A time-varying radiation boundary fast reconstruction method for complex outdoor environment

Abstract

The application discloses a time-varying radiation boundary fast reconstruction method for complex outdoor environment, and relates to the technical field of surface thermal response analysis, and the method comprises the following steps: determining the geometric parameters and surface material parameters of a scene; in a pre-computation stage, performing path tracing, sampling and recording the radiation propagation coefficients corresponding to the paths starting from the receiving texture units; in a reconstruction stage, obtaining the time-varying radiation source parameters at the current moment, calculating the incident irradiance according to the time-varying radiation source parameters and the radiation propagation coefficients, and taking the radiation input in the thermal boundary condition; establishing a one-dimensional transient heat conduction model along the thickness direction of the texture corresponding surface, and solving the surface temperature of each texture unit. The application separates the fixed scene radiation propagation relationship from the time-varying radiation source through pre-computation, and multiplexes the same set of coefficients at multiple moments to quickly reconstruct the incident irradiance, thereby realizing the ability of maintaining the path tracing processing of complex occlusion and multiple reflections, reducing the repeated calculation cost, and efficiently obtaining the time-varying radiation boundary.

Description

Technical Field

[0001] This application relates to the field of surface thermal response analysis technology, and in particular to a method for rapid reconstruction of time-varying radiation boundaries for complex outdoor environments. Background Technology

[0002] In complex outdoor environments, significant radiative coupling exists between building surfaces, the ground, and adjacent objects. Surface temperature is influenced not only by direct sunlight and sky-scattered radiation but also by geometric shading, multiple reflections between surfaces, and long-wave heat radiation exchange between adjacent surfaces. The time-varying incident radiation boundary of the surface is used for thermal response analysis, serving as an important tool for conducting refined thermal environment assessments and surface temperature predictions.

[0003] Existing building energy consumption simulation software typically uses methods such as solar radiation distribution, apparent factors, or empirical correlations to describe radiation boundary conditions. These methods are well-suited for regular building layouts, but their ability to represent fine-grained shading, multiple reflections, and localized radiation exchange in arbitrarily complex outdoor geometries is limited.

[0004] Monte Carlo path tracing methods can directly describe the propagation, shading, reflection, and absorption of radiative energy in complex geometries and have been used to solve various heat transfer problems. Related research uses the radiative flux results obtained from path tracing as boundary inputs for thermal response simulations to handle radiative heat transfer calculations under complex geometric conditions. However, re-performing a complete path tracing sampling at every time step is computationally expensive and difficult to directly apply to the rapid updating of radiative boundaries in complex outdoor environments with multiple time steps and large-scale scenarios.

[0005] Therefore, existing technologies cannot reduce the cost of repetitive calculations in multi-moment thermal response analysis while maintaining the ability to handle complex occlusions and multiple reflections in path tracing, and cannot achieve efficient acquisition of time-varying radiation boundaries. Summary of the Invention

[0006] The purpose of this application is to provide a method for rapid reconstruction of time-varying radiation boundaries in complex outdoor environments. By pre-calculating the radiation propagation relationship of a fixed scene from the time-varying radiation source, and reusing the same set of coefficients at multiple times to rapidly reconstruct the incident irradiance, this method reduces the cost of repetitive calculations in multi-time thermal response analysis while maintaining the ability to handle complex occlusions and multiple reflections through path tracking, and also achieves efficient acquisition of time-varying radiation boundaries.

[0007] To achieve the above objectives, this application provides the following solution: In a first aspect, this application provides a method for rapid reconstruction of time-varying radiation boundaries in complex outdoor environments, comprising: determining the geometric parameters and surface material parameters of the scene; in a pre-calculation stage, performing path tracing based on the scene, sampling and recording the radiation propagation coefficient corresponding to the path originating from the receiving texture unit; wherein, the radiation propagation coefficient characterizes the radiation propagation relationship determined by geometric occlusion, surface reflection, and multiple reflections in the fixed scene, and is separated from the time-varying radiation source term; in the reconstruction stage, obtaining the time-varying radiation source parameters at the current moment, the time-varying radiation source parameters including the solar direction, solar normal direct irradiance, equivalent sky irradiance, and the surface temperature of other texture units in the scene besides the receiving texture unit; and calculating the incident irradiance of the receiving texture unit at the current moment based on the time-varying radiation source parameters and the radiation propagation coefficient, as the radiation input in the thermal boundary condition.

[0008] In one embodiment, the incident irradiance of the receiving texture unit is composed of the following radiation terms: direct solar shortwave incident irradiance, indirect solar shortwave incident irradiance, sky shortwave irradiance, sky longwave irradiance, and inter-surface longwave incident irradiance.

[0009] In one embodiment, the radiation propagation coefficient includes: a sky radiation term propagation coefficient, used to characterize the radiation propagation capability of the receiving texture unit that is directly visible to the sky and escapes to the sky after being reflected from the scene surface; a solar shortwave radiation term propagation coefficient, used to characterize the solar reflection shortwave radiation propagation capability of the other texture units to the receiving texture unit; and an inter-surface longwave radiation term propagation coefficient, used to characterize the longwave thermal radiation propagation capability of the other texture units to the receiving texture unit.

[0010] In one embodiment, the reconstruction stage, calculating the incident irradiance of the receiving texture unit based on the time-varying radiation source parameters and the radiation propagation coefficient, includes: calculating the short-wave and long-wave incident irradiance of the receiving texture unit based on the sky radiation term propagation coefficient and the equivalent sky irradiance at the current moment; wherein, the sky radiation coefficient is obtained by performing multiple importance sampling weighted merging on the sky branch directly connected to the path tracing and the path escape to the sky branch under the uniform sky assumption.

[0011] In one embodiment, the reconstruction stage, calculating the incident irradiance of the receiving texture unit based on the time-varying radiation source parameters and the radiation propagation coefficient, includes: calculating the solar indirect shortwave incident irradiance of the receiving texture unit based on the solar shortwave radiation term propagation coefficient, the shortwave reflectivity of each texture unit, the solar direction at the current moment, and the solar normal direct irradiance.

[0012] In one embodiment, the reconstruction stage, calculating the incident irradiance of the receiving texture unit based on the time-varying radiation source parameters and the radiation propagation coefficient, includes: calculating the inter-surface long-wavelength incident irradiance of the receiving texture unit based on the propagation coefficient of the inter-surface long-wavelength radiation term, the long-wavelength emissivity of the other texture units, and the surface temperature of the other texture units at the current moment.

[0013] In one embodiment, during the reconstruction phase, the direct shortwave incident irradiance of the sun is obtained by: uniformly sampling within the area corresponding to the receiving texture unit, gradually increasing the number of sampling points in stages, and updating the estimated value of the solar direction incident cosine-visibility joint factor of the receiving texture unit in each stage; calculating the direct shortwave incident irradiance of the sun based on the estimated value of the solar direction incident cosine-visibility joint factor and the current solar normal direct irradiance; wherein, when the change in the estimated value between adjacent stages is less than a preset threshold, sampling of the receiving texture unit is stopped; otherwise, the number of sampling points continues to increase.

