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Uncertainty Quantification for Modeling and Simulation with Calibration

Authors:
Ma Zhibo
Yu Ming

Keywords: uncertainty quantification; modeling & simulation; calibration; verification & validation; reliability certification

Abstract:
Calibration improves the consistency between simulation results and test data of a system, but it doesn't mean that the epistemic uncertainty of Modeling and Simulation (M&S) for subsystem is reduced, so propagation analysis with many uncertain inputs often leads to an overvaluation of uncertainty. As new system-level test is unavailable, it is unpractical to quantify M&S uncertainty with comparison between simulation results and test data. Taking advantage of the fact that calibration reduces the epistemic uncertainty of system-level simulation, we propose a method for Uncertainty Quantification (UQ), in which the uncertainty from comparison with existing system-level test data and the propagated uncertainty induced by additional cognitive defect for new system are used rationally. An example with virtual tests is displayed in which the method is demonstrated and validated.

Pages: 7 to 12

Copyright: Copyright (c) IARIA, 2015

Publication date: July 19, 2015

Published in: conference

ISSN: 2308-4499

ISBN: 978-1-61208-419-0

Location: Nice,France

Dates: from July 19, 2015 to July 24, 2015