Urban domain large-scale computational fluid mechanics analysis simplified modeling method and device

Abstract

The invention discloses an urban domain large-scale computational fluid mechanics analysis simplified modeling method and device, and belongs to the technical field of civil engineering computational fluid mechanics, and the method comprises the steps: obtaining geographic information system data of a target urban domain; dividing the target city area into a building area and a non-building area; for the building area, classifying the building area into a building dense area and a non-building dense area according to the building coverage rate; for the building dense area, modeling all buildings in the building dense area into a three-dimensional geometric model as a three-dimensional geometric model of the corresponding area; for a non-building dense area, constructing a three-dimensional geometric model of each building in the non-building dense area, and taking a combination of the three-dimensional geometric models of the buildings as a three-dimensional geometric model of a corresponding area; and carrying out assembling and attribute endowing on each three-dimensional geometric model to finish modeling of the computational fluid mechanics analysis model. According to the method, computational fluid mechanics efficient modeling can be carried out on a large-scale urban domain.

Description

Technical Field

[0001] The invention relates to the technical field of computational fluid dynamics in civil engineering, and in particular to a simplified modeling method and device for large-scale computational fluid dynamics analysis in urban areas. Background Art

[0002] As global climate change intensifies, cities are facing a variety of climate problems. It is crucial to apply computational fluid dynamics to study a series of issues in cities, such as ventilation design, pedestrian comfort, and urban heat island effect.

[0003] Computational fluid dynamics simulations of urban areas usually rely on the finite volume method to discretize and solve the NS equations, the governing equations of motion of air and fluid. For large-scale urban areas (for example, an area of ​​more than 100 square kilometers), computational fluid dynamics analysis and modeling need to process the geometric features of each building in the area, which is extremely labor-intensive, requires extremely high computing resources, and takes a long time to calculate. Therefore, due to the limitations of hardware conditions, the current computational fluid dynamics analysis and modeling methods are applicable to smaller urban areas, generally limited to 50 square kilometers. However, real urban areas generally exceed 50 square kilometers, which makes it difficult to perform computational fluid dynamics analysis and modeling on complete real urban areas. Existing analysis examples can generally only model and analyze local areas of the city. This limits the application potential of computational fluid dynamics simulation technology in large cities or regions, making it difficult to provide practical support for the research of important issues such as ventilation design, pedestrian comfort, and heat island effect in large cities or large-scale areas.

[0004] In this context, if a simplified modeling method for computational fluid dynamics analysis suitable for large-scale urban domains (for example, an area of ​​more than 200 square kilometers) is established, it can provide a basic tool for computational fluid dynamics simulation of complete and real urban areas, and significantly unleash the potential of computational fluid dynamics technology in many related applications such as urban management.

[0005] Currently, there is a lack of a simplified modeling method for large-scale computational fluid dynamics analysis in urban areas in the existing technology. Summary of the invention

[0006] The present invention provides a simplified modeling method and device for large-scale computational fluid dynamics analysis in urban areas, so as to solve the technical problems that the existing urban area computational fluid dynamics analysis modeling methods are applicable to a small scale and are difficult to model the entire city.

[0007] In order to solve the above technical problems, the present invention provides the following technical solutions:

[0008] On the one hand, the present invention provides a simplified modeling method for large-scale computational fluid dynamics analysis in urban areas, the simplified modeling method for large-scale computational fluid dynamics analysis in urban areas comprising:

[0009] Obtain geographic information system data of the target city area;

[0010] Based on the acquired GIS data, the target city domain is divided into functional areas, and the target city domain is divided into multiple building areas and multiple non-building areas;

[0011] For built-up areas, they are classified into built-up dense areas and non-built-up dense areas according to their building coverage ratio;

[0012] For the built-up area, all the buildings therein are modeled as a three-dimensional geometric model as the three-dimensional geometric model of the corresponding built-up area; for the non-built-up area, a three-dimensional geometric model of each building therein is constructed, and the combination of the three-dimensional geometric models of each building is used as the three-dimensional geometric model of the corresponding non-built-up area;

[0013] The three-dimensional geometric models of each densely built area and the three-dimensional geometric models of each non-densely built area are assembled and assigned attributes, and finally the computational fluid dynamics analysis model of the target urban area is completed.

