a grid affected by temperature diffusion through the collision and flow process in temperature diffusion.

[0096] According to an indoor temperature simulation method provided by an embodiment of the present invention, before obtaining the value of the second collision operator of the grid in the discrete direction i at the current time based on the probability of the temperature magnitude of the grid at the current time, the probability of the temperature magnitude of the grid being in equilibrium in the discrete direction i at the current time, and the relaxation factor of the grid with respect to thermal diffusion, the method further includes: obtaining the probability of the temperature magnitude of the grid in the discrete direction i at the current time based on the temperature of the grid at the current time; obtaining the probability of the temperature magnitude of the grid being in equilibrium in the discrete direction i at the current time based on the temperature and velocity of the grid at the current time, the weight of the discrete direction i, the discrete velocity of the discrete direction i, the speed of sound, the enthalpy of the grid at the current time, and the specific heat capacity parameter of the material in the grid.

[0097] The updating of at least one state of the grid through the collision and flow process in temperature diffusion includes: for the grid at each position, obtaining the probability of the temperature of the grid in the discrete direction i at the current time according to the temperature of the grid at the current time; obtaining the probability of the temperature of the grid in the discrete direction i at the current time according to the temperature and velocity of the grid at the current time, the weight of the discrete direction i, the discrete velocity of the discrete direction i, the speed of sound, the enthalpy of the grid at the current time and the specific heat capacity parameter of the material in the grid; obtaining the probability of the temperature of the grid in the discrete direction i at the current time being in equilibrium according to the temperature and velocity of the grid at the current time, the weight of the discrete direction i, the discrete velocity of the discrete direction i, the speed of sound, the enthalpy of the grid at the current time and the specific heat capacity parameter of the material in the grid; obtaining the probability of the temperature of the grid in the discrete direction i at the current time being in equilibrium according to the temperature of the grid at the current time The value of the second collision operator of the grid in the discrete direction i at the current time is obtained according to the probability of the temperature magnitude in the discrete direction i, the probability of the temperature magnitude of the grid in equilibrium in the discrete direction i at the current time, and the relaxation factor of the grid with respect to thermal diffusion; the probability of the temperature magnitude in the discrete direction i at the next moment is obtained according to the value of the second collision operator of the adjacent grid, the probability of the temperature magnitude in the discrete direction i at the current time, and the time step for time discretization; the temperature of the grid at the next moment is obtained according to the probability of the temperature magnitude in the discrete direction i at the next moment.

[0098] To simulate heat transfer between air fluid and solids such as furniture walls, the embodiment of the present invention introduces the physical quantity enthalpy to unify the heat transfer process.

[0099] Based on the principle of similarity, fluids with the same Reynolds number and geometric structure are dynamically similar. Spatial discretization is a process of establishing similarity, and the medium of communication is the dimensionless quantity Reynolds number. The spatial discretization process needs to consider the stability of the simulation to ensure that the relaxation factor is not too small. Based on the conditions that the compressibility of air cannot be ignored, the viscosity of air is small, and the spatial discretization is limited, the embodiment of the present invention can also stabilize the simulation process by adopting a turbulence model (such as the Smagorinsky-subgrid-scale model) to solve the instability problem under large Reynolds numbers.

[0100] The indoor temperature simulation method provided by the embodiment of the present invention provides a method for updating the temperature of a grid affected by temperature diffusion through the collision and flow process in temperature diffusion.

[0101] According to an indoor temperature simulation method provided by an embodiment of the present invention, the probability of obtaining the temperature of the grid at the current time in a discrete direction i is expressed as:

[0102]

[0103] Wherein, T(x, t) represents the temperature of the grid with spatial coordinate x at the current time, g i (x, t) represents the probability of the temperature of the grid with spatial coordinate x in the discrete direction i at the current time;

[0104] The probability of the temperature of the grid being in equilibrium in the discrete direction i at the current time is obtained based on the temperature and velocity of the grid at the current time, the weight of the discrete direction i, the discrete velocity in the discrete direction i, the speed of sound, the enthalpy of the grid at the current time, and the specific heat capacity parameter of the material in the grid, and is expressed as:

[0105]

