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https://hdl.handle.net/2142/72201
Description
Title
Development of Pavement Prediction Models
Author(s)
Lee, Ying-Haur
Issue Date
1993
Doctoral Committee Chair(s)
Darter, Michael I.
Department of Study
Civil Engineering
Discipline
Civil Engineering
Degree Granting Institution
University of Illinois at Urbana-Champaign
Degree Name
Ph.D.
Degree Level
Dissertation
Keyword(s)
Engineering, Civil
Abstract
This study is an in-depth and comprehensive investigation of the development of pavement prediction models. It addresses a crucial need to develop improved prediction models for various pavement applications such as design, evaluation, rehabilitation, and network management systems.
Different modeling approaches previously used and problems encountered were first investigated. Unfortunately, the current state-of-the-art modeling process using traditional regression techniques alone is very inadequate. Furthermore, very few guidelines are currently available.
The tasks undertaken under this research study included: (1) providing practical guidelines and numerical illustrations in conducting traditional regression analyses; (2) introducing some modern regression techniques to achieve some special goals including "robust" outliers detections, optimal variable transformations, error variance stabilization, and inclusion of variable interactions; (3) developing a systematic modeling approach with detailed step-by-step guidelines; and (4) demonstrating the proposed modeling approach. The importance of incorporating subject-related engineering knowledge, proper functional forms, and some applicable engineering boundary conditions into the modeling process was emphasized as well. The use of graphical visualization and data smoothing techniques was also a very crucial component of the proposed modeling approach.
The proposed systematic modeling approach is generally applicable to various practical pavement prediction problems such as analyzing field-collected pavement performance data and theoretical pavement structural responses, which may or may not contain data contamination. For demonstration purposes, the following three case studies were conducted: (1) mechanistic design models of loading and curling in concrete pavements using dimensional analysis; (2) simplified pavement performance models for use in the Highway Performance Monitoring System (HPMS) analytical process; and (3) a study of the performance model of Illinois continuously reinforced concrete pavements.
It could also be used for trial implementation on the on-going Long-Term Pavement Performance (LTPP) studies under the Strategic Highway Research Program (SHRP) to develop improved pavement deterioration predictive models.
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