[0014] Furthermore, the geographic information system data includes: bottom surface contour data of each building in the target urban area, building height data of each building, and main road network distribution data.

[0015] Furthermore, the target city domain is divided into multiple building areas and multiple non-building areas based on the acquired geographic information system data, including:

[0016] According to the main road network distribution data in the target urban area, the main roads in the target urban area are used to divide the target urban area into functional areas, and the target urban area is divided into multiple building areas and multiple non-building areas.

[0017] Furthermore, the building area is classified into a building-intensive area and a non-building-intensive area according to its building coverage rate, including:

[0018] For the building area, calculate its building coverage rate; the calculation formula of the building coverage rate is:

[0019]

[0020] Among them, BD represents the building coverage ratio; BP i represents the bottom surface area of ​​the i-th building in the building area to be calculated for building coverage; I represents the number of buildings in the building area to be calculated for building coverage; BA represents the total area of ​​the building area to be calculated for building coverage;

[0021] When the building coverage ratio of a built-up area is not less than 0.1, it is classified as a densely built-up area; when the building coverage ratio of a built-up area is less than 0.1, it is classified as a non-densely built-up area.

[0022] Furthermore, for the building-dense area, all the buildings in the area are modeled as a three-dimensional geometric model as the three-dimensional geometric model of the corresponding building-dense area, including:

[0023] Counting the building height data of each building in the building-dense area, and calculating the characteristic height of the building-dense area based on the building height data of each building;

[0024] The outline boundary of the building-dense area is used as the bottom polygon, and the bottom polygon is stretched upward along the height direction to the characteristic height of the building-dense area to form a three-dimensional geometric model of the corresponding building-dense area.

[0025] Furthermore, the characteristic height of the building-dense area is calculated based on the building height data of each building, including:

[0026] The normal distribution function is used to fit the building height data of each building in the densely built area. The mean value of the normal distribution fitting function is μ, and the standard deviation is σ;

[0027] The data of building height less than (μ-σ) or greater than (μ+σ) in the building density area are eliminated to obtain a new set of data. The average value of this new set of data is calculated as the characteristic height of the corresponding building density area.

[0028] Furthermore, the three-dimensional geometric models of each densely built area and the three-dimensional geometric models of each non-densely built area are assembled and attributed, and finally the computational fluid dynamics analysis model of the target urban area is completed, including:

[0029] The three-dimensional geometric model of each building-dense area is treated as a porous medium to obtain a processed three-dimensional geometric model; wherein, when the three-dimensional geometric model of each building-dense area is treated as a porous medium, the porosity of each three-dimensional geometric model is determined according to the following formula:

[0030]

[0031] Where BP represents the porosity of the three-dimensional geometric model; BP i represents the bottom surface area of ​​the i-th building in the region where the porosity of the three-dimensional geometric model is to be calculated; N represents the number of buildings in the region where the porosity of the three-dimensional geometric model is to be calculated; h i The equivalent height of the i-th building in the region where the porosity of the 3D geometric model is to be calculated, H r The characteristic height of the region representing the porosity of the three-dimensional geometric model to be calculated isi <H r The building, h i Take the real height of this building, for h i ≥H r Building, set h i =H r ; BA represents the total area of ​​the region where the porosity of the three-dimensional geometric model is to be calculated.

[0032] Assemble the processed 3D geometric models corresponding to each densely built area and the 3D geometric models of each non-densely built area according to their geographical locations to form a simplified 3D geometric model of the target urban area;

[0033] Based on the simplified three-dimensional geometric model of the target urban area, a computational fluid dynamics analysis domain is established, and grid division and boundary condition setting are performed to establish a computational fluid dynamics analysis model of the target urban area.

