CN116070414B - Wind resource simulation method and device based on surface relief complexity - Google Patents
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Abstract
The application disclosesWind resource simulation method and device based on surface relief complexity, wherein the method comprises the following steps: firstly dividing a calculation domain into M multiplied by N subfields, wherein the subfields are regular polygons, and secondly, acquiring elevation data h of each subfield k And according to the elevation data h k Calculating the standard deviation S of the elevation corresponding to each sub-domain ij Secondly, according to the elevation standard deviation S corresponding to each sub-domain ij Calculating the average value of the standard deviation of the elevation of all subdomains in the calculation domainThen judging the elevation standard deviation S corresponding to each sub-domain ij Whether or not it is greater than the standard deviation average value of elevationIf a subdomainSelecting LES model to make simulation on the subdomain wind resource, if a subdomain isThen the RANS model is selected to perform simulation on the subdomain wind resources. The device comprises a segmentation module, an acquisition module, a calculation module, a judgment module and a simulation module. According to the surface morphology and the complexity, LES and RANS models are respectively selected, so that the calculation accuracy of the terrain wind field is improved, and the calculation resources are saved.
Description
Technical Field
The application belongs to the field of wind resource evaluation in wind engineering, and particularly relates to a wind resource simulation method and device based on surface relief complexity.
Background
In recent years, computational fluid dynamics (Computational Fluid Dynamics, CFD) is gaining increasing attention in the field of computational wind engineering, especially in the field of complex terrain wind resource assessment. The creation of terrain computing grid models using raster data of terrain elevations has become a primary method for CFD to simulate wind farms of complex terrain. At present, the method for accurately solving the Navier-Stokes equation in turbulent flow with high Reynolds number under complex terrain is not possible to realize.
The existing Reynolds average simulation (RANS) and large vortex simulation (LES) of two alternative methods are not used for directly simulating the Navier-Stokes equation, namely, not directly solving, but the additional condition of a control equation is introduced by the two methods for closing the model, wherein the closing means that there are enough equations to solve all unknowns.
Reynolds average simulations are mainly used for practical engineering calculations and models used, such as the spark-Allmaras model, the k- ε series, the k- ω series, and RSM. LES provides a processing way to solve large vortices directly by means of temporal and spatial filtering, and to solve small vortex models to perform the system of equations closure. In general, LES is much more accurate than RANS, but is far LESs computationally efficient than the RANS model.
At present, compared with a mesoscale mode, the spatial resolution of the CFD mode is higher (the minimum horizontal lattice distance can reach 10 m), and the real terrain can be described more finely. However, if the size of the calculation domain to be studied is increased, the resolution of the grid is higher, which means that the number of the whole grids is also larger, and if the LES model with higher precision is still used for solving calculation globally, the wind resource evaluation efficiency is significantly reduced.
The prior patent CN114297952A discloses a method and a system for analyzing a micro-terrain wind field of a nuclear power plant, wherein the method is used for determining a CFD calculation domain of the model by establishing a 3D model of the nuclear power plant, carrying out CFD numerical simulation based on the CFD calculation domain after grid division and calculation working conditions to obtain the micro-terrain wind field distribution condition of the CFD calculation domain, and identifying risk sensitive areas of the nuclear power plant under different wind influence conditions.
The prior patent CN111833445A discloses a regional terrain segmentation and digital elevation model acquisition method based on multi-source data, which acquires a hierarchical digital elevation model by adopting a terrain segmentation method, processes the digital elevation model on the basis of the regional terrain segmentation and reduces the manual processing workload of a later digital elevation model.
However, in both the above two patents, a solution is not provided for rapid evaluation of wind resources of complex terrains in a large area, and meanwhile, the problems of low wind field simulation precision and low simulation efficiency in complex terrains are not solved.
Therefore, it is needed to provide a rapid evaluation scheme for wind resources of complex terrains in a large area, and meanwhile, the numerical simulation efficiency can be improved to a certain extent on the basis of the simulation precision of the wind field of the local area.
Disclosure of Invention
Based on the technical problems, the main purpose of the application is to provide a wind resource simulation method and device based on the surface fluctuation complexity, and different models are selected for simulation according to the terrain complexity so as to achieve the purpose of improving the simulation precision and the simulation efficiency at the same time.
