Orange Park, Fla. — The Asphalt Pavement Alliance is hosting a webinar on May 30 to introduce Version 4.3 of PerRoad Perpetual Pavement design software. Developed at Auburn University, PerRoad uses the mechanistic-empirical design philosophy to estimate stresses and strains that would prove detrimental for fatigue cracking or structural rutting.
PerRoad Version 4.3 incorporates recent research conducted on the Pavement Test Track at the National Center for Asphalt Technology at Auburn University and then validated with live traffic on Perpetual Pavement sections. The new features allow PerRoad to perform a conventional mechanistic-empirical (M-E) design to directly compare against Perpetual Pavement designs. It can also use strain distribution or a single endurance limit strain value to design a Perpetual Pavement.
“Perpetual Pavement designs allow us to limit distresses to the easily repaired surface,” stated David Timm, Ph.D., P.E., developer of PerRoad. “By coupling layered elastic analysis with a statistical analysis procedure, PerRoad helps a designer understand the layer thicknesses and other values that will ensure a long-life asphalt pavement.”
To introduce these new features, as well as to discuss the Perpetual Pavement design philosophy, Timm, Ph.D., P.E., will present a webinar Tuesday, May 30 at 1:00 EDT. The webinar will teach attendees how to use PerRoad 4.3 to compare pavement designs developed through the 1993 AASHTO Pavement Design Procedure, the AASHTO MEPDG process, and other M-E Design procedures. Attendees can receive 1 professional development hour (PDH) for participating in the webinar.
To register for the free webinar, visit https://attendee.gototraining.com/r/6439457356261879298.
PerRoad, which is available for free from www.AsphaltRoads.org/PerRoad uses the mechanistic-empirical design philosophy. The program couples layered elastic analysis with a statistical analysis procedure (Monte Carlo simulation) to estimate stresses and strains within a pavement. Version 4.3 provides design results as percentile responses and as conventional designs with transfer functions.