Construction with digital twin information systems

IF 2.4 Q3 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
R. Sacks, I. Brilakis, Ergo Pikas, Haiyan Xie, M. Girolami
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引用次数: 163

Abstract

Abstract The concept of a “digital twin” as a model for data-driven management and control of physical systems has emerged over the past decade in the domains of manufacturing, production, and operations. In the context of buildings and civil infrastructure, the notion of a digital twin remains ill-defined, with little or no consensus among researchers and practitioners of the ways in which digital twin processes and data-centric technologies can support design and construction. This paper builds on existing concepts of Building Information Modeling (BIM), lean project production systems, automated data acquisition from construction sites and supply chains, and artificial intelligence to formulate a mode of construction that applies digital twin information systems to achieve closed loop control systems. It contributes a set of four core information and control concepts for digital twin construction (DTC), which define the dimensions of the conceptual space for the information used in DTC workflows. Working from the core concepts, we propose a DTC information system workflow—including information stores, information processing functions, and monitoring technologies—according to three concentric control workflow cycles. DTC should be viewed as a comprehensive mode of construction that prioritizes closing the control loops rather than an extension of BIM tools integrated with sensing and monitoring technologies.
建设数字孪生信息系统
作为数据驱动的物理系统管理和控制模型的“数字孪生”概念在过去十年中出现在制造、生产和运营领域。在建筑和民用基础设施的背景下,数字孪生的概念仍然定义不清,研究人员和实践者对数字孪生过程和以数据为中心的技术支持设计和施工的方式几乎没有共识。本文在现有建筑信息模型(BIM)、精益项目生产系统、建筑工地和供应链自动化数据采集、人工智能等概念的基础上,提出了一种应用数字孪生信息系统实现闭环控制系统的施工模式。它为数字孪生构造(DTC)提供了一组四个核心信息和控制概念,这些概念定义了DTC工作流中使用的信息的概念空间的维度。从核心概念出发,我们提出了一个DTC信息系统工作流,包括信息存储,信息处理功能和监控技术,根据三个同心控制工作流周期。DTC应被视为一种综合的建设模式,优先关闭控制回路,而不是BIM工具与传感和监控技术的扩展。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
DataCentric Engineering
DataCentric Engineering Engineering-General Engineering
CiteScore
5.60
自引率
0.00%
发文量
26
审稿时长
12 weeks
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