Stochastic modeling and analysis of random surface roughness
Abstract
A novel framework is proposed for predicting statistical features of turbulent flows over generic surface topography using stochastic models of low complexity. This approach relies on the multivariate parameterization of the roughness wake and a linear approximation of the flow dynamics subject to additive and multiplicative stochastic excitation. The roughness wake, which denotes roughness-induced changes to the turbulent mean flow profile, will be determined using a stochastic interpolation method over the results of a small number of high-fidelity simulations. Given the uncertain nature of the roughness, the roughness wake translates into a multiplicative source of uncertainty in the dynamics of velocity fluctuations around the mean flow. In combination with the turbulence modeling framework of the frequency response analysis of the resulting stochastic differential equations will allow us to predict structural and statistical features of turbulent flow over random surface roughness in a computationally efficient manner that favors an improved physical understanding of the influence of realistic roughness.
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Feb 29, 2024
- Source ID
- FA95502310219
Entities
People
- Armin Zare
Organizations
- Air Force Office of Scientific Research
- United States Air Force
- University of Texas at Dallas