[0034] On the other hand, the present invention also provides a simplified modeling device for large-scale computational fluid dynamics analysis in urban areas, the simplified modeling device for large-scale computational fluid dynamics analysis in urban areas comprising:

[0035] A data acquisition module is used to acquire geographic information system data of the target city area;

[0036] A functional area division module is used to divide the target city domain into multiple building areas and multiple non-building areas based on the acquired geographic information system data;

[0037] The target city domain 3D geometry module builds modules for:

[0038] For built-up areas, they are classified into built-up dense areas and non-built-up dense areas according to their building coverage ratio;

[0039] For the built-up area, all the buildings therein are modeled as a three-dimensional geometric model as the three-dimensional geometric model of the corresponding built-up area; for the non-built-up area, a three-dimensional geometric model of each building therein is constructed, and the combination of the three-dimensional geometric models of each building is used as the three-dimensional geometric model of the corresponding non-built-up area;

[0040] The computational fluid dynamics analysis model building module is used to assemble and assign attributes to the three-dimensional geometric models of each densely built area and the three-dimensional geometric models of each non-densely built area constructed by the three-dimensional geometric module construction module of the target urban area, and finally complete the modeling of the computational fluid dynamics analysis model of the target urban area.

[0041] On the other hand, the present invention further provides an electronic device, comprising a processor and a memory; wherein the memory stores at least one instruction, and the instruction is loaded and executed by the processor to implement the above method.

[0042] In yet another aspect, the present invention further provides a computer-readable storage medium, wherein at least one instruction is stored in the storage medium, and the instruction is loaded and executed by a processor to implement the above method.

[0043] The beneficial effects brought about by the technical solution provided by the present invention include at least:

[0044] The technical solution of the present invention merges and simplifies the buildings within the street grid, thereby solving the problem of computational fluid dynamics analysis and modeling in large-scale urban areas, and helping to achieve large-scale wind field simulation and analysis in the entire city, thereby providing technical support for related applications such as smart cities and resilient cities. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0046] Figure 1 It is a schematic diagram of the execution flow of a simplified modeling method for large-scale computational fluid dynamics analysis in an urban area provided by an embodiment of the present invention;

[0047] Figure 2 This is a schematic diagram of geographic information system data of a real large-scale urban area provided by an embodiment of the present invention;

[0048] Figure 3 It is a schematic diagram of the height distribution of all buildings in a functional area with a building coverage rate exceeding 0.1 in a real large-scale urban area provided by an embodiment of the present invention;

[0049] Figure 4 It is a system block diagram of an electronic device provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0050] In order to make the objectives, technical solutions and advantages of the present invention more clear, the embodiments of the present invention will be further described in detail below with reference to the accompanying drawings.

[0051] First of all, it should be noted that in the embodiments of the present invention, words such as "exemplarily" and "for example" are used to indicate examples, illustrations or explanations. Any embodiment or design described as "exemplary" in the present invention should not be interpreted as being more preferred or more advantageous than other embodiments or designs. Specifically, the use of the word "exemplarily" is intended to present the concept in a concrete way. In addition, in the embodiments of the present invention, the meaning expressed by "and / or" can be both, or it can be either of the two.

[0052] First embodiment

[0053] In order to solve the technical problem that the current urban domain computational fluid dynamics analysis modeling methods are applicable to a small scale and are difficult to model the entire city, this embodiment provides a simplified modeling method for large-scale computational fluid dynamics analysis in an urban domain. The method can be implemented by an electronic device, which can be a terminal or a server.

[0054] The execution flow of this method is as follows Figure 1 As shown, the following steps are included:

[0055] S1, obtain the GIS data of the target city area;

[0056] It should be noted that the GIS data acquired in this embodiment includes building bottom contour data, building height data, and trunk road network distribution data of the target city area. The means of acquiring GIS data include acquiring from public maps, from government websites, from remote sensing image data, etc. Among them, the building bottom contour data refers to the shape data of the building bottom polygon.

[0057] In this embodiment, a district of a city is taken as the target city domain. The corresponding geographic information system data is as follows: Figure 2 The area covers more than 400 square kilometers and contains more than 20,000 buildings.

[0058] S2, based on the acquired GIS data, functionally divide the target urban area into multiple built-up areas and multiple non-built-up areas;

[0059] Specifically, in this embodiment, the method of dividing the target urban area into functional areas is: based on the main road network distribution data, the target urban area is divided into several functional areas according to the main roads, and the functional areas include building areas and non-building areas; wherein, the building area refers to the area within the city dominated by buildings, and the non-building area refers to other areas within the city dominated by parks and trees.

