Wind Field Calculation Research Articles

Application of Computer-based Simulation Analysis in Green Architecture Design

Through simulation calculation of sunshine, wind field and noise in Lize Financial Business District, it is suggested that natural light should be introduced into the room to make up for the influence of insufficient sunshine, or lighting fixtures with low energy consumption should be selected for artificial lighting., land owners should design solar photovoltaic power generation properly, an open structure should be adopted at the bottom of the annex building to guide the natural wind and enhance the ventilation. According to the sound insulation requirements at different heights of buildings and those in different facade directions at the same height, sound-proof windows made of different materials with different performance should be selected to ensure the maximum use of natural lighting and ventilation, energy conservation and environmental optimization of buildings in the region, meeting the requirements of people for indoor and outdoor comfort.

Automatic block dimensioning on GPU-accelerated programs through particle swarm optimization

Abstract Context Nowadays, the use of GPU to improve performance of computationally expensive systems are widely explored. On GPU-accelerated programs, performance is related to the partition of the problem into blocks of threads in such a way that the parallel tasks to be executed better fit the GPU architecture. Although there exists some general guidelines to help defining block dimensions, finding the optimum partition is still a complex and problem dependent task. In this work, it has been investigated the use of particle swarm optimization (PSO) to optimize blocks dimensions aiming to minimize programs execution time. The approach was evaluated on a GPU-accelerated wind field calculation program, in which block dimensioning was based on literature guidelines and empirical adjusts. Before PSO optimization, the program was about 25 times faster than the sequential program. After applying PSO, speedup increased to about 60 times. Unexpected optimized configurations were observed, ratifying that finding optimum dimensioning is a complex task. So the use of a robust optimization tool, such as PSO, demonstrated to be very profitable, allowing automatic optimization of blocks dimensions without necessity of a priori knowledge about problem, programs peculiarities and GPU architecture. Objective Improve speedup of GPU-accelerated programs by automatic defining optimized block dimensions using PSO. Method A GPU-accelerated wind field calculation problem has been focused. A PSO was interfaced to the program in order to find the block dimensions that leads to a minimum execution time. Results were compared to literature results. Results The speedup obtained with the proposed approach is more than 2 times the original speedup. Conclusion PSO, demonstrated to be very profitable, allowing automatic optimization of blocks dimensions without necessity of a priori knowledge about problem/programs peculiarities and/or GPU architecture.

Numerical Simulation and Analysis on Spray Drift Movement of Multirotor Plant Protection Unmanned Aerial Vehicle

In recent years, multirotor unmanned aerial vehicles (UAVs) have become more and more important in the field of plant protection in China. Multirotor unmanned plant protection UAVs have been widely used in vast plains, hills, mountains, and other regions, and become an integral part of China’s agricultural mechanization and modernization. The easy takeoff and landing performances of UAVs are urgently required for timely and effective spraying, especially in dispersed plots and hilly mountains. However, the unclearness of wind field distribution leads to more serious droplet drift problems. The drift and distribution of droplets, which depend on airflow distribution characteristics of UAVs and the droplet size of the nozzle, are directly related to the control effect of pesticide and crop growth in different growth periods. This paper proposes an approach to research the influence of the downwash and windward airflow on the motion distribution of droplet group for the SLK-5 six-rotor plant protection UAV. At first, based on the Navier-Stokes (N-S) equation and SST k–ε turbulence model, the three-dimensional wind field numerical model is established for a six-rotor plant protection UAV under 3 kg load condition. Droplet discrete phase is added to N-S equation, the momentum and energy equations are also corrected for continuous phase to establish a two-phase flow model, and a three-dimensional two-phase flow model is finally established for the six-rotor plant protection UAV. By comparing with the experiment, this paper verifies the feasibility and accuracy of a computational fluid dynamics (CFD) method in the calculation of wind field and spraying two-phase flow field. Analyses are carried out through the combination of computational fluid dynamics and radial basis neural network, and this paper, finally, discusses the influence of windward airflow and droplet size on the movement of droplet groups.