According to one aspect of the application, the application provides a wind resource simulation method based on the complexity of surface relief, which comprises the following steps:
the computational domain is segmented into M x N subfields that are regular polygons.
Acquiring elevation data hk of each subdomain and according to the elevation data h k Calculating the standard deviation S of the elevation corresponding to each sub-domain ij 。
According to the elevation standard deviation S corresponding to each sub-domain ij Calculating the average value of the standard deviation of the elevation of all subdomains in the calculation domain
Judging the elevation standard deviation S corresponding to each sub-domain ij Whether or not it is greater than the standard deviation average value of elevation
If a subdomainThen the LES model is selected to perform simulation on the subdomain wind resources.
If a subdomainThen the RANS model is selected to perform simulation on the subdomain wind resources.
Alternatively, the diameter Δx of the subdomain is the calculated maximum elevation difference Δh of the terrain in the domain max 5 times of (2).
Optionally, according to elevation data h k Calculating the standard deviation S of the elevation corresponding to each sub-domain ij Comprising:
calculating the average elevation of each subfield based on formula one: wherein ,/>Is the average elevation, h k Elevation data for a single subdomain.
According to elevation data h of each subdomain k And calculating the standard deviation of the elevation of each subdomain by using a formula II: wherein ,hk Elevation data for individual subfields, +.>Is the average elevation.
Optionally, according to the elevation standard deviation S corresponding to each sub-domain ij Calculating the average value of the standard deviation of the elevation of all subdomains in the calculation domainComprising the following steps: calculating the standard deviation average value +.>And (3) a formula III: wherein ,Sij Is the standard deviation of elevation->Is the standard deviation average value of elevation.
Optionally, the method further comprises: and when the sub-domain wind resource is simulated, synchronously carrying out data interpolation and data exchange on the interfaces of the adjacent sub-domains.
According to the technical scheme, the wind resource simulation method based on the surface relief complexity has at least the following beneficial effects:
1. according to the application, the calculation domain is automatically divided into a plurality of sub-domains, and whether the elevation standard deviation corresponding to each sub-domain is larger than the elevation standard deviation average value is calculated and judged, so that the terrain complexity of the sub-domain is judged, a model for carrying out simulation calculation on the sub-domain is determined, the synchronous expansion simulation calculation on a plurality of servers is realized, and the wind resource evaluation simulation structure of a large-scale complex terrain is optimized.
2. According to the application, LES model and RANS model are respectively selected for different subdomains according to different ground surface forms and complexity, so that the calculation precision of the terrain wind field can be effectively improved, the calculation resources are saved, and the calculation efficiency is effectively improved.
According to another aspect of the present application, the present application provides a wind resource simulation apparatus based on complexity of surface relief, including:
and the segmentation module is used for segmenting the calculation domain into M multiplied by N subdomains, wherein the subdomains are regular polygons.
An acquisition module for acquiring elevation data h of each subdomain k And according to the elevation data h k Calculating the standard deviation S of the elevation corresponding to each sub-domain ij 。
A calculation module for calculating the standard deviation S of the elevation corresponding to each sub-domain ij Calculating the average value of the standard deviation of the elevation of all subdomains in the calculation domain
A judging module for judging the elevation standard deviation S corresponding to each sub-domain ij Whether or not it is greater than the standard deviation average value of elevation
Simulation module for when a subdomainSelecting an LES model to perform simulation on the subdomain wind resources; when a subdomain->And selecting a RANS model to perform simulation on the subdomain wind resources.
Alternatively, the diameter Δx of the subdomain is the calculated maximum elevation difference Δh of the terrain in the domain max 5 times of (2).
Optionally, the acquiring module is configured to:
calculating the average elevation of each subfield based on formula one: wherein ,/>Is the average elevation, h k Elevation data for a single subdomain.
According to elevation data h of each subdomain k And calculating the standard deviation of the elevation of each subdomain by using a formula II: wherein ,hk Elevation data for individual subfields, +.>Is the average elevation.
Optionally, the computing module is configured to: calculating the standard deviation average value of the elevation by using a formula IIIAnd (3) a formula III: wherein ,Sij Is the standard deviation of elevation->Is the standard deviation average value of elevation.