[0060] S3, for built-up areas, classifies them into built-up dense areas and non-built-up dense areas according to their building coverage ratio;

[0061] Specifically, in this embodiment, the implementation process of the above S3 is as follows:

[0062] S31, for the building area, draw the outline boundary of the area with the outermost building of the area as the boundary, extract the bottom surface polygon data of all buildings in the area, and calculate the building coverage rate of the area. The formula is:

[0063]

[0064] Among them, BD represents the building coverage ratio; BP i represents the area of ​​the bottom polygon of the i-th building in the building area to be calculated for building coverage; I represents the number of buildings in the building area to be calculated for building coverage; BA represents the area of ​​the outline boundary of the building area to be calculated for building coverage;

[0065] S32, classify the building area according to the building coverage rate; if the building coverage rate of the building area is not less than 0.1, classify it as a densely built area, and record the area as A BN If the building coverage rate of the built-up area is less than 0.1, it is classified as a non-densely built-up area and the area is recorded as A BS .

[0066] S4, for the building-dense area, all the buildings therein are modeled as a three-dimensional geometric model as the three-dimensional geometric model of the corresponding building-dense area; for the non-building-dense area, a three-dimensional geometric model of each building therein is constructed, and the combination of the three-dimensional geometric models of each building is used as the three-dimensional geometric model of the corresponding non-building-dense area;

[0067] Specifically, in this embodiment, the implementation process of the above S4 is as follows:

[0068] S41, for the building-dense area, the building height data of each building in the building-dense area is counted, and the characteristic height of the building-dense area is calculated based on the building height data of each building. The calculation process is as follows:

[0069] The height data of all buildings in the functional area are taken as a set of data, and the normal distribution function is used to fit this set of data. The mean value of the normal distribution fitting function is μ, and the standard deviation is σ. The data less than (μ-σ) and greater than (μ+σ) in this set of data are eliminated to obtain a new set of data. The average value of this new set of data is calculated, and the calculated average value of this new set of data is used as the characteristic height of the functional area.

[0070] Figure 3The height distribution diagram of all buildings in a functional area with a building coverage rate exceeding 0.1 in the target city area provided by this embodiment is shown. There are 619 buildings in this area, and the average value of the normal distribution fitting function of the building height is 14.8m and the standard deviation is 12.7m. The characteristic height of this area is 11.9m.

[0071] S42, using the outline boundary of the densely built-up area as a bottom polygon, stretching the bottom polygon upward along the height direction to a characteristic height of the densely built-up area, to form a three-dimensional geometric model of the corresponding densely built-up area;

[0072] S43, for non-building dense areas, the bottom polygon of each building in the functional area is stretched upward along the height direction to the building height to form a three-dimensional geometric model of each building. The three-dimensional geometric model of each discrete building in the functional area constitutes the three-dimensional geometric model of the functional area.

[0073] For functional areas divided into non-building areas, there is no need to establish their three-dimensional geometric models.

[0074] S5, assembling and assigning attributes to the three-dimensional geometric models of each densely built area and the three-dimensional geometric models of each non-densely built area, and finally completing the modeling of the computational fluid dynamics analysis model of the target urban area;

[0075] Specifically, in this embodiment, the implementation process of the above S5 is as follows:

[0076] S51, treating the three-dimensional geometric model of each densely built area as a porous medium to obtain a processed three-dimensional geometric model; wherein, when treating the three-dimensional geometric model of each densely built area as a porous medium, the porosity of each three-dimensional geometric model is determined according to the following formula:

[0077]

[0078] Where BP represents the porosity of the three-dimensional geometric model of the porous medium in the functional area; BP i represents the area of ​​the bottom polygon of the i-th building in the functional area; N represents the number of buildings in the functional area; h i represents the equivalent height of the i-th building in the functional area, H r Represents the characteristic height of the functional area, where h i <H r The building corresponding to h i Take the real height of the building, for h i ≥H r If the building is i =H r ; BA represents the area of ​​the contour boundary of the functional area.

