Validation Framework of a Digital Twin: A System Identification Approach

被引：0
|
作者：
Purdue University, School of Industrial Engineering, 315 N. Grant Street, West Lafayette [1 ]
IN, United States
机构：
来源：
INCOSE Int. Sym. | 2024年 / 1卷 / 249-267期
关键词：
The constant improvement and developments in Artificial Intelligence/Machine learning models coupled with increased computing power have led to the incorporation of AI/ML for simulating learning and problem-solving in simple and complex engineering systems. This latent uncertainty and unpredictable characteristics of AI-enabled systems challenges engineers and industry stakeholders who care about ensuring the right systems are built (system validation). Digital Twins are an excellent example of such AI-enabled systems due to their data-dependent nature when tasked with replicating; monitoring; and updating physical assets for structural health monitoring and control. However; Digital Twins' system validation has not been well-researched. This study delves into existing research and frameworks for validating Digital Twins and proposes a novel model-centric validation framework based on system identification techniques. As a case study; we apply this model-centric validation framework towards partially validating a Digital Twin for a single-heat-pipe test article for a Microre-actor Agile Non-nuclear Experimental Testbed. Copyright © 2024 by Ibukun Phillips and Robert Kenley. Permission granted to INCOSE to publish and use;
D O I：
10.1002/iis2.13145
中图分类号：
学科分类号：
摘要：
引用
收藏
相关论文
共 50 条
  • [1] Development and validation of a digital twin framework for SMT manufacturing
    Seidel, Reinhardt
    Rachinger, Ben
    Thielen, Nils
    Schmidt, Konstantin
    Meier, Sven
    Franke, Joerg
    COMPUTERS IN INDUSTRY, 2023, 145
  • [2] A Digital Twin Framework for Flexible Manufacturing System
    Sid-Lakhdar, Mokhtar Nizar
    Benderbal, Hichem Haddou
    Souier, Mehdi
    ADVANCES IN PRODUCTION MANAGEMENT SYSTEMS-PRODUCTION MANAGEMENT SYSTEMS FOR VOLATILE, UNCERTAIN, COMPLEX, AND AMBIGUOUS ENVIRONMENTS, APMS 2024, PT VI, 2024, 733 : 155 - 167
  • [3] Urban flooding digital twin system framework
    Ge, Chenyu
    Qin, Shengfeng
    SYSTEMS SCIENCE & CONTROL ENGINEERING, 2025, 13 (01)
  • [4] Toward digital validation for rapid product development based on digital twin: a framework
    Huang, Sihan
    Wang, Guoxin
    Lei, Dong
    Yan, Yan
    INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY, 2022, 119 (3-4): : 2509 - 2523
  • [5] Toward digital validation for rapid product development based on digital twin: a framework
    Sihan Huang
    Guoxin Wang
    Dong Lei
    Yan Yan
    The International Journal of Advanced Manufacturing Technology, 2022, 119 : 2509 - 2523
  • [6] Software Testing Approach for Digital Twin Verification and Validation
    Zahediyami, Milad
    Gorecki, Simon
    Traore, Mamadou Kaba
    NAVIGATING UNPREDICTABILITY: COLLABORATIVE NETWORKS IN NON-LINEAR WORLDS, PRO-VE 2024, PT II, 2024, 727 : 115 - 129
  • [7] Hybrid validation - Digital twin
    Renelt, Andreas
    VDI Berichte, 2024, 2024 (2431): : 121 - 124
  • [8] Digital Twin's Anatomy: A Cross-Sector Framework With Healthcare Validation
    Araghi, Sina Namaki
    Liu, Zhengyu
    Sarkar, Arkopaul
    Louge, Thierry
    Karray, Mohamed Hedi
    IEEE ACCESS, 2025, 13 : 21306 - 21334
  • [9] A Framework for an Indoor Safety Management System Based on Digital Twin
    Liu, Zhansheng
    Zhang, Anshan
    Wang, Wensi
    SENSORS, 2020, 20 (20) : 1 - 20
  • [10] A Digital Twin Framework for Mechanical System Health State Estimation?
    Toothman, Maxwell
    Braun, Birgit
    Bury, Scott J.
    Dessauer, Michael
    Henderson, Kaytlin
    Phillips, Steven
    Ye, Yixin
    Tilbury, Dawn M.
    Moyne, James
    Barton, Kira
    IFAC PAPERSONLINE, 2021, 54 (20): : 1 - 7
12345