Seven ways digital twins can help build sustainable infrastructure

1. Optimising embodied carbon

From the early design stages, infrastructure designers should be empowered to prioritise sustainability and reducing environmental footprints. Embodied carbon in construction and material transportation is an important focus area, not only because it can no longer be avoided or reduced once the infrastructure is built, but because many of the products and materials involved (steel or cement, for example) are highly carbon-intensive and difficult to replace.

Digital twins can integrate automated workflows with carbon calculation tools to seamlessly generate carbon reports and visualise those calculations within 3D digital models, supporting design optimisation based on carbon intensity. Ideally, and to facilitate carbon transparency across the supply chain, the infrastructure digital models created in the design stage shouldn’t be required in any specific proprietary format; rather, they should be consumed by a vendor-agnostic digital twin platform, independent of the origin or vendor.

2. Designing environmentally resilient infrastructure

Climate change requires a greater degree of infrastructure resilience to extreme weather patterns. Structural finite element analysis and design application can support the environmentally resilient design of buildings, bridges, tunnels, towers and industrial facilities. One asset for which this is particularly crucial is offshore wind farms, which must be weatherproof against extreme wind speed and turbulence to reduce the risk of turbine damage and downtime.

Structural software solutions can help design offshore wind power infrastructure (such as turbines and their foundations) that is more robust against high winds and extreme loads, as well as develop advanced control strategies to mitigate the effects of extreme weather events (e.g. blade pitch, yaw and load controls). These solutions can also simulate the response of wind turbines to extreme weather events, such as hurricanes and tornadoes.

3. Hyperscaling new sources of clean energy production

With three-quarters of global greenhouse gas emissions associated with the energy sector, diversifying energy production from renewable sources is critical to achieving net-zero milestones and diminishing our reliance on specific technologies and resources. As a result, we can curb the environmental vulnerabilities of overdependence on a single renewable energy solution.

A good alternative source of energy is geothermal. From a technological and historical perspective, identifying fruitful geothermal resources has been difficult, and drilling in the wrong location is costly. Part of the solution is to create conceptual models to locate geothermal resources.

However, once a geothermal reservoir is located, its behavior must also be understood for asset development, optimisation and improved reservoir performance. Understanding the flow of fluids through porous media rocks​ is critical for techno-economic analysis of the projects. Advanced subsurface modeling and analysis solutions can be used collaboratively to accelerate and de-risk the implementation of these projects.

As technology advances and economies of scale are realised, the role of green hydrogen in the energy transition is expected to grow, due to its potential to decarbonise hard-to-electrify sectors (e.g. heavy industry), store renewable energy, and enhance grid stability.

Pipeline design, analysis and optimisation tools are essential for developing green hydrogen plants. These tools help model stress and strain in hydrogen pipes, design corrosion-resistant pipelines, analyse thermal expansion and optimise for cost-effectiveness. They ensure safe, reliable, and economical hydrogen pipelines for underground storage, transportation to refuelling stations, and injection into natural gas pipelines. Additionally, they enable the creation of detailed design documentation, 3D models, and fatigue analysis.

4. Improving mobility planning

Promoting efficiency in collective modes of transportation is a crucial aspect of sustainable mobility. More citizens will be able to leverage those transportation modes if the time needed to exit or enter terminals (such as railway stations) is the shortest possible. Pedestrian flow can be fully simulated and optimised using advanced pedestrian simulation and modelling software, which also allows testing of evacuation strategies.

The same goes for multimodal transportation. As more people flock to cities, more types of transportation and greater numbers of vehicles exist. Managing mobility is a challenge any local government must manage: what (and where) changes need to be implemented to avoid vehicle congestion, how to integrate lanes for micromobility and buses, and in what way to respond to urban changes and citizens’ preferences. All these scenarios can be thoroughly tested and simulated with mobility simulation software.

5. Planning and managing sustainable cities  

City planners may want to aggregate diverse data types for any number of reasons: more immersive visualisation, better stakeholder communication, increased holistic management and better support for sustainability and resilient outcomes. Cloud-based geospatial visualisation solutions can support this through what is usually called a “single pane of glass”.

It all starts with a digital surface model. With photogrammetry tools, we can generate 3D reality mesh and digital surface models computed from previously collected remote images, positioning data or point clouds obtained from drones, cars, or satellite sensors. We can then use those data layers for different purposes, such as contextual information (e.g. background tiles) for visualising other layers, as input data for other models, or for AI-driven feature extraction for object detection and recognition (e.g. computer vision).

This technology has a range of applications, including:

• computing and/or visualising 3D visual scenarios for city-scale flood risks;
• promoting sustainable practices across the city regarding energy needs for buildings and facilities;
• modelling urban heat and sidewalk/road safety simulations; and
• assessing individual trees’ health conditions to predict maintenance needs and repair.

6. Monitoring critical infrastructure assets

As climate mitigation increases our need for more critical infrastructure related to clean energy production and flood control, such as hydropower dams, the higher climate risks bring us more focus on monitoring those assets. Fortunately, we can leverage IoT and AI to build advanced monitoring and inspection systems.

High-fidelity reality mesh models from dams (based on drone surveys, for instance) can be leveraged for remote, virtual inspections. For instance, a technician in Australia can inspect a dam in the US. Computer vision and AI can also improve inspections for automatic crack detection. IoT sensors can then be implemented to build early warning systems that automatically trigger alarms when a ground deformation is identified, or an environmental anomaly (such as stage level rise) is detected. All this can be accomplished with digital dam monitoring solutions.

7. Managing water distribution systems

Data-driven solutions for smart management of water distribution bring several benefits in terms of improved environmental performance. One example is energy-efficient pump optimisation.

Energy costs often comprise 25%-30% of a utility’s total operation and maintenance costs, while pump energy specifically can make up as much as 50% of a water utility’s electricity consumption. However, by leveraging digital twins, operators can import pump performance data while managing their water supply network and compare operational data with pump curves to assess how well the operating point matches the best efficiency point. They can also compare pump operations over historical periods by pulling pump data from different times to see if performance changes.

In addition, these solutions can help reduce non-revenue water (NRW), water that has been produced and is ‘lost’ before it reaches the customer. NRW has a significant economic impact – recent data estimates that global annual NRW is 126 billion cubic metres, translating to roughly $40bn in annual losses. Digital twins can help monitor flows and pressures, identify anomalous events, understand water losses, and prioritise areas for replacement that need it most. The result is a significant reduction of NRW of 20% or more.

A dynamic solution

Digital twins are rapidly transforming the way we design, build and operate infrastructure. This transformative technology offers a powerful tool to accelerate the transition towards a sustainable future, enabling data-driven decision-making throughout the infrastructure lifecycle.

From optimising green hydrogen plants to managing critical water resources, the applications of digital twins in sustainable infrastructure development are vast and ever-evolving. By embracing this technology, we unlock the potential to build a future where infrastructure is not just functional, but environmentally responsible, resilient and contributing to a thriving planet.

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