Radio telescope station site wind field regulation and control method based on measured data and CFD

Abstract

The invention discloses a radio telescope station site wind field regulation and control method based on actual measurement data and CFD, and solves the problems that wind speed measurement of a single wind tower in the prior art is difficult to comprehensively reflect the complete view of a complex station site terrain wind field, and a wind speed sudden increase area cannot be effectively identified. The method comprises the following steps: carrying out data preprocessing on wind speed and wind direction data, and carrying out model preprocessing on digital elevation model data; boundary conditions are calculated according to the preprocessed wind speed and wind direction data; taking the site average wind characteristics and the fluctuating wind characteristics as boundary conditions, and performing CFD simulation by using the three-dimensional terrain model to obtain a simulation result; identifying a plurality of key areas with sudden wind speed increase according to a simulation result, setting a windproof net in the plurality of key areas according to different windproof schemes, and performing simulation according to the different windproof schemes to obtain an optimal windproof scheme; according to the invention, the influence of wind disturbance on the radio telescope is effectively reduced, and the operation stability and observation performance of equipment are guaranteed.

Description

Technical Field

[0001] The present invention relates to the technical field of radio astronomy and fluid dynamics simulation, and in particular to a method for controlling a wind field at a radio telescope site based on measured data and CFD (Computational Fluid Dynamics Simulation). Background Art

[0002] Radio telescopes are large, precision instruments used by astronomers to observe cosmic particles and electromagnetic waves reaching Earth. To improve sensitivity and resolution, radio telescopes are typically equipped with large-aperture reflectors. As the reflector's aperture increases, the impact of wind loads on its performance becomes more significant.

[0003] On the one hand, wind pressure is proportional to the square of the reflector's aperture, which may cause deformation of the reflector, thereby reducing the sensitivity and resolution of the radio telescope. On the other hand, wind torque is proportional to the cube of the aperture, which may cause pointing errors in the radio telescope. Therefore, in order to ensure the observation performance of large-aperture radio telescopes, it is necessary to reduce the impact of wind loads on them. Taking the 110m Qitai Radio Telescope (QTT) under construction in China as an example, its pointing accuracy is required to reach 2.5 arc seconds, and the surface accuracy must be better than 0.3mm. Under such strict technical requirements, even slight wind-induced disturbances may cause a significant decline in the telescope's observation performance, affecting the stability of astronomical observations.

[0004] Currently, common wind load suppression methods mainly include: optimizing the structural design to improve the rigidity and wind resistance of the telescope. Although this can reduce wind-induced deformation, it will significantly increase the weight of the equipment and is difficult to apply to large-aperture radio telescopes; using a radome can reduce direct wind loads, but it will affect the electrical performance of the radio telescope in high-frequency observations and cannot be applied to large-aperture radio telescopes; although control strategies such as proportional-integral-derivative control (PID), H-infinity control and neural network algorithms can partially compensate for wind disturbances, they are limited in effect when dealing with pulsating wind loads.

[0005] In this context, the use of windbreaks for radio telescopes offers a novel approach to addressing the wind disturbance challenge. By rationally planning the layout of windbreaks, the airflow path can be redirected before it reaches the radio telescope, effectively reducing wind speed and weakening turbulence.

[0006] Wind speed measurement based on a single wind tower is difficult to fully reflect the overall picture of the wind field in complex site terrain and cannot effectively identify areas with sudden wind speed increases. Summary of the Invention

[0007] The present invention provides a method for regulating the wind field of a radio telescope site based on measured data and CFD, which solves the problem in the prior art that the wind speed measurement of a single wind tower is difficult to comprehensively reflect the overall situation of the complex terrain wind field of the site and cannot effectively identify the areas with sudden increase in wind speed, and realizes effectively reducing the influence of wind disturbance on the radio telescope and ensuring the stability of equipment operation and the observation performance.