[0014] In one embodiment, the method further includes: using the incident irradiance of the receiving texture unit as the radiation input in the thermal boundary condition, establishing a one-dimensional transient thermal conduction model along the thickness direction of the surface corresponding to the texture unit, and solving for the surface temperature of each texture unit; wherein, the calculation of the inter-surface long-wave irradiance depends on the surface temperature of the other texture units, and fixed-point iteration is used in each time step to update the inter-surface long-wave irradiance according to the current surface temperature, and then substitute it into the thermal conduction model to solve until the temperature field converges.

[0015] Secondly, this application provides a system for rapid reconstruction of time-varying radiation boundaries in complex outdoor environments, comprising: a pre-calculation module, used to perform path tracing based on the scene after the geometric parameters and surface material parameters of a fixed scene are determined, and to sample and record the radiation propagation coefficient corresponding to the path starting from the receiving texture unit; wherein the radiation propagation coefficient characterizes the radiation propagation relationship in the scene determined by geometric occlusion, surface reflection and multiple reflections, and is separated from the radiation source term that changes with time; and a reconstruction module, used to obtain the time-varying radiation source parameters at the current moment, and to calculate the incident irradiance of the receiving texture unit at the current moment based on the time-varying radiation source parameters and the radiation propagation coefficient, as the radiation input in the thermal boundary condition; the time-varying radiation source parameters include at least the solar direction, the solar normal direct irradiance, the equivalent sky irradiance, and the surface temperature of other texture units in the scene other than the receiving texture unit.

[0016] Thirdly, this application provides a computer device, including: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the steps of the method for rapid reconstruction of time-varying radiation boundaries for complex outdoor environments as described above.

[0017] According to the specific embodiments provided in this application, the following technical effects are disclosed: This application provides a method for rapid reconstruction of time-varying radiation boundaries in complex outdoor environments. By determining fixed geometric parameters and surface material parameters of the scene, it provides unchanging scene input conditions for the pre-computation stage, enabling the unique determination of geometric occlusion relationships, surface reflection characteristics, and multiple reflection paths in the scene. This lays the foundation for subsequently separating the radiation propagation relationship from the time-varying radiation source term. Through path tracing based on a fixed scene in the pre-computation stage, the radiation propagation coefficients corresponding to the paths originating from the receiving texture units are sampled and recorded. This separates the radiation propagation relationship determined by geometric occlusion, surface reflection, and multiple reflections from the time-varying radiation source term, solving the problem of repeatedly executing complete time-sequence calculations. To address the issue of excessive computational cost caused by path tracing, this method enables the reuse of the radiation propagation coefficient across multiple time points with only a single pre-calculation, under the condition of fixed scene geometry and material parameters. This avoids the redundant computational overhead of re-performing the complete path tracing sampling at each time point. By acquiring the time-varying radiation source parameters at the current time point during the reconstruction phase and quickly calculating the incident irradiance of the received texture unit at the current time point based on the radiation propagation coefficient recorded in the pre-calculation phase, the problem of efficient updating of radiation boundaries at multiple time points is solved. This achieves the ability to handle complex occlusion and multiple reflections while maintaining the accuracy of path tracing, and reduces the computation time of incident irradiance, providing a rapidly updatable thermal boundary condition radiation input for subsequent temperature solutions. Attached Figure Description

[0018] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0019] Figure 1 A flowchart illustrating a method for rapid reconstruction of time-varying radiation boundaries in complex outdoor environments, provided in Embodiment 1 of this application; Figure 2 for Figure 1 A detailed flowchart of step S2; Figure 3 This is a path tracing diagram provided in Embodiment 1 of this application; Figure 4for Figure 1 A detailed flowchart of step S3; Figure 5 for Figure 4 A detailed flowchart of step S33; Figure 6 for Figure 1 A detailed flowchart of step S4; Figure 7 for Figure 6 A detailed flowchart of step S43; Figure 8 This is a schematic diagram showing the difference distribution between the incident irradiance reconstruction results and the traditional complete path tracing calculation results in a simulation verification example of a small-scale complex occlusion scene in this application; Figure 9 A comparison table of simulation errors and time consumption for small-scale complex occlusion scenarios in this application; Figure 10 A schematic diagram showing the difference between the incident irradiance reconstruction results using the method of this invention and the traditional complete path tracing calculation results in a large-scale urban block scene simulation verification example; Figure 11 A comparison of the temperature field and the distribution of long-wave radiation incident irradiance between surfaces under conditions considering and not considering the temperature coupling simulation verification example of inter-surface long-wave radiation exchange. Figure 12 A statistical table of the temperature response to the inter-surface long-wave radiation exchange in a temperature coupling simulation verification example of inter-surface long-wave radiation. Figure 13 Table of material parameters of the experimental target in the experimental scenario for outdoor infrared thermal imaging benchmark verification example; Figure 14 A comparison diagram of the measured infrared temperature cloud map at different times in an outdoor infrared thermal imaging benchmark verification example and the simulated temperature cloud map of the present invention; Figure 15 The curves showing the changes in measured and simulated temperatures over time for three representative regions, R1, R2, and R3, in an outdoor infrared thermal imaging benchmark verification example. Figure 16 This is a schematic diagram of the functional modules of a rapid reconstruction system for time-varying radiation boundaries in complex outdoor environments, provided in Embodiment 3 of this application. Figure 17 This is an application environment diagram for a method for rapid reconstruction of time-varying radiation boundaries in complex outdoor environments, provided in Embodiment 4 of this application. Detailed Implementation

[0020] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0021] To make the above-mentioned objectives, features and advantages of this application more apparent and understandable, the application will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0022] Example 1 In one exemplary embodiment, such as Figure 1 As shown, a method for rapid reconstruction of time-varying radiation boundaries in complex outdoor environments is provided. This method is executed by a computer device and includes the following steps: S1, determine the geometric parameters and surface material parameters of the scene.

[0023] S2, the pre-computation stage, performs path tracing based on the scene, samples and records the radiation propagation coefficients corresponding to the paths originating from the receiving texture units.

[0024] Among them, the radiation propagation coefficient characterizes the radiation propagation relationship in a fixed scene determined by geometric occlusion, surface reflection and multiple reflections, and is separated from the radiation source term that changes with time.

[0025] S3, the reconstruction phase, obtains the time-varying radiation source parameters at the current moment, and calculates the incident irradiance of the received texture unit at the current moment based on the time-varying radiation source parameters and the radiation propagation coefficient, which is used as the radiation input in the thermal boundary condition.

[0026] The time-varying radiation source parameters include the solar direction, solar normal direct irradiance, equivalent sky irradiance, and the surface temperature of other texture units in the scene besides the receiving texture unit.

[0027] Implementing steps S1 to S3 as described above, step S1 provides fixed scene input conditions for the pre-calculation stage, ensuring that the geometric occlusion relationships, surface reflection characteristics, and multiple reflection paths in the scene are uniquely determined. This lays the foundation for separating the radiation propagation relationship from the time-varying radiation source term. Step S2 separates the radiation propagation relationship determined by geometric occlusion, surface reflection, and multiple reflections in the scene from the time-varying radiation source term, solving the problem of excessive computational cost caused by repeatedly performing full path tracing at each time step. This allows the radiation propagation coefficient to be reused at multiple time steps with only one pre-calculation under the condition of fixed scene geometry and material parameters, avoiding the repetitive computational overhead of re-performing full path tracing sampling at each time step. Step S3 solves the problem of efficient updating of radiation boundaries at multiple time steps, reducing the calculation time of incident irradiance while maintaining the path tracing accuracy and the ability to handle complex occlusion and multiple reflections. This provides a rapidly updatable thermal boundary condition radiation input for subsequent temperature solutions.

