We talk with leading educators and researchers to learn more about the people and topics of asphalt technology.
Dr. Mena I. Souliman, Ph.D., P.E., F.IRF is an Associate Professor in Civil Engineering at the University of Texas at Tyler and director of the Texas Rural Transportation Research Center (TRTRC).
What drew you to transportation engineering?
I always enjoyed seeing roadways being built when I was a child. I used to be amazed, looking at roadways and moving cars from the seat of an airplane right after takeoff. My uncle was a civil engineer and I used to listen to his stories about roadway construction. When I went to college, I was first interested in structural engineering but moving on to my master’s and Ph.D. journey at Arizona State University, I became interested in pavement materials. I found that this field is, relatively speaking compared to other civil engineering areas, still in its infancy where there are a lot of unanswered questions on how asphalt pavement structures function and how such structures are highly affected by the surrounding environmental, geographical and traffic conditions.
Are there many advancements when it comes to asphalt fatigue endurance limit prediction?
My Ph.D. work at ASU concentrated on developing a clear linkage between the concepts of asphalt healing and asphalt fatigue endurance limit. Several studies in the past looked at either one of these two concepts but none accredited that having an endurance limit is due to the fact that asphalt does heal. I developed a healing-based prediction model that predicted endurance limit for conventional asphalt pavements. Currently, I am working at predicting the endurance limit for non-conventional asphalt mixtures such as asphalt rubber, warm mix asphalt, RAP and RAS. My research group and other researchers around the world are also working on developing self-healing asphalt materials, which will eventually improve the fatigue endurance limit for asphalt mixtures.
What special considerations are there for designing asphalt bicycle lanes?
In 2017 I was approached by the city of Tyler, Texas to design an asphalt bicycle lane network for the city. I came up with the Bicycle Lane Engineered Scoring System (BLESS) which included a mathematical algorithm to guide engineers on how to select the appropriate candidate roadways that can lead to a safe introduction of a designated bicycle lane. Such methodology included factors as the pavement surface roughness of the bike lane, vertical grades, the width of the existing vehicular lanes, number of existing lanes, the existing speed limit, traffic volume, as well as the available sight distance. The developed BLESS was presented at the transportation research board annual meeting in Washington D.C. in January of 2020. The developed system can be utilized to build bike lane networks for any other midsized cities in the nation. The design phase was completed last August and now the city is in the process of soliciting proposals from contractors in order to start the construction work in 2021.
How can 3-D finite element modeling improve pavement design?
It is a great tool that can allow us to understand and test structures under many conditions. This eventually would reduce the amount of lab and/or field-testing that we may need to do. 3-D finite element can also be adapted to meet certain cracking or rutting specifications for accuracy in order to decrease the need for physical prototypes in the mixture design process. Creating multiple iterations of initial asphalt pavement prototypes is usually a costly and timely process. Instead of spending weeks on hard prototyping, the asphalt pavement designer can model different designs and materials in hours via software packages such as the 3-D Move Analysis package which I have been using quite extensively for the past 5 years.
What are some areas that current students should focus on for their asphalt research?
With reduced annual budgets allocated to road construction, I think students should consider focusing on ways and topics that can make us use our limited resources in a more efficient way. Such topics include, but are certainly not limited to, how to build more sustainable asphalt pavement structures using recycled materials such as recycled rubber and plastics. Another topic would be studying autonomous vehicles and how we can mitigate their adverse effects on asphalt pavement structures. One last hot topic is the use of artificial intelligence and machine-learning techniques that can help us predict the future performance of asphalt pavement structures while we can reduce how much field and lab testing we need to continue doing over time.
