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Author: Mohamed Y. Shahin
Publisher:
ISBN:
Category : Pavements
Languages : en
Pages : 18
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Book Description
Author: Mohamed Y. Shahin
Publisher:
ISBN:
Category : Pavements
Languages : en
Pages : 18
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Book Description
Author: Luis Esteban Amador Jimenez
Publisher: LAP Lambert Academic Publishing
ISBN: 9783659157882
Category :
Languages : en
Pages : 116
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Book Description
Deterioration models are employed to forecast pavement performance and to support decisions of funds allocation for maintenance and rehabilitation. However, they traditionally lack a measure of reliability. This book uses multilevel Bayesian regression modeling for mixing prior knowledge with experimental observations in order to develop deterioration modeling with the ability to quantify uncertainty. It explicitly considers materials properties, structural capacity (or strength), external loading and environmental exposure by adapting classical mechanistic models. Two network level case studies illustrate the applicability of the method and deal with some of the practical limitations: (1) a novel method develops performance modeling from two time series data, using the concept of apparent age, (2) another model uses pavement roughness and strength to address practical limitations such as missing data, incorporating expert criteria and handling predictors from different data structures. The methods presented can help local, regional or national authorities to develop initial, practical or more advanced models for pavement deterioration, capable of capturing uncertainty.
Author:
Publisher:
ISBN:
Category :
Languages : en
Pages : 13
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Book Description
The Ontario Pavement Analysis of Costs system has been in service for Ontario asphalt flexible pavement design and performance prediction since the early 1970s. It uses a deflection-based deterministic model for selecting the best pavement structural design alternative in terms of pavement functional and structural performance and the total life-cycle costs. However, because of the existence of uncertainties and variations in pavement design variables and parameters in the pavement deterioration models, it is not adequate to apply deterministic models to all situations of pavement management. It is therefore necessary to predict pavement performance by employing probabilistic-based models. In this paper, a new concept of system conversion between a deterministic model and a probabilistic model is discussed first. A method by which a deterministic pavement performance prediction model, such as the Ontario asphalt pavement deterioration model, can be converted into a probabilistic model is presented. A transformed probabilistic model is constructed by generating a set of time-related nonhomogeneous Markovian transition probability matrices, which is determined by Monte Carlo simulation. Each of the transition probability matrices characterizes the pavement deterioration rate for the given pavement age and traffic characteristics. A Bayesian technique is then employed to update the predicted pavement performance in terms of the pavement condition state vectors and expected pavement condition state values by integrating additional information such as the actually measured performance data of the pavement.
Author: Mladjan John Grujicic
Publisher:
ISBN:
Category : Metropolitan areas
Languages : en
Pages : 211
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Book Description
Accurate prediction of pavement deterioration is vital for an efficient and cost-effective allocation of available budgets for keeping an agency's road networks operating at a desirable level. Currently, most cities in the Dallas-Fort Worth Metroplex area are using the software PAVERTM and the associated performance models to predict future conditions as they do not have available reliable prediction models. However, the problem with this type of modeling is that the models are not calibrated to local conditions.The Pavement Deterioration Prediction models that have been developed in this research will help any pavement management agencies within DFW Metroplex area to identify and predict the future pavement performance for any planning period. The models were developed based on the available data collected by the city's pavement management department for the DFW Metroplex area. In this research, a family modeling approach has been used as this method reduces the number of independent variables in performance modeling to a single variable (age in this research) by enabling the development of models in each pavement family. Separate models are also developed for areas with expansive and non-expansive subgrade soil. A total of eleven models are developed for the areas non-expansive subgrade soil area and nine models for the areas with expansive subgrade soil. Deterministic models that are developed are applicable to cities with available historical data on PCI or IRI. The developed probabilistic models are applicable to cities with a current pavement condition data, but no less than the last two consecutive years.
Author: Kaan Özbay
Publisher:
ISBN:
Category : Pavements
Languages : en
Pages : 152
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Book Description
The significant contribution of the research presented in this report lies in the fact that it utilizes the most comprehensive database of pavement conditions that is readily available and promises to provide the sought data in future years. The first part of this report reviews the existing literature covering related topics including pavement roughness, the LLTP background, artificial neural networks, regression analysis and the existing pavement deterioration models. The second part discusses the work done in data analysis and data manipulation in addition to the development of the training of the neural network model. The third part deals with various aspects of the model development using neural networks and regression analysis. The next part concludes the research with summarizing the results of model development. The models developed in this research are then compared to some existing models by applying the models to similar data sets and performing statistical analysis of the results.
