Collaborative Reliability Analysis under the Framework of Multidisciplinary Systems Design

Abstract

Traditional Multidisciplinary Design Optimization (MDO) generates deterministic optimal designs, which are frequently pushed to the limits of design constraint boundaries, leaving little or no room to accommodate uncertainties in system input, modeling, and simulation. As a result, the design solution obtained may be highly sensitive to the variations of system input which will lead to performance loss and the solution is often risky (high likelihood of undesired events). Reliability-based design is one of the alternative techniques for design under uncertainty. The natural method to perform reliability analysis in multidisciplinary systems is the all-in-one approach where the existing reliability analysis techniques are applied directly to the system-level multidisciplinary analysis. However, the all-on-one reliability analysis method requires a double loop procedure and therefore is generally very time consuming. To improve the efficiency of reliability analysis under the MDO framework, a collaborative reliability analysis method is proposed in this paper.The procedure of the traditional Most Probable Point (MPP) based reliability analysis method is combined with the collaborative disciplinary analyses to automatically satisfy the interdisciplinary consistency when conducting reliability analysis. As a result, only a single loop procedure is required and all the computations are conducted concurrently at the individual discipline-level. Compared with the existing reliability analysis methods in MDO, the proposed method is efficient and therefore provides a cheaper tool to evaluate design feasibility in MDO under uncertainty. Two examples are used for the purpose of verification.

Multifidelity Uncertainty Propagation in Coupled Multidisciplinary Systems

“…Past work has dealt with uncertainty analysis of feedback-coupled systems by using decoupling approaches such as collaborative reliability analysis, 16 the first order reliability method (FORM) 17 and a likelihood-based approach, 18 and polynomial chaos expansion based method. 19 FORM and the likelihood-based decoupling approach cast the feedback-coupled system as a feed-forward system, thus avoiding coupled system analyses and their associated FPI, but at the cost of neglecting the dependence between the inputs and the coupling variables.…”

Multi-disciplinary analysis and optimization under uncertainty

“…Studies on uncertainty propagation through feedback-coupled MDA are even fewer [9,10,11,26,19], and have only addressed aleatory uncertainty.…”

“…Du and Chen [9] included the disciplinary constraints in the most probable point (MPP) estimation for reliability analysis.…”

“…However, such analysis is computationally prohibitive. Therefore, efficient alternatives, in the presence of aleatory uncertainty alone, have been investigated by several researchers [9,10,11,22,23,24] (see Section 1.1).…”

“…For example, in the decoupled approach adopted by Du and Chen [9] and Mahadevan and Smith [10], the probability density functions (PDF) of the coupling variables are calculated by Taylor series-based first-order second moment approximation. These approaches improve the efficiency by 12 trading off the accuracy since they ignore the dependence between the coupling variables.…”