[0106] in, represents the probability of the temperature of the grid with spatial coordinate x being in equilibrium at the current time in the discrete direction i, H(x,t) represents the enthalpy of the grid with spatial coordinate x at the current time, C p Represents the specific heat capacity parameter of the substance in the lattice with spatial coordinate x, I represents the unit vector, the symbol: represents tensor contraction, the symbol represents the vector outer product;

[0107] The value of the second collision operator of the grid in the discrete direction i at the current time is obtained according to the probability of the temperature of the grid in the discrete direction i at the current time, the probability of the temperature of the grid in the equilibrium state in the discrete direction i at the current time, and the relaxation factor of the grid with respect to thermal diffusion, and is expressed as:

[0108]

[0109] Among them, Ω g,i (x, t) represents the second collision operator of the grid with spatial coordinate x in the discrete direction i at the current time, τ g represents the relaxation factor of the lattice with respect to thermal diffusion;

[0110] The probability of the temperature of the grid in the discrete direction i at the next moment is obtained based on the value of the second collision operator of the adjacent grid, the probability of the temperature in the discrete direction i at the current time, and the time step of the time discretization, which is expressed as:

[0111] g i (x+c i Δt,t+Δt)-g i (x, t) = ΔtΩ g,i (x,t)

[0112] Among them, g i (x+c i Δt,t+Δt) represents the probability of the temperature of the grid adjacent to the grid with spatial coordinate x in the discrete direction i at the next moment;

[0113] The temperature of the grid at the next moment is obtained according to the probability of the temperature of the grid in the discrete direction i at the next moment, which is expressed as:

[0114]

[0115] Among them, T(x+c i Δt,t+Δt) represents the temperature of the grid adjacent to the grid with spatial coordinate x at the next moment.

[0116] In order to simulate the heat conduction process between fluid and solid, the enthalpy H distribution is used to unify the thermal properties of each substance:

[0117] H(x,t)=C p ·Txt)

[0118] Here, H(x, t) represents the enthalpy of the grid cell at the spatial coordinate x at the current time. Different substances transfer heat differently, resulting in different relaxation factors. The relationship between the relaxation factor and thermal diffusion remains unchanged; it is simply differentiated for each substance.

[0119] If enthalpy is not introduced, the probability that the temperature of the grid with spatial coordinate x is in equilibrium in the discrete direction i at the current time is Expressed as:

[0120]

[0121] The other formulas for updating at least one of the states of the lattice by collision and flow processes in temperature diffusion remain unchanged.

[0122] The macroscopic temperature T and heat flux q are calculated as follows:

[0123]

[0124] Among them, q(x,t) represents the heat flux of the grid with spatial coordinate x at the current time.

[0125] The relationship between thermal diffusivity and relaxation factor is as follows:

[0126]

[0127] Here, κ represents the thermal diffusivity of the lattice.

[0128] The indoor temperature simulation method provided by the embodiment of the present invention provides a specific formula for updating the temperature of a grid affected by temperature diffusion through the collision and flow process in temperature diffusion.

[0129] According to an embodiment of the present invention, a method for simulating indoor temperature is provided, the method further comprising: constructing a velocity field sampling function based on a mapping relationship between velocity and position; calculating the next position of the particle based on the velocity field sampling function, the current position of the particle, and the time step for performing time discretization, and sequentially connecting the positions of the particle to obtain and display the motion trajectory of the particle.

[0130] A simulation time can be set, and the velocity field sampling function can be constructed according to the mapping relationship between velocity and position, which can be expressed as Since the position and velocity of each grid can be obtained within a certain simulation time, the velocity of each position point can be obtained by interpolation, thereby obtaining the mapping relationship between velocity and position, and then constructing the velocity field sampling function.

[0131] Simulation results can be displayed using particle flow. For each particle, the next position is calculated based on the velocity field sampling function, the particle's current position, and the time step for time discretization. The particle's positions are sequentially connected to obtain the particle's trajectory and displayed. The trajectory of all particles can also be combined for display.

[0132] Since air is invisible and dense, in order to demonstrate the flow of air, the embodiment of the present invention adopts a particle flow method for presentation, and a high-order Runge-Kutta method is used to calculate the flow path of the sampled particles in space.

