Browsing by Author "Matias de Oliveira, Jhenyffer Lorrany"

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    A Heterogeneous Markov Chain Model to Predict Pavement Deterioration and Optimize Repair Activities
    (2021-12) Matias de Oliveira, Jhenyffer Lorrany
    In an era where system needs exceed available funding across all infrastructure components, planners and decision makers need tools to make informed decisions about the value of assets, such as accurate models to predict pavement condition over time. This prediction is essential in pavement management systems (PMS) because it provides information that allows forecasting repair demands and optimizing life-cycle costs. Markov Chains have been proposed in the past as a tool for forecasting pavement performance and deterioration. A weakness of the traditional Markov Chain is that the conventional transition matrix has limited ability to account for site-specific variability. To address this problem, this dissertation proposes a combination of ordinal logistic regression and Markov Chains. The logistic regression models were found to bring two major improvements to the Markov model. First, the enhanced Markov transition probability matrix allows for site specific predictions because the models use specific characteristics of each pavement section. Second, the enhanced matrix offers additional benefits by allowing the comparison of several factors and the analysis of how each of them influences the pavement performance and deterioration, as well as providing an understanding of the interaction between these several external factors, such as district location, repair history, functional class, base thickness, speed limit and pavement thickness. Numerical examples are provided to demonstrate how the Markov Transition Matrix can be used to model future pavement deterioration. The final Markov probability matrix was also used to determine an optimal sequence of pavement repair activities.
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    Investigation of Cracking Resistance of Asphalt Mixtures and Binders
    (Minnesota Department of Transportation, 2019-01) Marasteanu, Mihai; Turos, Mugurel; Ghosh, Debaroti; Matias de Oliveira, Jhenyffer Lorrany; Yan, Tianhao
    In this study, the viability of using three test methods for asphalt mixtures and one test method for asphalt binders are investigated. These test methods are: Bending Beam Rheometer (BBR) for creep and strength of asphalt mixtures; low temperature Semi Circular Bend (SCB) test for fracture energy of asphalt mixtures; Dynamic Modulus (E*) test of asphalt mixtures using the Indirect Tensile Test (IDT) configuration; and BBR strength test of asphalt binders. The materials used in the experimental work were used in MnROAD cells constructed in the summer of 2016 as part of the MnROAD Cracking Group (CG) experiment, a 3-year pooled-fund project. The results show that the testing methods investigated provide repeatable results that follow trends similar to the one observed using traditional methods. The results also show that the properties are highly temperature dependent and the ranking observed at one temperature can change at a different temperature. In addition, it is observed that materials with similar rheological properties, such as complex modulus absolute value |E*|, creep stiffness S, and m-value, do not necessarily have the same fracture resistance. These results confirm one more time the need for a fracture/strength test for correctly evaluating cracking resistance of asphalt materials.