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SIMPLIFIED PAVEMENT PERFORMANCE MODELS

Ying-Haur Lee, Alaeddin Mohseni, M I Darter

Open publisher page 49 citations

Abstract

There is a great need for simplified pavement performance models that can be used for forecasting pavement condition on the basis of a minimal amount of available data. The development of predictive models is summarized for five conventional pavement types: asphalt concrete (flexible), composite, jointed plain concrete, jointed reinforced concrete, and continuously reinforced concrete. These models predict the present serviceability rating (PSR) using only knowledge of the pavement's age, cumulative equivalent single-axle loads, and a pavement structural parameter (structural number for flexible, overlay thickness for composite and slab thickness for concrete pavements). The models were developed from data from several reliable and readily available data bases in Illinois. A unique calibration technique was introduced and incorporated into the proposed models so that they can be used to predict the performance of existing and new pavements. The models were then extended through the development of adjustment factors to various functional groups and climatic zones using data from the actual multiyear nationwide Highway Performance Monitoring System (HPMS) data bases. The accuracy of PSR prediction was tested for several thousand HPMS sections throughout the United States using a user-friendly computer program (SIMPERF). The results appeared to be very reasonable in a large proportion of cases analyzed. However, the models are empirical and definitely not suitable for use in pavement design or for comparison of the performance of different pavement types.

About this research paper

What this paper is about

There is a great need for simplified pavement performance models that can be used for forecasting pavement condition on the basis of a minimal amount of available data. The development of predictive models is summarized for five conventional pavement types: asphalt concrete (flexible), composite, jointed plain concrete, jointed reinforced concrete, and continuously reinforced concrete. These models predict the present serviceability rating (PSR) using only knowledge of the pavement's age, cumulative equivalent single-axle loads, and a pavement structural parameter (structural number for flexible, overlay thickness for composite and slab thickness for concrete pavements). The models were developed from data from several reliable and readily available data bases in Illinois. A unique calibration technique was introduced and incorporated into the proposed models so that they can be used to predict the performance of existing and new pavements. The models were then extended through the development of adjustment factors to various functional groups and climatic zones using data from the actual multiyear nationwide Highway Performance Monitoring System (HPMS) data bases. The accuracy of PSR prediction was tested for several thousand HPMS sections throughout the United States using a user-friendly computer program (SIMPERF). The results appeared to be very reasonable in a large proportion of cases analyzed. However, the models are empirical and definitely not suitable for use in pavement design or for comparison of the performance of different pavement types.

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Available abstract

There is a great need for simplified pavement performance models that can be used for forecasting pavement condition on the basis of a minimal amount of available data. The development of predictive models is summarized for five conventional pavement types: asphalt concrete (flexible), composite, jointed plain concrete, jointed reinforced concrete, and continuously reinforced concrete. These models predict the present serviceability rating (PSR) using only knowledge of the pavement's age, cumulative equivalent single-axle loads, and a pavement structural parameter (structural number for flexible, overlay thickness for composite and slab thickness for concrete pavements). The models were developed from data from several reliable and readily available data bases in Illinois. A unique calibration technique was introduced and incorporated into the proposed models so that they can be used to predict the performance of existing and new pavements. The models were then extended through the development of adjustment factors to various functional groups and climatic zones using data from the actual multiyear nationwide Highway Performance Monitoring System (HPMS) data bases. The accuracy of PSR prediction was tested for several thousand HPMS sections throughout the United States using a user-friendly computer program (SIMPERF). The results appeared to be very reasonable in a large proportion of cases analyzed. However, the models are empirical and definitely not suitable for use in pavement design or for comparison of the performance of different pavement types.

Key concepts: Serviceability (structure), Overlay, Slab, Pavement engineering, Structural engineering, Asphalt pavement, Computer science, Predictive modelling

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