Identification of Damaging Road Events Using Pseudo Damage Density

As a vehicle travels along a road, it experiences a variety of Damaging Events (DEs) in addition to lengthy regions that contribute insignificant damage. Identifying the DEs in a measured road profile would improve the efficiency of vehicle durability analysis and testing. The objective of this work is to develop a method to identify and quantify significantly damaging road events based on pseudo damage (PD) density: the PD per distance traveled. DEs are defined as regions that cause significant PD in one or more load paths of interest and are separated by Inactive Regions (IRs). Once IRs are identified, an optimization problem is formulated, through which the optimum set of DEs is identified. This optimum set is constrained to account for some minimum fraction of PD in all load paths and maximizes the efficiency of the representation. A proof of concept is provided, in which a golden quarter-car model with two load paths (spring and damper) is simulated on a Federal Highway Administration (FHWA) Long-Term Pavement Performance (LTPP) program test site. Applying the proposed method to this simple example, in which 70% of the PD in each load path is accounted for, resulted in three-quarters of the PD accounted for with one-quarter of the locations, achieving a maximum efficiency of three.