A novel method of Newton iteration-based interval analysis for multidisciplinary systems  

作　　者：Lei Wang Chuang Xiong RuiXing Wang XiaoJun Wang Di Wu 

机构地区：[1]Institute of Solid Mechanics, Beihang University [2]China Academy of Launch Vehicle Technology R&D Center

出　　处：《Science China(Physics,Mechanics & Astronomy)》2017年第9期47-62,共16页中国科学：物理学、力学、天文学（英文版）

基　　金：supported by the National Natural Science Foundation of China(Grant No.11602012);the 111 Project(Grant No.B07009);the Defense Industrial Technology Development Program(Grant No.JCKY2016601B001);and the China Postdoctoral Science Foundation(Grant No.2016M591038)

摘　　要：A Newton iteration-based interval uncertainty analysis method(NI-IUAM) is proposed to analyze the propagating effect of interval uncertainty in multidisciplinary systems. NI-IUAM decomposes one multidisciplinary system into single disciplines and utilizes a Newton iteration equation to obtain the upper and lower bounds of coupled state variables at each iterative step.NI-IUAM only needs to determine the bounds of uncertain parameters and does not require specific distribution formats. In this way, NI-IUAM may greatly reduce the necessity for raw data. In addition, NI-IUAM can accelerate the convergence process as a result of the super-linear convergence of Newton iteration. The applicability of the proposed method is discussed, in particular that solutions obtained in each discipline must be compatible in multidisciplinary systems. The validity and efficiency of NI-IUAM is demonstrated by both numerical and engineering examples.A Newton iteration-based interval uncertainty analysis method （NI-IUAM） is proposed to analyze the propagating effect of interval uncertainty in multidisciplinary systems. NI-IUAM decomposes one multidisciplinary system into single disciplines and utilizes a Newton iteration equation to obtain the upper and lower bounds of coupled state variables at each iterative step. NI-IUAM only needs to determine the bounds of uncertain parameters and does not require specific distribution formats. In this way, NI-IUAM may greatly reduce the necessity for raw data. In addition, NI-IUAM can accelerate the convergence process as a result of the super-linear convergence of Newton iteration. The applicability of the proposed method is discussed, in particular that solutions obtained in each discipline must be compatible in multidisciplinary systems. The validity and efficiency of NI-IUAM is demonstrated by both numerical and engineering examples.

关 键 词：multidisciplinary systems uncertainty propagation insufficient sample data interval uncertainty analysis method Newton iteration 

分 类 号：O241.6[理学—计算数学] O159[理学—数学]