[0079] In addition, it should be noted that the above processing is mainly to show that the densely built area is not a simple prism after being simplified and modeled, and the interior of the prism is also ventilated (in actual conditions, wind can also pass through the gaps between buildings in the densely built area). BS In areas that are not densely built-up areas, each building is directly treated as a solid entity and does not need to be treated as a porous medium.

[0080] S52, assembling the processed three-dimensional geometric models corresponding to each densely built area and the three-dimensional geometric models of each non-densely built area according to their geographical locations to form a simplified three-dimensional geometric model of the target urban area;

[0081] S53, based on the simplified three-dimensional geometric model of the target urban domain, a computational fluid dynamics analysis domain is established, and meshing and boundary condition setting are performed to establish a computational fluid dynamics analysis model of the target urban domain.

[0082] In summary, this embodiment provides a simplified modeling method for large-scale computational fluid dynamics analysis in urban areas. This method merges and simplifies the buildings within the street grid, thereby solving the problem of large-scale computational fluid dynamics analysis and modeling in urban areas, and helps to realize large-scale wind field simulation and analysis in the entire city, thereby providing technical support for related applications such as smart cities and resilient cities.

[0083] Second embodiment

[0084] This embodiment provides a simplified modeling device for large-scale computational fluid dynamics analysis in an urban area, and the simplified modeling device for large-scale computational fluid dynamics analysis in an urban area includes the following modules:

[0085] A data acquisition module is used to acquire geographic information system data of the target city area;

[0086] A functional area division module is used to divide the target city domain into multiple building areas and multiple non-building areas based on the acquired geographic information system data;

[0087] The target city domain 3D geometry module builds modules for:

[0088] For built-up areas, they are classified into built-up dense areas and non-built-up dense areas according to their building coverage ratio;

[0089] For the built-up area, all the buildings therein are modeled as a three-dimensional geometric model as the three-dimensional geometric model of the corresponding built-up area; for the non-built-up area, a three-dimensional geometric model of each building therein is constructed, and the combination of the three-dimensional geometric models of each building is used as the three-dimensional geometric model of the corresponding non-built-up area;

[0090] The computational fluid dynamics analysis model building module is used to assemble and assign attributes to the three-dimensional geometric models of each densely built area and the three-dimensional geometric models of each non-densely built area constructed by the three-dimensional geometric module construction module of the target urban area, and finally complete the modeling of the computational fluid dynamics analysis model of the target urban area.

[0091] It should be noted that the simplified modeling device for large-scale computational fluid dynamics analysis in urban areas of this embodiment corresponds to the simplified modeling method for large-scale computational fluid dynamics analysis in urban areas of the first embodiment mentioned above; the functions implemented by each functional module in the simplified modeling device for large-scale computational fluid dynamics analysis in urban areas of this embodiment correspond one-to-one to each process step in the simplified modeling method for large-scale computational fluid dynamics analysis in urban areas of the first embodiment mentioned above; therefore, they will not be repeated here.

[0092] Third embodiment

[0093] This embodiment provides an electronic device, such as Figure 4 As shown, the electronic device includes: a processor and a memory; wherein the processor and the memory can be connected via a communication bus; the memory stores at least one instruction, and the instruction is loaded and executed by the processor to implement the method of the first embodiment. In addition, the electronic device may also include a transceiver, the processor and the transceiver can be connected via a communication bus, and the transceiver is used to communicate with other devices.

[0094] Next, combine Figure 4 The following is a detailed introduction to the various components of the electronic device:

[0095] Among them, the processor is the control center of the electronic device, and the electronic device may include multiple processors, each of which may be a single-core processor (single-CPU) or a multi-core processor (multi-CPU). The processor here may be a processor or a general term for multiple processing elements. For example, the processor is one or more central processing units (CPUs), or other general-purpose processors, application specific integrated circuits (ASICs), or one or more integrated circuits configured to implement an embodiment of the present invention, such as one or more microprocessors (digital signal processors, DSPs), or one or more field programmable gate arrays (field programmable gate arrays, FPGAs), or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or any conventional processor, etc. The processor may execute various functions of the electronic device by running or executing software programs stored in the memory and calling data stored in the memory.