Optionally, the simulation module is further configured to: and when the sub-domain wind resource is simulated, synchronously carrying out data interpolation and data exchange on the interfaces of the adjacent sub-domains.
According to the technical scheme, the wind resource simulation device based on the surface relief complexity has at least the following beneficial effects:
1. according to the application, the calculation domain is automatically divided into a plurality of sub-domains, and whether the elevation standard deviation corresponding to each sub-domain is larger than the elevation standard deviation average value is calculated and judged, so that the terrain complexity of the sub-domain is judged, a model for carrying out simulation calculation on the sub-domain is determined, the synchronous expansion simulation calculation on a plurality of servers is realized, and the wind resource evaluation simulation structure of a large-scale complex terrain is optimized.
2. According to the application, LES model and RANS model are respectively selected for different subdomains according to different ground surface forms and complexity, so that the calculation precision of the terrain wind field can be effectively improved, the calculation resources are saved, and the calculation efficiency is effectively improved.
Drawings
The accompanying drawings, which are included to provide a further understanding of the application and are incorporated in and constitute a part of this specification, illustrate embodiments of the application and together with the description serve to explain the application. In the drawings:
FIG. 1 is a flow chart of a wind resource simulation method based on surface relief complexity according to an embodiment of the present application;
FIG. 2 is a schematic diagram illustrating the computational domain block partitioning and turbulence model selection according to an embodiment of the present application;
FIG. 3 is a schematic view showing the effect of ridge trend of a computing domain in one embodiment of the present application;
fig. 4 is a schematic structural diagram of a wind resource simulation device based on the complexity of surface relief according to an embodiment of the present application.
Detailed Description
It should be noted that, without conflict, the embodiments of the present application and features of the embodiments may be combined with each other. The application will be described in detail below with reference to the drawings in connection with embodiments.
The application is described in further detail below in connection with specific examples which are not to be construed as limiting the scope of the application as claimed.
Examples
In order to achieve the above object, according to one aspect of the present application, a wind resource simulation method based on the complexity of surface relief is provided.
A flow chart of a wind resource simulation method based on surface relief complexity according to an embodiment of the present application is shown in fig. 1, and as shown, the method includes the steps of:
s1, dividing the calculation domain into M multiplied by N subdomains, wherein the subdomains are regular polygons.
In the present embodiment, a regular hexagonal block is used to divide a large-sized computation region into M×N small-sized subfields, wherein the diameter Δx of the regular hexagonal subfields is the maximum altitude difference Δh of the topography in the computation region max 5 times of (2).
Specifically, the partial division effect of the calculation domain in the present embodiment is shown in FIG. 2, which is exemplified by the figure, the calculation domain is divided into 5×8 small-sized subfields, and the diameter Δx of the regular hexagonal subfields represents the distance from B to C, and the value is the difference Δh between the maximum elevation and the minimum elevation of the terrain elevation in the calculation domain max 5 times of (2).
S2, acquiring elevation data h of each subdomain k And according to the elevation data h k Calculate Gao Chengbiao corresponding to each sub-domainDifference of accuracy S ij 。
Specifically, after the calculation region is divided by S1, each subdomain contains a certain amount of topographic elevation data, and the discrete elevation data contained in a single subdomain is expressed as h k Where k=1, 2,3 … … n.
Standard deviation S of elevation corresponding to each subdomain ij The calculation mode of (2) is as follows:
firstly, the elevation data h of each subdomain is acquired according to the actual topography k The average elevation of each subfield is calculated based on equation one.
For average elevation, the discrete elevation data h contained in a single sub-field k Average of the sum, where i and j represent the number of rows and columns, respectively, of the sub-field, numbered from the first regular hexagonal sub-field in the upper left corner, +.>Representing the average elevation of the first column sub-field of the first row.
Second, according to the elevation data h of each subdomain k And average elevationAnd calculating the standard deviation of the elevation of each subdomain by using a formula II.
Examples: standard deviation S of elevation of subdomain at first row and first column position 11 From the elevation data h contained in the sub-field 1 ……h n And average elevationCalculated by a formula II.
