CN110263369B - Building surface wind resistance grade design method based on climate analysis and numerical simulation - Google Patents
Building surface wind resistance grade design method based on climate analysis and numerical simulation Download PDFInfo
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Abstract
The invention discloses a method for designing wind resistance grades on a building surface based on climate analysis and numerical simulation. When extreme strong wind of a building area is simulated by using the extremum distribution model, the simulation results of different extremum distribution models and parameter estimation schemes are checked, and finally the extremum model which is closer to the actual value is determined, so that the simulation result is more reliable than that of the single extremum model. In CFD numerical simulation, the extreme wind of the initial field is divided into 16 wind directions, different wind directions correspond to different wind speed values, the simulation result is more comprehensive than the simulation of the extreme wind of only one wind direction, and the cost is saved compared with the situation that the extreme wind of the initial field corresponds to the same wind speed value of 16 wind directions in building design.
Description
Technical Field
The invention relates to the technical field of building design, in particular to a method for designing a wind resistance grade of a building surface based on climate analysis and numerical simulation.
Background
Wind is a meteorological factor that needs careful consideration in building design, and with global warming, extremely high wind events are more frequent, and wind disaster accidents occur. In the last century, a hotel in Ningxia flies down with a curtain wall glass under the occasional gusts, and the pedestrians at the gate of the hotel are killed on the spot; in addition, all curtain wall glass is almost destroyed under the strong blowing of strong wind at night of the Yifu building of Zhejiang university; in typhoon seasons, the case of blowing down the building, the structural belt, curtain wall glass and the like by leeward is quite common in coastal cities. Therefore, how to utilize climate analysis and numerical mode to guide building planning and layout according to the wind environment of the place where the building is located and accurately calculate the wind resistance grade of the surface of the building, so that the building cost can be saved while the wind disaster is prevented, and the method is an urgent task in front of building design departments and construction units.
The foreign research on the wind environment of the building starts from the middle 60 th century, and in 1965, on a meeting which is held in London and is based on a 'building structure and a wind effect generated by the building structure', baines proposes the wind environment influence characteristics of the high-rise building obtained through wind tunnel experiments and field investigation, and the wind tunnel experiments are gradually applied to the simulation of the wind environment of the urban building. Stathopoulos and Wu (1995) discusses the influence on wind speed from street space density, surrounding building height, relative position, wind direction angle by wind tunnel experiments. However, in wind tunnel experiments, all physical quantities cannot be satisfied at the same time, the preparation time is long, the experiment cost is high, the model manufacturing is time-consuming and labor-consuming, and the model manufacturing cannot be widely applied, and along with the continuous development of computer technology and simulation software, the CFD (Computational Fluid Dynamics, computable fluid dynamics) numerical simulation is a research method which is widely applied at the present stage. Compared with wind tunnel experiments, the numerical simulation is more convenient and efficient, the feasibility and the accuracy of the numerical simulation are also verified by a plurality of students, for example, in 2009, the wind tunnel experiments and CFD numerical simulation are adopted by Block en and Person to average the wind environment around a certain stadium, and the experimental results and the simulation results are compared, so that the result coincidence degree of the two results is extremely high.
In the current wind load and wind resistance design of buildings in China, the wind load and wind resistance design is mainly calculated according to the maximum wind speed of each station in the reproduction period of 50 years, but the wind disaster accidents frequently occur prove that the wind resistance design of the building industry still has the following problems. First, with global warming, extreme wind disasters will become more frequent, and recurring periods can be 100 years or longer, and thus should be specific to individual buildings; secondly, the national station distribution with long-time observation data is sparse, and some of the national stations are far away from a target building, and correction is needed by utilizing automatic weather station data closest to the building; thirdly, wind tunnel tests used by a plurality of building units neglect the influence of surrounding terrains and buildings on target buildings; fourth, in the previous study, only the absolute wind speed value is considered for the high wind in the reproduction period, but no wind direction is considered, and if the simulation of the high wind in 16 directions can be performed, the simulation has great significance for the economical efficiency and the safety of a specific building. Therefore, based on climate analysis and numerical simulation, more refined calculation of the wind resistance level of the building surface is of great necessity.