A Spark-Based High Performance Computational Approach for Simulating Typhoon Wind Fields

The impacts of typhoons on coastal areas around the globe necessitate the risk assessments of typhoon events to analyze their paths, intensity, and impacts on the environment for disaster prevention and reduction as well as for the scientific assessments of typhoon impacts. To this end, the typhoon wind field needs to be obtained by inversion to attain its temporal and spatial scopes of influence and disaster-inducing intensities using simulation algorithms that are based on the existing typhoon path data. The wind field calculation is a typical kind of compute-intensive processing. It is time-consuming (especially when the temporal resolution and the spatial resolution are high) to an extent, which makes it difficult for a traditional stand-alone computation to meet the application needs for typhoon risk assessments. Therefore, studies need to be conducted to accelerate the wind field calculations. Currently, the most economical and relatively feasible method is to rapidly generate a large quantity of typhoon risk data using multi-thread, graphics processing unit computing or clustering technologies (e.g., cloud computing). Hence, we have attempted to use the latest cloud computing framework, Spark, for the rapid simulation of the typhoon wind field. This paper proposed a storage model for typhoon paths and wind fields under the Spark environment, as well as a wind field parallel acceleration method based on Spark. Using this approach, we have calculated a total of 1038 historical wind fields that impacted the northwestern Pacific Ocean from 1949 to 2014. The results indicate that the Spark-based wind field computation method proposed in this paper has a greater advantage in terms of performance, which facilitates the typhoon risk assessment feasibility.

Enhanced air dispersion modelling at a typical Chinese nuclear power plant site: Coupling RIMPUFF with two advanced diagnostic wind models

An enhanced air dispersion modelling scheme is proposed to cope with the building layout and complex terrain of a typical Chinese nuclear power plant (NPP) site. In this modelling, the California Meteorological Model (CALMET) and the Stationary Wind Fit and Turbulence (SWIFT) are coupled with the Risø Mesoscale PUFF model (RIMPUFF) for refined wind field calculation. The near-field diffusion coefficient correction scheme of the Atmospheric Relative Concentrations in the Building Wakes Computer Code (ARCON96) is adopted to characterize dispersion in building arrays. The proposed method is evaluated by a wind tunnel experiment that replicates the typical Chinese NPP site. For both wind speed/direction and air concentration, the enhanced modelling predictions agree well with the observations. The fraction of the predictions within a factor of 2 and 5 of observations exceeds 55% and 82% respectively in the building area and the complex terrain area. This demonstrates the feasibility of the new enhanced modelling for typical Chinese NPP sites.

Wind field parallelization based on Schwarz alternating domain decomposition method

Wind field is a critical issue in forest fire propagation prediction. However, wind field calculation is a complex problem that, for large terrains, involves solving huge linear systems. To solve such systems, the Preconditioned Conjugate Gradient (PCG) solver is applied. SSOR and Jacobi preconditioners are usually used, but solving such systems takes too much time and makes the approach unfeasible in real time operation. Parallelization appears as a way to make the approach operational in real time. The PCG with both preconditioners has been parallelized to accelerate the execution. However, the improvement in execution time is not enough, and the Schwarz alternating domain decomposition has been applied to exploit a second level of parallelism. Using this method, the linear system is decomposed in a set of overlapped subdomains that can be solved in parallel using a Master/Worker paradigm, where each worker exploits the PCG solver parallelism. As a result, the wind field calculation time is significantly reduced; for example, a large map of 1200×1200 cells, whose solution took more than 2000 seconds in the original WindNinja, can now be solved in less than 240 seconds using 4 subdomain and 4 cores per subdomain.

Fluctuating wind field analysis based on random Fourier spectrum for wind induced response of high-rise structures

An accurate calculation of the stochastic wind field is the foundation for analyzing wind-induced structure response and reliability. In this research, the spatial correlation of structural wind field was considered based on the time domain method. A method for calculating the stochastic wind field based on cross stochastic Fourier spectrum was proposed. A flowchart of the proposed methodology is also presented in this study to represent the algorithm and workflow. Along with the analysis of regional wind speed distribution, the wind speed time history sample was calculated, and the efficiency can therefore be verified. Results show that the proposed method and programs could provide an efficient simulation for the wind-induced structure response analysis, and help determine the related parameters easily.

