Design for ACP100 long term cooling flow resistance with random forests and inverse quantification. (January 2023)

• Record Type: Journal Article
• Authors: Xiong, Qingwen; Shen, Yaou; Dang, Gaojian; Qiu, Zhifang; Deng, Jian; Du, Peng; Ding, Shuhua; Wu, Zenghui
• Is Part Of: Annals of nuclear energy. Volume 180(2023)
• Publication Date: 2023-01
• Subjects: ACP100 -- DEDVI -- Long-term cooling -- Resistance design -- Inverse quantification; Nuclear energy -- Periodicals; Nuclear engineering -- Periodicals; 621.4805
• DOI: 10.1016/j.anucene.2022.109477
• Languages: English
• ISSNs: 0306-4549

Abstract

Highlights: Transient analysis of the ACP100 long term cooling using ARSAC. Flow resistance design of the recirculation pipeline using random forests and inverse quantification. Validation of the flow resistance design results with forward uncertainty propagation. Abstract: The ACP100 is an integrated small modular reactor with passive designs, and core cooling in the long-term cooling phase of the double-ended direct vessel injection (DEDVI) pipe break accident relies on the natural circulation in the sump recirculation pipeline. Therefore, the design of the recirculation pipeline flow resistance is very important. The ARSAC was used in the study to carry out the design for the recirculation pipeline flow resistance of the ACP100. The surrogate model of the accident simulation was constructed using the random forests algorithm, followed by using an inverse quantification method to determine the flow resistance distributions of the filter and related pipe, and finally the forward uncertainty propagation was performed for validation. The resistance design method utilized in the study has a high degree of freedom and is able to take the manufacturing uncertainty into consideration, which could facilitate the subsequent geometry design.