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Turbulence generation from a stochastic wavelet model
Proceedings. Mathematical, Physical, and Engineering Sciences
|October 19, 2018
Summary
A novel stochastic wavelet method generates turbulence fields efficiently, requiring smaller bases than Fourier methods. This approach enables adaptive, cost-effective generation of inhomogeneous turbulence with high accuracy.
Area of Science:
- Fluid Dynamics
- Computational Physics
- Turbulence Modeling
Background:
- Accurate turbulence generation is crucial for simulating complex fluid flows.
- Existing methods like synthetic Fourier methods have limitations in computational cost and adaptability.
- The need for efficient and accurate turbulence generation for both homogeneous and inhomogeneous cases persists.
Purpose of the Study:
- To introduce a new turbulence generation method utilizing stochastic wavelets.
- To evaluate the efficiency and accuracy of this new method compared to existing techniques.
- To demonstrate the capability of generating adaptive inhomogeneous and anisotropic turbulence fields.
Main Methods:
- Development of a turbulence generation method based on stochastic wavelets.
- Testing turbulence field properties in both homogeneous and inhomogeneous scenarios.
- Implementation of a scale reduction algorithm for adaptive generation of inhomogeneous turbulence.
- Adjustment of the generating formula for fully inhomogeneous and anisotropic turbulence with RANS data.
Main Results:
- Turbulence fields generated with significantly smaller bases compared to synthetic Fourier methods.
- Comparable accuracy achieved with the stochastic wavelet method.
- Adaptive generation of inhomogeneous turbulence via scale reduction proved computationally inexpensive and accurate.
- The generating formula successfully produced fully inhomogeneous and anisotropic turbulence under divergence-free constraints.
- Generated turbulence fields showed good agreement with input data and theoretical predictions.
Conclusions:
- The stochastic wavelet method offers a more computationally efficient alternative for turbulence generation.
- The method provides a robust framework for generating accurate homogeneous and inhomogeneous turbulence.
- This approach advances the capability to model complex turbulent flows, particularly those requiring anisotropic and inhomogeneous characteristics.
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