[0008] The present invention provides a method for regulating the wind field of a radio telescope site based on measured data and CFD, and the method includes:

[0009] Obtain the wind speed and wind direction data collected by the wind tower, perform data preprocessing on the wind speed and wind direction data to obtain the preprocessed wind speed and wind direction data; obtain the digital elevation model data of the site area, and perform model preprocessing on the digital elevation model data to obtain the three-dimensional terrain model of the radio telescope site;

[0010] Calculate the average wind characteristics and pulsating wind characteristics of the site according to the preprocessed wind speed and wind direction data;

[0011] Use the average wind characteristics and the pulsating wind characteristics of the site as boundary conditions, and perform CFD simulation using the three-dimensional terrain model to obtain the simulation results;

[0012] Identify multiple key areas with sudden increase in wind speed according to the simulation results, set windbreak nets in the multiple key areas according to different wind prevention schemes, and perform simulation according to different wind prevention schemes to obtain the optimal wind prevention scheme.

[0013] In a possible implementation manner, the performing data preprocessing on the wind speed and wind direction data to obtain the preprocessed wind speed and wind direction data includes:

[0014] Perform abnormal data preprocessing on the wind speed and wind direction data by using interpolation patching or deletion to obtain the preprocessed wind speed and wind direction data; wherein, the abnormal data includes: time series overlapping data and / or missing data.

[0015] In a possible implementation manner, the performing model preprocessing on the digital elevation model data to obtain the three-dimensional terrain model of the radio telescope site includes:

[0016] Process the digital elevation model data through a geographic information system to obtain geographic elevation data;

[0017] Convert the geographic elevation data into three-dimensional space coordinate points and export them to generate three-dimensional coordinate point cloud data that can be recognized by modeling software;

[0018] Using 3D modeling software, a 3D terrain model of the radio telescope site is constructed based on the 3D coordinate point cloud data to ensure that the spatial accuracy of the model is consistent with the real terrain features.

[0019] In a possible implementation, calculating the average wind characteristics and fluctuating wind characteristics of the site based on the preprocessed wind speed and wind direction data includes:

[0020] Calculating the average wind profile based on the wind speed and wind direction in the preprocessed wind speed and wind direction data;

[0021] Calculating the turbulence intensity within a period of time based on the wind speed in the preprocessed wind speed and wind direction data; wherein, the average wind characteristics of the site include: wind speed, wind direction, and average wind profile; the fluctuating wind characteristics include: the turbulence intensity within a period of time.

[0022] In a possible implementation, calculating the average wind profile based on the preprocessed wind speed and wind direction data includes:

[0023] Calculating the average wind profile based on the preprocessed wind speed and wind direction data using the average wind profile calculation formula; wherein, the average wind profile calculation formula is expressed as:

[0024]

[0025] wherein, U ref represents the wind speed at the reference height; Z represents the height; a represents the wind profile exponent; U z represents the average wind profile at height Z.

[0026] In a possible implementation, calculating the turbulence intensity within a period of time based on the preprocessed wind speed and wind direction data includes:

[0027] Calculating the turbulence intensity within a period of time based on the preprocessed wind speed and wind direction data using the turbulence intensity calculation formula; wherein, the turbulence intensity calculation formula is expressed as:

[0028]

[0029] wherein, σ u represents the standard deviation of the wind speed fluctuation within a period of time; U represents the average wind speed within a period of time; I represents the turbulence intensity within a period of time.

[0030] In a possible implementation, the

[0031] Identifying multiple key areas with sudden wind speed increase based on the simulation results, and setting windbreak nets according to different wind prevention schemes in the multiple key areas, includes:

[0032] According to the terrain features and the wind direction, and in combination with the simulation results, clarify the scope and shape of the areas with sudden wind speed increase, and obtain multiple key areas with sudden wind speed increase;

[0033] Adopt the additional source term method to define the windbreak net as a porous medium model, and introduce different porous medium models at different positions in multiple key areas respectively to obtain different windbreak schemes for setting up the windbreak net.

[0034] In one possible implementation, the simulating according to different windbreak schemes to obtain the optimal windbreak scheme includes:

[0035] Determine the momentum corresponding to different windbreak schemes, and design the pore size of the porous medium model in the windbreak scheme according to different momenta;

[0036] Judge whether the wind speeds corresponding to different windbreak schemes can reach the windproof efficiency index. If so, obtain the optimal windbreak scheme; if not, discard the scheme.