S3, according to the elevation standard deviation S corresponding to each sub-domain ij Calculating the average value of the standard deviation of the elevation of all subdomains in the calculation domain
Calculating the standard deviation average value of the elevation by using a formula III
wherein ,Sij Is the standard deviation of the elevation and is used for the control of the height,m is the row value of the divided calculation domain, and N is the column value of the divided calculation domain.
S4, judging the elevation standard deviation S corresponding to each sub-domain ij Whether or not it is greater than the standard deviation average value of elevation
Based on the step, the terrain complexity of the subdomain can be judged according to the judging result, and then a model for carrying out simulation calculation on the subdomain is determined.
S5, if a subdomainThen the LES model is selected to perform simulation on the subdomain wind resources.
It can be understood that if the standard deviation S of the elevation of a certain subdomain ij Is greater than the standard deviation average value of elevationThen this is indicatedThe surface relief in the subdomain is larger, the complexity of the terrain is higher, and an LES model with higher precision is adopted for simulation calculation.
S6, if a subdomainThen the RANS model is selected to perform simulation on the subdomain wind resources.
It can be understood that if the standard deviation S of the elevation of a certain subdomain ij Is smaller than the standard deviation average value of elevationThe method shows that the surface fluctuation in the subdomain is small, the terrain is simpler, and the RANS model calculation is adopted.
The ridge trend is marked with a broken line in FIG. 3, and as shown in FIG. 3, the surface of the earth is greatly fluctuated in the area near the line, i.e. the area corresponds to a difference in height Cheng BiaozhunCorresponds to subdomain A in FIG. 2 21 、A 22 、A 23 、A 25 、A 27 ；A 31 、A 32 、A 33 、A 34 、A 36 、A 37 、A 38 ；A 41 、A 44 、A 45 、A 48 And (3) unfolding and calculating by selecting an LES model with higher calculation accuracy, and adopting a RANS model for other areas.
In addition, when the sub-domain wind resource is simulated, data interpolation and data exchange are synchronously carried out on the interfaces of the adjacent sub-domains, so that the junction positions of the adjacent sub-domains are smoothly transited.
In summary, as can be seen from the above description, embodiments of the wind resource simulation method based on the complexity of surface relief achieve the following technical effects:
1. according to the application, the calculation domain is automatically divided into a plurality of sub-domains, and whether the elevation standard deviation corresponding to each sub-domain is larger than the elevation standard deviation average value is calculated and judged, so that the terrain complexity of the sub-domain is judged, a model for carrying out simulation calculation on the sub-domain is determined, the synchronous expansion simulation calculation on a plurality of servers is realized, and the wind resource evaluation simulation structure of a large-scale complex terrain is optimized.
2. According to the application, LES model and RANS model are respectively selected for different subdomains according to different ground surface forms and complexity, so that the calculation precision of the terrain wind field can be effectively improved, the calculation resources are saved, and the calculation efficiency is effectively improved.
According to another aspect of the present application, the present application further provides a wind resource simulation apparatus based on complexity of surface relief, the apparatus specifically including:
the segmentation module 41 is configured to segment the calculation domain into m×n subfields, where the subfields are regular polygons.
Wherein the diameter Deltax of the subdomain is the maximum altitude difference Deltah of the terrain in the calculated domain max 5 times of (2).
An acquisition module 42 for acquiring elevation data h of each sub-field k And according to the elevation data h k Calculating the standard deviation S of the elevation corresponding to each sub-domain ij 。
Specifically, the obtaining module 42 is configured to:
calculating the average elevation of each subfield based on formula one: wherein ,/>Is the average elevation, h k Elevation data for a single subdomain.
According to elevation data h of each subdomain k And calculating the standard deviation of the elevation of each subdomain by using a formula II: wherein ,hk Elevation data for individual subfields, +.>Is the average elevation.
A calculation module 43 for calculating the standard deviation S of the elevation corresponding to each sub-domain ij Calculating the average value of the standard deviation of the elevation of all subdomains in the calculation domain
Specifically, the calculating module 43 is configured to: calculating the standard deviation average value of the elevation by using a formula IIIAnd (3) a formula III: wherein ,Sij Is the standard deviation of elevation->Is the standard deviation average value of elevation.
