UC Davis

The primary goal of this dissertation is to develop frameworks, quantitative models, and databases to support data-driven, informed, and integrated decision-making for managing the vast transportation infrastructure in California. This research focuses on optimizing maintenance and rehabilitation (M&R) strategies for jointed plain concrete pavements (JPCP) to ensure cost-effectiveness and minimal disruption to traffic flow. The study aims to address the need for improved performance models for slab and lane replacement procedures, considering the unique environmental and traffic conditions in California.

The dissertation comprises several key components:

• Development of Performance Models: This research develops empirical-mechanistic models to predict the performance of slab and lane replacement treatments on JPCP. These models are intended to enhance the decision-making framework within Caltrans' pavement management system (PMS), optimizing M&R strategies based on life-cycle costs and environmental impacts. The performance models utilize extensive pavement condition data collected through Caltrans' automated pavement condition survey (APCS), which includes high-definition images and laser measurements of performance indices such as surface roughness, transverse and longitudinal cracking, corner cracking, and faulting.• Calibration of ME Design Models: The study involves the calibration of the mechanistic- empirical pavement design guide (MEPDG) models to California's specific conditions. Previous attempts at local calibration by other state highway agencies have been limited in scope and data availability. This research leverages a much larger dataset from Caltrans' PMS database, covering diverse climate regions and pavement conditions across the state. The calibration process aims to improve the accuracy of performance prediction for transverse cracking model. • Incorporating Longitudinal Cracking in Design: Longitudinal cracking, a prevalent issue in California's dry climate, has not traditionally been considered in pavement design models developed for more humid climates. This study identifies the underlying causes of longitudinal cracking, including differential shrinkage, slab geometry, and traffic loading, and proposes design recommendations to mitigate this distress. Through finite element simulations and analysis of PMS data, the study develops a comprehensive understanding of the factors contributing to longitudinal cracking. • Framework for Optimized Pavement Management: The dissertation proposes a robust framework for managing the state's highway network, ensuring cost-effective and durable pavement designs that accommodate California's unique environmental and traffic conditions. By developing performance models for slab and lane replacement, the research enhances the ability to predict pavement performance and optimize maintenance and rehabilitation strategies. The findings provide practical solutions for extending the service life of rigid pavements and minimizing disruptions to traffic flow. • Statewide Data Collection and Analysis: The study collects statewide median values for JPCP design variables from historical test data of JPCP projects across California. This data serves as a benchmark for assessing pavement performance and is crucial for calibrating the MEPDG models using an extensive dataset from the Caltrans PMS database. The calibration approach developed in this study considers within-project, between-project, and between-contractor variability, thereby improving the reliability of performance predictions.

The research addresses critical gaps in the knowledge and practice of pavement engineering, particularly in the context of California's diverse climate regions. By providing a comprehensive analysis of the factors influencing slab and lane replacement performance, developing accurate performance prediction models, and proposing new design guidelines for longitudinal cracking, this dissertation contributes significantly to the field of pavement management. The outcomes of this research offer a robust framework for efficient asset management, ensuring that maintenance and rehabilitation activities are performed in a timely, cost-effective manner, thereby extending the service life of California's highway network and reducing traffic disruptions.