[0037] In one possible implementation, the calculation formula of the momentum is expressed as:

[0038]

[0039] wherein, μ represents the fluid viscosity coefficient; D i represents the i-th component of the viscous drag coefficient. Under the condition of high Reynolds number, the viscous drag term can be ignored; C i represents the i-th component of the inertial drag coefficient; ρ represents the air density; u represents the velocity; u i represents the i-th component of the velocity.

[0040] One or more technical solutions provided in the present invention have at least the following technical effects or advantages:

[0041] By combining the wind speed and wind direction data collected by the wind tower with the CFD simulation to analyze the wind field distribution of the site, the CFD simulation can not only supplement the limitations of the measured data in terms of spatial and temporal resolution, but also deeply analyze the wind speed, wind direction and turbulence characteristics through high-precision terrain modeling, providing an important reference basis for the wind field analysis of complex site environments; by applying the wind speed and wind direction data collected by the wind tower and the CFD simulation, restoring the wind field distribution of the site, identifying the areas with sudden wind speed increase, and designing the layout scheme of the windbreak net, it can effectively reduce the influence of wind disturbance on the radio telescope and ensure the stability of the equipment operation and the observation performance. Description of the Drawings

[0042] Figure 1 It is a flow chart of the steps of the method for regulating the wind field of a radio telescope site based on measured data and CFD provided by an embodiment of the present invention;

[0043] Figure 2a Frequency distribution diagram of measured wind speed, wind direction and wind data in 16 directions provided by the embodiments of the present invention;

[0044] Figure 2b Variation diagram of wind direction with wind speed of measured data provided by the embodiments of the invention;

[0045] Figure 3a Turbulence intensity distribution diagram of measured data provided by the embodiments of the present invention;

[0046] Figure 3b Probability distribution diagram of turbulence intensity in different wind speed ranges of measured data provided by the embodiments of the invention;

[0047] Figure 4 Three-dimensional terrain model diagram of the site area provided by the embodiments of the present invention;

[0048] Figure 5a Wind speed cloud diagram of the high wind speed area of the site under the north wind condition provided by the embodiments of the invention;

[0049] Figure 5b Wind speed cloud diagram of the high wind speed area of the site under the south wind condition provided by the embodiments of the invention;

[0050] Figure 6a Wind speed distribution cloud diagram of the site after northward regulation provided by the embodiments of the invention;

[0051] Figure 6b Wind speed distribution cloud diagram of the site after southward regulation provided by the embodiments of the invention. Detailed implementation manners

[0052] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, rather than all of the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0053] The present invention provides a method for regulating the wind field of a radio telescope site based on measured data and CFD, and the method includes the following steps S101 to S104.

[0054] S101, obtain the wind speed and wind direction data collected by the wind tower, perform data preprocessing on the wind speed and wind direction data to obtain the preprocessed wind speed and wind direction data; obtain the digital elevation model data of the site area, perform model preprocessing on the digital elevation model data to obtain the three-dimensional terrain model of the radio telescope site;

[0055] Specifically, in step S101, data preprocessing is performed on the wind speed and direction data to obtain the preprocessed wind speed and direction data, including: performing abnormal data preprocessing on the wind speed and direction data by interpolation patching or deletion to obtain the preprocessed wind speed and direction data; where the abnormal data includes: time series overlapping data and / or missing data.

[0056] Exemplarily, the abnormal data is classified into 3 categories: typical abnormal data, outlier screening, and other abnormal data screening. Typical abnormal data: identifiers such as "NAN", "999", etc. appear in the collected data; Outlier: The collected value has a large deviation compared with the values at the previous and subsequent moments and does not conform to the actual wind data; Other abnormal data refers to problems such as data missing, time series overlapping, etc. For the processing of abnormal data, mainly two means of invalid data elimination and adjacent point interpolation patching are adopted.

[0057] Specifically, in step S101, model preprocessing is performed on the digital elevation model data to obtain the three-dimensional terrain model of the radio telescope site, including the following S1011 to S1013.