[0096] In a specific implementation, as an embodiment, the processor may include one or more CPUs, such as Figure 4 The CPU0 and CPU1 shown in the figure are, of course, only exemplary.

[0097] The memory is used to store the software program for executing the solution of the present invention, and the execution is controlled by the processor. The specific implementation method can refer to the above method embodiment and will not be repeated here.

[0098] Optionally, the memory may be a read-only memory (ROM) or other types of static storage devices that can store static information and instructions, a random access memory (RAM) or other types of dynamic storage devices that can store information and instructions, or an electrically erasable programmable read-only memory (EEPROM), a compact disc read-only memory (CD-ROM) or other optical disc storage, optical disc storage (including compressed optical discs, laser discs, optical discs, digital versatile discs, Blu-ray discs, etc.), a magnetic disk storage medium or other magnetic storage device, or any other medium that can be used to carry or store the desired program code in the form of instructions or data structures and can be accessed by a computer, but is not limited thereto. The memory may be integrated with the processor or exist independently and accessed through the interface circuit ( Figure 4 (not shown) is coupled to the processor, which is not specifically limited in this embodiment of the present invention.

[0099] The transceiver may include a receiver and a transmitter ( Figure 4 The receiver is used to implement the receiving function, and the transmitter is used to implement the sending function. The transceiver can be integrated with the processor or exist independently and communicate with the electronic device through the interface circuit ( Figure 4 (not shown) is coupled to the processor, which is not specifically limited in this embodiment of the present invention.

[0100] In addition, it should be noted that Figure 4 The structure of the electronic device shown in the figure does not constitute a limitation on the device, and the actual device may include more or fewer components than shown in the figure, or combine certain components, or arrange the components differently. In addition, the technical effects achieved by the electronic device when executing the method of the first embodiment above can refer to the technical effects described in the first embodiment above, so they are not repeated here.

[0101] Fourth embodiment

[0102] This embodiment provides a computer-readable storage medium, which stores at least one instruction, and the instruction is loaded and executed by a processor to implement the method of the first embodiment. The computer-readable storage medium may be a ROM, a random access memory, a CD-ROM, a magnetic tape, a floppy disk, an optical data storage device, etc. The instructions stored therein may be loaded by a processor in a terminal to execute the method.

[0103] In addition, it should be noted that the present invention can be provided as a method, an apparatus or a computer program product. Therefore, the embodiment of the present invention can be in the form of a full or partial hardware embodiment, a full or partial software embodiment or an embodiment combining software and hardware. Moreover, when implemented using software, the embodiment of the present invention can be in the form of a computer program product implemented on one or more computer-usable storage media containing computer-usable program codes. The computer program product includes one or more computer instructions or computer programs. When the computer instructions or computer programs are loaded or executed on a computer, the process or function described in the embodiment of the present invention is generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable devices. The computer instructions can be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another computer-readable storage medium, for example, the computer instructions can be transmitted from one website site, computer, server or data center to another website site, computer, server or data center by wired (e.g., infrared, wireless, microwave, etc.). The computer-readable storage medium can be any available medium that can be accessed by a computer or a data storage device such as a server or data center containing one or more available media sets. The available medium may be a magnetic medium (eg, a floppy disk, a hard disk, a magnetic tape), an optical medium (eg, a DVD), or a semiconductor medium. The semiconductor medium may be a solid state hard disk.