[0133] For the particle's position p(t) at the current moment, its position at the next moment is calculated as:

[0134]

[0135] The Runge-Kutta method is used to approximate the above integral and calculate the trajectory of the particle in space. The calculation of the particle from the current position p(t) to the next position is as follows:

[0136]

[0137]

[0138] Figure 5 Schematic diagram of the position of particle flow in the indoor temperature simulation method provided by an embodiment of the present invention. Figure 6 Schematic diagram of the motion trajectory of particle flow in the indoor temperature simulation method provided by an embodiment of the present invention.

[0139] The indoor temperature simulation method provided by an embodiment of the present invention constructs a velocity field sampling function based on the mapping relationship between velocity and position, calculates the next position of the particle based on the velocity field sampling function, the current position of the particle, and the time step for time discretization, and sequentially connects the various positions of the particle to obtain and display the particle's motion trajectory, thereby simulating air flow using particle flow.

[0140] According to an embodiment of the present invention, an indoor temperature simulation method is provided, the method further comprising: obtaining the grid that the particle passes through according to the motion trajectory of the particle, and displaying the line of the motion trajectory in different colors according to the temperature of the grid that the particle passes through.

[0141] Since the temperature of the grid at different locations can be obtained within the set simulation time, the grid that the particle passes through can be obtained based on the particle's trajectory. The trajectory lines can be displayed in different colors based on the temperature of the grid that the particle passes through, thereby realizing the display of temperature changes at different locations of the particle flow.

[0142] The indoor temperature simulation method provided by the embodiment of the present invention obtains the grid that the particle passes through according to the particle's motion trajectory, displays the lines of the motion trajectory in different colors according to the temperature of the grid that the particle passes through, and uses particle flow to realize the display of temperature changes at different positions.

[0143] It should be noted that the multiple preferred implementations given in this embodiment can be freely combined under the premise that there is no logic or structure conflict with each other, and the present invention does not limit this.

[0144] The indoor temperature simulation device provided by an embodiment of the present invention is described below. The indoor temperature simulation device described below and the indoor temperature simulation method described above can be referenced to each other.

[0145] Figure 7 FIG. 1 is a schematic diagram of the structure of the indoor temperature simulation device provided by an embodiment of the present invention. Figure 7 As shown, the device includes a conversion relationship establishment module 10, a discretization processing module 20 and a loop simulation module 30, wherein: the conversion relationship establishment module 10 is used to establish a conversion relationship between the Boltzmann space and the physical quantities of the real physical space; the discretization processing module 20 is used to load the house geometric model, spatially discretize the house geometric model to obtain multiple grids, classify the multiple grids, and set the physical property parameters and initial states of each type of the grid; wherein the states include temperature and speed; the loop simulation module 30 is used to execute the following loop until the set termination condition is reached: for the grid affected by air convection, update at least one of the states of the grid through the collision and flow process in the air convection; for the grid affected by temperature diffusion, update at least one of the states of the grid through the collision and flow process in the temperature diffusion; obtain the preset physical quantity of the real physical space according to the conversion relationship and the state of the grid; wherein the preset physical quantity includes temperature.

[0146] The indoor temperature simulation device provided by an embodiment of the present invention establishes a conversion relationship between the Boltzmann space and the physical quantities of the real physical space, spatially discretizes the house geometric model to obtain multiple grids, classifies the multiple grids, and sets the physical property parameters of each type of grid and the initial state of each grid. For grids affected by air convection, at least one state of the grid is updated through the collision and flow process in the air convection. For grids affected by temperature diffusion, at least one state of the grid is updated through the collision and flow process in the temperature diffusion. Preset physical quantities including temperature in the real physical space are obtained based on the conversion relationship and the state of the grid, thereby realizing indoor temperature simulation using the lattice Boltzmann method and improving the simplicity and accuracy of temperature simulation.

[0147] According to an indoor temperature simulation device provided by an embodiment of the present invention, the circulation simulation module 30 is further used to: modify the state of at least one of the grids at the boundary before updating at least one of the states of the grids affected by air convection through the collision and flow process in the air convection; wherein the grids at the boundary are the union of the boundary grids in the grids affected by air convection and the boundary grids in the grids affected by temperature diffusion.

