Researchers at the University of Mississippi are leveraging artificial intelligence to create more resilient and sustainable infrastructure, optimizing materials and reducing costs.
From predicting potholes to designing more durable concrete, artificial intelligence is transforming the future of infrastructure. A new study from the University of Mississippi, published in the International Journal of Pavement Engineering, explored the capabilities of different AI algorithms to predict moisture damage in asphalt pavements with reclaimed asphalt pavement (RAP) materials.
“The goal of our team in the NextGen Infrastructure Lab is to move toward the next generation of sustainable and resilient infrastructure,” Ali Behnood, an assistant professor of civil engineering at the University of Mississippi, said in a news release. “We’re optimizing the use of recycled materials, industrial by-products, renewable resources and alternative sustainable materials in construction, while also reducing physical, labor, energy, environmental impact and lifecycle maintenance costs.”
Behnood conducted the study with Abolfazl Afshin, a doctoral student in civil engineering.
“We focused on moisture damage, which is one of the most critical issues in asphalt pavements, particularly for wet and cold regions, because it results in a variety of distresses like stripping, potholes and cracking,” Afshin said in the news release. “We evaluated the effectiveness of four different artificial intelligence algorithms in predicting moisture damage in asphalt mixtures containing (reclaimed asphalt pavement) materials.”
“What we found was that these algorithms are able to effectively predict moisture damage in asphalt mixtures with high accuracy. Based on these results, we can optimize material selection and predict failure probability in the pavement’s life cycle,” he continued.
In 2021, state and local governments spent over $206 billion on road maintenance, with the Department of Transportation reporting nearly $1 trillion in backlog repairs and maintenance required for roads and bridges. The optimization of asphalt mixtures using AI could significantly reduce these maintenance costs and extend the lifespan of roads.
Behnood emphasized the importance of AI in simplifying the traditionally labor-intensive and costly process of determining the best material mixtures.
“Artificial intelligence-based algorithms offer a cost-effective and efficient alternative to traditional, time-consuming and energy-intensive lab-based approaches,” he added.
The practical applications of Behnood’s team’s research are extensive.
“The results of all these studies can be used by practicing engineers, by the Department of Transportation, federal agencies, private sectors – whoever who works in this area – to move toward sustainable, cost-effective approaches in the design,” Behnood added. “The tools we develop can be used by any practicing engineers.”
Moreover, Behnood sees AI playing a vital role in various infrastructure aspects beyond pavement durability.
“AI can also play a crucial role in disaster resilience and risk management,” he added. “In the event of disasters or natural hazards, evacuation becomes critical, and AI can identify optimized routes tailored to various evacuation scenarios, ensuring efficiency and safety.”
By integrating AI-driven methods across diverse facets of construction and infrastructure, Behnood and his team are contributing to sustainability and societal progress.
“There are so many examples of how we can use AI for sustainability in all elements of construction and infrastructure. This is a huge area, and we are doing our little part to help society,” Behnood concluded.