Cracking pavement isn’t just a nuisance for drivers — it’s a costly problem for transportation agencies.
University of Illinois Urbana-Champaign researchers developed a way to predict cracking potential of modified asphalt binder, helping agencies and contractors to select materials with the best long-term performance before mix production begins.
Imad Al-Qadi, Illinois Center for Transportation director and Grainger Distinguished Chair in Engineering, worked with Illinois Department of Transportation’s Kelly Senger and Brian Hill, chief chemist and hot-mix asphalt operations engineer, respectively, in the ICT-IDOT project, “R27-250: Using Advanced Binder Rheological Parameters to Predict Cracking Potential of Hot-Mix Asphalt Mixtures with Modified Binders.”
Asphalt binder holds aggregate together in pavement and gives it flexibility to withstand stresses from traffic and the environment. With roadways experiencing heavier traffic loads and increased use of recycled materials, agencies are turning to binder modifiers like polymers and softeners to increase the performance of pavements.
Traditional performance testing methods may not capture modified binder’s cracking potential accurately and advanced methods are time-consuming, so Al-Qadi’s team aimed to develop a model that uses characteristics of asphalt binder to determine a mix’s potential performance.
The team added various polymers and softeners to binder, improving strength in heat and flexibility in cold, then used advanced testing and aging simulations to replicate mixing, paving and field use.
They evaluated the best-performing blends in hot-mix asphalt using the Illinois Flexibility Index Test to measure cracking potential and the Hamburg Wheel-Tracking Test to assess rutting, or surface deformation.
By studying how different binders respond to stress and temperature changes, Al-Qadi’s team developed a model that allows users to predict pavement cracking based on binder characteristics such as its resistance to deformation, stress relaxation rate and amount of recycled material.
“Our predictive model links binder characteristics directly to pavement performance,” Al-Qadi said. “This lets us flag problem binders early and focus on those with the best potential, saving time and money during design, while helping contractors to select the best binder and optimum modification to control in-service pavement cracking.”
The team also developed a risk-based framework that classifies binders as good, borderline or needing more testing, helping agencies quickly identify the best options for durable pavements.
The research offers IDOT a data-driven path to smarter pavement design, before a single ton of asphalt is laid, saving agencies time and resources while giving drivers smoother, longer-lasting roads.
“There was incredible teamwork between our team at ICT and IDOT, including the technical advisory members, with ongoing input from both sides,” Al-Qadi said. “That collaboration helped us exceed the project’s original objectives and deliver something that benefits everyone.”
“The work by ICT engineers and students has been remarkable, led by Gafar Sulaiman, Hong Lang and Uthman Mohamed Ali,” he added.