The Dynamic Modulus (E*) mixture test is key to mechanistic-empirical pavement design. However, the traditional E* tests are expensive, complex and time consuming to run. Most agencies and road owners don't calibrate the models to account for new materials that have been introduced into the industry such as RAP/RAS/, additives, warm mix, etc. Also, the existing models are volumetrics based. The AI-powered IDEAL E* test integrates the IDEAL Cracking tests, Finite Element Analysis and machine learning to produce E* values more quickly and with less effort than traditional E* testing
Keywords
Artifical Intelligence
Rationale
The AI-powered IDEAL D* test makes it easier to characterize materials used in roadway construction for pavement design. The traditional test methods are time consuming and difficult to perform as well as require expensive test equipment. This method takes advantage of artificial intelligence, neural networks and machine learning to help advance the materials characterization process for pavement design purposes.
