Xiaoqian Chen

TL;DR: A comprehensive review of Uncertainty-Based Multidisciplinary Design Optimization (UMDO) theory and the state of the art in UMDO methods for aerospace vehicles is presented.

TL;DR: A comprehensive review of typical improved Monte Carlo methods and summarizes their characteristics to aid the uncertainty-based multidisciplinary design optimization (UMDO).

TL;DR: A width optimization method, concurrent subspace width optimization (CSWO), is proposed based on a decomposition and coordination strategy that decomposes the large-scale width optimization problem into several subspace optimization (SSO) problems, each of which has a single optimization variable and smaller training and validation data sets so as to greatly simplify optimization complexity.

TL;DR: A multistage-multilevel MDO procedure is proposed in this paper by integrating multiple-discipline-feasible (MDF) and concurrent subspace optimization (CSSO), termed as MDF-CSSO, to solve uncertainty-based optimization problems.

TL;DR: An uncertainty quantification methodology based on active subspaces is established for satellite conceptual design and exhibits high accuracy and strong adaptability, which provides a potential template to tackle multidisciplinary uncertainty in practical satellite systems.