[0148] The indoor temperature simulation device provided by the embodiment of the present invention further improves the accuracy of simulation by modifying the state of at least one grid at the boundary.

[0149] According to an indoor temperature simulation device provided by an embodiment of the present invention, the conversion relationship establishment module 10, when used to establish the conversion relationship between the Boltzmann space and the physical quantities of the real physical space, is specifically used to: set the spatial step for spatial discretization, the time step for time discretization and the density of various substances in the house geometric model in the real physical space; obtain the spatial step, time step and density of the Boltzmann space; and establish the conversion relationship between the physical quantities of the Boltzmann space and the real physical space based on the conversion relationship between the spatial step, the time step and the density in the real physical space and the Boltzmann space.

[0150] The indoor temperature simulation device provided by the embodiment of the present invention improves the speed and accuracy of establishing the conversion relationship between the Boltzmann space and the physical quantities of the real physical space by uniquely establishing the conversion relationship between the Boltzmann space and the physical quantities of the real physical space based on the conversion relationship between length, time, and density.

[0151] According to an indoor temperature simulation device provided by an embodiment of the present invention, the physical property parameters of the grid include a relaxation factor; when the circulation simulation module 30 is used to update at least one of the states of the grid through the collision and flow process in the air convection, it is specifically used to: for the grid at each position, obtain the value of the first collision operator of the grid in the discrete direction i at the current time according to the probability of the speed of the grid in the discrete direction i at the current time, the probability of the speed of the grid in the discrete direction i at the current time in equilibrium, and the relaxation factor of the grid with respect to air convection; obtain the probability of the speed of the grid in the discrete direction at the next moment according to the value of the first collision operator of the adjacent grid, the value of the atmospheric buoyancy in the discrete direction at the current time, the probability of the speed in the discrete direction at the current time, and the time step for time discretization; obtain the speed of the grid at the next moment according to the probability of the speed of the grid in the discrete direction i at the next moment, the density of the grid at the next moment, and the discrete speed of the discrete direction i.

[0152] The indoor temperature simulation device provided by the embodiment of the present invention realizes updating the speed of the grid affected by air convection through the collision and flow process in air convection.

[0153] According to an indoor temperature simulation device provided by an embodiment of the present invention, the circulation simulation module 30 is further used to: obtain the probability of the speed of the grid in the discrete direction i at the current time according to the density of the grid at the current time; obtain the probability of the speed of the grid in the discrete direction i at the current time according to the density and speed of the grid at the current time, the weight of the discrete direction i, the discrete speed of the discrete direction i and the speed of sound; before obtaining the speed of the grid at the next moment according to the probability of the speed of the grid in the discrete direction i at the next moment, the density of the grid at the next moment and the discrete speed of the discrete direction i, the circulation simulation module 30 is further used to: obtain the density of the grid at the next moment according to the probability of the speed of the grid in the discrete direction i at the next moment.

[0154] The indoor temperature simulation device provided by the embodiment of the present invention realizes updating the speed of the grid affected by air convection through the collision and flow process in air convection.

[0155] According to an indoor temperature simulation device provided by an embodiment of the present invention, the physical property parameters of the grid also include the specific heat capacity parameters of the material in the grid; the state also includes enthalpy; when the circulation simulation module 30 is used to update at least one of the states of the grid through the collision and flow process in temperature diffusion, it is specifically used to: for the grid at each position, according to the probability of the temperature size of the grid in the discrete direction i at the current time, the probability of the temperature size of the grid in the discrete direction i at the current time is in equilibrium, and the relaxation factor of the grid with respect to thermal diffusion, obtain the value of the second collision operator of the grid in the discrete direction i at the current time; according to the value of the second collision operator of the adjacent grid, the probability of the temperature size in the discrete direction i at the current time and the time step for time discretization, obtain the probability of the temperature size of the grid in the discrete direction i at the next moment; according to the probability of the temperature size of the grid in the discrete direction i at the next moment, obtain the temperature of the grid at the next moment.

[0156] The indoor temperature simulation device provided by the embodiment of the present invention realizes updating the temperature of the grid affected by temperature diffusion through the collision and flow process in temperature diffusion.

