Advances in Materials and Pavement Performance Prediction contains the papers presented at the International Conference on Advances in Materials and Pavement Performance Prediction (AM3P, Doha, Qatar, 16- 18 April 2018).

There has been an increasing emphasis internationally in the design and construction of sustainable pavement systems. Advances in Materials and Pavement Prediction reflects this development highlighting various approaches to predict pavement performance. The contributions discuss links and interactions between material characterization methods, empirical predictions, mechanistic modeling, and statistically-sound calibration and validation methods. There is also emphasis on comparisons between modeling results and observed performance. The topics of the book include (but are not limited to):

• Experimental laboratory material characterization
• Field measurements and in situ material characterization
• Constitutive modeling and simulation
• Innovative pavement materials and interface systems
• Non-destructive measurement techniques
• Surface characterization, tire-surface interaction, pavement noise
• Pavement rehabilitation
• Case studies

Advances in Materials and Pavement Performance Prediction will be of interest to academics and engineers involved in pavement engineering.

part 1|27 pages

Modeling distress in flexible pavements

part 3|25 pages

Structural health assessment

part 4|26 pages

Measuring and modeling mixture performance – 1

part 6|25 pages

Computational modeling to understand mixture production and behavior

part 7|28 pages

Measuring and modeling performance of asphalt binders

part 8|27 pages

Binders and emulsions: workability, adhesion and rheology

part 10|28 pages

Modeling and measurement of noise and tire-pavement interaction

part 13|25 pages

Developments in structural design of pavements

part 15|26 pages

Mixes and binders with additives and industrial waste

part 22|24 pages

Innovations in pavement maintenance, analysis, and design

part 23|24 pages

New asphalt mix paradigms