Evaluating gantry crane-way pavement performance: An inverse approach. (March 2021) - Ghasemi, Parnian; Aslani, Mohamad; Ashlock, Jeramy C.; Williams, R. Christopher; Schaefer, Vernon R.
Abstract: Gantry-crane pavements and foundations are significant assets within intermodal facilities. The performance of these pavements, which are subjected to highly-variable loads, is critical to safe operations. Traffic interruptions and costs associated with maintaining and rehabilitating distressed or failed pavements in associated areas are of particular importance. The purpose of this study was to evaluate structural behavior and improve design procedures for gantry crane way pavement used at intermodal facilities by assessing interactions among pavements, subgrades, and operational loading conditions. The performance of the gantry crane pavements and foundations was assessed using a finite-element (FE) model, while pavement structural response to a crane load was measured using strain gages installed in the field. Measuring material properties using in-situ/laboratory tests was not possible in this work due to the limited resources, restricted access to intermodal facilities, and tight schedule of rail freight transport(i.e. tight schedule of cranes). To verify the materials properties and ensure a consistent behavior of the developed FE model with respect to the field measurements, an inverse design approach was implemented. Because of the significant cost of FE simulation, the gradient-based solver used in this study is based on a trust region algorithm. The verified model was used to predict the critical responses of Portland cement concrete (PCC) layer, base course, and subgrade soil. These parameters were then used to conduct a pavement fatigue damage analysis, parametric analyses of material strength and slab geometry were carried out based on Model Code, and resulting fatigue-life recommendations for improved designs were made. The developed FE model along with the inverse approach create a framework that can be used in further health monitoring problems when a specific parameter cannot be directly observed.