Disclosure of Invention
Aiming at the defects of the prior art, the invention provides the method for determining the extremum model which is closer to the actual value by checking the simulation results of different extremum distribution models and parameter estimation schemes; and in CFD numerical simulation, the extremely high wind of the initial field is divided into 16 wind directions, so that the simulation is more comprehensive, the cost is saved, and the design method for the wind resistance grade of the building surface based on climate analysis and numerical simulation is provided.
In order to solve the technical problems, the invention adopts the following technical scheme: a method for designing a wind resistance grade of a building surface based on climate analysis and numerical simulation is characterized by comprising the following steps of: the process is carried out according to the following procedure,
1. the method comprises the following specific steps of:
1) Establishing a national station annual maximum wind speed and an annual maximum wind speed sequence;
2) Fitting a national station annual maximum wind speed and an annual maximum wind speed sequence by using a plurality of extremum probability distribution models, finding out a model with the best fitting effect, obtaining the annual maximum wind speeds of a plurality of wind directions in different reproduction periods by using the model, and providing the annual maximum wind speeds of a plurality of wind directions in different reproduction periods based on gust factors;
3) Correcting the position of the building area by utilizing local weather station data;
4) Simulating an extreme value distribution model with optimal annual maximum wind speed and annual maximum wind speed fitting effect of the national station by using the probability distribution model Gumbel, frecht, weibull, GEV or GPD;
2. CFD numerical simulation:
1) After the reproduction period wind speeds of different heights and different wind directions of the building area are obtained, simulating the wind speed of the building surface, and integrating the simulation results of all the wind directions to finally obtain the wind resistance grade of the building surface;
2) Before simulation, carrying out three-dimensional modeling on the current building, and carrying out parameter setting before simulation;
3) The k-epsilon model is selected to simulate a wind field near the building, and all control differential equations of the k-epsilon model comprise a continuity equation, a momentum equation, a k equation and an epsilon equation, wherein the specific calculation formula is as follows:
continuity equation:，
momentum equation:，
k equation:，
epsilon equation:，
wherein the turbulent viscosity coefficient isModel constant->，/>，/>，/>，/>；
4) The WIND field type is selected as WIND, the speed interface of the inlet boundary layer is set as a power exponent function higher than the ground, the power exponent is 0.3, the flow of the supposed WIND on the outflow surface is recovered to the state without building blocking, the outlet pressure is set as atmospheric pressure, the simulation iteration times are set, each WIND direction and the corresponding WIND speed are used as initial WIND fields, and simulation is started;
finally, after the simulation results of a plurality of scenes are obtained, the maximum value of the simulation results of the scenes is taken from the building surface, and the wind resistance grade of the building surface is comprehensively obtained, wherein the specific formula is as follows:
wind speed simulated for 16 scenes respectively, wherein +.>Is the building position in the rectangular coordinate system.
In step 4) of the first step, a distribution model gummel distribution is used, the function expression of which is:
wherein,for the sample->For the position parameter +.>Is a scale parameter.
In the second step, PHOENICS software developed by CHAM institute of Imperial academy of technology in the United kingdom is utilized to simulate the wind speed of the building surface, and parameter settings before simulation are carried out on PHOENICS, and various turbulence models including various variations of a Reynolds stress model, a flux model, a multi-fluid turbulence model and a k-epsilon model are built in PHOENICS, and the wind flow of the building belongs to incompressible low-speed turbulence and accords with Boussinesq assumption.
In step 2) of the second step, since the surrounding terrain and the building may have a certain influence on the wind speed of the target building, the terrain and the surrounding building near the target building need to be actually represented, but if there is no terrain that significantly affects the wind speed, it may not be represented.
In the second step, step 4), during simulation, the length and width of the calculated area are respectively 2.5km and 2.3km, the height is 0.6km, the horizontal resolution is 10m, the vertical resolution is 5m, the directions of X and Y, Z are respectively 250, 230 and 80 grids, and the simulation iteration number is 500. Of course, this is only a specific scheme, and parameters corresponding to different buildings can also be different.
