A Posteriori Error Estimates for DDDAS Inference Problems

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• 作者：Vishwas Rao ^{visrao@vt.edu" class="auth_mail} ; Adrian Sandu ^{asandu7@vt.edu" class="auth_mail}
• 关键词：Inverse problems ; sensitivity analysis ; DDDAS ; data assimilation ; a posteriori error
• 刊名：Procedia Computer Science
• 出版年：2014
• 年：2014
• 卷：29
• 期：Complete
• 页码：1256-1265
• 全文大小：554 K

文摘

Inference problems in dynamically data-driven application systems use physical measurements along with a physical model to estimate the parameters or state of a physical system. Errors in measurements and uncertainties in the model lead to inaccurate inference results. This work develops a methodology to estimate the impact of various errors on the variational solution of a DDDAS inference problem. The methodology is based on models described by ordinary differential equations, and use first-order and second-order adjoint methodologies. Numerical experiments with the heat equation illustrate the use of the proposed error estimation machin- ery.