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Uncertainty quantification and error estimation in scramjet simulation

Jeroen A. S. Witteveen · Karthik Duraisamy · Gianluca Iaccarino

19 citations0/0 files storedAIAA International Space Planes and Hypersonic Systems and Technologies Conference

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Probabilistic and Robust Engineering Design Computational Fluid Dynamics and Aerodynamics Model Reduction and Neural Networks

Abstract

The numerical prediction of scramjet in-flight performance is a landmark example in which current simulation capability is overwhelmed by abundant uncertainty and error. The aim of this work is to develop a decision-making tool for balancing the available computational resources in order to equally reduce the effects of all sources of uncertainty and error below a confidence threshold. To that end, a nested uncertainty quantification and error estimation loop is proposed that balances aleatoric uncertainty, epistemic uncertainty, and numerical error in an efficient way. Application to a nozzle flow problem shows a reduction of the confidence interval by three orders of magnitude. The framework applied to the HyShot II scramjet flight experiment validation simulation indicates that the epistemic uncertainty in the RANS turbulence model is the dominating contribution to the confidence interval.

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References

1991Stochastic Finite Elements: A Spectral Approach 2002The Wiener--Askey Polynomial Chaos for Stochastic Differential Equations 2005High-Order Collocation Methods for Differential Equations with Random Inputs 2007A Stochastic Collocation Method for Elliptic Partial Differential Equations with Random Input Data 2004Verification, validation, and predictive capability in computational engineering and physics 2010Numerical approach for quantification of epistemic uncertainty 2010Simplex Elements Stochastic Collocation for Uncertainty Propagation in Robust Design Optimization

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2018Enhancing Model Predictability for a Scramjet Using Probabilistic Learning on Manifolds 2017Global Sensitivity Analysis and Quantification of Model Error for Large Eddy Simulation in Scramjet Design 2019Uncertainty Propagation Using Conditional Random Fields in Large-Eddy Simulations of Scramjet Computations 2018Uncertainty quantification of a generic scramjet engine using a probabilistic collocation and a hybrid approach

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