[0028] In addition, this application may also implement step S4 after step S3: take the incident irradiance of the received texture unit as the radiation input in the thermal boundary condition, establish a one-dimensional transient thermal conduction model along the surface thickness direction of the texture unit, and solve the surface temperature of each texture unit.

[0029] By using the incident irradiance of the received texture unit as the radiation input in the thermal boundary condition, a one-dimensional transient thermal conduction model is established along the surface thickness direction of the texture unit and the surface temperature of each texture unit is solved. This solves the problem of connecting the solution from the time-varying radiation boundary to the surface temperature solution, and realizes the surface temperature prediction based on the rapid reconstruction of the radiation boundary in complex outdoor environments. It provides a complete and efficient computational path for multi-time thermal response analysis.

[0030] The implementation process of one embodiment of this application will be described in detail below with reference to specific examples.

[0031] For example, in step S1, the geometric parameters of the scene include the three-dimensional geometric model data of each surface in the scene, such as the vertex coordinates and normal directions of triangular facets. Surface material parameters include the short-wavelength reflectivity, long-wavelength emissivity, and surface scattering function corresponding to each texture unit. After determining the above parameters, the geometric structure and material properties of the scene remain unchanged in subsequent calculations.

[0032] The scene surface can be discretized into multiple texture units after the texture map is unfolded. Each texture unit This corresponds to a local area on the surface of the scene model. The texture unit belongs to a triangular facet. The three vertices are respectively , and For texture units Generate in its corresponding surface area Sampling points evenly distributed by area For each sampling point, its three-dimensional position can be obtained by interpolating the centroid of the triangle's vertices. Each sampling point can be determined by three non-negative weights. , , It means that among them, satisfying When these weights are generated uniformly according to the area of ​​the corresponding surface region, the sampling points... The three-dimensional coordinates are: (Equation 1); In the above formula, Represents texture unit The first One sampling point, .

[0033] For each sampling point Perform path tracing separately to obtain each sampling point. The estimated incident irradiance values ​​are averaged to obtain the texture unit. Estimated incident irradiance: (Equation 2); In the above formula, Represents texture unit Take the averaged estimated value of incident irradiance. For texture units The total number of sampling points on the surface For the first The incident irradiance estimate obtained by path tracing at each sampling point.

[0034] For example, such as Figure 2 As shown, the pre-calculation stage of step S2 includes the following steps: S21, Receive texture unit and sampling point determined.

[0035] Specifically, each effective texture unit i generated after the texture map is unfolded is used as the receiving point.

[0036] S22, perform path tracing sampling and direct connection estimation.

[0037] Specifically, for the starting point of texture unit i Path tracing starts from this starting point. A main path is generated, and it intersects with the surfaces in the scene in sequence to form path vertices. ,like Figure 3 The diagram shown illustrates the path tracing process. Wherein, The first intersection, The subsequent vertices are the possible reflection intersections that may occur later.

[0038] For any intersection point in the path ,remember For the surface normal at that point, define from Point to the previous intersection point The direction is the direction of launch. , defined from Point to the next intersection point The direction is the incident direction. ,Right now: (Equation 3); (Equation 4); At each intersection At the same time, main path propagation and direct connection estimation are performed.

[0039] For main path propagation: According to the surface scattering function and preset sampling probability density The direction of the next jump is determined by sampling the direction of the hemisphere. It continues to propagate to the next intersection. .

[0040] Following the path recursively, the single-sample Monte Carlo estimation can be expressed as: (Equation 5); in, For emitted radiance, For self-luminous radiance, The incident radiance.

[0041] Furthermore, the intersection points along the path satisfy the following recurrence relation: (Equation 6); Expanding the recurrence relation along the path, then the point Along the sampling direction The received incident radiance can be represented as: (Equation 7); in, From the first intersection Spread to the vertices The cumulative path weight is defined as: (Equation 8); In the above formula, k represents the path from the first intersection point. To the Intersection points The index.

[0042] For direct connection estimation: From the current intersection point Samples are taken directly from external radiation sources such as the sun or sky, and their direct contribution is estimated through visibility detection.

[0043] Therefore, as described in step S22, both main path propagation and direct connectivity estimation are performed simultaneously at each intersection point. In the main path propagation, some paths eventually escape to the sky hemisphere after multiple reflections, forming an indirect contribution to sky radiation; direct connectivity estimation samples directly from the intersection point towards the sky or the sun and performs occlusion detection, forming a direct contribution to external radiation sources.

[0044] S23, Multiple importance sampling merging and radiative propagation coefficient classification record for sky radiation terms.

[0045] Specifically, for the sky radiation term, at the intersection point There are two contribution channels: one is the contribution obtained by directly sampling the sky direction from the intersection point through direct connection estimation; the other is the contribution formed by the main path escaping to the sky hemisphere after reflection from the scene surface. To avoid double counting and reduce estimation variance, multiple importance sampling is used to weight and combine the two types of contributions. Let the sampling probability density of the direct connection estimation branch be... The probability density of the sampling branch of the surface scattering function of the main path is The weights of the two types of branches are as follows: (Equation 9); (Equation 10); The contribution of directly connecting to the sky uses weights. Weighted, the contribution of the main path escape to the sky is weighted. Weighting allows us to combine the two samples to obtain the total contribution of this sampling to the sky radiation term.

[0046] After completing the above merging process, the propagation contribution of each sample is categorized according to the radiation source type and accumulated into the corresponding radiation propagation coefficients. The radiation propagation coefficients include three categories: sky radiation term propagation coefficient, solar shortwave radiation term propagation coefficient, and inter-surface longwave radiation term propagation coefficient.

[0047] Sky radiation propagation coefficient: accumulated separately for shortwave and longwave channels, denoted as... and This coefficient includes all sky contributions after weighted merging based on multiple importance sampling, i.e., the contribution of the directly visible sky and the contribution that escapes to the sky hemisphere after one or more reflections from the scene surface. Furthermore, the pre-calculation stage of this embodiment assumes that the sky is uniformly distributed in all directions, and this coefficient is calculated under the assumption of a uniform sky.

[0048] Solar shortwave radiation propagation coefficient: If a path originating from a receiving texture unit sequentially hits several textures, each hit texture unit on the path is considered a potential solar reflector. The propagation weights of the receiving texture units are aggregated into the solar shortwave radiation propagation coefficient according to the texture number. In, that is The cumulative shortwave radiation propagation capability of other texture units j to receiving texture unit i is characterized, and other texture units j are considered as potential solar reflectors.

[0049] Propagation coefficient of inter-surface long-wavelength radiation: In this embodiment, the gray-body Lambertian emission assumption is adopted, and the same path sampling and weight accumulation are performed on the inter-surface long-wavelength radiation propagation as described above. This can be understood as follows: if the path originating from receiving texture unit i hits other texture units j, the propagation weights are aggregated into the inter-surface long-wavelength radiation propagation coefficient. In, that is Characterizes the cumulative long-wavelength radiation propagation capability of other texture units j to the receiving texture unit i.

