Manufacturing professionals were among the first adopters of digital twins. With the technology, engineers can see highly detailed, virtual versions of real-life assets, such as facilities and pieces of equipment. They can see the effects of changes before implementing them. Now many industries have embraced digital twins.
Reduce the Overall Weight of Structures
It’s often desirable to make structures as lightweight as possible without sacrificing safety. Taking that approach tends to make costs more manageable. A recent project involving offshore wind jacket foundations and predictive digital twins showed that virtual models could cut the weight of the required steel for the project. This effort led to a 30 percent reduction in steel weight. The client has also used digital twins for oil and gas installations and has achieved a 10 percent weight reduction in such cases.
The digital twins achieved impressive accuracy due to real-time data feeds. Future research for this project will use machine learning and optimization routines to understand how the structural designs behave under typical conditions. Engineers can then use that information to shape future decisions for offshore wind power setups.
It’s still relatively uncommon to rely on digital twins for that reason. However, as more engineers explore their possibilities, such use cases may become more widespread. That’s especially likely if the efforts provide meaningful benefits.
Thomas Leurent is the CEO of Akselos, which provided the digital twin software for the offshore wind pilot project. He suggested that future digital twin usage could result in improved designs, saying, “The pilot project has shown just how much overconservatism exists in the current design process and the astonishing amount of value that can be realized by adopting emerging technologies like our digital twins.”
Enhance Public Usage Experiences
Digital twin software can also aid engineers in assessing how to make the most beneficial changes in public spaces. Planning and civil engineering professionals could glean the most accurate details before pressing ahead with an upcoming project.
A new endeavor occurring at Dublin City University will result in Ireland’s first digital twin version of a higher education campus. The virtualized environment will collect data from Internet of Things (IoT) sensors about things like footfall, areas of congestion and energy usage. People working on the project hope the data will provide insights into the institution’s student and staff experience.
A British project seeks to move beyond the boundaries of a single site when using digital twin software. It aims to link the data from single virtual models together, creating a gigantic national network. That approach could reduce costs while increasing the overall value for people who use roads, parks and other public spaces.
Digital twins could also help keep people safer during emergencies. One endeavor examined the possibilities of using building information modeling (BIM) and 3D cameras to create a digital twin of fire exits and related data for an existing building. It could aid in safe evacuations, help firefighters become familiar with the structure before arriving at the scene of an emergency, and allow inspectors to verify that fire extinguishers and smoke alarms are installed in the designated places.
A digital twin like that could make it easier for engineers to verify that a building under construction or being remodeled will meet fire codes. Some programs at the university level have fire science modules that students take during their coursework. However, even if aspiring engineers do not add such courses to their curriculum, they still must assess how to make public spaces as safe as possible if a blaze should occur.
Improve Monitoring of Critical Structures
Research also shows the promise of applying the technology to infrastructure monitoring needs. For example, digital twin insights could tell engineers when a bridge needs repair work. If an engineering team gets that alert early enough, work could occur over a shorter period, reducing disruptions for the affected parties.
For example, Victoria, Australia, has more than 7,000 bridges that need regular checks to ensure their safety and functionality. Plus, an estimated $45 billion will be spent between 2010 and 2024 to maintain and renew local Australian roads. However, using digital twin software to monitor the condition and usage of such infrastructure could help engineers plan when to begin essential work, enabling them to avoid waiting too long and potentially making costs rise.
Engineers can also apply other technologies to their digital twin usage, including artificial intelligence (AI). One project involved training a neural network with thousands of paired images to find areas of excessive stress and strain. Besides enabling better monitoring, that approach could improve material selections during the building process.
Improve Product Usability and Quality
Many engineers have opportunities to work on pioneering projects that could shape people’s lives soon and for decades into the future. In such cases, a digital twin for engineers could help teams visualize a product’s dimensions, features and other crucial characteristics. This could reduce the likelihood that an item fails to perform as expected once it’s prototyped or goes into production.
In one instance, researchers proposed building a digital twin that captures the entire life cycle of electric car batteries. They envisioned a virtual model that included details from a battery’s earliest design phases through what happens on a production line. They also suggested the digital twin be immediately updated when changes occur. That way, engineers and all other involved parties can stay abreast of the latest developments.
This example shows how crossover can happen between the engineering and manufacturing industries. It’s already common for professionals from both realms to have ongoing communications throughout a product’s development. However, a digital twin could make those discussions more seamless and productive.
Minimize Preventable Problems
Engineers can’t predict the future with certainty. However, they can apply their experience and knowledge to every project, using those assets to influence their decisions. Before long, it could be common to see a digital twin engineering application that makes professionals better able to address problems before they arise.
Karen Wilcox is the director of the Oden Institute for Computational Engineering and Sciences at The University of Texas at Austin. She’s well aware of the growing interest in using drones to deliver everything from pizzas to medicine. Wilcox imagines a time soon when operating drones have accompanying digital twins that track changes in the aerial vehicle.
An associated project involving multiple universities creates a digital twin that shows the whole vehicle as well as each component. The virtual version also uses physics-based models to gather data about the drone’s in-flight behavior. Information from onboard sensors goes into a predictive analytics model that provides future-oriented insights into the vehicle’s health.
In one experiment, the team simulated a case where a drone suffered light damage in flight. The digital twin and sensors made it possible for the team to get details about the incident and how it would affect the drone’s structural integrity. The collected data and smart algorithms also recommended that operational changes be made to the vehicle so that it could keep flying after the incident occurred.
Digital Twin Software Shows Promise in Engineering
Today’s engineers frequently participate in projects that require meeting deadlines, staying under budget and mitigating possible problems. The examples here and elsewhere highlight why it might become a more common practice for engineers to use digital twin technology. They could provide valuable visibility, enabling engineering professionals to succeed more often in problem-solving and make informed decisions at all stages of their work.