[0104] The embodiments of the present invention are described with reference to the flowcharts and / or block diagrams of the methods, terminal devices (systems), and computer program products according to the embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of the processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, an embedded processor, or other programmable data processing terminal device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing terminal device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0105] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing terminal device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce a manufactured product including an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1These computer program instructions can also be loaded onto a computer or other programmable data processing terminal device, so that a series of operation steps are executed on the computer or other programmable terminal device to produce a computer-implemented process, so that the instructions executed on the computer or other programmable terminal device provide for implementing the process in the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0106] It should also be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. The terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that the process, method, article or terminal device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or terminal device. In the absence of more restrictions, the elements defined by the sentence "including one..." do not exclude the existence of other identical elements in the process, method, article or terminal device including the elements. In addition, the term "and / or" is only an association relationship describing the associated objects, indicating that there can be three relationships, for example, A and / or B, which can represent: A exists alone, A and B exist at the same time, and B exists alone, wherein A and B can be singular or plural. In addition, the character " / " in this article generally indicates that the objects before and after are in an "or" relationship, but it may also indicate an "and / or" relationship. Please refer to the context for specific understanding. "At least one" means one or more, and "plurality" means two or more. "At least one of the following" or similar expressions refers to any combination of these items, including any combination of single or plural items. For example, at least one of a, b or c can be represented by: a, b, c, ab, ac, bc or abc, where a, b, c can be single or plural.

[0107] In addition, it can be understood that in various embodiments of the present invention, the size of the serial numbers of the above-mentioned processes does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present invention.

[0108] Those skilled in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of the present invention.

[0109] In several embodiments provided by the present invention, it should be understood that the disclosed equipment, devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic, for example, the division of functional modules / units is only a logical function division, and there may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another device, or some features can be ignored or not executed. Another point, the coupling or direct coupling or communication connection between each other shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms. The unit described as a separate component may or may not be physically separated, and the component displayed as a unit may or may not be a physical unit, that is, it may be located in one place, or it may be distributed on multiple network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the scheme of this embodiment. In addition, each functional unit in each embodiment of the present invention can be integrated in a processing unit, or each unit can exist physically alone, or two or more units can be integrated in one unit.

[0110] If the method is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. 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, which is stored in a storage medium and includes several instructions for a computer device (which can be a personal computer, a server, or a 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.

[0111] Finally, it should be noted that the above is only a preferred embodiment of the present invention. It should be pointed out that although the preferred embodiment of the present invention has been described, for ordinary technicians in this technical field, once the basic creative concept of the present invention is known, several improvements and modifications can be made without departing from the principles of the present invention. These improvements and modifications should also be regarded as the protection scope of the present invention. Therefore, the attached claims are intended to be interpreted as including the preferred embodiment and all changes and modifications that fall within the scope of the embodiments of the present invention.

Claims

1. A simplified modeling method for large-scale computational fluid dynamics analysis in urban areas, characterized in that: include: Obtain geographic information system data of the target city area; Based on the acquired GIS data, the target city domain is divided into functional areas, and the target city domain is divided into multiple building areas and multiple non-building areas; For built-up areas, they are classified into built-up dense areas and non-built-up dense areas according to their building coverage ratio; For the built-up area, all the buildings therein are modeled as a three-dimensional geometric model as the three-dimensional geometric model of the corresponding built-up area; for the non-built-up area, a three-dimensional geometric model of each building therein is constructed, and the combination of the three-dimensional geometric models of each building is used as the three-dimensional geometric model of the corresponding non-built-up area; The three-dimensional geometric models of each densely built area and the three-dimensional geometric models of each non-densely built area are assembled and assigned attributes, and finally the computational fluid dynamics analysis model of the target urban area is completed.

2. The simplified modeling method for large-scale computational fluid dynamics analysis in urban areas according to claim 1, characterized in that: The geographic information system data includes: bottom surface contour data of each building in the target urban area, building height data of each building, and main road network distribution data.

3. The simplified modeling method for large-scale computational fluid dynamics analysis in urban areas according to claim 2, characterized in that: Based on the acquired geographic information system data, the target city domain is divided into functional areas, and the target city domain is divided into multiple building areas and multiple non-building areas, including: According to the main road network distribution data in the target urban area, the main roads in the target urban area are used to divide the target urban area into functional areas, and the target urban area is divided into multiple building areas and multiple non-building areas.