[0058] S1011, process the digital elevation model data through a geographic information system to obtain geographic elevation data;

[0059] S1012, convert the geographic elevation data into three-dimensional space coordinate points and export them to generate three-dimensional coordinate point cloud data recognizable by the modeling software;

[0060] S1013, use three-dimensional modeling software to construct the three-dimensional terrain model of the radio telescope site based on the three-dimensional coordinate point cloud data to ensure that the spatial accuracy of the model conforms to the true terrain characteristics.

[0061] Exemplarily, the obtained digital elevation model (DEM) data should include the site area and its surrounding terrain, ensure that the established three-dimensional terrain model is large enough to ensure the full development of the flow field, preprocess the DEM data using GIS software, and import the three-dimensional coordinate point cloud data into the modeling software to establish the site terrain model.

[0062] S102, calculate the site mean wind characteristics and fluctuating wind characteristics based on the preprocessed wind speed and direction data;

[0063] Specifically, in step S102, calculate the site mean wind characteristics and fluctuating wind characteristics based on the preprocessed wind speed and direction data, including the following S1021 to S1022.

[0064] S1021, calculate the mean wind profile based on the preprocessed wind speed and direction data;

[0065] Here, calculating the mean wind profile based on the preprocessed wind speed and direction data includes:

[0066] According to the preprocessed wind speed and wind direction data, the mean wind profile is calculated using the mean wind profile calculation formula; among them, the mean wind profile calculation formula is expressed as:

[0067]

[0068] Among them, U ref represents the wind speed at the reference height; Z represents the height; a represents the wind profile exponent; U z represents the mean wind profile at height Z.

[0069] S1022. Calculate the turbulence intensity within a period of time according to the preprocessed wind speed and wind direction data; among them, the average wind characteristics of the site include: wind speed, wind direction, and mean wind profile; the pulsating wind characteristics include: the turbulence intensity within a period of time.

[0070] Here,

[0071] Calculating the turbulence intensity within a period of time according to the preprocessed wind speed and wind direction data includes:

[0072] According to the preprocessed wind speed and wind direction data, the turbulence intensity within a period of time is calculated using the turbulence intensity calculation formula; among them, the turbulence intensity calculation formula is expressed as:

[0073]

[0074] Among them, σ u represents the standard deviation of the wind speed fluctuation within a period of time; U represents the average wind speed within a period of time; I represents the turbulence intensity within a period of time.

[0075] Exemplarily, the average wind characteristics include wind speed, wind direction, and mean wind profile, and the pulsating wind characteristics include turbulence intensity and wind power spectral density. Combine the wind characteristics of the site with the national terrain classification standard to judge the terrain type of the site area.

[0076] S103. Use the average wind characteristics and pulsating wind characteristics of the site as boundary conditions, and perform CFD simulation using the three-dimensional terrain model to obtain the simulation results;

[0077] Exemplarily, in the boundary condition setting, the inlet boundary condition should include wind speed and wind direction, mean wind profile, and turbulence-related parameters, etc. Among them, the mean wind profile and turbulence-related parameters can both be realized through UDF programming in the Fluent software. Subsequently, set the wall roughness constant and roughness height according to the landform type to ensure that the model conforms to the actual environmental characteristics.

[0078] Take the main wind direction of the site area and the concerned wind speed grade as the typical wind conditions, carry out CFD simulation and conduct effectiveness verification.

[0079] S104. Identify multiple key areas with sudden increases in wind speed based on the simulation results. Set up windbreak nets in the multiple key areas according to different windbreak plans, and perform simulations according to different windbreak plans to obtain the optimal windbreak plan.

[0080] Specifically, in step S104, setting up windbreak nets in the multiple key areas according to different windbreak plans includes the following steps S1041 to S1042.

[0081] S1041. Based on the terrain features and the incoming wind direction, combined with the simulation results, clarify the scope and shape of the areas with sudden increases in wind speed to obtain multiple key areas with sudden increases in wind speed.

