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Most mechanistic-empirical methods for determining the integrity of an existing pavement rely on the use of deflection-based nondestructive evaluation devices to determine the integrity of a pavement section. To estimate the remaining life associated with two types of distress in a flexible pavement, namely fatigue cracking and rutting, the critical strains and stresses at the interfaces of the layers of the pavement should be known. After the critical strains are calculated, a number of models can be used to estimate the remaining life. This report presents a case study that shows the feasibility of using an algorithm based on artificial neural network technology (ANN) to estimate the remaining life of flexible pavements. The report includes, in detail, the development and results of a system of ANN models that have been developed to predict the critical strains for a wide range of three and four layer flexible pavement sections with variable depth to bedrock. The inputs to these ANN models are only the best estimates of the thickness of each layer and the surface deflections obtained from a Falling Weight Deflectometer (FWD).
A software program has been developed to predict the remaining life of flexible pavements using artificial neural network (ANN) technology. The remaining life due to either rutting or fatigue cracking can be predicted. The inputs to the software are the best estimate of the thickness of the layers, the deflection basin measured with a falling weight deflectometer (FWD), and optionally, the extent of damage at the time of the FWD test. The outputs are the best estimate of the remaining life and the pavement performance curve. If uncertainty in the thicknesses, FWD measurements and traffic exists, a probabilistic description of the remaining life is also provided. The main benefit of the proposed approach is that the backcalculation process for determining moduli is not necessary. The remaining lives or alternatively the critical stresses needed to calculate them are directly estimated. As such, the results seem to be more robust. In this paper, the overall procedure and the details of the methodology followed in developing the software are described. A case study is included to demonstrate the application of the methodology.
Most mechanistic-empirical methods for determining the remaining life of an existing pavement rely on the use of deflection-based nondestructive evaluation (NDE) devices. This report describes a methodology based on Artificial Neural Network (ANN) techniques to estimate the remaining life of flexible pavements given the occurrence of two possible failure modes: rutting and fatigue cracking. The ANN techniques are also used to develop models that predict the critical strains at the interfaces of the pavement. The inputs to all the models are the best estimates of the thickness of each layer and the surface deflections obtained from a Falling Weight Deflectometer test. Uncertainty in these variables is accounted for by the proposed methodology. The report also describes an approach to the production of pavement performance curves using the results of the ANN models.
As with the previous two symposia, the 32 papers from the June/July, 1999, Seattle symposium present advances in the nondestructive testing of pavements using conventional falling weight deflectometer techniques and other promising techniques such as ground penetrating radar, rolling weight deflecto
Innovations in Road, Railway and Airfield Bearing Capacity – Volume 1 comprises the first part of contributions to the 11th International Conference on Bearing Capacity of Roads, Railways and Airfields (2022). In anticipation of the event, it unveils state-of-the-art information and research on the latest policies, traffic loading measurements, in-situ measurements and condition surveys, functional testing, deflection measurement evaluation, structural performance prediction for pavements and tracks, new construction and rehabilitation design systems, frost affected areas, drainage and environmental effects, reinforcement, traditional and recycled materials, full scale testing and on case histories of road, railways and airfields. This edited work is intended for a global audience of road, railway and airfield engineers, researchers and consultants, as well as building and maintenance companies looking to further upgrade their practices in the field.
The term “soft computing” applies to variants of and combinations under the four broad categories of evolutionary computing, neural networks, fuzzy logic, and Bayesian statistics. Although each one has its separate strengths, the complem- tary nature of these techniques when used in combination (hybrid) makes them a powerful alternative for solving complex problems where conventional mat- matical methods fail. The use of intelligent and soft computing techniques in the field of geo- chanical and pavement engineering has steadily increased over the past decade owing to their ability to admit approximate reasoning, imprecision, uncertainty and partial truth. Since real-life infrastructure engineering decisions are made in ambiguous environments that require human expertise, the application of soft computing techniques has been an attractive option in pavement and geomecha- cal modeling. The objective of this carefully edited book is to highlight key recent advances made in the application of soft computing techniques in pavement and geo- chanical systems. Soft computing techniques discussed in this book include, but are not limited to: neural networks, evolutionary computing, swarm intelligence, probabilistic modeling, kernel machines, knowledge discovery and data mining, neuro-fuzzy systems and hybrid approaches. Highlighted application areas include infrastructure materials modeling, pavement analysis and design, rapid interpre- tion of nondestructive testing results, porous asphalt concrete distress modeling, model parameter identification, pavement engineering inversion problems, s- grade soils characterization, and backcalculation of pavement layer thickness and moduli.
Bearing Capacity of Roads, Railways and Airfields focuses on issues pertaining to the bearing capacity of highway and airfield pavements and railroad track structures and provided a forum to promote efficient design, construction and maintenance of the transportation infrastructure. The collection of papers from the Eighth International Conference
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.
Innovations in Road, Railway and Airfield Bearing Capacity – Volume 1 comprises the first part of contributions to the 11th International Conference on Bearing Capacity of Roads, Railways and Airfields (2022). In anticipation of the event, it unveils state-of-the-art information and research on the latest policies, traffic loading measurements, in-situ measurements and condition surveys, functional testing, deflection measurement evaluation, structural performance prediction for pavements and tracks, new construction and rehabilitation design systems, frost affected areas, drainage and environmental effects, reinforcement, traditional and recycled materials, full scale testing and on case histories of road, railways and airfields. This edited work is intended for a global audience of road, railway and airfield engineers, researchers and consultants, as well as building and maintenance companies looking to further upgrade their practices in the field.
This book is an outcome of the sixth conference on bearing capacity of roads and airfield held in Lisbon, Portugal. It focuses on railway tracks and covers following topics: bearing capacity policies, concepts, costs and condition surveys; analysis and modelling; design and environmental effects.