INSIGHT | DATA, DIGITAL & BIM
COHESIVE KNOWLEDGE SYSTEMS IN TUNNELLING
Project delivery in tunnelling can be transformed through ‘Integrated Data Intelligence’ using cohesive knowledge systems, says Rajat Gangrade, Technical Advisor –
Geotechnical and Tunnelling, HNTB. He is noted for developing innovative digital tools for tunnel risk management, modelling geotechnical parameter uncertainty, and advancing the analysis of TBM-ground interactions.
The tunnelling sector is undergoing technological transformation driven by urbanisation, and advances in value engineering. As tunnel construction projects grow in complexity and scale, the stakeholders’ requirements on transparent data sharing, real-time operational insights, and evidence-backed decision-making across every phase of a tunnel’s lifecycle are on the rise. Traditional approaches, where project information is
fragmented between teams and technologies, are no longer observed as sustainable to support the industry’s goals of safety, efficiency, and resiliency. Contemporary tunnel design and construction involves interdisciplinary collaboration, real-time data integration, and sophisticated risk mitigation strategies that challenge traditional project delivery methods. The emergence of ‘cohesive knowledge systems’
– which are integrated data management systems supporting data-driven and adaptive decision- making – represents a paradigm shift that promises to revolutionise how tunnel infrastructure projects are conceived, planned, executed, and maintained. Tunnelling projects in North America, and globally,
are increasingly embracing such integrated digital ecosystems for efficient collaborative workflows across disciplines, predictive risk management, and more importantly, to meet stakeholders’ digital delivery requirements. However, the potential of these emerging technologies remains largely unexploited, as there is lack of validated approaches in support of their use.
CURRENT LANDSCAPE OF TUNNELING DATA MANAGEMENT Modern tunnelling projects generate vast quantities of heterogeneous data across multiple domains. Geotechnical investigations help produce stratigraphic
profiles and design parameters, tunnel boring machines (TBMs) generate real-time operational data, Geographic Information Systems (GIS) capture spatial relationships, and ‘as-built’ documentation of structures and utilities records the final tunnel environment.
30 | October 2025 Traditionally, these data streams exist in isolation
across disparate formats, unique locations, and systems managed by separate teams. The integration of these data relies primarily on manual team collaboration and vigilance. Modern tunnelling projects operate within a complex
stakeholder matrix encompassing government agencies, community groups, environmental organisations, utility companies, and regulatory bodies — each demanding real-time transparency, predictive risk assessment, and collaborative decision-making capabilities. This stakeholder complexity, particularly acute in urban environments where tunnel construction intersects with a dense network of existing infrastructure, necessitates sophisticated coordination protocols that extend far beyond traditional project management methodologies. As the industry builds upon its established data
management foundations, adopting more integrated practices will unlock the full potential of emerging technological capabilities. Fragmented information systems, incompatible data formats, and discipline- specific technology barriers prevent the seamless integration required for intelligent construction processes. This fragmentation not only limits operational efficiency but also constrains the collaborative workflows essential for managing complex urban infrastructure projects, where coordination between multiple engineering disciplines and regulatory agencies is paramount. The financial implications are substantial. Industry estimates and contemporary research
suggest that poor data integration contributes to cost overruns of 15%-30% on typical tunnelling projects, while schedule delays often extend 6-18 months beyond original projections. More critically, the safety implications of inadequate information synthesis can be severe, with ground instability, equipment failures, and impacts to structures more often traced to insufficient integration of available data sources.
Page 1 |
Page 2 |
Page 3 |
Page 4 |
Page 5 |
Page 6 |
Page 7 |
Page 8 |
Page 9 |
Page 10 |
Page 11 |
Page 12 |
Page 13 |
Page 14 |
Page 15 |
Page 16 |
Page 17 |
Page 18 |
Page 19 |
Page 20 |
Page 21 |
Page 22 |
Page 23 |
Page 24 |
Page 25 |
Page 26 |
Page 27 |
Page 28 |
Page 29 |
Page 30 |
Page 31 |
Page 32 |
Page 33 |
Page 34 |
Page 35 |
Page 36 |
Page 37 |
Page 38 |
Page 39 |
Page 40 |
Page 41 |
Page 42 |
Page 43 |
Page 44 |
Page 45
