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Data-Driven Digital Twin for Estimating Response of Pipe System Subjected to Seismic Load and Arbitrary Loads

지진하중 및 임의의 하중을 받는 배관 시스템에 대한 응답을 추정하기 위한 데이터 기반 디지털 트윈

  • Kim, Dongchang (Department of Convergence & Fusion System Engineering, Kyungpook National University) ;
  • Kim, Gungyu (Department of Convergence & Fusion System Engineering, Kyungpook National University) ;
  • Kwag, Shinyoung (Department of Civil & Environmental Engineering, Hanbat National University) ;
  • Eem, Seunghyun (Department of Convergence & Fusion System Engineering, Kyungpook National University)
  • 김동창 (경북대학교 융복합시스템공학과) ;
  • 김건규 (경북대학교 융복합시스템공학과) ;
  • 곽신영 (한밭대학교 건설환경공학과) ;
  • 임승현 (경북대학교 융복합시스템공학과)
  • Received : 2023.04.25
  • Accepted : 2023.07.25
  • Published : 2023.11.01

Abstract

The importance of Structural Health Monitoring (SHM) in the industry is increasing due to various loads, such as earthquakes and wind, having a significant impact on the performance of structures and equipment. Estimating responses is crucial for the effective health management of these assets. However, using numerous sensors in facilities and equipment for response estimation causes economic challenges. Additionally, it could require a response from locations where sensors cannot be attached. Digital twin technology has garnered significant attention in the industry to address these challenges. This paper constructs a digital twin system utilizing the Long Short-Term Memory (LSTM) model to estimate responses in a pipe system under simultaneous seismic load and arbitrary loads. The performance of the data-driven digital twin system was verified through a comparative analysis of experimental data, demonstrating that the constructed digital twin system successfully estimated the responses.

Keywords

Acknowledgement

본 연구는 2022년도 산업통상자원부의 재원으로 한국에너지기술평가원(KETEP)의 지원과 한국연구재단의 지원을 받아 수행한 을 받아 수행한 연구과제입니다((No. 20224B10200050; No. RS-2022-00154571).

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