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Scholarly Works (6 results)

  • Thesis
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UC Davis Electronic Theses and Dissertations (2024)

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.

    Cover page: Calibration of Mechanistic-Empirical (ME) Design Methods and Development of Statistical Performance Models for Optimized Life-Cycle Asset Management of Jointed Concrete Pavements in California
    • Article
    Research Reports (2022)
    This report summarizes the work conducted to develop the jointed plain concrete pavement (JPCP) tables of the new Caltrans HighwayDesign Manual (HDM) Rigid Pavement Design Catalog. The tables consider the different pavement structures that are expected toperform properly on the Caltrans road network. The tables were developed using Pavement ME (version 2.5.5) with the nationallycalibrated transverse cracking model. Pavement ME inputs were determined by considering the state’s climate, traffic, materials, andconstruction practices. A design life of 40 years, 10% target transverse cracking, and 95% design reliability were chosen for developmentof the tables. Transverse joint faulting and the International Roughness Index (IRI) were also determined for the sections in the JPCPtables using Pavement ME (version 2.5.5) nationally calibrated models and compared to Caltrans faulting and IRI limits of 0.15 in. and170 in./mi., respectively. The tables will be included in the printed version of the new HDM Rigid Pavement Design Catalog.
      Cover page: Development of Caltrans Jointed Plain Concrete Pavement Design Catalog Tables Using Pavement ME
      • Article
      Research Reports (2021)
      The Mechanistic-Empirical Pavement Design Guide (MEPDG) is a comprehensive tool developed in 2002 by the American Association of State Highway and Transportation Officials (AASHTO) to analyze and design both flexible and rigid pavements. The models in the MEPDG are implemented in software called Pavement ME, a program calibrated using Long-Term Pavement Performance (LTPP) sections from throughout the United States, including some from California. The MEPDG recommends that nationally calibrated models be validated using local data, and if necessary, recalibrated, which makes sense when considering the climate and materials differences between California and the rest of the nation. The first step in recalibrating Pavement ME is to perform a sensitivity analysis to identify which variables are most important and to look for results that do not match expected performance. The factorial for the sensitivity analysis was designed to identify sensitivity and is not the factorial to be used for the development of design tools. This report presents the results of a sensitivity analysis showing the effects of design input variables controlled by the designer, and those not known to the designer. The sensitivity analysis shows that the overall jointed plain concrete pavements (JPCP) performance prediction by Pavement ME is reasonable. The distresses predicted by Pavement ME did not show any unexpected trends for any of the variables considered in this sensitivity analysis. Over the course of this study, no major issues were identified in running Pavement ME. The next steps are to complete the calibration using California pavement management system data and then to develop the design tool with the calibrated Pavement ME coefficients.
        Cover page: Pavement ME Sensitivity Analysis (Version 2.5.3)
        • Article
        Policy Briefs (2020)
        Medium- and heavy-duty trucks on California’s roads are shifting from conventional gasoline and diesel propulsion systems to alternative fuel (natural gas, electric, and fuel cell) propulsion technologies, spurred by the state’s greenhouse gas (GHG) reduction goals. While these alternative fuel trucks produce fewer emissions, they are also currently heavier than their conventional counterparts. Heavier loads can cause more damage to pavements and bridges, triggering concerns that clean truck technologies could actually increase GHG emissions by necessitating either construction of stronger pavements or more maintenance to keep pavements functional. California Assembly Bill 2061 (2018) allows a 2,000-pound gross vehicle weight limit increase for near-zero-emission vehicles and zero-emission vehicles to enable these trucks to carry the same loads as their conventional counterparts. The law also asked the UC Institute of Transportation Studies to evaluate the new law’s implications for GHG emissions and transportation infrastructure damage. To conduct this analysis, researchers at UC Davis considered three adoption scenarios of alternative fuel trucks in two timeframes, 2030 and 2050 (Figure 1). Based on these scenarios, the researchers used life cycle assessment and life cycle cost analysis to evaluate how heavier trucks might affect pavement and bridge deterioration, GHG emissions, and state and local government pavement costs. The study did not evaluate the safety implications of increasing allowable gross vehicle weights.
          Cover page: Heavier Alternative Fuel Trucks Are Not Expected to Cause Significant Additional Pavement Damage
