Development, verification and application of the uncertainty analysis platform CUSA. (1st October 2022)

• Record Type: Journal Article
• Authors: Hao, Chen; Ma, Ji; Zhou, Xiaoyu; Liang, Xinyuan; Chen, Xingwu; Liu, Guanghao
• Is Part Of: Ocean engineering. Volume 261(2022)
• Publication Date: 2022-10-01
• Subjects: Modeling and simulation -- SU analysis -- Statistical sampling method -- CUSA; Ocean engineering -- Periodicals; Ocean engineering; Periodicals; 620.4162
• DOI: 10.1016/j.oceaneng.2022.112160
• Languages: English
• ISSNs: 0029-8018

Abstract

Abstract: Modeling and simulation technology has gradually become an important approach to describe objective physical phenomena and carry out further research and design. However, uncertainty in the basic input of the modeling and simulation process there naturally exists, which will inevitably propagate to the simulation results. Due to the wide applicability and easy implementation, statistical sampling-based Sensitivity and Uncertainty (SU) analysis has become the mainstream option for uncertainty propagation and quantification analysis in the modeling and simulation process. This paper first establishes a statistical sampling-based framework and gives theories and implemented methods involved in our framework in detail. Based on these theories and methods, a user-friendly and functional SU analysis platform called CUSA with a Human Machine Interface (HMI) has been developed. The verification results of the main function and basic theory prove the correctness and stability of CUSA. Finally, this paper summarizes CUSA's representative applications in previous studies and conduct the uncertainty analysis of total neutron physics calculation for a mini-core using CUSA. Highlights: The comprehensive statistical sampling-based sensitivity and uncertainty analysis method is proposed. An analysis platform with Human Machine Interface (HMI) called CUSA has been developed based on the proposed theories. Total verification and the application on the numerical reactor core prove the correctness and stability of CUSA.