A rapid random flow generator based on ‘GPU stream cubes’ for turbulent wind fields

The computational efficiency bottlenecks of existing random flow generators were analysed. To address these bottlenecks, a three-dimensional turbulent wind field random parallel generator based on GPU (Graphics Processing Unit) acceleration strategies was proposed. The proposed method employs a ‘GPU stream cubes’ strategy to enable efficient parallel synthesis of inlet turbulence. Multiple simulation scenarios were used to evaluate different acceleration schemes and verify the effectiveness of the proposed approach. The three-dimensional scheme achieves speedups exceeding 100× in most configurations, whereas the one-dimensional scheme provides only limited acceleration. For identical wind-field parameters, the GPU-based results agree well with the traditional CPU-based method, indicating that accuracy and stability are preserved. Four representative urban wind-field cases, from an idealised block to a WRF–CFD multiscale-coupled scenario, further demonstrate the applicability of the method to city-scale inflow turbulence synthesis. In addition, an efficient turbulence generation software tool for wind turbine simulation was developed based on the proposed method.