4. The simplified modeling method for large-scale computational fluid dynamics analysis in urban areas according to claim 1, characterized in that: The building area is classified into built-up areas and non-built-up areas according to its building coverage rate, including: For the building area, calculate its building coverage rate; the calculation formula of the building coverage rate is: Among them, BD represents the building coverage ratio; BP i represents the bottom surface area of ​​the i-th building in the building area to be calculated for building coverage; I represents the number of buildings in the building area to be calculated for building coverage; BA represents the total area of ​​the building area to be calculated for building coverage; When the building coverage ratio of a built-up area is not less than 0.1, it is classified as a densely built-up area; when the building coverage ratio of a built-up area is less than 0.1, it is classified as a non-densely built-up area.

5. The simplified modeling method for large-scale computational fluid dynamics analysis in urban areas according to claim 1, characterized in that: For the building-dense area, all the buildings in the area are modeled as a three-dimensional geometric model as the three-dimensional geometric model of the corresponding building-dense area, including: Counting the building height data of each building in the building-dense area, and calculating the characteristic height of the building-dense area based on the building height data of each building; The outline boundary of the building-dense area is used as the bottom polygon, and the bottom polygon is stretched upward along the height direction to the characteristic height of the building-dense area to form a three-dimensional geometric model of the corresponding building-dense area.

6. The simplified modeling method for large-scale computational fluid dynamics analysis in urban areas according to claim 5, characterized in that: The characteristic height of the building-dense area is calculated based on the building height data of each building, including: The normal distribution function is used to fit the building height data of each building in the densely built area. The mean value of the normal distribution fitting function is μ, and the standard deviation is σ; The data of building height less than (μ-σ) or greater than (μ+σ) in the building density area are eliminated to obtain a new set of data. The average value of this new set of data is calculated as the characteristic height of the corresponding building density area.

7. The simplified modeling method for large-scale computational fluid dynamics analysis in urban areas according to claim 1, characterized in that: The three-dimensional geometric models of each densely built area and the three-dimensional geometric models of each non-densely built area are assembled and attributed, and finally the computational fluid dynamics analysis model of the target urban area is completed, including: The three-dimensional geometric model of each building-dense area is treated as a porous medium to obtain a processed three-dimensional geometric model; wherein, when the three-dimensional geometric model of each building-dense area is treated as a porous medium, the porosity of each three-dimensional geometric model is determined according to the following formula: Where BP represents the porosity of the three-dimensional geometric model; BP i represents the bottom surface area of ​​the i-th building in the region where the porosity of the three-dimensional geometric model is to be calculated; N represents the number of buildings in the region where the porosity of the three-dimensional geometric model is to be calculated; h i The equivalent height of the i-th building in the region where the porosity of the 3D geometric model is to be calculated, H r The characteristic height of the region representing the porosity of the three-dimensional geometric model to be calculated is i <H r The building, h i Take the real height of this building, for h i ≥H r Building, set h i =H r BA represents the total area of ​​the region where the porosity of the three-dimensional geometric model is to be calculated; Assemble the processed 3D geometric models corresponding to each densely built area and the 3D geometric models of each non-densely built area according to their geographical locations to form a simplified 3D geometric model of the target urban area; Based on the simplified three-dimensional geometric model of the target urban area, a computational fluid dynamics analysis domain is established, and grid division and boundary condition setting are performed to establish a computational fluid dynamics analysis model of the target urban area.

8. A simplified modeling device for large-scale computational fluid dynamics analysis in urban areas, characterized in that: include: A data acquisition module is used to acquire geographic information system data of the target city area; A functional area division module is used to divide the target city domain into multiple building areas and multiple non-building areas based on the acquired geographic information system data; The target city domain 3D geometry module builds modules for: For built-up areas, they are classified into built-up dense areas and non-built-up dense areas according to their building coverage ratio; For the built-up area, all the buildings therein are modeled as a three-dimensional geometric model as the three-dimensional geometric model of the corresponding built-up area; for the non-built-up area, a three-dimensional geometric model of each building therein is constructed, and the combination of the three-dimensional geometric models of each building is used as the three-dimensional geometric model of the corresponding non-built-up area; The computational fluid dynamics analysis model building module is used to assemble and assign attributes to the three-dimensional geometric models of each densely built area and the three-dimensional geometric models of each non-densely built area constructed by the three-dimensional geometric module construction module of the target urban area, and finally complete the modeling of the computational fluid dynamics analysis model of the target urban area.

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