BIM based digitalization for infrastructure asset management in Indian construction industry: A Review

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by Rhijul Sood, Laishram Boeing Singh | IIT Guwahati
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Infrastructure sector is a backbone of economic development for most of the countries worldwide. But, maintenance of existing as well as newly built infrastructure projects is falling behind even after heavy expenditures.

The present Asset Management (AM) procedures result in over expenditures due to various factors which have been addressed by various authors. The paper has summarized different categorizations of factors which causes barriers for adoption of digital technology such as Building Information Modelling (BIM) particularly in India construction industry scenario.

The COVID-19 pandemic has made all the people related to construction industry, particularly the primary stakeholders realize about shifting the focus on digital technology including BIM during all the life cycle phases of an infrastructure asset.

This paper, therefore, aims to answer systematically about impact of Covid-19 on global construction industry, BIM technology, asset management using BIM, Indian construction industry and the challenges it faces in adopting BIM during various lifecycle stages.

The research listed 35 peer-reviewed articles from three databases which demonstrate the status of BIM implementation in India for AM and the detailed factors which are responsible for low level of maturity of BIM in Indian construction sites.

The paper also discuss about the Indian government policies related to Make In India, Digital India and National Infrastructure Pipeline (NIP) to make construction sector more advanced, competitive and developed through such initiatives.

Digital Twin Construction

by Rafael Sacks, Jhonattan G. Martinez, and Timson Yeung
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Virtual Construction Laboratory (VClab) | National Building Research Institute | Technion–Israel Institute of Technology
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With the growing maturity of site and supply chain monitoring technologies for the construction, the opportunity arises for the sector to catapult to more efficient production, business models, and value chains rooted in concepts associated with the Industry 4.0 paradigm [1]. This new paradigm for production control in construction is called ‘Digital Twin Construction’ (DTC) [2]. Integration of lean construction principles of planning, control, and production flow with monitoring technologies and artificially intelligent software modules to infer project status information is key to the DTC paradigm.

This mini-symposium aims to attract papers presenting new findings in the field of building information modeling and digital twin technology; simulation and process modeling; big data, sensing, and machine learning; built environment monitoring; control, analysis, and design; Information and communication technologies; project design, construction, planning, and management; reality capture technologies and robotics, automation, and control. The topics to be covered, but not limited to, are:

• Methods for data acquisition on site
• Merging and interpreting monitoring data to provide helpful project status information (PSI)
• Algorithms for processing raw monitored data
• Comparison of intent information (project design and process plan) with status information (as-built and as-performed information) to formulate actionable knowledge
• Simulation, prediction, and optimization of expected project performance
• Delivering project intent information to actors in a construction project

Amongst others, we specifically call on researchers engaged in current EU research projects on the theme of Digital Building Twins (Ashvin, BIMprove, BIM2TWIN, COGITO) to participate and share their findings.

Space Partitions: An alternative to domain assembly in geometric modeling

by W. Huhnt, P. J. Pahl, C. Clemen, V. Galishnikova, G. Suter, T. Hartmann
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Technical University of Berlin | HTW Dresden – University of Applied Sciences | People’s Friendship University of Russia |  TU Wien, Austria
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Geometric modeling is state of the art in all engineering disciplines. The geometric description of spaces, components and rooms, which are referred to as domains, is fundamental for a wide range of applications in Building Information Modeling. The traditional focus in geometry is on the shape of domains. Domains are constructed step by step and assembled to form a model. Topological neighborhood relations between domains are usually regarded as a helpful additional feature.

Space partitioning changes the focus on geometry in a fundamental way. Topology becomes the center of attention. Topological data structures store topology explicitly. The benefits are obvious: the extent of geometrical calculations with their well-known problems of topological inconsistencies is dramatically reduced, and they frequently become unnecessary.

Space partitioning is not new, but its potential has not yet been investigated in the required detail to the best knowledge of the authors of this proposal. The intended special session presents research on space partitions with a special focus on applications in architecture and civil engineering.

The following list of examples, which will be used to illustrate the power
of space partitions, is not complete:

• Multiply-connected and non-convex domains are state of the art in architecture and civil engineering. However, traditional approaches subdivide these domains into sets of simply-connected and convex objects. Thus the number of objects increases. This influences the storage requirements and the runtime behavior. Space partitions can handle multiply-connected and non-convex domains without subdivision.
• Topological data structures are not readily understandable by users due to their complexity. On the other hand, efficient algorithms require such data structures. The challenge is to hide topological
  data structures from the user. In a space partitioning approach, a suitable separation of the topological and the geometric models can lead to efficient topological data structures, which are completely hidden from the user.
• Point clouds are state of the art as origin for the measurement of the geometry of buildings. Existing approaches identify surfaces. They do not make use of the fundamental information that there is an empty space from the laser to all detected surfaces. This information can be considered in a space partitioning approach to improve the methods of detection of surfaces of buildings.
• Existing boundary representations of domains can be transformed into a space partition. This permits the identification of clashes and voids in a single step. Research results can illustrate the benefits.