What digital twin (DT) means for the construction and engineering industry

Dr Mohamed Nazier: Dr Maher, welcome to the Anticipate podcast. Let’s kick this episode off with a general question about DT. It is now used in many industries. From your perspective, how would you define it, and what does it mean for engineering, especially around construction and manufacturing?

Maher: To understand DT, we must travel back in time to understand how engineering and industrial manufacturing evolved. Before the 1800s, we had the craftsmanship age. Craftsmen used to work faster and produce high quality, and that is what gave them the edge. From 1800 to 1950, we had the machine age. We understood the underlying physical laws of mechanics, electromagnetism and other fields of science. We learnt to design machines to manipulate these laws and assist us in engineering and construction. So, back then, if you had more sophisticated machines and assembly lines, you had the competitive edge. From the 1950s to the 2000s, we entered the information age. Here, we started to have integrated circuits, affordable and accessible computers, automated equipment and information systems. Now we have the internet of things (IoT) which is the idea of using sensors to acquire data about various systems. So in this age, information has given us the edge. In each of these ages, data volume, variety and complexity have increased. Lastly, we entered the big data age. Here we have very advanced physical models, lots of data, and artificial intelligence (AI). Engineering systems are becoming much more complex, and they involve solving many physics problems. Hence, the models we need to build to keep up with these systems must also be very complex. Here is where digital twin (DT) comes in. DT is an agglomeration of all these physical models and the data we have in complex engineering systems. It incorporates the physical laws for every engineering, construction and manufacturing model. DT was not feasible twenty years ago. But now we have capable computers that can model an entire infrastructure system much more easily.

Dr Nazier: From hand workmanship to the industrial revolution, then digital, how did this idea of digital twining really come about in academics and the industry?

Dr Maher: There are several prominent examples in the literature that pinpoint the initial phases of digital twinning. The one that really stands out is the concept that was introduced by NASA in the 1960s and 1970s, especially during the Apollo era. NASA made duplicates of the various space systems that they put together. These duplicates were mostly used for training purposes. During the Apollo13 mission, when an oxygen tank exploded, resulting in damage to the oxygen supply and propulsion systems, these duplicates were used on the ground and were crucial in saving the lives of those astronauts. Although Apollo 13 did not use IoT, Nasa did use many sensors and telecommunication technology which allowed for access of the information in the spaceship and updating these simulators on the ground.

Dr Nazier: It is exciting how most of the critical missions produce technologies that we use in the construction and engineering industry.

Dr Maher: Yes, we have also learnt a lot from the aviation industry. They have DT, for example, for jet engines and other critical components of aeroplanes. So, there are a lot of technologies out there now, but the question is how to integrate them and make the best use of them in our own field.

The difference between DT, BIM and cyber-physical systems (CPS)

Dr Nazier: Some of our listeners may be familiar with BIM and cyber-physical systems (CPS). I think they are more advanced in our field than DT at the time being, but I think DT seems to be catching up. So, it might be worth it to speak about the differences between DT, BIM and CPS.

Dr Maher: BIM is pretty ubiquitous now. We have been using it in various parts of infrastructure system design and construction. But the main difference between DT and BIM is the connections. These are essential for DT but not necessary for BIM. BIM is a digital representation of a physical part. For BIM, the physical counterpart may or may not exist yet. As for CPS, the physical and virtual parts may not be the same thing which is not the case for DT.

The five main components of DT

Dr Nazier: So far, you’ve talked about the real physical system. What other constituents does a digital twin have?

Dr Maher: Within our field, we can break down DT into five components. The first one is the physical part. This can be a single system like a bridge or a series of complex systems like those in manufacturing and virtual system. Then you have the virtual part, which is usually a 3D graphics model of the physical system. The virtual part should mirror the physical one. Then you have the connections, which are essentially the IoT part. Here is where you have information access points such as sensors, cameras, scanners. The connection is any device that is installed on the physical part that can inform and update the virtual part. Data come from individual connections or many fused together. The next element is service which is the objective of DT. It is the problem that we are looking to optimise using the digital twin technology. It could be an O&M task, asset management, or resiliency assessment. These are emerging areas where DT can be effectively utilised. In many systems, we have an additional feature called feedback. This is where the virtual component informs and updates the physical part. So, it is actually looking at the future. It is not a necessary component, but it can be implemented and utilised.

Realising the full potential of DT in the civil infrastructure domain

Dr Nazier: Similar to most technologies nowadays, the questions normally are how much of it that you want to use, what is the cost to benefit ratio? What is the value of using different elements? What is the applicability of using it? So, in the civil infrastructure domain, how can DT better serve the industry?

Dr Maher: We must first consider the types of physical parts that appear throughout the lifecycle of a civil infrastructure asset. Think of a network of bridges, for example. Before an asset is built, the physical can be the environment, the surroundings, regulations, existing projects, etc. While it is under construction, the physical part can be construction processes. During the O&M phase, it can be the asset and all its complexities, including the interaction with the surroundings and people. In the design, DT can be used for virtual verification of a preliminary design by conducting simulation and analysis. In a virtual environment, the design can be tested, improved, updated and verified. DT can also help determine design constraints and is now being used extensively by forward-looking consulting firms. Constructability analysis and testing of site management scenarios can result in better design alternatives.

The construction industry has been gradually moving toward adopting the big data age. There are a lot of BIM and CPS applications that are now being used in the construction industry. In the construction phase, DT can serve to monitor targets such as workers, machinery and materials. This can also serve functions such as construction progress monitoring, quality and safety monitoring and management.