[0050] Furthermore, the effective total path samples obtained by the receiving texture unit in the pre-computation stage can be denoted as... A strip is used for the incident radiometer in the subsequent reconstruction phase. Therefore, after the pre-calculation phase is completed, the sky radiation term propagation coefficient... and Propagation coefficient of solar shortwave radiation term Propagation coefficient of long-wave radiation term between surfaces and the number of valid path samples for each texture unit All data has been recorded and together constitutes the radiation propagation coefficient table. During the reconstruction phase, based on the current time-varying radiation source parameters and the radiation propagation coefficient table generated in the pre-calculation phase, the incident irradiance of each receiving texture unit is quickly calculated at different times, without the need to re-execute the complete path tracing.

[0051] For example, such as Figure 4 As shown, the reconstruction phase of step S3 includes the following steps: S31, obtain the time-varying radiation source parameters at the current moment.

[0052] Specifically, the time-varying radiation source parameters at the current time t are obtained, including: solar direction s(t), solar normal direct irradiance DNI(t), equivalent sky irradiance, and surface temperature of other texture units in the scene besides the receiving texture unit. The equivalent sky radiance includes the equivalent sky shortwave radiance. Equivalent radiance of long-wavelength sky And the equivalent radiance of shortwave in the sky. The equivalent longwave radiance of the sky is calculated from the current shortwave irradiance. It is calculated from the current long-wave irradiance of the sky.

[0053] S32, calculate the short-wavelength incident irradiance and long-wavelength incident irradiance of the receiving texture unit.

[0054] Specifically, based on the sky radiation term propagation coefficient and the equivalent sky radiance at the current moment, the sky short-wave incident irradiance and sky long-wave incident irradiance of the receiving texture unit are calculated.

[0055] Under the assumption of a uniform sky, the shortwave incident irradiance of the sky and long-wave incident irradiance of the sky The calculation formulas are as follows: (Equation 11); (Equation 12); in, For receiving texture units The total number of valid path samples obtained in the pre-computation phase. and The sky radiation term propagation coefficients recorded in the pre-calculation phase have been weighted and merged by multiple importance sampling of directly connected sky branches and path escape to sky branches during the pre-calculation phase.

[0056] In another implementation, a non-uniform sky distribution can be further considered. The sky hemisphere can be discretized into a directional texture map and extended to a direction-dependent sky radiation term propagation coefficient within the same framework of the pre-computation stage. In the reconstruction stage, the sky shortwave incident irradiance and sky longwave incident irradiance under a non-uniform sky distribution are obtained.

[0057] S33, calculate the direct shortwave incident irradiance of the sun.

[0058] Specifically, the direct shortwave solar irradiance does not rely on the radiative propagation coefficient table recorded in the pre-calculation phase, but is calculated directly at each moment based on the current solar direction and scene shading relationship. For example... Figure 5 As shown, the direct shortwave solar irradiance is obtained through the following sub-steps: S331, uniformly sample within the area corresponding to the receiving texture unit, and gradually increase the number of sampling points in stages.

[0059] Specifically, suppose that there are a total of texture units i receiving textures. Solar sampling points evenly distributed by area , .

[0060] S332 updates the estimate of the solar direction incident cosine-visibility joint factor of the receiving texture unit at each stage.

[0061] Specifically, at each stage, the solar direction incident cosine-visibility joint factor of the receiving texture unit is updated based on the sampling point of the current stage. The estimated value. Specifically, let the current solar direction be s(t), and the surface normal of the receiving texture unit i be... ,but: (Equation 13); in, Let cosine be the angle of incidence between the surface normal at the sampling point and the direction of the sun. Sampling points Along the direction of the sun The visibility function takes the value 1 when there is no occlusion and 0 when there is occlusion.

[0062] S333, makes a judgment on the relationship between the estimated value change in adjacent stages and the preset threshold.

[0063] Specifically, it is determined whether the change in the estimated value between adjacent stages is less than a preset threshold. If the change in the estimated value between adjacent stages is less than the preset threshold, sampling of the receiving texture unit is stopped, and the process proceeds to the next step S334. Otherwise, the number of sampling points is gradually increased according to the stages, and the process returns to the previous step S332 to continue updating. The estimated value.

[0064] S334, calculates the direct shortwave incident irradiance of the sun.

[0065] Specifically, based on the solar direction incident cosine-visibility joint factor The final estimated value is used to calculate the solar direct shortwave incident irradiance, along with the current solar normal direct irradiance DNI(t). The calculation method is as follows: (Equation 14).

[0066] S34, calculates the solar indirect shortwave incident irradiance.

[0067] Specifically, regarding the indirect shortwave contribution formed by the sun after reflection from the surface, under the Lambert reflection assumption, the solar shortwave radiance reflected by other texture units j is: (Equation 15); where, For other texture units shortwave reflectivity, For other texture units The incident cosine-visibility joint factor under the current solar orientation is calculated by the method in step S33.

[0068] The solar indirect shortwave incident irradiance of receiving texture unit i is a weighted sum of the contributions from all other texture units. The calculation formula is: (Equation 16); In equation (16), This represents the summation over all possible other texture units j; The propagation coefficient of the solar shortwave radiation term recorded in the pre-calculation stage characterizes the cumulative shortwave radiation propagation capability of other texture units j to the receiving texture unit i.

[0069] S35 calculates the long-wavelength incident irradiance between surfaces, which serves as the radiation input in the thermal boundary condition.

[0070] Specifically, the inter-surface long-wavelength radiation term adopts the gray-body Lambertian emission assumption. The long-wavelength emission of other texture units j is determined by their surface temperature, and the equivalent emission radiance is: (Equation 17); where, For the long-wavelength emissivity of other texture units j, This is the Stefan-Boltzmann constant. For the surface temperature of other texture units j at the current time t, express The fourth power.

[0071] The inter-plane long-wavelength incident irradiance of receiving texture unit i is a weighted sum of the contributions of each other texture unit, and the inter-plane long-wavelength incident irradiance of receiving texture unit i is... The calculation formula is: (Equation 18); In equation (18), The propagation coefficient of the inter-surface long-wave radiation term recorded in the pre-calculation stage characterizes the cumulative long-wave radiation propagation capability of other texture units j to the receiving texture unit i.

[0072] For example, such as Figure 6 As shown, step S4 includes the following steps: S41, Establish a one-dimensional transient heat conduction model.

[0073] Specifically, for each texture unit, a one-dimensional transient heat conduction equation is established along its thickness direction: (Equation 19); In the above formula, For material density, For the specific heat capacity of the material, The thermal conductivity of the material. For temperature, Let z be the time and z be the thickness.

[0074] S42, establish the surface energy balance equation.

[0075] Specifically, at z=0 on the outer surface, the energy balance equation is: Equation (20); In the above formula: The total shortwave incident irradiance of receiving texture unit i, including direct solar shortwave incident irradiance. Indirect shortwave solar irradiance and sky shortwave incident irradiance ; The long-wave incident irradiance of the sky; The inter-surface long-wavelength incident irradiance; The shortwave absorption rate of receiving texture unit i; The long-wavelength absorption rate of the receiving texture unit i; For receiving texture unit i, the long-wavelength emissivity; It is the Stefan-Boltzmann constant; To receive the surface temperature of texture unit i at time t; The convective heat transfer coefficient of the receiving texture unit i at time t; Let be the air temperature at time t.

[0076] S43, fixed-point iterative solution of the temperature field.

