Modeling Pavement Performance Based on LTPP Database for Flexible Pavements

Year 2020, Volume: 31 Issue: 4, 10127 - 10146, 01.07.2020

Mostafa Radwan , Mostafa Abo-hashema Moatafa Hashem Hamdy Faheem

https://doi.org/10.18400/tekderg.476606

Cited By: 13

Abstract

In many countries, incredible investments have been made in constructing
roads that require conducting periodic evaluation and timely maintenance and rehabilitation
(M&R) plan to keep the network operating under acceptable level of service.
The timely M&R plan necessitates accurately predicting pavement
performance, which is an essential element of road infrastructure asset
management systems or Pavement Management Systems (PMS). Consequently, there is
always a need to develop and to update performance prediction models embedded
in PMS applications. This study focuses in developing distress prediction
models for flexible pavements located in non-freeze climatic zone, which
represent most of developing countries such as Egypt, using data extracted from
the Long-Term Pavement Performance (LTPP) program. Ten distress performance prediction
models were developed in this study for both wet- and dry-non freeze climatic
zones, which are alligator (Fatigue) cracking, longitudinal cracking,
transverse cracking, ravelling, bleeding, and rut depth models. These models
can play an important role assisting decision makers in predicting pavement
performance, identifying M&R needs, rational budget planning and resource
allocation.

Keywords

Prediction models, distress models, ltpp, statistical modeling, flexible pavement, non-freeze climatic zone

Modeling Pavement Performance Based on LTPP Database for Flexible Pavements

Abstract

In many countries, incredible investments have been made in constructing roads that require conducting periodic evaluation and timely maintenance and rehabilitation (M&R) plan to keep the network operating under acceptable level of service. The timely M&R plan necessitates accurately predicting pavement performance, which is an essential element of road infrastructure asset management systems or Pavement Management Systems (PMS). Consequently, there is always a need to develop and to update performance prediction models embedded in PMS applications. This study focuses in developing distress prediction models for flexible pavements located in non-freeze climatic zone, which represent most of developing countries such as Egypt, using data extracted from the Long-Term Pavement Performance (LTPP) program. Ten distress performance prediction models were developed in this study for both wet- and dry-non freeze climatic zones, which are alligator (Fatigue) cracking, longitudinal cracking, transverse cracking, ravelling, bleeding, and rut depth models. These models can play an important role assisting decision makers in predicting pavement performance, identifying M&R needs, rational budget planning and resource allocation.

Keywords

Prediction models, distress models, ltpp, statistical modeling, flexible pavement, non-freeze climatic zone

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