In the first step, the annual maximum wind speed is 10min average annual maximum wind speed, and the annual maximum wind speed is 3s instantaneous annual maximum wind speed, wherein the annual maximum wind speed is subdivided into 16 wind directions, and the annual maximum wind speed records the corresponding wind directions.
In the first step and the second step, the annual maximum wind speeds of different reproduction periods of 16 wind directions are obtained by using a plurality of extremum probability distribution models, and the annual maximum wind speeds of different reproduction periods of 16 wind directions are given based on gust factors.
The invention calculates the wind resistance grade of the building surface based on climate analysis and numerical simulation, and the calculation is divided into two parts, namely, the strong wind simulation of different reproduction periods of the building area and the CFD numerical simulation. When extreme strong wind of a building area is simulated by using the extremum distribution model, the simulation results of different extremum distribution models and parameter estimation schemes are checked, and finally the extremum model which is closer to the actual value is determined, so that the simulation result is more reliable than that of the single extremum model. In CFD numerical simulation, the extreme wind of the initial field is divided into 16 wind directions, different wind directions correspond to different wind speed values, the simulation result is more comprehensive than the simulation of the extreme wind of only one wind direction, and the cost is saved compared with the situation that the extreme wind of the initial field corresponds to the same wind speed value of 16 wind directions in building design.
Drawings
FIG. 1 is a schematic diagram of a simulation flow of the present invention;
FIG. 2 is a schematic view of a certain identified super high-rise building group in the gold bay area of Zhuhai city, wherein (a) is a three-dimensional perspective model view and (b) is an overhead view;
FIG. 3 is a graph of building surface and ground wind velocity profile, where a, c, e are front view (north upward), b, d, f are back view (north upward), in m/s;
FIG. 4 is a schematic representation of the division of the strong wind on the surface of the aforementioned marked super high building complex in the gold bay area of the Zhuhai city, where (a) is the front side and (b) is the back side.
Detailed Description
The invention is further described below in connection with specific embodiments.
In this embodiment, the method for designing the wind resistance level of the building surface based on climate analysis and numerical simulation takes a certain marked ultra-high building group in the gold bay area of the zhuhai city as an example, and analyzes the wind resistance level of the building surface, and referring to fig. 1, the specific steps are as follows:
1. high wind simulation of different reproduction periods of building area
The reproduction period calculation needs to be based on long-term climate statistics, and the longer the data time is, the more accurate the calculation result is. The data of the national station generally has a longer period, and can be used as a sample of an extremum distribution model so as to simulate extremely high winds under different reproduction periods. However, sometimes the national station is far away from the target building, for example, the distance between the pearl sea station and a certain marked ultrahigh building group in the gold bay area of the pearl sea city is about 30km, the middle is blocked by mountains and rivers, the weather background of the target building can not be represented well, the observation period of the automatic red flag weather station near the building is short, and the automatic red flag weather station can not be directly used for calculating an extremum model, so that the extremely high wind simulation result of the pearl sea station can only be corrected by using the data of the red flag station. The method comprises the following specific steps:
(1) Establishing a sequence of the annual maximum wind speed and the annual maximum wind speed of the pearl sea station, wherein the annual maximum wind speed is only 10min, the average annual maximum wind speed is 3s of instantaneous annual maximum wind speed, the annual maximum wind speed is subdivided into 16 wind directions, and the annual maximum wind speed only records the corresponding wind direction;
(2) Fitting the annual maximum wind speed and the annual maximum wind speed sequence of the pearl sea station by using a plurality of extremum probability distribution models, finding out a model with the best fitting effect, obtaining the annual maximum wind speeds of different reproduction periods of 16 wind directions by using the model, and giving the annual maximum wind speeds of different reproduction periods of 16 wind directions based on gust factors (refer to 2012 edition of building structure load specification);
(3) The red flag automatic weather station data is utilized to correct the red flag automatic weather station data to the position of a building area (refer to the "weather feasibility demonstration Specification-wind resistance parameter calculation").
