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Multi-fidelity model fusion and uncertainty quantification using high dimensional model representation

Kubicek, Martin and Mehta, Piyush M. and Minisci, Edmondo and Vasile, Massimiliano (2016) Multi-fidelity model fusion and uncertainty quantification using high dimensional model representation. In: Spaceflight Mechanics 2016. Advances in the Astronautical Sciences . American Astronautical Society, San Diego, California, pp. 1987-2002. ISBN 9780877036333

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High-fidelity modeling based on experiments or simulations is generally very expensive. Low-fidelity models, when available, typically have simplifying assumptions made during the development and hence are quick but not so accurate. We present development of a new and novel approach for multi-fidelity model fusion to achieve the accuracy of the expensive high-fidelity methods with the speed of the inaccurate low-fidelity models. The multi-fidelity fusion model and the associated uncertainties is achieved using a new derivation of the high dimensional model representation (HDMR) method. The method can provide valuable insights for efficient placement of the expensive high-fidelity simulations in the domain towards reducing the multi-fidelity model uncertainties. The method is applied and validated with aerodynamic and aerothermodynamic models for atmospheric re-entry.