[0157] According to an indoor temperature simulation device provided by an embodiment of the present invention, the circulation simulation module 30 is also used to: obtain the probability of the temperature size of the grid in the discrete direction i at the current time based on the temperature of the grid at the current time; obtain the probability of the temperature size of the grid in the discrete direction i at the current time based on the temperature of the grid at the current time; obtain the probability of the temperature size of the grid in the discrete direction i at the current time based on the temperature and velocity of the grid at the current time, the weight of the discrete direction i, the discrete velocity of the discrete direction i, the speed of sound, the enthalpy of the grid at the current time and the specific heat capacity parameter of the material in the grid before obtaining the value of the second collision operator of the grid in the discrete direction i at the current time.

[0158] The indoor temperature simulation device provided by the embodiment of the present invention realizes updating the temperature of the grid affected by temperature diffusion through the collision and flow process in temperature diffusion.

[0159] According to an indoor temperature simulation device provided by an embodiment of the present invention, the cyclic simulation module 30 is further used to: construct a velocity field sampling function based on the mapping relationship between velocity and position; calculate the next position of the particle based on the velocity field sampling function, the current position of the particle and the time step for time discretization, and sequentially connect the various positions of the particle to obtain the motion trajectory of the particle and display it.

[0160] The indoor temperature simulation device provided by an embodiment of the present invention constructs a velocity field sampling function based on the mapping relationship between velocity and position, calculates the next position of the particle based on the velocity field sampling function, the current position of the particle, and the time step for time discretization, and sequentially connects the various positions of the particle to obtain and display the particle's motion trajectory, thereby simulating air flow using particle flow.

[0161] According to an indoor temperature simulation device provided by an embodiment of the present invention, the cycle simulation module 30 is further used to: obtain the grid passed by the particle according to the motion trajectory of the particle, and display the line of the motion trajectory in different colors according to the temperature of the grid passed by the particle.

[0162] The indoor temperature simulation device provided by the embodiment of the present invention obtains the grid that the particle passes through according to the particle's motion trajectory, displays the lines of the motion trajectory in different colors according to the temperature of the grid that the particle passes through, and uses particle flow to realize the display of temperature changes at different positions.

[0163] Figure 8 Schematic diagram of the structure of an electronic device provided by an embodiment of the present invention. Figure 8 As shown, the electronic device may include: a processor (processor) 810, a communication interface (Communications Interface) 820, a memory (memory) 830 and a communication bus 840, wherein the processor 810, the communication interface 820, and the memory 830 communicate with each other through the communication bus 840. The processor 810 can call the logic instructions in the memory 830 to execute the indoor temperature simulation method, which includes: establishing a conversion relationship between the Boltzmann space and the physical quantities of the real physical space; loading the house geometric model, spatially discretizing the house geometric model to obtain multiple grids, classifying the multiple grids, and setting the physical property parameters of each type of grid and the initial state of each grid; wherein the state includes temperature and speed; executing the following loop until the set termination condition is reached: for the grid affected by air convection, updating at least one of the states of the grid through the collision and flow process in the air convection; for the grid affected by temperature diffusion, updating at least one of the states of the grid through the collision and flow process in the temperature diffusion; obtaining the preset physical quantity of the real physical space according to the conversion relationship and the state of the grid; wherein the preset physical quantity includes temperature.

[0164] In addition, the logic instructions in the above-mentioned memory 830 can be implemented in the form of a software functional unit and can be stored in a computer-readable storage medium when sold or used as an independent product. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes several instructions for enabling a computer device (which can be a personal computer, server, or network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: various media that can store program codes, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk.

[0165] On the other hand, an embodiment of the present invention also provides a computer program product, which includes a computer program, which can be stored on a non-transitory computer-readable storage medium. When the computer program is executed by a processor, the computer can execute the indoor temperature simulation method provided by the above methods, which includes: establishing a conversion relationship between the Boltzmann space and the physical quantities of the real physical space; loading a house geometric model, spatially discretizing the house geometric model to obtain multiple grids, classifying the multiple grids, and setting the physical property parameters of each type of grid and the initial state of each grid; wherein the state includes temperature and speed; executing the following loop until the set termination condition is reached: for the grid affected by air convection, updating at least one of the states of the grid through collision and flow processes in air convection; for the grid affected by temperature diffusion, updating at least one of the states of the grid through collision and flow processes in temperature diffusion; obtaining a preset physical quantity of the real physical space based on the conversion relationship and the state of the grid; wherein the preset physical quantity includes temperature.

