超越数字阴影:数字孪生用于监测大型基础设施项目的土方作业

AI in civil engineering Pub Date : 2022-01-01 Epub Date: 2022-12-28 DOI:10.1007/s43503-022-00009-5
Kay Rogage, Elham Mahamedi, Ioannis Brilakis, Mohamad Kassem
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引用次数: 3

摘要

目前关于数字孪生(DT)的研究主要集中在建筑资产在其运营阶段的性能以及城市环境上。然而,数字孪生对施工阶段没有给予足够的重视,为此,本文提出了施工阶段的数字孪生框架,开发了DT原型,并对其进行了测试,用于测量土方施工的生产率和监控。土方工程框架及其原型以多功能性、可扩展性、可用性和自动化的原则为基础,使土方工程能够满足大型土方工程项目的要求及其运作的动态性。部署了云计算和仪表板可视化,以实现自动化和可重复的数据管道和大规模数据分析,并提供近乎实时的见解。在英格兰东北部的一个高速公路项目中对DT原型的测试成功地证明了它通过使用以下方法产生关键见解的能力:(i)预测设备利用率和生产率;探测用于不同任务(即装货、拖运、倾倒、返回或空转)的时间百分比、设备在一段时间内行驶的距离和速度分布;及(iii)可视化某些土方工程的运作。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Beyond digital shadows: Digital Twin used for monitoring earthwork operation in large infrastructure projects.

Current research on Digital Twin (DT) is largely focused on the performance of built assets in their operational phases as well as on urban environment. However, Digital Twin has not been given enough attention to construction phases, for which this paper proposes a Digital Twin framework for the construction phase, develops a DT prototype and tests it for the use case of measuring the productivity and monitoring of earthwork operation. The DT framework and its prototype are underpinned by the principles of versatility, scalability, usability and automation to enable the DT to fulfil the requirements of large-sized earthwork projects and the dynamic nature of their operation. Cloud computing and dashboard visualisation were deployed to enable automated and repeatable data pipelines and data analytics at scale and to provide insights in near-real time. The testing of the DT prototype in a motorway project in the Northeast of England successfully demonstrated its ability to produce key insights by using the following approaches: (i) To predict equipment utilisation ratios and productivities; (ii) To detect the percentage of time spent on different tasks (i.e., loading, hauling, dumping, returning or idling), the distance travelled by equipment over time and the speed distribution; and (iii) To visualise certain earthwork operations.

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