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The proliferation of technological capability, miniaturization, and demand for aerial intelligence is pushing unmanned aerial systems (UAS) into the realm of a multi-billion dollar industry. This book surveys the UAS landscape from history to future applications. It discusses commercial applications, integration into the national airspace system (NAS), System function, operational procedures, safety concerns, and a host of other relevant topics. The book is dynamic and well-illustrated with separate sections for terminology and web- based resources for further information.
Inspired from the legacy of the previous four 3DFEM conferences held in Delft and Athens as well as the successful 2018 AM3P conference held in Doha, the 2020 AM3P conference continues the pavement mechanics theme including pavement models, experimental methods to estimate model parameters, and their implementation in predicting pavement performance. The AM3P conference is organized by the Standing International Advisory Committee (SIAC), at the time of this publication chaired by Professors Tom Scarpas, Eyad Masad, and Amit Bhasin. Advances in Materials and Pavement Performance Prediction II includes over 111 papers presented at the 2020 AM3P Conference. The technical topics covered include: - rigid pavements - pavement geotechnics - statistical and data tools in pavement engineering - pavement structures - asphalt mixtures - asphalt binders The book will be invaluable to academics and engineers involved or interested in pavement engineering, pavement models, experimental methods to estimate model parameters, and their implementation in predicting pavement performance.
Sponsored by the Highway Division of ASCE; Long-Term Performance Program of the Federal Highway Administration. This collection contains papers from the International Contest on LTPP [Long-Term Performance Program] Data Analysis 1998-1999. This competition involved university students in the analysis of data in the LTPP database. Topics include: effect of locked-in curvature on portland cement concrete pavement; evaluation of a pavement performance prediction model using LTPP data; prediction of pavement performance?a neural network approach; and effectiveness of preventative maintenance strategies for asphalt concrete pavements based on LTPP distress data.