Turbulence Generation from a stochastic wavelet model
For researchers in fluid dynamics and turbulence simulation, this offers a more efficient and adaptive alternative to existing synthetic turbulence methods.
The paper introduces a turbulence generation method using stochastic wavelets that requires fewer basis functions than Fourier methods and adaptively handles inhomogeneous turbulence with lower computational cost, achieving good agreement with theoretical results.
This research presents a new turbulence generation method based on stochastic wavelets and tests its various properties in both homogeneous and inhomogeneous turbulence. Turbulence field can be generated with less basis compared to previous synthetic Fourier methods. Adaptive generation of inhomogeneous turbulence is achieved by scale reduction algorithm and lead to smaller computation cost. The generated turbulence shows good agreement with input data and theoretical results.