A Comprehensive Review of Digital Twin -- Part 2: Roles of Uncertainty Quantification and Optimization, a Battery Digital Twin, and Perspectives

• URL: http://arxiv.org/abs/2208.12904v1
• Date: Sat, 27 Aug 2022 01:36:15 GMT
• Title: A Comprehensive Review of Digital Twin -- Part 2: Roles of Uncertainty Quantification and Optimization, a Battery Digital Twin, and Perspectives
• Authors: Adam Thelen, Xiaoge Zhang, Olga Fink, Yan Lu, Sayan Ghosh, Byeng D. Youn, Michael D. Todd, Sankaran Mahadevan, Chao Hu, Zhen Hu
• Abstract summary: Second paper presents a literature review of key enabling technologies of digital twins. Third paper presents a case study where a battery digital twin is constructed and tested to illustrate some of the modeling and twinning methods reviewed.
• Score: 11.241244950889886
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: As an emerging technology in the era of Industry 4.0, digital twin is gaining unprecedented attention because of its promise to further optimize process design, quality control, health monitoring, decision and policy making, and more, by comprehensively modeling the physical world as a group of interconnected digital models. In a two-part series of papers, we examine the fundamental role of different modeling techniques, twinning enabling technologies, and uncertainty quantification and optimization methods commonly used in digital twins. This second paper presents a literature review of key enabling technologies of digital twins, with an emphasis on uncertainty quantification, optimization methods, open source datasets and tools, major findings, challenges, and future directions. Discussions focus on current methods of uncertainty quantification and optimization and how they are applied in different dimensions of a digital twin. Additionally, this paper presents a case study where a battery digital twin is constructed and tested to illustrate some of the modeling and twinning methods reviewed in this two-part review. Code and preprocessed data for generating all the results and figures presented in the case study are available on GitHub.

Related papers

• Sparse Attention-driven Quality Prediction for Production Process Optimization in Digital Twins [53.70191138561039]
  We propose to deploy a digital twin of the production line by encoding its operational logic in a data-driven approach. We adopt a quality prediction model for production process based on self-attention-enabled temporal convolutional neural networks. Our operation experiments on a specific tobacco shredding line demonstrate that the proposed digital twin-based production process optimization method fosters seamless integration between virtual and real production lines.
  arXiv  Detail & Related papers  (2024-05-20T09:28:23Z)
• From Digital Twins to Digital Twin Prototypes: Concepts, Formalization, and Applications [55.57032418885258]
  There is no consensual definition of what a digital twin is. Our digital twin prototype (DTP) approach supports engineers during the development and automated testing of embedded software systems.
  arXiv  Detail & Related papers  (2024-01-15T22:13:48Z)
• Digital Twin Framework for Optimal and Autonomous Decision-Making in Cyber-Physical Systems: Enhancing Reliability and Adaptability in the Oil and Gas Industry [0.0]
  This work proposes a digital twin framework for optimal and autonomous decision-making applied to a gas-lift process in the oil and gas industry. The framework combines Bayesian inference, Monte Carlo simulations, transfer learning, online learning, and novel strategies to confer cognition to the DT.
  arXiv  Detail & Related papers  (2023-11-21T18:02:52Z)
• A No-Reference Quality Assessment Method for Digital Human Head [56.17852258306602]
  We develop a novel no-reference (NR) method based on Transformer to deal with digital human quality assessment (DHQA) Specifically, the front 2D projections of the digital humans are rendered as inputs and the vision transformer (ViT) is employed for the feature extraction. Then we design a multi-task module to jointly classify the distortion types and predict the perceptual quality levels of digital humans.
  arXiv  Detail & Related papers  (2023-10-25T16:01:05Z)
• Qualitative and quantitative evaluation of a methodology for the Digital Twin creation of brownfield production systems [0.7373617024876725]
  The Digital Twin is the cyber part of a cyber-physical production system providing several benefits such as virtual commissioning or predictive maintenance. The existing production systems are lacking a Digital Twin which has to be created manually in a time-consuming and error-prone process.
  arXiv  Detail & Related papers  (2023-09-01T08:19:35Z)
• A Comprehensive Review of Digital Twin -- Part 1: Modeling and Twinning Enabling Technologies [11.241244950889886]
  Digital twin is an emerging technology in the era of Industry 4.0. Digital twins can model the physical world as a group of interconnected digital models. In part two of this review, the role of uncertainty quantification and optimization are discussed.
  arXiv  Detail & Related papers  (2022-08-26T15:01:26Z)
• The Digital Twin Landscape at the Crossroads of Predictive Maintenance, Machine Learning and Physics Based Modeling [14.781000287006755]
  The history of the term digital twin is explored, as well as its initial context in the fields of product life cycle management, asset maintenance, and equipment fleet management, operations, and planning. The application of a digital twin framework is highlighted in the field of predictive maintenance, and its extensions utilizing machine learning and physics based modeling.
  arXiv  Detail & Related papers  (2022-06-21T15:17:10Z)
• Automatic digital twin data model generation of building energy systems from piping and instrumentation diagrams [58.720142291102135]
  We present an approach to recognize symbols and connections of P&ID from buildings in a completely automated way. We apply algorithms for symbol recognition, line recognition and derivation of connections to the data sets. The approach can be used in further processes like control generation, (distributed) model predictive control or fault detection.
  arXiv  Detail & Related papers  (2021-08-31T15:09:39Z)
• Digital Twins: State of the Art Theory and Practice, Challenges, and Open Research Questions [62.67593386796497]
  This work explores the various DT features and current approaches, the shortcomings and reasons behind the delay in the implementation and adoption of digital twin. The major reasons for this delay are the lack of a universal reference framework, domain dependence, security concerns of shared data, reliance of digital twin on other technologies, and lack of quantitative metrics.
  arXiv  Detail & Related papers  (2020-11-02T19:08:49Z)
• Man, machine and work in a digital twin setup: a case study [77.34726150561087]
  A digital twin as a virtual counterpart of a physical human-robot assembly system is built as a front-runner for validation and control through design, build, and operation. The forms of digital twins along the system life cycle, the building blocks, and potential advantages are presented.
  arXiv  Detail & Related papers  (2020-06-15T20:54:43Z)
• The role of surrogate models in the development of digital twins of dynamic systems [0.0]
  Digital twin technology has significant promise, relevance and potential of widespread applicability. Digital twins are expected to exploit data and computational methods. We have explored the possibility of using surrogate models within the digital twin technology.
  arXiv  Detail & Related papers  (2020-01-25T10:48:35Z)

This list is automatically generated from the titles and abstracts of the papers in this site.

This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.