[0082] It can be understood that the simulation results include a wind speed distribution cloud map. Therefore, based on terrain features such as slope and aspect and the main incoming wind direction, it is possible to clarify the scope and shape of the areas with sudden increases in wind speed.

[0083] S1042. Use the additional source term method to define the windbreak net as a porous medium model, and introduce different porous medium models at different positions in the multiple key areas to obtain different windbreak plans for setting up the windbreak net.

[0084] It can be understood that the additional source term method (Source Term Method) is a commonly used numerical simulation technique in computational fluid dynamics (CFD), mainly used to handle complex boundary conditions or special physical phenomena. The core idea of the additional source term method is to simulate certain physical effects or achieve specific boundary conditions by adding additional source terms to the control equations, without explicitly modifying the computational grid or boundaries.

[0085] Specifically, in step S104, performing simulations according to different windbreak plans to obtain the optimal windbreak plan includes:

[0086] (1) Determine the momentum corresponding to different windbreak plans, and design the aperture size of the porous medium model in the windbreak plan according to different momenta.

[0087] Here, the calculation formula for momentum is expressed as:

[0088]

[0089] where represents the fluid viscosity coefficient; D i represents the i-th component of the viscous drag coefficient; C i represents the i-th component of the inertial drag coefficient; ρ represents the air density; u represents the velocity; u i represents the i-th component of the velocity.

[0090] (2) Determine whether the wind speeds corresponding to different wind protection schemes can reach the wind protection efficiency index. If so, obtain the optimal wind protection scheme; if not, discard the scheme.

[0091] Exemplarily, use CFD post-processing software to draw the cloud map of wind speed and direction distribution under typical wind conditions, identify the key areas where the wind speed suddenly increases, design the windbreak layout scheme for this area, and clarify parameters such as length, number of rows, and spacing. Subsequently, adopt the additional source term method to carry out the layout optimization design of the windbreak. Define it as a porous medium domain in the flow field domain, add a source term in formula (3), and simulate the changes in the airflow before and after passing through the windbreak. Finally, by comparing the wind protection efficiencies of multiple windbreak layout schemes, select the scheme that meets the requirements of the wind protection efficiency index for the position of the radio telescope.

[0092] In a simulation experiment provided by the present invention, the present invention will be further described below in conjunction with the accompanying drawings and examples:

[0093] Taking the 110m aperture omnidirectional movable radio telescope QTT (Qitai radiotelescope) under construction in Qitai, Xinjiang as an example, referring to Figure 1 , the present invention is a method for regulating the wind field of a radio telescope site based on measured data and CFD, and the specific steps are as follows:

[0094] S101, the measured data of the wind tower is stored in an Excel file and imported into Matlab software. Abnormal data is preprocessed by means of invalid data elimination and adjacent point interpolation repair. Use the digital elevation model (DEM) to establish a three-dimensional terrain model of the radio telescope site. Based on the geospatial data cloud, obtain the elevation data of the terrain within a range of 3.8km×5.3km×1km around the QTT site, as Figure 4 shown, the resolution of the elevation data is 30m. Convert the elevation data into three-dimensional space coordinate point cloud data through GIS software, and use three-dimensional modeling software to establish a three-dimensional terrain model of the QTT site.

[0095] S102, analyze the distribution of wind speed and direction at the QTT site using the measured wind data at the 10m position of the 55m gradient wind tower in the central area of the QTT site. Figure 2a shows the frequency distribution of wind data in 16 directions from March to December 2017. Among them, the main wind directions in March, April, and May are northwest, and the wind directions from June to December are mainly concentrated in the two directions of due south and southeast by south. Figure 2b shows the change of wind direction with wind speed. It can be found that the greater the wind speed, the more concentrated the wind direction is in the due south direction. When the wind speed is greater than 10m / s, the proportion of wind data in the due south direction has reached 60%.

[0096] The wind profile index at the station site was fitted using the measured data from the wind tower. The reference height was selected as 10m, and the wind profile indices at heights of 20m, 30m, 40m and 50m were calculated, as shown in Table 1 below.