          • Article
          Research Reports (2021)
          The Mechanistic-Empirical Pavement Design Guide (MEPDG) is a comprehensive method, including models and guidance, developed in 2002 by the American Association of State Highway and Transportation Officials (AASHTO) to analyze and design both flexible and rigid pavements. The MEPDG is implemented in a software called Pavement ME. The MEPDG models were calibrated using data from the Long-Term Pavement Performance (LTPP) sections from throughout the United States, including some from California. The MEPDG recommends that nationally calibrated models be validated using local data and, if necessary, recalibrated. This recommendation is particularly applicable to the Caltrans road network, considering the climate and materials differences between California and the rest of the nation. The first step in recalibrating Pavement ME is to perform a sensitivity analysis to identify which variables are most important and to look for results that do not match expected performance. This was the subject of a previous report titled Pavement ME Sensitivity Analysis. Based on the sensitivity analysis, the decision was made to perform a new calibration of the MEPDG models as implemented in Pavement ME software. A new approach was developed for the calibration. This new approach uses network-level performance data from the pavement management system (PMS) with orders of magnitude more observations and length of pavement than are used in the traditional approach and in the national calibration of the MEPDG models. The framework does not require sampling of materials from specific sections in the network. Rather, it uses the statewide median values from mechanistic testing from a representative sample of materials across the network. Variability of performance and reliability of design (probability that the design will meet or exceed the design life) is accounted for through separate consideration of within-project and between-project variability. The calibration reduced significant bias in the application of the nationally calibrated models to California. This report presents the results of the application of the new procedure to calibrate the Pavement ME transverse cracking model for jointed plain concrete pavements (JPCP). The California pavement management system (PaveM) database—with about 4600 lane-miles of JPCP built on 446 lane replacement projects completed between 1947 and 2017—was used to calibrate the transverse cracking model in Pavement ME. The nationally calibrated Pavement ME transverse cracking model prediction on the PaveM performance database has bias and standard error of 13.3% and 23.03%, respectively. After calibration, the bias and standard error of the locally calibrated model decreased to 0.039% and 5.69%, respectively.
            Cover page: Pavement ME JPCP Transverse Cracking Model Calibration and Design Catalog Framework (Version 2.5.5)
            • Article
            ITS reports (2020)
            California’s truck fleet composition is shifting to include more natural gas vehicles (NGVs), electric vehicles (EVs), and fuel cell vehicles (FCVs), and it will shift more quickly to meet state greenhouse gas (GHG) emission goals. These alternative fuel trucks (AFTs) may introduce heavier axle loads, which may increase pavement damage and GHG emissions from work to maintain pavements. This project aimed to provide conceptual-level estimates of the effects of vehicle fleet changes on road and bridge infrastructure. Three AFT implementation scenarios were analyzed using typical Calif. state and local pavement structures, and a federal study’s results were used to assess the effects on bridges. This study found that more NGV, EV, and FC trucks are expected among short-haul and medium-duty vehicles than among long-haul vehicles, for which range issues arise with EVs and FCs. But the estimates predicted that by 2050, alternative fuels would power 25–70% of long-haul and 40–95% of short-haul and medium-duty trucks. AFT implementation is expected to be focused in the 11 counties with the greatest freight traffic—primarily urban counties along major freight corridors. Results from the implementation scenarios suggest that introducing heavier AFTs will only result in minimal additional pavement damage, with its extent dependent on the pavement structure and AFT implementation scenario. Although allowing weight increases of up to 2,000 lbs. is unlikely to cause major issues on more modern bridges, the effects of truck concentrations at those new limits on inadequate bridges needs more careful evaluation. The study’s most aggressive market penetration scenario yielded an approximate net reduction in annual well-to-wheel truck propulsion emissions of 1,200–2,700 kT per year of CO2 -e by 2030, and 6,300–34,000 kT by 2050 versus current truck technologies. Negligible effects on GHG emissions from pavement maintenance and rehabilitation resulted from AFT implementation.
              Cover page: Effects of Increased Weights of Alternative Fuel Trucks on Pavement and Bridges
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