Hybrid application to accelerate wind field calculation

Wind field calculation is a crucial point in predicting forest fire evolution in real emergencies. Such wind field calculation involves complex models that must be solved in a very short time to accomplish the real-time constraints of forest fire propagation prediction. However, when the terrain map under consideration is large (for example, 30km×30km) and the resolution is high (for example, 30m), the time incurred by wind field calculation makes its use unfeasible in real emergencies. To accelerate the wind field calculation, several approaches have been studied (map partitioning, domain decomposition and matrix storage). The results are quite significant, but in large cases, the execution time does not meet the expected objectives. Therefore, a new approach, integrating all the previous work, has been designed, and a hybrid MPI-OpenMP version of WindNinja has been implemented. This hybrid application exploits different sources of parallelism to reduce execution time without introducing a significant loss of accuracy in wind field calculation. The results obtained with different terrain maps show that the execution time is reduced to below an established limit of 100s.

Applying domain decomposition to wind field calculation

Predicting forest fire propagation is a crucial issue to mitigate fire damages.Wind significantly affects forest fire propagation.Wind field calculation implies solving extremely large systems of equations.The Schur method has been applied to accelerate wind field calculation.Execution time is reduced to accomplish operational requirements. Forest fire are natural hazards that every year cause significant looses. Predicting the evolution of a forest fire is a critical issue in mitigating its effects. Such predictions must accomplish strict real time constraints to be effective. Wind field calculation is a key issue in providing accurate forest fire propagation predictions. However, it implies solving large linear systems with 105 to 108 variables that takes too long using conventional methods. Therefore, the domain decomposition Schur method has been applied to accelerate wind field calculation. Using the Schur method, the linear system is significantly reduced and several phases can be parallelised exploiting cluster computing capabilities. Results show that the execution time for the wind field calculation of a map of 800 × 800 cells has been reduced from 400 s to 90 s using 10 nodes.

Applying vectorization of diagonal sparse matrix to accelerate wind field calculation

Wind field calculation is a critical issue in reaching accurate forest fire propagation predictions. However, when the involved terrain map is large, the amount of memory and the execution time can prevent them from being useful in an operational environment. Wind field calculation involves sparse matrices that are usually stored in CSR storage format. This storage format can cause sparse matrix-vector multiplications to create a bottleneck due to the number of cache misses involved. Moreover, the matrices involved are extremely sparse and follow a very well-defined pattern. Therefore, a new storage system has been designed to reduce memory requirements and cache misses in this particular sparse matrix-vector multiplication. Sparse matrix-vector multiplication has been implemented using this new storage format and taking advantage of the inherent parallelism of the operation. The new method has been implemented in OpenMP, MPI and CUDA and has been tested on different hardware configurations. The results are very promising and the execution time and memory requirements are significantly reduced.

Determining map partitioning to minimize wind field uncertainty in forest fire propagation prediction

Wind speed and direction are the parameters that most significantly affect forest fire propagation. The accurate estimation of such parameters is critical in providing precise predictions of forest fire propagation. Wind speed and direction can be measured in meteorological stations or estimated from meteorological models, but, in both cases, they are obtained at a very low resolution. Moreover, the meteorological wind is modified by the terrain topography and a complete wind field is generated with different wind speed and direction at any point of the terrain. So, wind field models providing wind speed and direction at a very high resolution (30m) are crucial in forest fire propagation prediction. WindNinja is one of the most widely used wind field simulators in this area. However, when the terrain map under consideration is very large (30km×30km or more), the execution time becomes unaffordable and the simulator cannot be used in real operation. A map partitioning strategy was developed to parallelize the wind field calculation and reduce the execution time to make it affordable. Map partitioning introduces a certain error in wind field that is propagated to forest fire propagation prediction. So, a complete methodology has been developed to determine the map partitioning that accomplishes real operation execution time constraints and keeps the forest fire propagation error below feasible limits. The experimental results show the execution time reduction accomplished and the accuracy of the wind field generated and forest fire propagation prediction.

