Interval uncertainty‐based multidisciplinary reliability analysis method for information‐poor complex system

Abstract Due to integrated structures and multiple functions, complex systems, such as large‐scale equipment and aerospace vehicle, faced prominent reliability problems. However, in real‐world applications, collecting sufficient reliability data is costly and time‐consuming. To overcome this difficulty, the information‐poor variables are modeled with interval models and the corresponding reliability analysis method for complex system is studied in this paper. First, we establish a multidisciplinary nonprobabilistic reliability model based on interval analysis, which is an optimization framework with an objective of nonprobabilistic reliability index and two constraints of interdisciplinary consistency equation and limit state equation. Second, two types of algorithms for the above model are studied. Based on typical methods of multidisciplinary design optimization (MDO), the direct algorithms including RA‐MDF and RA‐IDF are developed. Then, a decoupled reliability analysis algorithm is proposed to realize parallel multidisciplinary reliability analysis, in which two methods of multidisciplinary interval uncertainty analysis are formulated to decouple the coupling relationship between disciplines. Finally, three examples are employed to illustrate the validity and efficiency of the proposed methods.