[0097] Analyzing the data in the table, we can observe that the wind profile index decreases with increasing altitude, indicating that the influence of surface roughness on wind speed weakens with increasing altitude, and wind speed changes tend to be stable. At low wind speeds, the surface friction effect is more significant. As wind speed increases, the turbulent kinetic energy increases significantly, the turbulent mixing effect becomes stronger, the surface friction effect is relatively weakened, the wind speed difference between altitudes decreases, and the overall wind profile index decreases.

[0098] Table 1 Wind profile index fitting table

[0099] 20m / 10m 30m / 10m 40m / 10m 50m / 10m >0m / s 0.374 0.319 0.296 0.285 >4m / s 0.163 0.137 0.132 0.129 >6m / s 0.160 0.134 0.131 0.126 >8m / s 0.152 0.126 0.124 0.117 >10m / s 0.122 0.103 0.099 0.095

[0100] From the perspective of wind speed variation, there are many sample points for low wind speeds. At low wind speeds, even if the wind speed changes slightly at altitude, the ratio of the two values can vary significantly. Therefore, the wind profile index fitted using all wind speed data (>0 m / s) will be biased upwards. However, the measured data contains relatively few sample points with wind speeds greater than 6 m / s. Therefore, it is recommended that the QTT wind profile index be fitted using data with wind speeds greater than 4 m / s. Ultimately, the fitted wind profile index is close to the recommended value of 0.15 for Class B landforms in China.

[0101] The turbulence intensity is calculated using formula (2). Figure 3 shows the distribution of turbulence intensity, reflecting its correlation characteristics with wind speed. Figure 3a The scatter plot of turbulence intensity versus wind speed shows the changing trend of turbulence intensity under different wind speed conditions. Due to the additional influence of thermal effects on turbulence, low-speed airflow is more prone to fluctuations and instability, resulting in a significant decrease in turbulence intensity with increasing wind speed, while turbulence intensity is higher at low wind speeds.

[0102] Figure 3b The probability distribution of turbulence intensity within different wind speed ranges is displayed, revealing the distribution characteristics of turbulence intensity at various wind speeds. When the wind speed is greater than 4m / s, the probability distribution of turbulence intensity tends to be stable, and the amplitude of variation is significantly reduced. By statistically analyzing the arithmetic mean of turbulence intensity within different wind speed ranges, the following results can be obtained: the average turbulence intensity is 0.303 when the wind speed is greater than 0m / s; 0.165 when the wind speed is greater than 4m / s; 0.136 when the wind speed is greater than 6m / s; 0.117 when the wind speed is greater than 8m / s; and 0.114 when the wind speed is greater than 10m / s. As the wind speed increases, the average turbulence intensity shows a continuous downward trend, indicating that the relative disturbance of turbulence in high wind speed environments is weakened and the airflow tends to be stable.

[0103] S103: Setting CFD simulation boundary conditions.

[0104] 3.1. The average wind profile, turbulent kinetic energy, and turbulent dissipation rate in the velocity inlet boundary condition are implemented by writing a UDF (User-Defined Function) in the Fluent software; the terrain boundary is defined as a no-slip boundary, the wall roughness constant is set to 0.5, and the roughness height is set to 0.35 m; the outlet condition is set as a pressure outlet, and the remaining surfaces are set as symmetry boundaries.

[0105] 3.2. Unstructured meshing is adopted. The thickness of the first inflation layer is 2 m, the growth rate is 1.05, and a total of 5 inflation layers are set. The results of the grid independence test show that a grid number of 4.5 million achieves a good balance between calculation accuracy and calculation efficiency.

[0106] 3.3. The Reynolds-averaged N-S equations are used in the numerical simulation method, the Realizable k-ε model is adopted for the turbulence model, a pressure-based steady solver is used, the pressure-velocity coupling is processed by the SIMPLEC algorithm, the discretization format is a second-order accuracy format, and the criterion for judging the simulation convergence is that each residual drops below 10 -3 as follows.

[0107] S104. Extract and analyze the simulation results to identify the key areas of sudden wind speed increase.