Wind Shear Stress Interpolation over Lake Surface from Routine Weather Data Considering the IBL Development

In this paper a simple diagnostic wind field calculation scheme is presented which provides a spatially variable wind stress field over the lake surface for hydrodynamic modeling purposes. The goal was to develop a scheme that requires routine wind time series as input from stations located over or around the lake. The main idea is to embed an internal boundary layer model within a horizontal interpolation scheme, in this case, with inverse-distance weighting. The wind model reproduces reasonably well the increment of wind stress along the fetch due to the abrupt roughness change at the shoreline and the gradual roughening of the wavy lake surface. The proposed method is validated with wind measurements observed around Lake Balaton and through hydrodynamic modeling. Sensitivity to the parameters is analyzed, including the effect of the temporal averaging of the wind.

Adapting Map Resolution to Accomplish Execution Time Constraints in Wind Field Calculation

Abstract Forest fire propagation prediction is a key point to fight against such hazards. Several models and simulators have been developed to predict forest fire propagation. These models require input parameters such as digital elevation map, vegetation map, and other parameters describing the vegetation and meteorological conditions. Coupling wind field model and forest fire propagation model improves accuracy prediction, but increases significantly prediction time. This fact is critical since propagation prediction must be provided in advance to allow the control centers to manage firefighters in the best possible way. This work analyses WindNinja execution time, describes a WindNinja parallelisation based on map partitioning, determines the limitations of such methodology for large maps and presents an improvement based on adapting map resolution to accomplish execution time limitations.

A Flow-Condition-Based Interpolation Method Combined with Splitting Algorithm for Wind Field Calculation

Wind field calculation is a research focus for wind disaster prevention in Civil Engineering. A new finite element procedure using flow-condition-based interpolation method combined with splitting algorithm is proposed in the paper. It used the analytical solution of one-dimensional advection–diffusion equation, and naturally introduced upwind effect in element interpolation functions. Further, combined with splitting algorithm, the element interpolation functions of velocity and pressure have concise format without meet Babuska-Brezzi condition. A two dimension four-node bilateral fluid element was constructed using flow-condition-based interpolation method and a corresponding program was developed. The solution procedure was discussed in detail and the numerical example solution was given to illustrate the capabilities of the procedure

Study on Application of Mesoscale Meteorological Model for Wave Hindcasting

For a prediction of wave field where wave observation data do not exist, numerical wave estimation models such as SWAN are effective. For these models, global meteorological databases provided by ECMWF or NCEP can be used as wind input data; however these data may be coarse for wave hindcasting. In this study, to evaluate the fine wind field data for the wave hindcasting, the mesoscale meteorological model MM5 was applied. By applying the wind fields evaluated by MM5 to SWAN, the wave hindcasting was available with good accuracy. Moreover, for high waves produced by typhoon, it is well known that typhoon bogussing is effective, while wind field calculation at higher resolution without bogussing gave good estimations of wave fields as well.

OBSERVATION OF SNOWFALL BY RADAR RAFNGAUGE

To utilize data of Radar rain gauge in prediction for snowfall disttibution a model was proposed In this model, a calculation of wind field on arbitrary terrain is included. The accuracy of the prediction model are examined by comparisons with field data of hourly measurements of snow fall at seven sites, maximum snow depth distribution in dam depth basin and dam inflow.

