Estimated aleatoric uncertainty from initial and inlet conditions for variable density mixing
Jan Felix Heyse, Zhu Huang, Gianluca Iaccarino

TL;DR
This paper quantifies aleatoric uncertainty in variable density flow simulations, showing robustness to inlet variations in jet mixing but sensitivity to initial conditions in Rayleigh-Taylor instability, using BHR-1 turbulence model.
Contribution
It introduces a method to estimate aleatoric uncertainty in variable density flows using Monte Carlo sampling and compares robustness across different flow scenarios.
Findings
Jet in co-flow case shows little sensitivity to inlet perturbations.
Tilted rocket rig case is highly sensitive to initial interface perturbations.
Uncertainty estimates align well with experimental data for the Rayleigh-Taylor case.
Abstract
Variable density flows occur in a variety of different systems with a wide range of scales, from astrophysics to atmospheric flows to inertial confinement fusion or reacting flows. Given the inherent limitations of RANS simulations, it is important to find ways to quantify the uncertainty in the predictions. The aleatoric uncertainty of two different variable density flows to inlet and initial conditions, respectively, is studied. The two cases are the turbulent mixing of a jet in a co-flow at small Atwood number , and the Rayleigh-Taylor mixing in a tilted rocket rig at medium . Uncertainty estimates are made for simulations using the BHR-1 turbulence model and compared to reference data. Estimated distributions of measurement uncertainties from an experimental report are used to do Monte-Carlo sampling for some inlet parameters of the jet in a co-flow case. The results show only…
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Taxonomy
TopicsFluid Dynamics and Turbulent Flows · Computational Fluid Dynamics and Aerodynamics · Combustion and flame dynamics