The common probability distribution model of the machine value is Gumbel, frecht, weibull, GEV, GPD, etc., and Gumbel distribution is recommended by building structure load standard, which is also an extremum distribution model with the best fitting effect of the annual maximum wind speed and the annual maximum wind speed of the pearl sea station, and the function expression is as follows:
（1）
wherein,for the sample->For the position parameter +.>Is a scale parameter.
2. CFD numerical simulation
After the reproduction period wind speeds of different heights and different wind directions of the building area are obtained, the PHOENICS software developed by CHAM institute of technology of Imperial academy of China is utilized to simulate the wind speed of the building surface, the simulation results of all wind directions are integrated, and finally the wind resistance grade of the building surface is obtained.
Before simulation, the current building is subjected to three-dimensional modeling, and fig. 2 (a) and (b) are respectively a three-dimensional model diagram and an overhead diagram of the building group, wherein Y points to north. Considering that the surrounding terrain and buildings may have some effect on the wind speed of the target building, it is generally necessary to actually embody the terrain and surrounding buildings near the target building. The method has no obvious topographic influence near a certain marked ultrahigh building group in the gold bay area of the Zhuhai city, and is built on the flat ground, so that the influence of the topography is not considered, and only the buildings within 1km of the target building are modeled.
The PHOENICS software is then subjected to pre-simulation parameter settings. The PHOENICS software incorporates a wide variety of turbulence models including Reynolds stress model, flux model, multi-fluid turbulence model and k- ε model variations, while the wind flow of a building is generally of incompressible, low velocity turbulence, conforming to the Boussinesq assumption, so the k- ε model is selected to simulate the wind field around the building. All control differential equations of the k-epsilon model comprise a continuity equation, a momentum equation, a k equation and an epsilon equation, and the specific calculation formula is as follows:
continuity equation:， （2）
momentum equation:， （3）
k equation: ， （4）
epsilon equation:， （5）
wherein the turbulent viscosity coefficient isModel constant->，/>，/>，/>，/>。
The WIND field type is selected as WIND, the inlet boundary layer velocity interface is set to a power exponent function above ground, the power exponent is 0.3, and the outlet pressure is set to atmospheric pressure assuming that the flow of WIND has recovered to a state without building blockage on the outlet face. The length and width of the calculated area are 2.5km and 2.3km respectively, the height is 0.6km, the horizontal resolution is 10m, the vertical resolution is 5m, and 250, 230 and 80 grid points are respectively arranged in the X and Y, Z directions. The simulation iteration number was 500, and the simulation was started with the initial wind field of 16 wind directions and the corresponding wind speeds. The 16 scenes of the 50-year recurrent extremely high wind simulation of a certain marked ultrahigh building group in the gold bay area of the pearl sea are shown in table 1, three wind directions with larger representative wind speeds in the 16 wind directions are ENE, E, ESE respectively, and the specific simulation results are shown in fig. 3.
Finally, after the simulation results of 16 scenes are obtained, the building surface takes the maximum value of the simulation results of 16 scenes, and the wind resistance grade of the building surface is comprehensively obtained, as shown in fig. 4, the specific formula is as follows:
（6）
wind speed simulated for 16 scenes respectively, wherein +.>Is the building position in the rectangular coordinate system.
Table 1 extreme gust simulation scenario for 50 years recurring period of certain marked ultra-high building group in gold bay area of zhuhai city
The foregoing detailed description of the invention has been presented for purposes of illustration and description, but is not intended to limit the scope of the invention, i.e., the invention is not limited to the details shown and described.
