Optimal uncertainty reduction for multi-disciplinary multi-output systems using sensitivity analysis
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- 作者：M. Li ; J. Hamel and S. Azarm
- 关键词：Uncertainty reduction ; Sensitivity analysis ; Multi ; disciplinary analysis ; Interval uncertainty
- 刊名：Structural and Multidisciplinary Optimization
- 出版时间：January, 2010
- 出版年：2010
- 期刊代码：141_1615-147X
- 类别：mat
- 卷：40
- 期：1-6
- 页码：77-96
- 数据来源：sp
摘要
We present a sensitivity analysis based uncertainty reduction approach, called Multi-dIsciplinary Multi-Output Sensitivity Analysis (MIMOSA), for the analysis model of a multi-disciplinary engineering system decomposed into multiple subsystems with each subsystem analysis having multiple inputs with reducible uncertainty and multiple outputs. MIMOSA can determine: (1) the sensitivity of system and subsystem outputs to input uncertainties at both system and subsystem levels, (2) the sensitivity of the system outputs to the variation from subsystem outputs, and (3) the optimal “investment” required to reduce uncertainty in inputs in order to obtain a maximum reduction in output variations at both the system and subsystem levels. A numerical and an engineering example with two and three subsystems, respectively, have been used to demonstrate the applicability of the MIMOSA approach.