A judging module 44 for judging the elevation standard deviation S corresponding to each sub-domain ij Whether or not it is greater than the standard deviation average value of elevation
A simulation module 45 for, when a subdomainWhen the LES model is selected to carry out simulation on the subdomain wind resource, when the subdomain is +.>And selecting a RANS model to perform simulation on the subdomain wind resources.
Specifically, the simulation module 45 is further configured to: and when the sub-domain wind resource is simulated, synchronously carrying out data interpolation and data exchange on the interfaces of the adjacent sub-domains.
It should be understood that the wind resource simulation device based on the surface relief complexity is consistent with the description of the corresponding embodiment of the wind resource simulation method based on the surface relief complexity, so that the description is not repeated in this embodiment.
In summary, as can be seen from the above description, embodiments of the wind resource simulation device based on the complexity of the surface relief achieve the following technical effects:
1. according to the application, the calculation domain is automatically divided into a plurality of sub-domains, and whether the elevation standard deviation corresponding to each sub-domain is larger than the elevation standard deviation average value is calculated and judged, so that the terrain complexity of the sub-domain is judged, a model for carrying out simulation calculation on the sub-domain is determined, the synchronous expansion simulation calculation on a plurality of servers is realized, and the wind resource evaluation simulation structure of a large-scale complex terrain is optimized.
2. According to the application, LES model and RANS model are respectively selected for different subdomains according to different ground surface forms and complexity, so that the calculation precision of the terrain wind field can be effectively improved, the calculation resources are saved, and the calculation efficiency is effectively improved.
It is noted that relational terms such as first and second, and the like are used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Moreover, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one … …" does not exclude the presence of other like elements in a process, method, article, or apparatus that comprises an element.
Logic and/or steps represented in the flowcharts or otherwise described herein, e.g., a ordered listing of executable instructions for implementing logical functions, can be embodied in any computer-readable medium for use by or in connection with an instruction execution system, apparatus, or device, such as a computer-based system, processor-containing system, or other system that can fetch the instructions from the instruction execution system, apparatus, or device and execute the instructions.
It is to be understood that portions of the present application may be implemented in hardware, software, firmware, or a combination thereof. In the above-described embodiments, the various steps or methods may be implemented in software or firmware stored in a memory and executed by a suitable instruction execution system.
It should be noted that in the description of the present specification, descriptions of terms "one embodiment," "some embodiments," "examples," "specific examples," or "some examples," etc., mean that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the present application. In this specification, schematic representations of the above terms are not necessarily directed to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples. Furthermore, the different embodiments or examples described in this specification and the features of the different embodiments or examples may be combined and combined by those skilled in the art without contradiction.
The above description is only of the preferred embodiments of the present application and is not intended to limit the present application, but various modifications and variations can be made to the present application by those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included in the protection scope of the present application.
Claims (10)
1. The wind resource simulation method based on the surface relief complexity is characterized by comprising the following steps of:
dividing a calculation domain into M multiplied by N subdomains, wherein the subdomains are regular polygons;
acquiring elevation data h of each subdomain k And according to the elevation data h k Calculating the standard deviation S of the elevation corresponding to each sub-domain ij ；
According to the elevation standard deviation S corresponding to each sub-domain ij Calculating the standard deviation average value of the elevations of all subdomains in the calculation domain
Judging the elevation standard deviation S corresponding to each sub-domain ij Whether or not it is greater than the elevation standard deviation average value
If a subdomainSelecting an LES model to perform simulation on the subdomain wind resources;
if a subdomainThen the RANS model is selected to perform simulation on the subdomain wind resources.
2. The method of claim 1, wherein the diameter Δx of the sub-region is the calculated maximum elevation difference Δh of the terrain elevation in the region max 5 times of (2).
3. The method according to claim 1, wherein, based on the elevation data h k Calculating the standard deviation S of the elevation corresponding to each sub-domain ij Comprising:
calculating the average elevation of each subfield based on formula one:
wherein ,is the average elevation, h k Number of elevations for a single subdomainAccording to the above;
according to elevation data h of each subdomain k And calculating the standard deviation of the elevation of each subdomain by using a formula II, wherein the formula II is as follows: wherein ,hk Elevation data for individual subfields, +.>Is the average elevation.
