Directly solving time-dependent reliability-based design optimization (TRBDO) with aleatory and epistemic uncertainties is time-demanding, which limits its engineering application. By treating aleatory and epistemic uncertainties with probability and evidence variables respectively, an advanced decoupling method named sequential optimization and unified time-dependent reliability analysis (SOUTRA) is proposed in this work. By the SOUTRA, the original nested optimization process is solved by a sequence of unified time-dependent reliability analysis, updated reliability index target estimation and deterministic optimization. Only few numbers of the unified time-dependent reliability analysis are required to derive the optimum by the SOUTRA; thus, it is highly efficient. Furthermore, in order to construct the deterministic optimization, a new probability transformation method named focal element midpoint (FEM) is established to convert the evidence variable into a random one. FEM can avoid the issues of uniformity approach and equal areas method, and both are used in the existing probability transformation. Several numerical and engineering applications are introduced to illustrate the effectiveness of the proposed SOUTRA.

直接解决具有不确定性和认知不确定性的基于时间的基于可靠性的设计优化（TRBDO）十分耗时，这限制了其工程应用。通过分别用概率变量和证据变量处理偶然不确定性和认知不确定性，提出了一种先进的解耦方法，称为顺序优化和统一时变可靠性分析（SOUTRA）。通过SOUTRA，通过一系列统一的时变可靠性分析，更新的可靠性指标目标估计和确定性优化解决了原始的嵌套优化过程。SOUTRA只需很少数量的时间相关的统一可靠度分析就可以得出最优值。因此，它是高效的。此外，为了构建确定性优化，建立了一种新的概率转换方法，称为焦点元素中点（FEM），将证据变量转换为随机变量。有限元法可以避免均一法和等面积法的问题，两者都用于现有的概率变换中。介绍了一些数值和工程应用程序，以说明所提出的SOUTRA的有效性。