Exploring the Future of Digital Twins in Civil Engineering

Digital twins in construction are virtual representations of physical objects, such as buildings, bridges, or entire cities, that use real-time data exchanges and advanced computer modeling to accurately simulate the behavior of their real-world counterparts.

Digital twin technology is useful for safely and efficiently designing, planning, and testing structures. It also supports effective monitoring and predictive maintenance activities throughout a building’s lifecycle.

Once a digital structure is established using 3D modeling technology, characteristics like stress loads and energy consumption can be captured and communicated from the real building using sensors, cameras, and survey data as the model is synchronized with reality.

Additional industries and professions that have embraced the benefits of digital twin technology include:

• Manufacturing operations that use twins to predict bottlenecks and improve productivity.

• Healthcare providers and medical researchers who study diseases using precise models of patient anatomy.

• Aircraft designers who test the feasibility of new concepts and changes virtually.

The components of a construction digital twin

A digital twin for construction is much more than just an accurate 3D model. Incorporating live data streams to mirror reality in virtual space is the key to on-demand testing, self-optimization, and unmatched visibility. The components of a digital twin that make this breakthrough possible include:

• Building Information Modeling (BIM): Multi-dimensional BIM models encode every specification, dimension, and material property within a highly detailed virtual platform that integrates real-time activity during and after construction. The BIM model forms the foundation for the digital twin building.

• Internet of Things (IoT): Real-time sensing using the Internet of Things (IoT) is the second important element of the digital twin, with everything from humidity and temperature to asset condition and location monitored continuously and transmitted back to the twin.

• Artificial Intelligence (AI): Machine learning and AI algorithms allow sensor data transferred to the BIM model to be converted into real-time insights on safety, maintenance, and performance. These capabilities also make advanced assessments of “what-if” scenarios possible during the design and construction phases.

Digital twin construction technology provides a long list of benefits that continues to grow as the applications and tools evolve. As with any advancement, there are also some challenges that must be addressed.

Advantages:

• Improved efficiency

Testing design concepts and changes using a digital twin rather than an actual structure or physical model saves teams time and money from concept through project completion. As the digital twin lives on throughout the building’s active life, sensor data makes it easier to predict maintenance requirements, optimize electricity and water consumption, and test proposed building upgrades without disturbing occupants.

• Better collaboration

A BIM digital twin breaks down silos between construction teams, designers, and construction architects by putting as much building information as possible onto a cloud-based platform that can be accessed from anywhere. With the status continually transferred from the field to the office, there is less chance of miscommunication.

• Enhanced safety

Safety is an important byproduct of digital twin technology in construction, since unsafe conditions can be detected more efficiently based on data transferred to the twin. During the design phase, engineers use the digital twin to accurately test the impact of earthquakes, high winds, and other extreme weather events.

• Real-time asset tracking

With an assist from the IoT, construction drones, and other monitoring and surveillance tools, the virtual model mirrors the conditions of the actual building, along with the machinery, materials, vehicles, and (sometimes) workers within it in real-time. This limits the need for physical monitoring and asset tracking activities and also makes resource allocation processes more efficient.

Challenges:

The shift to digital construction practices also brings issues and challenges that include:

• Data overload

A building digital twin can become one small part of a system-wide twin spanning an entire city. This type of expansion can easily lead to data overload, with more data available than can be effectively stored or analyzed. This also makes it difficult to eliminate sources of data noise that impact decision-making and accuracy.

• Security concerns

The ongoing connection between digital twins and physical structures can make them a target for attackers seeking to identify weaknesses or intercept data transmissions. Any implementation of digital twins in construction should include advanced cybersecurity solutions and access controls to guard against these attacks and threats.

• Resistance to change

Construction software for planning, estimating, scheduling, and other important functions is quickly changing perceptions about the value of technology, but digital twins take this evolution to an even higher level. Limited implementation for small projects helps to break down resistance by demonstrating the benefits without fully detaching from traditional methods.

• Connectivity infrastructure

Connectivity is what separates detailed BIM models and simulations from fully integrated digital twins for construction. Establishing a network of IoT sensors to turn static models into real-time twins can be a time-consuming and expensive prospect. To ensure accuracy and safety, this infrastructure must be fully installed and tested before launching the system.