4. The method according to claim 1, wherein the standard deviation S of elevation corresponding to each sub-domain ij Calculating the standard deviation average value of the elevations of all subdomains in the calculation domainComprising the following steps:
calculating the standard deviation average value of the elevation by using a formula IIIAnd (3) a formula III: /> wherein ,Sij Is the standard deviation of elevation->Is the standard deviation average value of elevation.
5. The method as recited in claim 1, further comprising: and when the sub-domain wind resource is simulated, synchronously carrying out data interpolation and data exchange on the interfaces of the adjacent sub-domains.
6. Wind resource simulation device based on surface relief complexity, characterized by comprising:
the segmentation module is used for segmenting the calculation domain into M multiplied by N subdomains, and the subdomains are regular polygons;
an acquisition module for acquiring elevation data h of each subdomain k And according to the elevation data h k Calculating the standard deviation S of the elevation corresponding to each sub-domain ij ；
A calculation module for calculating the standard deviation S of the elevation corresponding to each sub-domain ij Calculating the standard deviation average value of the elevations of all subdomains in the calculation domain
A judging module for judging the elevation standard deviation S corresponding to each sub-domain ij Whether or not it is greater than the elevation standard deviation average value
Simulation module for when a subdomainSelecting an LES model to perform simulation on the subdomain wind resources; when a subdomain->And selecting a RANS model to perform simulation on the subdomain wind resources.
7. The apparatus of claim 6, wherein the diameter Δx of the sub-region is the calculated maximum elevation difference Δh of the terrain elevation in the region max 5 times of (2).
8. The apparatus of claim 6, wherein the acquisition module is to:
calculating an average for each subfield based on equation oneElevation, equation one:
wherein ,is the average elevation, h k Elevation data for a single subdomain;
according to elevation data h of each subdomain k And calculating the standard deviation of the elevation of each subdomain by using a formula II, wherein the formula II is as follows: wherein ,hk Elevation data for individual subfields, +.>Is the average elevation.
9. The apparatus of claim 6, wherein the computing module is to: calculating the standard deviation average value of the elevation by using a formula IIIAnd (3) a formula III:
wherein ,Sij Is the standard deviation of elevation->Is the standard deviation average value of elevation.
10. The apparatus of claim 6, wherein the analog module is further to: and when the sub-domain wind resource is simulated, synchronously carrying out data interpolation and data exchange on the interfaces of the adjacent sub-domains.
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Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111369436A (en) * | 2020-02-27 | 2020-07-03 | 山东科技大学 | Airborne LiDAR point cloud rarefying method considering multi-terrain features |
| CN112417783A (en) * | 2020-11-20 | 2021-02-26 | 西安热工研究院有限公司 | Mixing turbulence calculation method |
| CN113656973A (en) * | 2021-08-20 | 2021-11-16 | 华北电力大学 | Wake flow hybrid simulation method, system, device and medium for wind power plant |
| CN113657055A (en) * | 2021-08-27 | 2021-11-16 | 西安热工研究院有限公司 | Inflow condition generation method and system for numerical simulation of wind field in complex terrain |
| CN114297952A (en) * | 2021-12-16 | 2022-04-08 | 苏州热工研究院有限公司 | Micro-terrain wind field analysis method and system for nuclear power plant |
-
2022
- 2022-12-12 CN CN202211591980.8A patent/CN116070414B/en active Active
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111369436A (en) * | 2020-02-27 | 2020-07-03 | 山东科技大学 | Airborne LiDAR point cloud rarefying method considering multi-terrain features |
| CN112417783A (en) * | 2020-11-20 | 2021-02-26 | 西安热工研究院有限公司 | Mixing turbulence calculation method |
| CN113656973A (en) * | 2021-08-20 | 2021-11-16 | 华北电力大学 | Wake flow hybrid simulation method, system, device and medium for wind power plant |
| CN113657055A (en) * | 2021-08-27 | 2021-11-16 | 西安热工研究院有限公司 | Inflow condition generation method and system for numerical simulation of wind field in complex terrain |
| CN114297952A (en) * | 2021-12-16 | 2022-04-08 | 苏州热工研究院有限公司 | Micro-terrain wind field analysis method and system for nuclear power plant |
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