Multi-fidelity data fusion for the design of multidisciplinary systems under uncertainty
Author(s)Feldstein, Alexander W
Massachusetts Institute of Technology. Department of Aeronautics and Astronautics.
Karen E. Willcox.
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This thesis presents a multi-fidelity methodology to enable the incorporation of high-fidelity data into a conceptual design process. The methodology is based upon a fidelity weighted combination of Gaussian Process surrogate models that takes into account both the quality of the Gaussian Process approximation and the confidence of the designer in the disciplinary model being approximated. The methodology is demonstrated on the stability and control analysis of a Blended-Wing-Body aircraft's center of gravity limits. The results show that low-fidelity data is enhanced by the presence of high-fidelity data in key areas of the design space. At the same time, the presence of even sparse high-fidelity data is key to reducing the variance in the stability and control analysis, thereby improving the quality of the predictions of the center of gravity limits.
Thesis: S.M., Massachusetts Institute of Technology, Department of Aeronautics and Astronautics, 2018.Cataloged from PDF version of thesis.Includes bibliographical references (pages 81-85).
DepartmentMassachusetts Institute of Technology. Department of Aeronautics and Astronautics.; Massachusetts Institute of Technology. Department of Aeronautics and Astronautics
Massachusetts Institute of Technology
Aeronautics and Astronautics.