Numerical simulation of daytime mesoscale flow over highly complex terrain: Alps case

The numerical study of mesoscale wind field and dispersion over terrains belonging to large mountain structures (e.g. Alps) poses a number of difficulties. Narrow valleys and steep slopes can considerably determine the temperature and pressure gradients, thus affecting the mesoscale systems in a quite complex manner. The adequate description of the local wind field, incorporating the high variability of the terrain features, is very important when a numerical simulation above highly complex terrain is attempted. The mathematical models used to reproduce the mesoscale flow in such cases must possess, besides the non-hydrostatic option, the ability to resolve the ground irregularities as realistically as possible. The increase of the spatial resolution would improve the terrain representation, but might require a prohibitively large CPU time and computer memory. DELTA-ADREA-DIPCOT is a numerical prediction code system, specifically designed to perform mesoscale wind field and dispersion calculations over terrains of high complexity, using moderate spatial resolution. This is achieved by recognizing subgrid ground features, such as slope and orientation variations, through a ground surface resolution higher than the one used for the atmosphere. The code system is here applied, focusing on the mesoscale meteorological systems over the Alpine mountainous area. The simulation is based on the data obtained in the framework of the TRANSALP Experimental Campaign, on 29 September 1990. The tracer concentration distribution is also examined, mainly as a further support to the meteorological conclusions. The predictions are compared with corresponding measurements and show a favourable agreement.

A numerical model for wind field and pollutant concentration calculations over complex terrain. Application to Athens, Greece

A non-hydrostatic, three-dimensional, prognostic, mesoscale model is developed for the calculation of the flow field and pollutant concentrations over complex terrain. The model solves numerically in an implicit, time-dependent manner the full Reynolds equations, in Cartesian, collocated grid arrangement. The differential equations are discretized by the finite volume method and solved iteratively with the SIMPLE algorithm. Turbulence closure is obtained by the two-equation ( k – ε ) turbulence model. A technique of partially covered cells is introduced for an accurate representation of complex terrain features. The greater area of Athens, Greece, which combines significant topographic and sea-breeze aerodynamic complexities, is chosen for the model performance evaluation. The results reproduce reasonably well the diurnal variation of the wind and pollutant concentration fields, and the comparison with available observations is satisfactory.

Simulation of Nocturnal Drainage Flows Enhanced by Deep Canyons: The Rocky Flats Case

Abstract The DELTA–ADREA (discretization with elements of triangle approach–atmospheric dispersion of pollutants over irregular terrain) numerical prediction model, developed at the National Center for Scientific Research Demokritos, is specifically designed to perform wind field calculations over terrains of high complexity. The numerical model has the capability to handle air–ground interaction processes by describing the ground-surface details while keeping the computation time at a reasonable level. The numerical model is applied here to a high-resolution topographical representation of the region surrounding the Rocky Flats Facility in Colorado, based on a digitized map consisting of approximately 4.8 × 106 points. Wind field calculations over the region are made using the atmospheric experimental data of 4 February 1991, collected by the participants within the Atmospheric Studies in Complex Terrain research program. The numerical predictions indicate strong drainage flows created at different altitudes with interaction between them, resulting in a quite complicated mesoscale wind field during nighttime. Available observations support the predicted flow features.

Wind flow simulation over greater Athens area with highly resolved topography

The code system containing the DELTA and the ADREA codes has been developed at the National Centre of Scientific Research (NCSR) “DEMOKRITOS” and performs mesoscale wind field calculations over terrains of high complexity. The code system follows a particular technique of discretization, according to which the ground can be treated with a resolution higher than the one used in the atmosphere. This technique, called “the high-resolution-ground-low-resolution-air” concept, offers to the code system the capability to reliably simulate the thermal air-ground interaction processes, keeping at the same time the computation storage and duration in reasonable levels. The above code system was applied to a high-resol ution representation of the Attika district, within a domain of 72 × 72 × 6.125 km 3. Mesoscale wind field calculations were made within the framework of the APSIS Phase-A Intercomparison Exercise, using the atmospheric radiosonde and surface data of 25 May 1990. In this particular day, the greater Athens area was dominated by the daytime thermally driven local systems, generated along the coastlines of the peninsula. The application of the DELTA-ADREA system reproduced the above mesoscale influences and exhibited a favourable agreement with observations.