Fast algorithm for a three-dimensional synthetic model of intermittent turbulence

Area of Science:

• Fluid Dynamics
• Computational Physics
• Data Science

Background:

• Synthetic turbulence models are crucial for validating theories and enhancing numerical simulations.
• Previous models, particularly for 1D and 3D turbulence, demanded significant computational power.
• There is a need for efficient synthetic turbulence models with adjustable parameters.

Purpose of the Study:

• To introduce a novel wavelet-based synthetic turbulence model.
• To enable the generation of synthetic turbulence with controllable spectral laws, intermittency, and anisotropy.
• To present a computationally efficient algorithm for creating broad-spectrum turbulence.

Main Methods:

• Development of a wavelet-based algorithm for synthetic turbulence generation.
• Algorithm based on the classic p-model of intermittent turbulence.
• Utilized spectral analysis, scale-dependent statistics of field increments, and multifractal analysis for validation.

Main Results:

• The wavelet-based model successfully generates synthetic turbulence with tunable spectral properties, intermittency, and anisotropy.
• The rapid algorithm achieves a broad spectral range with modest computational resources.
• Validation diagnostics confirmed the model's excellent performance in representing intermittent turbulence characteristics.

Conclusions:

• The presented wavelet-based model provides an efficient and versatile tool for generating synthetic turbulence.
• This approach significantly reduces computational demands compared to previous methods.
• The model is well-suited for applications requiring realistic turbulence fields for testing and analysis.