[0108] 4.1. Since the main wind directions at the QTT site are north and south, and strong winds are mostly concentrated in the due south direction, two velocity inlets, north and south, are set, the initial wind speed is set to 10 m / s, and the post-processing software is used to analyze the flow field structure of the site. The wind speed distribution contour map is shown in Figure 5.

[0109] 4.2. Under the condition of northward incoming wind, the terrain on the north side of the site has a significant constraining effect on the airflow. The airflow is forced to gather in the narrow valley, resulting in an increase in wind speed and forming a typical "canyon wind effect". After the airflow passes through the valley mouth, it gradually climbs along the terrain, forming Figure 5a a high wind speed area.

[0110] 4.3. Under the condition of southward incoming wind, due to the openness of the terrain on the south side and the acceleration effect of the distant mountains, a wind speed sudden increase area appears in the southwest direction of the radio telescope, as shown in Figure 5b Figure. This terrain acceleration effect significantly affects the wind speed distribution at the QTT site and also explains the phenomenon that the southward incoming wind accounts for the highest proportion of strong winds in the measured wind data. The layout of the windbreak net at this location should be considered as a key point in the future.

[0111] S105. Design and optimize the windbreak net layout plan.

[0112] 5.1. According to topographic features such as slope and aspect, and the main wind direction, combined with the CFD simulation results, clarify the scope and shape of the area with sudden wind speed increase, and set up a windbreak layout plan for the area with sudden wind speed increase.

[0113] 5.2. Define the windbreak as a porous medium model using the additional source term method, introduce different windbreak layout plans, and simulate the wind speed regulation effect. Define the windbreak as a porous zone in the flow field domain, add an additional source term to the momentum equation, and simulate the changes in the airflow before and after passing through the windbreak, so as to solve the problems of modeling and mesh generation.

[0114] The simplified form of the additional source term in the momentum equation is formula (3). In actual situations, the viscous drag coefficient is much smaller than the inertial drag coefficient, and the viscous loss term -μD i u i can be neglected.

[0115] 5.3. The optimized windbreak layout plan for the valley on the north side of the QTT site is as Figure 6a shown. The five-pointed star represents the QTT position. Comparing each layout plan, the finally selected double-layer layout plan can play a role in extending the windbreak distance; for the area with sudden wind speed increase on the south side of the site, a 200m-long windbreak arranged on the south side of QTT can effectively reduce the wind speed at the position of the radio telescope. The simulation results show that the wind speed at the antenna position drops by about 30%, as Figure 6b shown.

[0116] The various embodiments in this specification are described in a progressive manner. For the same or similar parts between the various embodiments, reference can be made to each other. The key points of each embodiment are the differences from other embodiments. All or part of the present invention can be used in many general or special computer system environments or configurations. For example: personal computers, server computers, handheld devices or portable devices, tablet devices, mobile communication terminals, multi-processor systems, microprocessor-based systems, programmable electronic devices, network PCs, minicomputers, mainframe computers, distributed computing environments including any of the above systems or devices, and so on.

[0117] The above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit the present invention; although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that: they can still modify the technical solutions recorded in the foregoing embodiments, or perform equivalent replacements on some or all of the technical features; and these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the present invention.

Claims

1. A method for regulating the wind field of a radio telescope site based on measured data and CFD, characterized in that, Including: Obtain the wind speed and direction data collected by the wind tower, perform data preprocessing on the wind speed and direction data to obtain the preprocessed wind speed and direction data; Obtain the digital elevation model data of the site area, perform model preprocessing on the digital elevation model data to obtain the three-dimensional terrain model of the radio telescope site; Calculate the average wind characteristics and pulsating wind characteristics of the site based on the preprocessed wind speed and direction data; Use the average wind characteristics and pulsating wind characteristics of the site as boundary conditions, and perform CFD simulation using the three-dimensional terrain model to obtain the simulation results; Identify multiple key areas with sudden wind speed increase according to the simulation results, set windbreak nets in the multiple key areas according to different wind prevention schemes, and perform simulation according to different wind prevention schemes to obtain the optimal wind prevention scheme.

