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TWIST - Twin Infrastructure for Safer Transport

TWIST develops an integrated Digital Risk Twin platform for Norway's transport infrastructure, combining real-time monitoring, AI-driven hazard models, and geotechnical expertise to enable proactive, data-driven risk management along critical road and rail corridors.

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Transport infrastructure under pressure

Norway's roads and railways run through some of Europe's most demanding terrain. Avalanches, debris flows, quick-clay landslides, and deteriorating infrastructure assets all pose risks to corridors that millions depend on, and that are essential to national security, emergency logistics, and everyday mobility.

Current risk management is largely reactive: hazard assessments are conducted in isolation, data from different sources rarely integrate, and decisions are often made without a complete picture of what is happening on the ground. As climate change intensifies, weather extremes and political developments place greater demands on Norway's total defense infrastructure; this approach is no longer sufficient. TWIST addresses this gap.

What is TWIST?

TWIST — Twin Infrastructure for Safer Transport — is a three-year strategic research project (2026–2028) at NGI that develops a Digital Risk Twin (DRT) platform for linear transport infrastructure. A Digital Risk Twin is a dynamic, data-driven virtual representation of a physical corridor that continuously learns from incoming data, simulates future scenarios, and generates decision-ready risk assessments.

Unlike conventional digital twins, which focus solely on asset performance, the TWIST platform incorporates multi-hazard risk modeling — covering natural hazards such as avalanches, debris flows, and quick clay landslides — and integrates socio-economic considerations and uncertainty quantification.

The platform is designed for dual use: supporting both civil infrastructure management and Norway's total defense strategy.

What makes TWIST novel?

Current risk models treat hazards individually. TWIST pioneers an approach that captures how hazards interact and cascade, how rainfall triggers debris flows that block roads, or how a quick clay slide takes out both a highway and a railway at once. By fusing data from satellites, ground sensors, meteorological networks, and BIM models into a single platform and applying advanced probabilistic methods to account for the inherent uncertainties in these data sources, TWIST will produce risk assessments that reflect real-world complexity.

The result is a platform that is not a passive data repository, but a living tool that supports informed decisions; for infrastructure owners, emergency services, and national preparedness planners alike.

Research questions

TWIST is organized around six core research questions:

  • RQ1: Which hazards pose the greatest risk of disrupting transport infrastructure at each site?

  • RQ2: How can associated risks be quantified in a probabilistic framework?

  • RQ3: How do uncertainties propagate when fusing data from multiple sources?

  • RQ4: Can improved data flow and real-time analysis reveal cascading and cross-hazard effects?

  • RQ5: How can the risk assessment framework support timely decisions for prevention and emergency response?

  • RQ6: How can the performance of a digital twin be optimized across varying data quality, resolution, and computational demands?

Work packages

WP0 – Project management and coordination
PI: Jessica Chiu  |  Deputy PI: Graham Gilbert

Responsible for overall project coordination, financial management, consortium meetings, and integration across work packages.

WP1 – Risk assessment and management
Leader: Sparsha Nagula  |  Deputy: Unni Eidsvig

Develops the multi-hazard risk assessment framework. Translates raw hazard-monitoring data into quantified, probabilistic risk for decision-making. Key outputs include dynamic risk maps and a response prioritization framework that go beyond static hazard maps to capture cascading effects and changing conditions in real time. Works closely with user partners to define risk acceptance criteria.

WP2 – Data acquisition and analysis
Leader: Minu Treesa Abraham  |  Deputy: Andreas-Nizar Granitzer

Collects, harmonizes, and analyzes site-specific hazard and infrastructure data. Applies data-driven and process-based models — including machine learning, probabilistic modeling, and uncertainty quantification — for hazard forecasting and dynamic risk assessment. Manages the iterative data-to-model feedback loop that enables the digital twin to be adaptive.

WP3 – Digital risk twin platform and information management
Leader: Osmund Maheswaran  |  Deputy: Haakon Robinson

Builds and tests the DRT platform, extending NGI's existing NGI Live monitoring infrastructure. Develops a prediction engine, BIM data integration, 2D/3D visualizations, and data export capabilities. The platform is designed to make risk assessments accessible and actionable for operators and emergency services.

WP4 – Dissemination and knowledge transfer
Leader: Tom Frode Hansen  |  Deputy: Per Olav Solberg

Manages all communication, dissemination, and stakeholder engagement. Ensures that project findings reach infrastructure owners, the research community, engineering consultants, and the general public — through publications, conferences, internal NGI channels, and national events.

Kick-off meeting, April 2026

TWIST held its kick-off meeting on 21 April 2026, bringing together the full project team for presentations from all work package leaders and a first workshop on communications strategy. The first meeting with the Steering Group took place on 29 April 2026.

Ongoing updates

Throughout 2026–2028, TWIST will publish research reports, journal articles, and updates from fieldwork and workshops on this page. As the project progresses, you will also find links to datasets, conference contributions, and outputs from the Digital Risk Twin platform.