[0077] Specifically, due to the inter-surface long-wavelength incident irradiance The temperature solution and long-wavelength radiation exchange are nonlinearly coupled, depending on the current surface temperature of other texture units. For example... Figure 7 As shown, this embodiment uses fixed-point iteration to solve the coupled problem at each time step. The specific iteration process is as follows: S431 uses the incident irradiance of the receiving texture unit as the radiation input in the thermal boundary condition, and solves the surface temperature of each texture unit based on a one-dimensional transient thermal conduction model.

[0078] Specifically, the solar direct shortwave incident irradiance obtained in step S334 is... The solar indirect shortwave incident irradiance obtained in step S34 The sky shortwave incident irradiance obtained in step S32 and long-wave incident irradiance of the sky and the inter-plane long-wavelength incident irradiance obtained in step S35 The radiation inputs of each texture unit are used together as the surface boundary conditions. Substituted into the surface energy balance equation of step S432 and combined with the one-dimensional transient heat conduction equation of step S431, the temperature field of each texture unit is solved to obtain the updated surface temperature.

[0079] S432 updates the inter-surface long-wave irradiance based on the current surface temperature.

[0080] Specifically, the current surface temperature of each texture unit obtained from step S431 is combined with the propagation coefficient of the inter-surface long-wave radiation term recorded in the pre-calculation stage. The inter-surface long-wavelength incident irradiance of the receiving texture unit is recalculated according to the formula in step S35.

[0081] S433, substitute the updated inter-surface long-wave irradiance into the heat conduction model for solution.

[0082] Specifically, the updated inter-surface long-wave incident irradiance from step S432 is substituted into the surface energy balance equation from step S42, and the temperature field of each texture unit is solved again based on the one-dimensional transient heat conduction model from step S41 to obtain the updated surface temperature.

[0083] S434 determines whether the temperature field converges.

[0084] Specifically, if convergence is achieved, proceed to the next time step; otherwise, return to sub-step S432 and continue iterating until the temperature field converges.

[0085] Through the above fixed-point iteration, the coupled solution of radiation transfer and heat conduction is realized in each time step, which accurately reflects the mutual influence between surface temperature and inter-surface long-wave radiation exchange in complex outdoor environments.

[0086] Example 2 This embodiment is a numerical simulation verification embodiment.

[0087] Simulation verification example of small-to-medium scale complex occlusion scene: This embodiment is based on the method for rapid reconstruction of time-varying radiation boundaries for complex outdoor environments described in Embodiment 1 above. Two sets of numerical simulation verifications are carried out using small-to-medium scale geometric scenes. The traditional complete Monte Carlo path tracing calculation results are used as a reference and compared with the method of this invention.

[0088] Basic simulation settings for small to medium-sized geometric scenarios: Geometric model setup: A small to medium-sized outdoor scene containing buildings and occlusion components, with a total of approximately 150,000 triangular faces. The scene has obvious occlusion and multiple reflection relationships. Geographical and temporal conditions: A simulation verification was conducted using typical meteorological environments in mid-latitude cities in North China, with comparisons made at three typical times: 9:00, 11:00, and 13:00. Traditional full path tracing parameter settings: 64 samples per receiving texture unit, 64 samples per hemispherical direction at each sampling point, and a maximum path depth of 5; the long-wave irradiance of the sky is fixed at 350W / m², and the sun position, direct solar irradiance DNI, and horizontal sky diffuse irradiance DHI are calculated by the pvlib-python model. The method of this invention is set up as follows: In the pre-calculation stage, a radiative transfer coefficient table is generated based on geometric, material properties and texture discretization relationship, and the propagation coefficients of sky radiation, solar shortwave radiation and inter-surface longwave radiation are generated at one time; at 9:00, 11:00 and 13:00, the pre-calculated propagation coefficients are directly reused, and only the time-varying radiation source parameters at the corresponding time are updated to reconstruct the incident irradiance.

[0089] like Figure 8 This diagram illustrates the difference between the incident irradiance reconstruction results using the method of this invention and the traditional complete path tracing calculation results at different times in a small-to-medium scale scene according to this embodiment. The diagram is divided into three horizontal rows, corresponding to the simulation times of 9:00, 11:00, and 13:00 from top to bottom. Each row contains two side-by-side graphs: the left side of each row shows the irradiance cloud map reconstructed by the method of this invention, and the right side shows the difference distribution cloud map between the traditional complete path tracing and the reconstruction results of this invention. The visualization results show that the overall spatial distribution of the rapid reconstruction results of this invention is consistent with that of the traditional complete path tracing results. Both occluded areas and locally high-irradiance areas can be reconstructed well. The difference between the two is mainly concentrated in the shadow boundary region. This is because at the shadow boundary, the visibility of direct sunlight may undergo abrupt changes in the texture unit, leading to differences in the average incident irradiance, thus easily causing discrepancies.

[0090] Regarding computational efficiency: statistics on the error, computation time, and speedup ratio for the three time sets are as follows: Figure 9 The table comparing simulation errors and time consumption for small- to medium-scale scenarios is shown below. Figure 9The quantitative data shows that the average relative errors at the three simulation time points are 0.0675%, 0.0562%, and 0.0548%, respectively, all below 0.1%; the maximum absolute errors are 46.51 W / m², 59.08 W / m², and 57.23 W / m², respectively. The overall error remains at a low level, indicating that the method presented in this application maintains relatively stable reconstruction accuracy even with changes in solar position and radiation boundary conditions. Furthermore, in terms of computational efficiency, the average computation time for complete path tracing at the three time points is approximately 3.49 minutes, while the average computation time for fast reconstruction is only approximately 136.19 ms. Compared to the traditional time-by-time complete path tracing, the method of this invention achieves an acceleration of approximately 1.5 × 10³ times. This demonstrates that when the geometric structure and material parameters remain unchanged, the pre-calculated radiation propagation coefficient can effectively reuse the fixed propagation information determined by geometric visibility and surface reflection relationships in path tracing, thereby significantly reducing the computational cost of updating the radiation boundary at multiple time points.

[0091] Large-scale urban street scene simulation verification example: This embodiment is based on the method for rapid reconstruction of time-varying radiation boundaries for complex outdoor environments described in Embodiment 1 above. Two sets of numerical simulation verifications are carried out using a large-scale urban geometric scene. The traditional complete Monte Carlo path tracing calculation results are used as a reference and compared with the method of this invention.

[0092] For simulation infrastructure in large-scale urban block scenarios: Geometric Model: A complete geometric model of a high-density urban block, with a total of approximately 305,760 triangular facets. It includes complex geometric structures such as multi-story buildings, streets, rooftops, and adjacent facades, and has relatively complex building occlusion relationships and a large computational scale. It is used to verify the adaptability of this method in large-scale engineering scenarios. Geographic and temporal conditions, and traditional complete path tracing parameter settings: Except for setting the texture space resolution to 800 and selecting the time 14:30, the other geographic and temporal conditions and traditional complete path tracing parameter settings in the above small and medium-sized geometric scenes are used. The method of this invention is set up as follows: In the pre-calculation stage, a radiative transfer coefficient table is generated based on geometry, material properties and texture discretization relationship, and the propagation coefficients of sky radiation, solar shortwave radiation and inter-surface longwave radiation are generated at one time; at 14:30, the pre-calculated propagation coefficients are directly reused, and only the time-varying radiation source parameters at the corresponding time are updated to reconstruct the incident irradiance.

