Digital Twin for Monitoring In-Service Performance of Post-Tensioned Self-Centering Cross-Laminated Timber Shear Walls

IF 4.7 2区 工程技术 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS
Ryan P. Longman, Yiye Xu, Qi Sun, Yelda Turkan, Mariapaola Riggio
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引用次数: 3

Abstract

A digital twin (DT) can be defined as a multiphysics, multiscale model in which a digital model, such as a building information model (BIM), is updated based on data obtained from a physical system, such as sensor data, results from probabilistic simulations, and material/structural models. This study describes sensor data integration within a BIM as the first critical step toward the implementation of DTs to support structural health monitoring (SHM). In particular, the study defines a methodological approach used to integrate the as-built geometry of existing buildings, as well as their material properties and sensor data into a digital model to assist in accessing sensor data to assess a building’s structural performance. A mass-timber structural system consisting of post-tensioned cross-laminated timber (CLT) self-centering shear walls at the George W. Peavy Forest Science Center (“Peavy Hall”) at Oregon State University was used as a case study to test the proposed approach. The BIM of the shear walls was developed using a Scan-to-BIM approach by converting light detection and ranging point clouds into a BIM. Sensors in the building recorded environmental and structural parameters influencing the long-term performance of the shear walls. Measurands included relative humidity, air and wood temperature, wood moisture content, displacements, and deformations of shear walls. The precise placement of these sensors and the possibility to associate the measured parameters of these entities within a BIM is hypothesized to assist with data management by adding a spatial element to data and analysis results. In addition, the integration into the IFC-BIM platform of a material- and phenomena-specific warning tool allows to promptly identify areas of concern in the monitored building. This can support facility managers in planning inspection and maintenance activities and eventually could lead to the prolonged service life of a building.
后张自定心交叉层合木剪力墙在役性能监测的数字孪生
数字孪生(DT)可以定义为多物理场、多尺度模型,其中数字模型(如建筑信息模型(BIM))基于从物理系统获得的数据(如传感器数据、概率模拟结果和材料/结构模型)进行更新。本研究将BIM中的传感器数据集成描述为实施DTs以支持结构健康监测(SHM)的第一个关键步骤。特别是,该研究定义了一种方法方法,用于将现有建筑的建成几何形状、材料特性和传感器数据整合到数字模型中,以帮助访问传感器数据以评估建筑的结构性能。俄勒冈州立大学George W. Peavy森林科学中心(“Peavy大厅”)的一个由后张交叉层压木材(CLT)自中心剪力墙组成的大木结构系统被用作案例研究,以测试所提出的方法。剪力墙的BIM是通过将光探测和测距点云转换为BIM,使用扫描到BIM的方法开发的。建筑中的传感器记录了影响剪力墙长期性能的环境和结构参数。测量包括相对湿度、空气和木材温度、木材含水量、位移和剪力墙变形。假设这些传感器的精确放置以及将这些实体的测量参数关联到BIM中的可能性,可以通过向数据和分析结果添加空间元素来协助数据管理。此外,在IFC-BIM平台中集成了针对特定材料和现象的预警工具,可以迅速识别受监控建筑中的问题区域。这可以帮助设施管理人员规划检查和维护活动,并最终延长建筑物的使用寿命。
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
Journal of Computing in Civil Engineering
Journal of Computing in Civil Engineering 工程技术-工程:土木
CiteScore
11.90
自引率
7.20%
发文量
58
审稿时长
6 months
期刊介绍: The Journal of Computing in Civil Engineering serves as a resource to researchers, practitioners, and students on advances and innovative ideas in computing as applicable to the engineering profession. Many such ideas emerge from recent developments in computer science, information science, computer engineering, knowledge engineering, and other technical fields. Some examples are innovations in artificial intelligence, parallel processing, distributed computing, graphics and imaging, and information technology. The journal publishes research, implementation, and applications in cross-disciplinary areas including software, such as new programming languages, database-management systems, computer-aided design systems, and expert systems; hardware for robotics, bar coding, remote sensing, data mining, and knowledge acquisition; and strategic issues such as the management of computing resources, implementation strategies, and organizational impacts.
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