Contact

Jessica Chiu
Principal Investigator, TWIST
jessica.chiu@ngi.no

Per Olav Solberg
Communications, WP4
per.olav.solberg@ngi.no

  • Transport infrastructure under pressure

    Norway's roads and railways run through some of Europe's most demanding terrain. Avalanches, debris flows, quick-clay landslides, and deteriorating infrastructure assets all pose risks to corridors that millions depend on, and that are essential to national security, emergency logistics, and everyday mobility.

    Current risk management is largely reactive: hazard assessments are conducted in isolation, data from different sources rarely integrate, and decisions are often made without a complete picture of what is happening on the ground. As climate change intensifies, weather extremes and political developments place greater demands on Norway's total defense infrastructure; this approach is no longer sufficient. TWIST addresses this gap.

    What is TWIST?

    TWIST — Twin Infrastructure for Safer Transport — is a three-year strategic research project (2026–2028) at NGI that develops a Digital Risk Twin (DRT) platform for linear transport infrastructure. A Digital Risk Twin is a dynamic, data-driven virtual representation of a physical corridor that continuously learns from incoming data, simulates future scenarios, and generates decision-ready risk assessments.

    Unlike conventional digital twins, which focus solely on asset performance, the TWIST platform incorporates multi-hazard risk modeling — covering natural hazards such as avalanches, debris flows, and quick clay landslides — and integrates socio-economic considerations and uncertainty quantification.

    The platform is designed for dual use: supporting both civil infrastructure management and Norway's total defense strategy.

    What makes TWIST novel?

    Current risk models treat hazards individually. TWIST pioneers an approach that captures how hazards interact and cascade, how rainfall triggers debris flows that block roads, or how a quick clay slide takes out both a highway and a railway at once. By fusing data from satellites, ground sensors, meteorological networks, and BIM models into a single platform and applying advanced probabilistic methods to account for the inherent uncertainties in these data sources, TWIST will produce risk assessments that reflect real-world complexity.

    The result is a platform that is not a passive data repository, but a living tool that supports informed decisions; for infrastructure owners, emergency services, and national preparedness planners alike.

  • Research questions

    TWIST is organized around six core research questions:

    • RQ1: Which hazards pose the greatest risk of disrupting transport infrastructure at each site?

    • RQ2: How can associated risks be quantified in a probabilistic framework?

    • RQ3: How do uncertainties propagate when fusing data from multiple sources?

    • RQ4: Can improved data flow and real-time analysis reveal cascading and cross-hazard effects?

    • RQ5: How can the risk assessment framework support timely decisions for prevention and emergency response?

    • RQ6: How can the performance of a digital twin be optimized across varying data quality, resolution, and computational demands?

    Work packages

    WP0 – Project management and coordination
    PI: Jessica Chiu  |  Deputy PI: Graham Gilbert

    Responsible for overall project coordination, financial management, consortium meetings, and integration across work packages.

    WP1 – Risk assessment and management
    Leader: Sparsha Nagula  |  Deputy: Unni Eidsvig

    Develops the multi-hazard risk assessment framework. Translates raw hazard-monitoring data into quantified, probabilistic risk for decision-making. Key outputs include dynamic risk maps and a response prioritization framework that go beyond static hazard maps to capture cascading effects and changing conditions in real time. Works closely with user partners to define risk acceptance criteria.

    WP2 – Data acquisition and analysis
    Leader: Minu Treesa Abraham  |  Deputy: Andreas-Nizar Granitzer

    Collects, harmonizes, and analyzes site-specific hazard and infrastructure data. Applies data-driven and process-based models — including machine learning, probabilistic modeling, and uncertainty quantification — for hazard forecasting and dynamic risk assessment. Manages the iterative data-to-model feedback loop that enables the digital twin to be adaptive.

    WP3 – Digital risk twin platform and information management
    Leader: Osmund Maheswaran  |  Deputy: Haakon Robinson

    Builds and tests the DRT platform, extending NGI's existing NGI Live monitoring infrastructure. Develops a prediction engine, BIM data integration, 2D/3D visualizations, and data export capabilities. The platform is designed to make risk assessments accessible and actionable for operators and emergency services.

    WP4 – Dissemination and knowledge transfer
    Leader: Tom Frode Hansen  |  Deputy: Per Olav Solberg

    Manages all communication, dissemination, and stakeholder engagement. Ensures that project findings reach infrastructure owners, the research community, engineering consultants, and the general public — through publications, conferences, internal NGI channels, and national events.

  • Kick-off meeting, April 2026

    TWIST held its kick-off meeting on 21 April 2026, bringing together the full project team for presentations from all work package leaders and a first workshop on communications strategy. The first meeting with the Steering Group took place on 29 April 2026.

    Ongoing updates

    Throughout 2026–2028, TWIST will publish research reports, journal articles, and updates from fieldwork and workshops on this page. As the project progresses, you will also find links to datasets, conference contributions, and outputs from the Digital Risk Twin platform.

  • Contact

    Jessica Chiu
    Principal Investigator, TWIST
    jessica.chiu@ngi.no

    Per Olav Solberg
    Communications, WP4
    per.olav.solberg@ngi.no

Portrait of Jessica Ka Yi Chiu

Jessica Ka Yi Chiu

Senior Engineering Geologist Rock Engineering jessica.ka.yi.chiu@ngi.no
 +47 968 77 853