[0093] like Figure 10 This diagram illustrates the difference between the incident irradiance reconstruction results obtained using the method of this invention and the traditional complete path tracing calculation results at 14:30 in a large-scale urban block scenario of this embodiment. Figure 10The image is divided into two horizontal rows: the top row is a global view of the scene, with the top left image showing the global irradiance cloud map reconstructed using this invention, and the top right image showing the global difference distribution between the reconstructed result and the true value; the bottom left image is a magnified view of the area within the red box in the top left image, and the bottom right image is a magnified sub-image of the difference, used to show the detailed distribution of the error concentration areas. As can be seen from the visualization, the rapid reconstruction result and the complete path tracing result maintain good consistency in overall spatial distribution. The difference between the two is mainly concentrated at building edges, shadow boundaries, and local geometric details, and its error distribution characteristics are basically consistent with the aforementioned small-to-medium scale scene verification scenario. It should be noted that there are a small number of invisible surfaces or locally overlapping surfaces located inside the city model. These areas may amplify local errors. Since these surfaces are not in the visible area, they were filtered out in the error statistics.

[0094] In terms of computational efficiency: the average computation time for complete path tracing of the city model is approximately 28.34 minutes, while the average total time for fast reconstruction is only approximately 1.78 seconds, corresponding to a speedup of approximately 9.55 × 10². Furthermore, the average relative error in this scenario is only 0.0387%. These results demonstrate that the proposed method not only maintains high reconstruction accuracy in small-to-medium scale scenarios but also significantly reduces the computational cost of time-by-time radiative boundary updates in complex city-level scenarios, showcasing the application potential of texture-level pre-computed radiative propagation coefficients in large-scale complex outdoor scenes.

[0095] Temperature coupling simulation verification example of inter-surface long-wave radiation: In this embodiment, the reconstructed irradiance is used as the input of a one-dimensional transient heat conduction model to simulate and analyze the influence of inter-surface long-wave radiation exchange on the local surface temperature response.

[0096] Simulation settings: The above small-to-medium scale geometric scene is used. Material parameters are standardized for temperature calculations, including: short-wave absorptivity of 0.76, long-wave absorptivity of 0.955, long-wave emissivity of 0.955, thermal conductivity of 0.8 W / (m·K), material thickness of 0.05 m, density of 1400 kg / m³, and specific heat capacity of 705.5 J / (kg·K). In the meteorological boundary conditions, the ambient wind speed is 2.5 m / s, the air pressure is 1013.25 hPa, and the relative humidity is 0.5. The temperature simulation period is from 7:00 to 12:00, with a time step of 5 minutes. The initial temperature of all texture units is set to 290 K. The period from 7:00 to 9:00 is used for preliminary calculations, solely for transient temperature field advancement. The calculation results from 9:00 to 12:00 are used for subsequent analysis. Within each time step, the coupling relationship between the temperature field and the long-wave radiation exchange between surfaces is processed using Picard fixed-point iteration. The maximum number of iterations is set to 4, and the temperature convergence threshold is set to 0.1K.

[0097] like Figure 11 The temperature field and the distribution of long-wave incident irradiance between surfaces are compared with and without considering the long-wave radiation exchange between surfaces at time 10:00. Figure 11 The images are divided into two horizontal rows. The upper left image shows the temperature field considering long-wave radiation exchange between surfaces; the upper right image shows the temperature field without considering long-wave radiation exchange between surfaces. The lower left image shows the temperature difference cloud map under two different conditions; and the lower right image shows the distribution cloud map of long-wave incident irradiance between the scene surfaces. Figure 11 It is evident that after introducing long-wave radiation exchange between surfaces, the temperature change does not occur uniformly throughout the entire geometric model. Instead, it is mainly concentrated near the walls, adjacent sides, and locally shaded areas. These areas have strong geometric proximity, making them more susceptible to receiving long-wave radiation generated by thermal emission from surrounding surfaces. The distribution of long-wave incident irradiance between surfaces further illustrates that higher long-wave incident radiation mainly occurs at wall angles, adjacent surfaces, and locally shaded areas, showing a good spatial correspondence with locations of significant temperature differences. This indicates that the influence of long-wave radiation exchange between surfaces on the temperature response has significant spatial locality, and its location is closely related to the surface relationships within the complex geometry. For open surfaces directly dominated by solar short-wave radiation, the temperature difference caused by long-wave exchange is relatively weak; however, for shaded areas and adjacent surfaces, long-wave radiation exchange has a more significant impact on the local temperature response.

[0098] Furthermore, the statistical impact of inter-surface long-wavelength radiation exchange on the temperature response is as follows: Figure 12 The statistical table is shown in the table. It can be seen that as time progressed from 9:00 to 12:00, the average inter-surface longwave incident irradiance increased from 119.35 W / m² to 128.77 W / m², and the maximum inter-surface longwave incident irradiance increased from 453.83 W / m² to 470.72 W / m². Correspondingly, the average temperature difference between considering and not considering inter-surface longwave radiation exchange increased from 3.78 ℃ to 4.59 ℃, and the maximum temperature difference increased from 14.35 ℃ to 18.44 ℃. These results indicate that as solar radiation increases and surface temperature rises, the influence of inter-surface longwave radiation exchange on the local temperature response also increases.

[0099] Furthermore, regarding computational efficiency: with the help of pre-computed long-wave propagation links, the average update time for inter-surface long-wave incident irradiance is 281.81 ms / step. This result shows that the pre-computed radiation propagation coefficient can update the long-wave radiation exchange term generated by thermal emission from other surfaces during temperature iteration with low computational overhead. Considering the temperature field differences, the distribution of inter-surface long-wave incident irradiance, and the computation time, it can be seen that inter-surface long-wave radiation exchange has a significant impact on the local surface temperature in complex geometries, and the method of this invention can efficiently incorporate this impact into the per-texture element temperature solution process.

[0100] Outdoor infrared thermal imaging measurement benchmark verification example: This embodiment uses the measured temperature of an infrared thermal imager to benchmark the simulation results and verify the applicability of the method of the present invention in the prediction of actual transient surface thermal response.

[0101] In the experimental scenario, two cubic targets were placed adjacent to each other in an outdoor environment. The left target was an aluminum box covered in green paint, and the right target was a concrete box. For ease of comparison and analysis, three representative areas were selected: the top area R1 of the aluminum box, the top area R2 of the concrete box, and the side surface area R3 of the concrete box at the adjacent position of the two boxes.

[0102] Meteorological monitoring equipment was also deployed on-site to collect parameters such as temperature, humidity, and air pressure. The numerical model established the geometric dimensions and relative positions of the two boxes based on the experimental scenario, and set material parameters for aluminum covered with green paint and concrete, respectively. The main material parameters of the two targets are as follows: Figure 13 The experimental target material parameters are shown in the table.

