建筑信息建模
演习
工程类
施工管理
过程(计算)
背景(考古学)
建筑工程
水力发电
数据管理
信息模型
计算机科学
系统工程
土木工程
软件工程
数据挖掘
操作系统
生物
电气工程
机械工程
古生物学
化学工程
相容性(地球化学)
作者
Abubakar Sharafat,Muhammad Shoaib Khan,Kamran Latif,Jongwon Seo
出处
期刊:Journal of Computing in Civil Engineering
[American Society of Civil Engineers]
日期:2020-12-18
卷期号:35 (2)
被引量:71
标识
DOI:10.1061/(asce)cp.1943-5487.0000955
摘要
Tunnel construction fundamentally differs from building and aboveground civil infrastructure projects. Drill-and-blast is one of the most common and flexible tunnel construction methods. However, it is complex and challenging because a large amount of data is generated from dispersed, independent, and heterogeneous sources. The tunneling industry still uses traditional project management techniques to manage complex interactions between these data sources that are hardly linked, and independent decisions are often made without considering all the relevant aspects. In this context, tunnel construction exhibits uncertainties and risks due to unforeseen circumstances, intricate design, and ineffective information management. Building information modeling (BIM) in the construction industry provides a solution to such issues with effective data information modeling. Existing research has considered a very general BIM semantic model and focused only a small portion of the entire drill-and-blast construction process. Tunnel boring machine (TBM) projects have successfully applied linked data models and multimodel concepts in BIM, but those technologies have yet to be adopted in drill-and-blast tunneling. To address that gap, a novel BIM-based multimodel tunnel information modeling (TIM) framework is presented here to improve project management, construction, and delivery by integrating five interlinked data models and project performance data for drill-and-blast tunnel construction. Data models of tunnel construction processes are linked to propose the Industry Foundation Classes (IFC)-Tunnel classes based on the objects, relationships, and property set definitions of the IFC schema. To validate the proposed framework, an implementation case study of a hydropower tunneling project is presented. The results indicate that the framework facilitates data sharing, information integration, data accessibility, design optimization, project communication, efficient project management, and visualization of tunnel design and construction processes.
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