![]() ![]() © 2014 American Society of Civil Engineers.Find a library where document is available. ![]() Evolutionary optimization/nonlinear optimization algorithms were implemented with the developed ANN models to improve the accuracy of predictions. The current study aims to develop a fully automated backcalculation software system, referred to as I-BACK, with improved accuracy and usability of Iowa FWD data. The Pavement ME Deflection Data Analysis and Backcalculation Tools is a standalone software program that can be used to generate backcalculation inputs to the AASHTO Pavement ME Design software for rehabilitation design. Researchers at Iowa State University (ISU) have developed a suite of advanced pavement layer moduli backcalculation models using the artificial neural networks (ANN) methodology for flexible, rigid, and composite pavements. More efficient and faster methods in FWD test data analysis were demanded and deemed necessary for routine analysis. However, the pavement layer moduli backcalculation techniques used so far have been cumbersome and time consuming. The Iowa Department of Transportation (DOT) has been collecting falling weight deflectometer (FWD) data on a regular basis. Backcalculation Software ELMOD Analysis of flexible Pavement Mohamed Elshaer Full PDF Package This Paper A short summary of this paper 8 Full PDFs related to this paper Read Paper Evaluation of Layer Moduli and Overlay Design Mohamed Elshaer Cairo University ffELMOD f1. I-BACK: Iowa's Intelligent Pavement Backcalculation Software ![]()
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