[0103] The comparison between the infrared measured temperature cloud maps at different times under the above experimental scenario and the simulated temperature cloud maps of this invention is shown in the figure below. Figure 14 As shown in the figure, it is divided into three columns: the leftmost column represents 12:00, the middle column represents 13:00, and the rightmost column represents 14:00. The figure reveals that the surface temperature of the green-painted aluminum box on the left is significantly higher than that of the concrete box on the right, while the overall temperature of the concrete box is relatively lower. Simultaneously, due to the obstruction of direct sunlight, a noticeable shadow area and local temperature gradient are formed between the two boxes. Similar spatial distribution characteristics can be observed in the simulation results, including the high-temperature region at the top of the aluminum box, the relatively lower temperature level of the concrete box, and the shadows and temperature transitions near the adjacent areas of the two boxes. Overall, the simulation results show good consistency with the measured infrared temperature field in terms of the high and low temperature distribution, the location of the shadow between the boxes, and the local temperature gradient, indicating that the proposed method can capture the main thermal response distribution in the experimental scenario, which is jointly formed by material differences, direct sunlight, geometric obstruction, and inter-surface radiative exchange.

[0104] like Figure 15The figure shows the measured and simulated temperature curves over time for three representative regions, R1, R2, and R3. The FLIR radiation-corrected infrared measured curve is the actual surface temperature of the enclosure, obtained using a FLIR 615 infrared thermal imager and corrected for radiance, and is used as a reference. The simulation curve considering long-wave radiation exchange is the surface temperature obtained by using the pre-calculated inter-surface long-wave radiation propagation coefficient of this invention, iteratively updating the inter-surface long-wave irradiance at fixed points at each time step, and coupling it with a one-dimensional transient heat conduction model. The simulation curve excluding long-wave radiation exchange is the surface temperature obtained by neglecting the long-wave thermal radiation exchange between the enclosures during the calculation process. As can be seen from the figure, the simulation curves considering and not considering inter-surface long-wave radiation exchange for the upper surface R1 of the aluminum box and the upper surface R2 of the concrete box basically overlap, indicating that these two top regions are almost unaffected by inter-box long-wave radiation exchange under the current geometric relationship. The simulation results generally reproduce the trend of the measured temperature, but there are still some deviations from the measured values. The maximum deviation is 2.66℃ in region R1 and 1.93℃ in region R2. These deviations may be related to factors such as wind speed variations in the actual outdoor environment, simplification of surrounding buildings, and temperature measurement errors of the thermal imager.

[0105] Unlike R1 and R2, R3 is located on the side of the concrete box closest to the green-painted aluminum box. Besides solar and sky radiation, it is also affected by long-wave thermal radiation from the heated surfaces of the adjacent aluminum box. Furthermore, over time, the R3 area is gradually shaded by the aluminum box. If the long-wave radiation exchange between surfaces is ignored, the simulated temperature continuously decreases with increasing shading time, which significantly deviates from the trend of measured infrared temperature changes, with a maximum error of 19.30℃. After introducing the long-wave radiation exchange between surfaces, the contribution of the adjacent heated surfaces to the long-wave radiation in the R3 area is taken into account, and the simulated curve significantly approaches the measured results, with the maximum error reduced to 1.79℃. This indicates that the long-wave radiation exchange between surfaces has a significant impact on the local temperature response of the adjacent shaded area.

[0106] Based on the combined spatial distribution of thermal images and the temperature curves of representative areas, it can be seen that the method proposed in this application can reproduce the main temperature distribution formed by the green-painted aluminum box and the concrete box under the combined effects of solar radiation, material differences, mutual shading, and inter-surface radiation exchange, and can describe the basic trend of representative areas changing over time. Compared with the calculation results that ignore the long-wave radiation exchange between surfaces, considering this factor significantly improves the temperature prediction of the adjacent shading areas of the two boxes. This indicates that pre-calculating the radiation propagation coefficient can not only improve the reconstruction efficiency of time-varying radiation boundary conditions, but also provide a more reasonable radiation boundary input for predicting the local surface thermal response in complex shading scenarios.

[0107] Example 3 This embodiment provides a system for rapid reconstruction of time-varying radiation boundaries in complex outdoor environments. This system corresponds to the method described in Embodiment 1, such as... Figure 16 As shown, the system includes: The pre-calculation module 201 is used to perform path tracing based on the scene after the geometric parameters and surface material parameters of the fixed scene are determined, and to sample and record the radiation propagation coefficient corresponding to the path starting from the receiving texture unit. The radiation propagation coefficient characterizes the radiation propagation relationship in the scene determined by geometric occlusion, surface reflection, and multiple reflections, and is separate from the time-varying radiation source term. The specific implementation of the pre-calculation module is consistent with the content described in the pre-calculation stage of Embodiment 1.

[0108] The reconstruction module 202 is used to acquire the time-varying radiation source parameters at the current moment, and calculate the incident irradiance of the receiving texture unit at the current moment based on the time-varying radiation source parameters and the radiation propagation coefficient, as the radiation input in the thermal boundary condition; the time-varying radiation source parameters include at least the solar direction, the solar normal direct irradiance, the equivalent sky irradiance, and the surface temperature of other texture units in the scene besides the receiving texture unit. The specific implementation of the reconstruction module is consistent with the content described in the reconstruction stage of Embodiment 1.

[0109] The system may also include a temperature solution module 203, which uses the incident irradiance of the received texture unit as the radiation input in the thermal boundary condition, establishes a one-dimensional transient thermal conduction model along the surface thickness direction corresponding to the texture unit, and solves for the surface temperature of each texture unit. The calculation of the inter-surface long-wave incident irradiance depends on the surface temperature of the other texture units. The temperature solution module uses fixed-point iteration in each time step, updates the inter-surface long-wave incident irradiance according to the current surface temperature, and then substitutes it into the one-dimensional transient thermal conduction model for solution until the temperature field converges. The specific implementation of the temperature solution module is consistent with the content described in the "Coupling with Temperature Solution" section of Embodiment 1.

[0110] Example 4 The method for rapid reconstruction of time-varying radiation boundaries in complex outdoor environments provided in this application can be applied to, for example... Figure 17 The application environment shown is illustrated. Terminal 101 communicates with server 102 via a network. A data storage system can store the data that server 102 needs to process. The data storage system can be set up independently, integrated into server 102, or placed in the cloud or on another server.

[0111] During the pre-calculation stage, the terminal 101 can send the fixed geometric parameters and surface material parameters of the scene to the server 102. After receiving the above parameters, the server 102 performs path tracing based on the scene, samples and records the radiation propagation coefficient, and stores the radiation propagation coefficient in the data storage system.

[0112] During the reconstruction phase, terminal 101 can send the time-varying radiation source parameters at the current moment to server 102. After receiving the time-varying radiation source parameters, server 102 retrieves the pre-calculated radiation propagation coefficient from the data storage system, calculates the incident irradiance based on the time-varying radiation source parameters and the radiation propagation coefficient, and uses it as the radiation input in the thermal boundary conditions. Server 102 can then feed back the obtained incident irradiance to terminal 101. Furthermore, server 102 can also use the incident irradiance as a radiation input to solve for temperature, and feed back the solved surface temperature field to terminal 101.

[0113] Furthermore, in some embodiments, the aforementioned pre-calculation and reconstruction stages can also be implemented independently by the server 102 or the terminal 101. For example, the terminal 101 can directly perform path tracing pre-calculation based on scene geometric parameters and material parameters, and quickly reconstruct the incident irradiance for the time-varying radiation source parameters at the time to be processed; alternatively, the server 102 can obtain scene parameters and time-varying radiation source parameters from the data storage system and independently complete the entire calculation process.