[0166] On the other hand, an embodiment of the present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, is implemented to execute the indoor temperature simulation method provided by the above-mentioned methods, the method comprising: establishing a conversion relationship between the Boltzmann space and the physical quantities of the real physical space; loading a house geometric model, spatially discretizing the house geometric model to obtain a plurality of grids, classifying the plurality of grids, and setting the physical property parameters of each type of the grid and the initial state of each grid; wherein the state includes temperature and speed; executing the following loop until the set termination condition is reached: for the grid affected by air convection, updating at least one of the states of the grid through collision and flow processes in air convection; for the grid affected by temperature diffusion, updating at least one of the states of the grid through collision and flow processes in temperature diffusion; obtaining a preset physical quantity of the real physical space based on the conversion relationship and the state of the grid; wherein the preset physical quantity includes temperature.

[0167] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units, i.e., they may be located in one location or distributed across multiple network units. Some or all of the modules may be selected based on actual needs to achieve the objectives of the present embodiment. Persons of ordinary skill in the art will be able to understand and implement the present invention without inventive effort.

[0168] Through the description of the above embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus a necessary general hardware platform, or of course, by hardware. Based on this understanding, the essence of the above technical solution or the part that contributes to the existing technology can be embodied in the form of a software product. The computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, a magnetic disk, an optical disk, etc., and includes a number of instructions for enabling a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in each embodiment or certain parts of the embodiments.

[0169] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the various embodiments of the present invention.

Claims

1. A method for simulating indoor temperature, characterized in that: include: Establish the conversion relationship between the physical quantities in Boltzmann space and real physical space; Loading a house geometric model, spatially discretizing the house geometric model to obtain a plurality of grids, classifying the plurality of grids, and setting physical property parameters of each type of grid and an initial state of each grid; wherein the state includes temperature and speed; Execute the following loop until the set termination condition is reached: For the grid affected by air convection, updating at least one state of the grid through collision and flow processes in the air convection; For the lattice affected by temperature diffusion, updating at least one state of the lattice through collision and flow processes in temperature diffusion; Obtaining a preset physical quantity of the real physical space according to the conversion relationship and the state of the grid; wherein the preset physical quantity includes temperature; Construct a velocity field sampling function based on the mapping relationship between velocity and position; The next position of the particle is calculated according to the velocity field sampling function, the current position of the particle and the time step for time discretization, and the positions of the particle are sequentially connected to obtain the motion trajectory of the particle and display it.

2. The indoor temperature simulation method according to claim 1, characterized in that: In the cycle, before updating at least one state of the grid affected by air convection through collision and flow processes in air convection, the method further includes: Modify the state of at least one of the grids at the boundary; wherein the grid at the boundary is the union of the boundary grids in the grids affected by air convection and the boundary grids in the grids affected by temperature diffusion.

3. The indoor temperature simulation method according to claim 1, characterized in that: The establishment of the conversion relationship between the physical quantities in the Boltzmann space and the real physical space includes: Setting the spatial step for spatial discretization, the time step for temporal discretization, and the density of various materials in the house geometric model in real physical space; Get the spatial step, time step and density of the Boltzmann space; A conversion relationship between physical quantities in the Boltzmann space and the real physical space is established according to the conversion relationship between the spatial step, the time step and the density in the real physical space and the Boltzmann space.

4. The indoor temperature simulation method according to claim 3, characterized in that: The physical property parameters of the grid include a relaxation factor; and updating at least one state of the grid through collision and flow processes in air convection includes: For the grid at each position, the value of the first collision operator of the grid in the discrete direction at the current time is obtained according to the probability of the velocity of the grid in the discrete direction at the current time, the probability of the velocity of the grid being in equilibrium in the discrete direction at the current time, and the relaxation factor of the grid with respect to air convection; Obtaining the probability of the velocity of the grid in the discrete direction at the next moment based on the value of the first collision operator of the adjacent grid, the value of the atmospheric buoyancy in the discrete direction at the current time, the probability of the velocity in the discrete direction at the current time, and the time step for time discretization; The speed of the grid at the next moment is obtained according to the probability of the speed of the grid in the discrete direction at the next moment, the density of the grid at the next moment and the discrete speed in the discrete direction.

