Modeling Pavement Temperature for Use in Binder Oxidation Models and Pavement Performance Prediction

2011 ◽  
Vol 23 (4) ◽  
pp. 351-359 ◽  
Author(s):  
Rongbin Han ◽  
Xin Jin ◽  
Charles J. Glover
Keyword(s):  
Performance Prediction ◽  
Pavement Performance ◽  
Pavement Temperature ◽  
Binder Oxidation ◽  
Pavement Performance Prediction

Pavement Management Systems: Past, Present, and Future

2003 ◽  
Vol 1853 (1) ◽  
pp. 65-71 ◽  
Author(s):  
Ram B. Kulkarni ◽  
Richard W. Miller
Keyword(s):  
Performance Prediction ◽  
Prediction Models ◽  
Pavement Management ◽  
Pavement Performance ◽  
Management Systems ◽  
Seamless Integration ◽  
Positioning Systems ◽  
Pavement Management Systems ◽  
Transportation Organization ◽  
Pavement Performance Prediction

The progress made over the past three decades in the key elements of pavement management systems was evaluated, and the significant improvements expected over the next 10 years were projected. Eight specific elements of a pavement management system were addressed: functions, data collection and management, pavement performance prediction, economic analysis, priority evaluation, optimization, institutional issues, and information technology. Among the significant improvements expected in pavement management systems in the next decade are improved linkage among, and better access to, databases; systematic updating of pavement performance prediction models by using data from ongoing pavement condition surveys; seamless integration of the multiple management systems of interest to a transportation organization; greater use of geographic information and Global Positioning Systems; increasing use of imaging and scanning and automatic interpretation technologies; and extensive use of formal optimization methods to make the best use of limited resources.

scholarly journals A Hybrid Model for Prediction in Asphalt Pavement Performance Based on Support Vector Machine and Grey Relation Analysis

2020 ◽  
Vol 2020 ◽  
pp. 1-14
Author(s):  
Xuancang Wang ◽  
Jing Zhao ◽  
Qiqi Li ◽  
Naren Fang ◽  
Peicheng Wang ◽  
...  
Keyword(s):  
Support Vector Machine ◽  
Prediction Model ◽  
Performance Prediction ◽  
Asphalt Pavement ◽  
Pavement Performance ◽  
Support Vector ◽  
Grey Relation Analysis ◽  
Relation Analysis ◽  
Pavement Performance Prediction ◽  
Grey Relation

Pavement performance prediction is a crucial issue in big data maintenance. This paper develops a hybrid grey relation analysis (GRA) and support vector machine regression (SVR) technique to predict pavement performance. The prediction model can solve the shortcomings of the traditional model including a single consideration factor, a short prediction period, and easy overfitting. GAR is employed in selecting the main factors affecting the performance of asphalt pavement. The SVR is performed to predict the performance. Finally, the data collected from the weather station installed on Guangyun Expressway were adopted to verify the validity of the GRA-SVR model. Meanwhile, the contrast with the grey model (GM (1, 1)), genetic algorithm optimization BP[[parms resize(1),pos(50,50),size(200,200),bgcol(156)]]081%, −0.823%, 1.270%, and −4.569%, respectively. The study concluded that the nonlinear and multivariate prediction model established by GRA-SVR has higher precision and operability, which can be used in long-period pavement performance prediction.

Rational Selection of Factors of Safety in Reliability-Based Design of Flexible Pavements in Saudi Arabia

1996 ◽  
Vol 1540 (1) ◽  
pp. 39-47 ◽  
Author(s):  
A. Samy Noureldin ◽  
Essam Sharaf ◽  
Abdulrahim Arafah ◽  
Faisal Al-Sugair
Keyword(s):  
Saudi Arabia ◽  
Performance Prediction ◽  
Flexible Pavement ◽  
Pavement Design ◽  
Pavement Performance ◽  
Design Performance ◽  
Reliability Based Design ◽  
Pavement Engineering ◽  
Pavement Performance Prediction ◽  
Selection Of

Explicit applications of reliability in pavement engineering have been of interest to pavement engineers for the last 10 years. Variabilities in parameters affecting pavement design performance result in variability in pavement performance prediction and thus affect the reliability of how long the pavement will last. Rational quantification of those variabilities is essential for incorporating reliability and selecting the proper factors of safety in the pavement design performance process. The prevailing methodology in Saudi Arabia of quantifying the variability in pavement performance due to the variabilities of the parameters affecting that performance is demonstrated. Factors of safety for flexible pavement design at various reliability levels and based on those prevailing variabilities are presented. These factors of safety are recommended for flexible pavement design in Saudi Arabia.

Development of Performance-Related Specifications for Hot-Mix Asphalt Pavements Through WesTrack

1997 ◽  
Vol 1575 (1) ◽  
pp. 85-91 ◽  
Author(s):  
Stephen B. Seeds ◽  
Rudramunniyappa Basavaraju ◽  
Jon A. Epps ◽  
Richard M. Weed
Keyword(s):  
Performance Prediction ◽  
Prediction Models ◽  
Hot Mix Asphalt ◽  
Permanent Deformation ◽  
Fatigue Cracking ◽  
Primary Objective ◽  
Pavement Performance ◽  
Void Content ◽  
Target Values ◽  
Pavement Performance Prediction

The primary objective of the FHWA-sponsored WesTrack project is to further the development of performance-related specifications for hotmix asphalt construction. This objective is being achieved, in part, through the accelerated loading of a full-scale test track facility in northern Nevada. Twenty-six hot-mix asphalt test sections constructed to meet the criteria set forth in a statistically based experiment design are providing performance data that will be used to improve existing (or develop new) pavement performance prediction relationships that better account for the effects that “off-target” values of asphalt content, air-void content, and aggregate gradation have on such distress factors as fatigue cracking, permanent deformation, roughness, raveling, and tirepavement friction. The concept of the planned new performance-related specification and how it will incorporate the modified pavement performance prediction models are described. The current plan for assessing contractor pay adjustments (i.e., penalties and bonuses) based on data collected from the as-constructed pavement is also discussed.

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