Author: Ryan M. Laub
Publisher:
ISBN:
Category :
Languages : en
Pages : 362
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Book Description
Author: Shiraz D. Tayabji
Publisher: ASTM International
ISBN: 0803128584
Category : Materials
Languages : en
Pages : 534
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Book Description
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
Author: A. Scarpas
Publisher: Springer Science & Business Media
ISBN: 9400745664
Category : Technology & Engineering
Languages : en
Pages : 1340
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Book Description
In the recent past, new materials, laboratory and in-situ testing methods and construction techniques have been introduced. In addition, modern computational techniques such as the finite element method enable the utilization of sophisticated constitutive models for realistic model-based predictions of the response of pavements. The 7th RILEM International Conference on Cracking of Pavements provided an international forum for the exchange of ideas, information and knowledge amongst experts involved in computational analysis, material production, experimental characterization, design and construction of pavements. All submitted contributions were subjected to an exhaustive refereed peer review procedure by the Scientific Committee, the Editors and a large group of international experts in the topic. On the basis of their recommendations, 129 contributions which best suited the goals and the objectives of the Conference were chosen for presentation and inclusion in the Proceedings. The strong message that emanates from the accepted contributions is that, by accounting for the idiosyncrasies of the response of pavement engineering materials, modern sophisticated constitutive models in combination with new experimental material characterization and construction techniques provide a powerful arsenal for understanding and designing against the mechanisms and the processes causing cracking and pavement response deterioration. As such they enable the adoption of truly "mechanistic" design methodologies. The papers represent the following topics: Laboratory evaluation of asphalt concrete cracking potential; Pavement cracking detection; Field investigation of pavement cracking; Pavement cracking modeling response, crack analysis and damage prediction; Performance of concrete pavements and white toppings; Fatigue cracking and damage characterization of asphalt concrete; Evaluation of the effectiveness of asphalt concrete modification; Crack growth parameters and mechanisms; Evaluation, quantification and modeling of asphalt healing properties; Reinforcement and interlayer systems for crack mitigation; Thermal and low temperature cracking of pavements; and Cracking propensity of WMA and recycled asphalts.
Author: Dallas N. Little
Publisher: Springer
ISBN: 331958443X
Category : Technology & Engineering
Languages : en
Pages : 702
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Book Description
This textbook lays out the state of the art for modeling of asphalt concrete as the major structural component of flexible pavements. The text adopts a pedagogy in which a scientific approach, based on materials science and continuum mechanics, predicts the performance of any configuration of flexible roadways subjected to cyclic loadings. The authors incorporate state-of the-art computational mechanics to predict the evolution of material properties, stresses and strains, and roadway deterioration. Designed specifically for both students and practitioners, the book presents fundamentally complex concepts in a clear and concise way that aids the roadway design community to assimilate the tools for designing sustainable roadways using both traditional and innovative technologies.
Author: Chenglong Luo
Publisher:
ISBN:
Category : Pavements
Languages : en
Pages : 79
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Book Description
Pavement deterioration is one of the most important driver for prioritizing pavement management and preservation (PMP) projects. The primary goal of this thesis is to provide reasonable predictive functions from multiple linear regression (MLR) models and artificial neural networks (ANN) that can be adopted by Kentucky Transportation Cabinet (KYTC). Furthermore, we use analytic hierarchy process (AHP) to design a composite pavement distress index in order to help Kentucky Transportation Cabinet (KYTC) prioritizing PMP projects based on 11 different distress indices. Numerical results show that the MLR models provide relatively high R square values of approximately 0.8. Both MLR and ANN models have small average squared errors (ASE). Finally, for all nine distress indices studied in this thesis, MRL models are recommended to KYTC due to their simplicity, interpretability along with robust performance that is comparable to the ANN model. Finally, a priority rating method is developed using analytical hierarchy process and it integrates 11 pavement distress indices into one priority score. A case study shows that the propose AHP-based rating method overcomes the drawback of KYTC's current rating system for overemphasizing the international roughness index (IRI) among all distress indices.