Claims (5)
1. A method for designing a wind resistance grade of a building surface based on climate analysis and numerical simulation is characterized by comprising the following steps of: the process is carried out according to the following procedure,
1. the method comprises the following specific steps of:
1) Establishing a national station annual maximum wind speed and an annual maximum wind speed sequence;
2) Fitting a national station annual maximum wind speed and an annual maximum wind speed sequence by using a plurality of extremum probability distribution models, finding out a model with the best fitting effect, obtaining the annual maximum wind speeds of a plurality of wind directions in different reproduction periods by using the model, and providing the annual maximum wind speeds of a plurality of wind directions in different reproduction periods based on gust factors;
3) Correcting the position of the building area by utilizing local weather station data;
4) Simulating the national station annual maximum wind speed and the extremum distribution model with the optimal annual maximum wind speed fitting effect by using the extremum probability distribution model Gumbel, frecht, weibull, GEV or the GPD;
2. CFD numerical simulation:
1) After the reproduction period wind speeds of different heights and different wind directions of the building area are obtained, simulating the wind speed of the building surface, and integrating the simulation results of all the wind directions to finally obtain the wind resistance grade of the building surface;
2) Before simulation, carrying out three-dimensional modeling on the current building, and carrying out parameter setting before simulation;
3) The k-epsilon model is selected to simulate a wind field near the building, and all control differential equations of the k-epsilon model comprise a continuity equation, a momentum equation, a k equation and an epsilon equation, wherein the specific calculation formula is as follows:
continuity equation:
momentum equation:
k equation:
epsilon equation:
wherein the turbulent viscosity coefficient isModel constant c μ ＝0.09，c 1 ＝1.44，c 2 ＝1.92，σ k ＝1.0，σ ε ＝1.3；
4) The WIND field type is selected as WIND, the speed interface of the inlet boundary layer is set as a power exponent function higher than the ground, the power exponent is 0.3, the flow of the supposed WIND on the outflow surface is recovered to the state without building blocking, the outlet pressure is set as atmospheric pressure, the simulation iteration times are set, each WIND direction and the corresponding WIND speed are used as initial WIND fields, and simulation is started;
finally, after the simulation results of a plurality of scenes are obtained, the maximum value of the simulation results of the scenes is taken from the building surface, and the wind resistance grade of the building surface is comprehensively obtained, wherein the specific formula is as follows:
u(i,j,k)＝max(u 1 (i,j,k),u 2 (i,j,k),...,u 16 (i,j,k))
u 1 (i,j,k),u 2 (i,j,k),...,u 16 (i, j, k) are wind speeds simulated by 16 scenes respectively, wherein i, j, k are building positions in a rectangular coordinate system;
in the step 2) of the second step, since the surrounding terrain and the buildings may have a certain influence on the wind speed of the target building, the terrain and the surrounding buildings near the target building need to be actually embodied;
in the first step, the annual maximum wind speed is 10min average annual maximum wind speed, and the annual maximum wind speed is 3s instantaneous annual maximum wind speed, wherein the annual maximum wind speed is subdivided into 16 wind directions, and the annual maximum wind speed records the corresponding wind directions.
2. The method for designing a wind resistance class of a building surface based on climate analysis and numerical simulation according to claim 1, wherein: in step 4) of the first step, a distribution model gummel distribution is used, the function expression of which is:
where x is the sample, μ is the position parameter, σ is the scale parameter.
3. The method for designing a wind resistance class of a building surface based on climate analysis and numerical simulation according to claim 1, wherein: in the second step, PHOENICS software developed by CHAM institute of Imperial academy of technology in the United kingdom is utilized to simulate the wind speed of the building surface, and parameter settings before simulation are carried out on PHOENICS, and various turbulence models including various variations of a Reynolds stress model, a flux model, a multi-fluid turbulence model and a k-epsilon model are built in PHOENICS, and the wind flow of the building belongs to incompressible low-speed turbulence and accords with Boussinesq assumption.
4. The method for designing a wind resistance class of a building surface based on climate analysis and numerical simulation according to claim 1, wherein: in the second step, step 4), during simulation, the length and width of the calculated area are 2.5km and 2.3km respectively, the height is 0.6km, the horizontal resolution is set to be 10m, the vertical resolution is set to be 5m, the directions of X and Y, Z are provided with 250, 230 and 80 grid points respectively, and the simulation iteration number is set to be 500.
5. The method for designing a wind resistance class of a building surface based on climate analysis and numerical simulation according to claim 1, wherein: in the first step and the second step, the annual maximum wind speeds of different reproduction periods of 16 wind directions are obtained by using a plurality of extremum probability distribution models, and the annual maximum wind speeds of different reproduction periods of 16 wind directions are given based on gust factors.
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| 极值风速风向的联合概率密度函数;楼文娟等;《浙江大学学报(工学版)》;20170630(第06期);第6-12页 * |
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