5. The indoor temperature simulation method according to claim 4, characterized in that: Before obtaining the value of the first collision operator of the grid in the discrete direction at the current time based on the probability of the speed of the grid in the discrete direction at the current time, the probability of the speed of the grid being in equilibrium in the discrete direction at the current time, and the relaxation factor of the grid with respect to air convection, the method further includes: Obtaining a probability of the speed of the grid in a discrete direction at the current time according to the density of the grid at the current time; Obtaining a probability that the grid is in equilibrium in the discrete direction at the current time based on the density and velocity of the grid at the current time, the weight of the discrete direction, the discrete velocity in the discrete direction, and the speed of sound; Before obtaining the speed of the grid at the next moment based on the probability of the speed of the grid in the discrete directions at the next moment, the density of the grid at the next moment, and the discrete speed in the discrete directions, the method further includes: The density of the grid at the next moment is obtained according to the probability of the speed of the grid in the discrete direction at the next moment.

6. The indoor temperature simulation method according to claim 5, characterized in that: The physical property parameters of the lattice also include specific heat capacity parameters of the material in the lattice; the state also includes enthalpy; and updating at least one of the states of the lattice through collision and flow processes in temperature diffusion includes: For the grid at each position, the value of the second collision operator of the grid in the discrete direction at the current time is obtained according to the probability of the temperature of the grid in the discrete direction at the current time, the probability of the temperature of the grid being in equilibrium in the discrete direction at the current time, and the relaxation factor of the grid with respect to thermal diffusion; Obtaining the probability of the temperature of the grid in the discrete direction at the next moment according to the value of the second collision operator of the adjacent grid, the probability of the temperature in the discrete direction at the current time, and the time step for time discretization; The temperature of the grid at the next moment is obtained according to the probability of the temperature magnitude of the grid in the discrete directions at the next moment.

7. The indoor temperature simulation method according to claim 6, characterized in that: Before obtaining the value of the second collision operator of the grid in the discrete direction at the current time based on the probability of the temperature of the grid in the discrete direction at the current time, the probability of the temperature of the grid being in equilibrium in the discrete direction at the current time, and the relaxation factor of the grid with respect to thermal diffusion, the method further includes: Obtaining a probability of the temperature of the grid at the current time in a discrete direction according to the temperature of the grid at the current time; The probability that the temperature of the grid is in equilibrium in the discrete direction at the current time is obtained based on the temperature and velocity of the grid at the current time, the weight of the discrete direction, the discrete velocity in the discrete direction, the speed of sound, the enthalpy of the grid at the current time and the specific heat capacity parameter of the material in the grid.

8. The indoor temperature simulation method according to claim 3, characterized in that: The method further comprises: The grid that the particle passes through is obtained according to the motion trajectory of the particle, and the line of the motion trajectory is displayed in different colors according to the temperature of the grid that the particle passes through.

9. An indoor temperature simulation device, characterized in that: include: The conversion relationship establishment module is used to establish the conversion relationship between the physical quantities in the Boltzmann space and the real physical space; a discretization processing module, configured to: load a geometric model of a house, spatially discretize the geometric model to obtain a plurality of grids, classify the plurality of grids, and set physical property parameters and initial states of each type of grid; wherein the states include temperature and speed; The loop simulation module is used to execute the following loop until the set termination condition is reached: For the grid affected by air convection, updating at least one state of the grid through collision and flow processes in the air convection; For the lattice affected by temperature diffusion, updating at least one state of the lattice through collision and flow processes in temperature diffusion; Obtaining a preset physical quantity of the real physical space according to the conversion relationship and the state of the grid; wherein the preset physical quantity includes temperature; Construct a velocity field sampling function based on the mapping relationship between velocity and position; The next position of the particle is calculated according to the velocity field sampling function, the current position of the particle and the time step for time discretization, and the positions of the particle are sequentially connected to obtain the motion trajectory of the particle and display it.

10. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the indoor temperature simulation method according to any one of claims 1 to 8 are implemented.

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