Yazar "Citir, Nazik" seçeneğine göre listele

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    Development of Pavement Performance and Remaining Service Life Prediction Tools for Iowa Jointed Plain Concrete Pavement Systems
    (Asce-Amer Soc Civil Engineers, 2023) Kaya, Orhan; Citir, Nazik; Ceylan, Halil; Kim, Sunghwan; Waid, Danny R.
    Moving Ahead for Progress in the Twenty-First Century (MAP-21) requires US state highway agencies (SHA) to utilize performance-based approaches in their pavement management decision-making processes, and use of a remaining service life (RSL) model would be one of such performance-based approaches for facilitating the pavement management decision-making process for SHAs. In this study, statistical and artificial neural network (ANN)-based pavement performance and RSL models were developed for Iowa jointed plain concrete pavement systems (JPCP) using actual pavement structural, traffic, construction history, and pavement performance records obtained from the Iowa Department of Transportation pavement-management information system database. While both models were found to be potentially useful for project and network level performance and RSL predictions, statistical and ANN-based models were respectively found to be more suitable for project and network level analysis. Using these models, efficient Microsoft Excel-based automation tools were created to predict future performance of a JPCP section and estimate RSL values based on predicted future performance and threshold limits for the performance indicators. Consequence analysis was also conducted to investigate the impact of traffic and preservation treatment (diamond grinding) on the RSL of a JPCP. The tool, also capable of estimating realistic pavement pretreatment and posttreatment performance and RSL, could be successfully used as part of performance-based pavement management strategies and helping decision-makers make better-informed pavement management decisions to properly allocate agency resource expenditures. Moreover, this study provides a better understanding of RSL and the factors that influence both the project and network level RSL.
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    Estimating local pavement performance and remaining service interval using neural networks-based models and automation tool
    (Taylor & Francis Ltd, 2024) Citir, Nazik; Kaya, Orhan; Ceylan, Halil; Kim, Sunghwan; Waid, Danny
    This study introduces an integrated approach to enhance county pavement management, emphasising operational efficiency in determining the Remaining Service Interval (RSI) for rigid and flexible pavements. It establishes a robust methodology for systematically processing raw county road data through dynamic segmentation and summarisation to create a structured pavement database. It also incorporates innovative approaches and input configurations in employing Artificial Neural Networks (ANNs) to predict current and future county pavement performance indicators, including International Roughness Index (IRI), rutting, transverse, and longitudinal cracks, even with limited data. Evaluation of the ANN models on independent county road databases exhibited high prediction accuracies (0.86 < R-2 < 0.99), varying with specific performance indicators. The study results in an automation tool for expediting road performance estimation over multiple years. This tool seamlessly integrates the ANN models, empowering county engineers to make data-driven decisions and optimise resource allocation for effective pavement management, achieving significant cost savings.
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    Incorporating the effectiveness of preservation and rehabilitation techniques on flexible pavement service life predictions using machine learning approach
    (American Society of Civil Engineers (ASCE), 2021) Citir, Nazik; Ceylan, Halil; Kim, Sunghwan; Kaya, Orhan
    A flexible pavement network may be exposed to traffic changes over time because of detours that may cause unusually high traffic loading on some parts of the pavement sections. Such sections, therefore, need to be preserved earlier than their expected service life. This study focuses on incorporating the effectiveness of preservation and rehabilitation techniques, e.g., functional thin overlay and structural asphalt overlay on flexible pavement service life predictions using a machine learning approach. The developed models are capable of estimating the current and future international roughness index (IRI) and of detecting performance recovery after application of preservation treatment, thereby forecasting the remaining service life. The traffic, pavement structural, and performance data were obtained from the pavement management information system (PMIS) of the Iowa Department of Transportation (DOT). This study describes realistic what-if scenarios considering various treatment techniques to provide a better understanding of the effectiveness of treatments on extending flexible pavement service life. Such outcomes will help facilitate better pavement preservation management strategies. © ASCE.All right reserved.
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    Öğe
    Incorporating the Effectiveness of Preservation and Rehabilitation Techniques on Flexible Pavement Service Life Predictions Using Machine Learning Approach
    (Amer Soc Civil Engineers, 2021) Citir, Nazik; Ceylan, Halil; Kim, Sunghwan; Kaya, Orhan
    A flexible pavement network may be exposed to traffic changes over time because of detours that may cause unusually high traffic loading on some parts of the pavement sections. Such sections, therefore, need to be preserved earlier than their expected service life. This study focuses on incorporating the effectiveness of preservation and rehabilitation techniques, e.g., functional thin overlay and structural asphalt overlay on flexible pavement service life predictions using a machine learning approach. The developed models are capable of estimating the current and future international roughness index (IRI) and of detecting performance recovery after application of preservation treatment, thereby forecasting the remaining service life. The traffic, pavement structural, and performance data were obtained from the pavement management information system (PMIS) of the Iowa Department of Transportation (DOT). This study describes realistic what-if scenarios considering various treatment techniques to provide a better understanding of the effectiveness of treatments on extending flexible pavement service life. Such outcomes will help facilitate better pavement preservation management strategies.