[0114] The terminal 101 can be, but is not limited to, various desktop computers, laptops, tablets, portable wearable devices, and industrial control computers. The server 102 can be implemented using a standalone server or a server cluster composed of multiple servers, or it can be a cloud server. When the terminal 101 completes the entire calculation process independently, the terminal 101 can be, but is not limited to, various personal computers, workstations, servers, industrial control computers, and other devices with strong computing capabilities.

[0115] Example 5 This embodiment provides a computer device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the method for rapid reconstruction of time-varying radiation boundaries for complex outdoor environments as described in Embodiment 1.

[0116] The memory stores data such as the radiation propagation coefficients obtained in the pre-calculation stage and the time-varying radiation source parameters required in the reconstruction stage. The processor performs computational tasks such as path tracing sampling, radiation propagation coefficient statistics, incident irradiance reconstruction, and temperature calculation.

[0117] In one exemplary embodiment, a computer-readable storage medium is also provided, storing a computer program that, when executed by a processor, implements the steps in the above-described method embodiments.

[0118] In one exemplary embodiment, a computer program product is also provided, including a computer program that, when executed by a processor, implements the steps in the above-described method embodiments.

[0119] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0120] This document uses specific examples to illustrate the principles and implementation methods of this application. The descriptions of the above embodiments are only for the purpose of helping to understand the methods and core ideas of this application. Furthermore, those skilled in the art will recognize that, based on the ideas of this application, there will be changes in the specific implementation methods and application scope. Therefore, the content of this specification should not be construed as a limitation of this application.

Claims

1. A method for rapid reconstruction of time-varying radiation boundaries in complex outdoor environments, characterized in that, include: Determine the geometric parameters and surface material parameters of the scene; In the pre-computation stage, path tracing is performed based on the scene, and the radiation propagation coefficient corresponding to the path starting from the receiving texture unit is sampled and recorded; wherein, the radiation propagation coefficient characterizes the radiation propagation relationship determined by geometric occlusion, surface reflection and multiple reflections in the fixed scene, and is separated from the radiation source term that changes with time; During the reconstruction phase, the time-varying radiation source parameters at the current moment are obtained. Based on the time-varying radiation source parameters and the radiation propagation coefficient, the incident irradiance of the receiving texture unit at the current moment is calculated as the radiation input in the thermal boundary condition. The time-varying radiation source parameters include the solar direction, solar normal direct irradiance, equivalent sky irradiance, and the surface temperature of other texture units in the scene besides the receiving texture unit.

2. The method for rapid reconstruction of time-varying radiation boundaries for complex outdoor environments according to claim 1, characterized in that, The incident irradiance of the receiving texture unit is composed of the following irradiance terms: Solar direct shortwave incident irradiance, solar indirect shortwave incident irradiance, sky shortwave irradiance, sky longwave irradiance, and inter-surface longwave incident irradiance.

3. The method for rapid reconstruction of time-varying radiation boundaries for complex outdoor environments according to claim 1, characterized in that, The radiation propagation coefficient includes: The sky radiation term propagation coefficient is used to characterize the radiation propagation capability of the receiving texture unit that is directly visible to the sky and escapes to the sky after being reflected from the scene surface. The solar shortwave radiation propagation coefficient is used to characterize the propagation capability of the solar reflected shortwave radiation of the other texture units to the receiving texture unit; The inter-surface long-wave radiation propagation coefficient is used to characterize the long-wave thermal radiation propagation capability of the other texture units to the receiving texture unit.

4. The method for rapid reconstruction of time-varying radiation boundaries in complex outdoor environments according to claim 3, characterized in that, The reconstruction phase involves calculating the incident irradiance of the receiving texture unit based on the time-varying radiation source parameters and the radiation propagation coefficient, including: Based on the propagation coefficient of the sky radiance term and the equivalent sky radiance at the current moment, the short-wave incident irradiance and long-wave incident irradiance of the receiving texture unit are calculated; wherein, the sky radiance coefficient is obtained by weighted merging of multiple importance samples of the sky branch directly connected to the path tracing and the path escape to the sky branch under the assumption of uniform sky.

5. The method for rapid reconstruction of time-varying radiation boundaries for complex outdoor environments according to claim 3, characterized in that, The reconstruction phase involves calculating the incident irradiance of the receiving texture unit based on the time-varying radiation source parameters and the radiation propagation coefficient, including: The solar indirect shortwave incident irradiance of the receiving texture unit is calculated based on the propagation coefficient of the solar shortwave radiation term, the shortwave reflectivity of the other texture units, the solar direction at the current moment, and the solar normal direct irradiance.

6. The method for rapid reconstruction of time-varying radiation boundaries for complex outdoor environments according to claim 3, characterized in that, The reconstruction phase involves calculating the incident irradiance of the receiving texture unit based on the time-varying radiation source parameters and the radiation propagation coefficient, including: The inter-surface long-wave radiation propagation coefficient, the long-wave emissivity of the other texture units, and the surface temperature of the other texture units at the current moment are used to calculate the inter-surface long-wave incident irradiance of the receiving texture unit.

7. The method for rapid reconstruction of time-varying radiation boundaries in complex outdoor environments according to claim 2, characterized in that, During the reconstruction phase, the solar direct shortwave incident irradiance is obtained through the following method: Uniform sampling is performed within the area corresponding to the receiving texture unit, and the number of sampling points is gradually increased in stages. At each stage, the estimated value of the solar direction incident cosine-visibility joint factor of the receiving texture unit is updated. The solar direct shortwave irradiance is calculated based on the estimated value of the solar direction incident cosine-visibility joint factor and the solar normal direct irradiance at the current moment. Specifically, when the estimated value change between adjacent stages is less than a preset threshold, the sampling of the receiving texture unit is stopped; otherwise, the number of sampling points continues to increase.

8. The method for rapid reconstruction of time-varying radiation boundaries in complex outdoor environments according to claim 2, characterized in that, Also includes: Using the incident irradiance of the receiving texture unit as the radiation input in the thermal boundary condition, a one-dimensional transient thermal conduction model is established along the surface thickness direction of the texture unit to solve the surface temperature of each texture unit. The calculation of the inter-surface long-wave irradiance depends on the surface temperature of the other texture units. Fixed-point iteration is used in each time step to update the inter-surface long-wave irradiance according to the current surface temperature, and then it is substituted into the thermal conductivity model to solve until the temperature field converges.

9. A system for rapid reconstruction of time-varying radiation boundaries in complex outdoor environments, characterized in that, include: The pre-calculation module is used to perform path tracing based on the scene after the geometric parameters and surface material parameters of the fixed scene are determined, and to sample and record the radiation propagation coefficient corresponding to the path starting from the receiving texture unit; wherein, the radiation propagation coefficient characterizes the radiation propagation relationship in the scene determined by geometric occlusion, surface reflection and multiple reflections, and is separated from the radiation source term that changes with time. The reconstruction module is used to obtain the time-varying radiation source parameters at the current moment, and calculate the incident irradiance of the receiving texture unit at the current moment based on the time-varying radiation source parameters and the radiation propagation coefficient, as the radiation input in the thermal boundary condition; the time-varying radiation source parameters include at least the solar direction, the solar normal direct irradiance, the equivalent sky irradiance, and the surface temperature of other texture units in the scene other than the receiving texture unit.

10. A computer device, comprising: A memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that the processor executes the computer program to implement the method for rapid reconstruction of time-varying radiation boundaries for complex outdoor environments as described in any one of claims 1-8.

Images