2. The method for regulating the wind field of a radio telescope site based on measured data and CFD according to claim 1, wherein The performing data preprocessing on the wind speed and direction data to obtain the preprocessed wind speed and direction data includes: Perform abnormal data preprocessing on the wind speed and direction data by interpolation patching or deletion to obtain the preprocessed wind speed and direction data; wherein, the abnormal data includes: time series overlapping data and / or missing data.

3. The method for regulating the wind field of a radio telescope site based on measured data and CFD according to claim 1, wherein The performing model preprocessing on the digital elevation model data to obtain the three-dimensional terrain model of the radio telescope site includes: Process the digital elevation model data through a geographic information system to obtain geographic elevation data; Convert the geographic elevation data into three-dimensional space coordinate points and export them to generate three-dimensional coordinate point cloud data recognizable by modeling software; Use three-dimensional modeling software to construct the three-dimensional terrain model of the radio telescope site according to the three-dimensional coordinate point cloud data to ensure that the spatial accuracy of the model conforms to the true terrain features.

4. The method for regulating the wind field of a radio telescope site based on measured data and CFD according to claim 1, wherein The calculating the average wind characteristics and pulsating wind characteristics of the site based on the preprocessed wind speed and direction data includes: Calculate the average wind profile based on the preprocessed wind speed and direction data; Calculate the turbulence intensity within a period of time based on the preprocessed wind speed and direction data; Wherein, the average wind characteristics of the site include: wind speed, wind direction and average wind profile; the pulsating wind characteristics include: turbulence intensity within a period of time.

5. The method for regulating the wind field of a radio telescope site based on measured data and CFD according to claim 4, wherein The calculating the average wind profile based on the preprocessed wind speed and direction data includes: Calculate the average wind profile based on the preprocessed wind speed and direction data using the average wind profile calculation formula; wherein, the average wind profile calculation formula is expressed as: Among them, U ref represents the wind speed at the reference height; Z represents the height; a represents the wind profile exponent; U z represents the average wind profile at height Z.

6. The method for regulating the wind field of a radio telescope site based on measured data and CFD according to claim 4, characterized in that The calculating the turbulence intensity within a period of time based on the preprocessed wind speed and direction data includes: Calculate the turbulence intensity within a period of time based on the preprocessed wind speed and direction data using the turbulence intensity calculation formula; wherein, the turbulence intensity calculation formula is expressed as: Among them, σ u represents the standard deviation of the wind speed fluctuation within a period of time; U represents the average wind speed within a period of time; I represents the turbulence intensity within a period of time.

7. The method for regulating the wind field of a radio telescope site based on measured data and CFD according to claim 1, characterized in that The identifying multiple key areas with sudden wind speed increase according to the simulation results and setting windbreak nets in the multiple key areas according to different wind prevention schemes includes: Based on the terrain characteristics and the incoming wind direction, combined with the simulation results, clarify the scope and shape of the area with sudden wind speed increase to obtain multiple key areas with sudden wind speed increase; Use the additional source term method to define the windbreak net as a porous medium model, and introduce different porous medium models at different positions in multiple key areas to obtain different wind prevention schemes for setting windbreak nets.

8. The method for regulating the wind field of a radio telescope site based on measured data and CFD according to claim 1, characterized in that Performing simulations according to different wind prevention schemes to obtain an optimal wind prevention scheme, including: Determining the momentum corresponding to different wind prevention schemes, and designing the aperture size of the porous medium model in the wind prevention scheme according to different momenta; Judging whether the wind speeds corresponding to different wind prevention schemes can reach the wind prevention efficiency index. If so, obtaining the optimal wind prevention scheme; if not, discarding the scheme.

9. The method for regulating the wind field of a radio telescope site based on measured data and CFD according to claim 8, wherein The calculation formula of the momentum is expressed as: where μ represents the fluid viscosity coefficient; D i represents the i-th component of the viscous drag coefficient. Under high Reynolds number conditions, the viscous drag term can be neglected; C i represents the i-th component of the inertial drag coefficient; ρ represents the air density; u represents the velocity; u i represents the i-th component of the velocity.

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