The operation and maintenance (O&M) phase of a project is the longest in the asset lifecycle, and thus it can potentially result in the highest DT return on investment. Continuous updating of the virtual model through the data obtained from the physical twin, and simulating the effects of different decisions, or including do-nothings, can also result in optimising the expenditure made in maintaining the asset. DT use has been extensive in O&M from a monitoring perspective to assist the detection of sudden defects or monitor slow but evolving deteriorations. Once the virtual part is updated, then the digital twin can assist with scenario analysis. Monitoring analysis can inform action and the kinds of corrective measures that must be taken to prolong the service life of the asset.

Dr Nazier: So basically, through the full life cycle of an asset, DT benefits can be achieved through different models and concepts. To dig deeper into the topic, perhaps we can speak about some of the DT uses in case studies or from your experience.

Dr Maher: There are many examples where DT is being used effectively. Some of the most prominent ones are:

• The Minnesota Department of Transportation is using drones to assist with their bridge network inspections. With this approach, they are able to see the changes over time and have a holistic view of their bridge network. Through this exercise, they reported saving of as much as 50%.
• In Norway, the eighty-year-old Stavå bridge has long been a source of concern for the Norwegian public and administration. So, Norway created a cloud-based version of the bridge, which was capable of detecting structural anomalies during the remaining life of this bridge. This DT system also had an automatic notification feature that sent out a notice to the authorities in April 2021, indicating a serious structural deficiency that led to rapid field deployment of inspectors. The bridge is currently closed, and a temporary one has been put into operation while a new one is already under construction. This would not have been possible with the usual management of data through the typical inspection process.
• DT is currently at the heart of smart cities. In Singapore, the smart city initiative that they have is using DT to address planning challenges, traffic congestion management, telephone cell-power optimisation and usage. It enables anything from simulating mobility and traffic patterns to optimising their cell-tower operations in addition to planning for emergency evacuations during big events such as the Formula 1 racing event they hosted.
• In the US, experts are interested in using DT for planning for the resiliency of infrastructure systems with respect to climate change.
• The National Highways Organisation in the UK is currently conducting an ambitious program that focuses on integrating connected and autonomous vehicles, DTs and IoT sensors into how they design, construct and maintain their highway network.

Dr Nazier: It is obvious from these examples that DT uses are not limited to only a specific phase. They are not limited to decision making but can also assist interventions and preventive maintenance. That is one area that we focus on in being future-ready in a lot of what we do. However, I am sure there are challenges with DT creation. Do you want to shed some light on this for our listeners?

Dr Maher: Some of the challenges related to DT can draw a roadmap to what a consulting engineer needs to really focus on if they want to get ahead with this practice. Creating a 3D virtual model that considers the laws of physics is a challenging task. Developing accurate virtual parts depends on the quality of data acquisition, data processing, modelling methods, and expertise. When it comes to data acquisition, sensors have many limitations that must be understood. If you are using an accelerometer, you will not be able to show static deflections of the structure. Creating a 3D model is also challenging. For many assets, as-built records either do not exist or are outdated. While new and more affordable approaches to creating a 3D model have been recently developed, modelling hidden parts of structures, such as rebars, is still a challenge.

The efficiency of data acquisition and processing can influence the modelling process. The models can vary in complexity and accuracy. In civil engineering, projects for different structures (tunnels, roadways, etc.) have each their own physics. Finding commercial software that addresses several of these areas is challenging. In terms of modelling algorisms, obviously, physics-based models are typically more desirable. However, these do not fit well with sensor data sometimes. So, black-box models, on the other hand, can fit well with sensor data, but the modelled parameters may not make much sense. So these are some nuances and problems that have solutions. Nevertheless, the practitioner must be aware of these challenges.

One thing that has been emerging in the last couple of years is the significant improvement in the integration of useful models in DT systems by Bentley Systems and Esri. This has made the creation of DT much easier. However, the underlying and fundamental element is expertise. So, we need to educate and train civil engineers to build these systems, and this goes beyond their traditional education curriculum. They have to become more familiar and well-versed with data and computer science.

The future of DT in the civil infrastructure domain

Dr Nazier: We, as WSP, are focused on digital solutions because the future of urbanisation and infrastructure development is definitely going to be accelerated through similar techniques. Understanding the challenges that underly some of these solutions will help us get there faster. So, we always think of future solutions delivered today for our clients. Most of the assets that we build would need to last 75 years or more. In five to 10 years, what do you think the future holds for us in this domain?

Dr Maher: To realise the full potential of digital twinning, we must first train the next generation of engineers and practitioners who can develop these sophisticated graphics-based models, visualise data through data tools and be able to write AI-based decision-making codes and so on.

The DT approach will promote the development of smart construction. The construction industry is already one of the major buyers of drones and scanning tools. This enhanced monitoring will combine with DT to create low-cost approaches to simulate, calculate, analyse, optimise and manage construction processes, quality and worker safety.

Automation will be a big part of digital. Therefore, AI approaches are going to be needed to minimise human intervention. It will be valuable in the analysis and diagnosis of defects and will enable decision making and automated control. Generative AI approaches will make design highly automated as well.

Blockchain is a method of preserving information in a distributed manner. This technology will contribute to better access and security of IoT, data and DT clouds. To make all of this feasible, we need 5G and high-data-rate internet satellites. Rapid connectivity tools will allow real-time monitoring.

Dr Nazier: Lots of progress is to be made. Collaboration between academia and our industry will be key in making this a success and evolving our engineers of the future.

Dr Maher: Recent market research has suggested that the digital twin market which is worth roughly about 4 billion today, is projected to reach 35.9 billion by 2025. This gives you an idea of where DT is headed.

Dr Nazier: Thank you so much, Dr Ali, for the invaluable insights you shared today. And to our audience, thanks for listening all the way through. Please leave us a comment if today’s discussion has sparked your interest, and don’t forget to join us in two weeks for a new talk.

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