Please use this identifier to cite or link to this item: https://bspace.buid.ac.ae1234/1474
Title: Forecasting Resilience Loss for Flexible Pavement under the Impact of Temperature due to Climate Change
Authors: ALARYANI, MOHAMMED MUFTAH
Keywords: resilience
flexible pavement
temperature
climate change
pavement management systems
Issue Date: Jun-2019
Publisher: The British University in Dubai (BUiD)
Abstract: Projects and programmes for maintenance and rehabilitation works are crucial for pavement assets in order to achieve the required levels of safety and operability. It is well documented in the literature that pavement network infrastructures age with time, are underfunded and, more importantly, are designed based on historical conditions. The HDM-4 model, which is extensively used in pavement management systems, does not utilise future climate predictions. Climate change is likely to threaten pavement infrastructures’ resilience through extreme weather events and chronically through gradual degradation. The objectives of the study were fivefold: firstly, to develop a modified HDM-4 model using pavement performance indicators (International Roughness Index and Pavement Condition Index) that assess the impacts of future climate change; secondly, to develop a Markov chain model for projection of pavement deterioration rate under different climate scenarios based on a modified HDM-4 model; thirdly, to establish the generic risk of pavement failure under the impact of climate change and quantify the risk interrelationships based on the received questionnaires using a deterministic risk analysis method; fourthly, to develop a system dynamics model for the projection of pavement deterioration rate for different risk scenarios; and, finally, to measure pavement resilience loss for the pavement network. The models were developed using data provided by the roads department in the Ministry of Public Works of the United Arab Emirates, Al Ain City Municipality, National Centre of Meteorology and Seismology, and questionnaires. A number of different methodologies were used such as linear and non-linear regression, simulation of system dynamics and probabilistic approach using a Markov chain. Both Markov chain and system dynamics models indicated that climate change impact can accelerate the rate of degradation for infrastructure assets. Moreover, the Markov chain model indicated resilience loss for the pavement network in the range of 27.86% to 32.4% for different climate change scenarios (2013, 2020, 2040 and 2060) over a period of 20 years’ prediction. In addition, for the ultimate worse scenario, the resilience loss score was 73.57%. This record showed a value close to the range of resilience loss generated from the system dynamics model (range between 75.67% and 81.0% resilience loss). This research provides an increased understanding of modelling and managing uncertainty in pavement deterioration with respect to climate change impacts. Developing different tools such as a pavement condition index model, modified HDM-4, and probabilistic and system dynamics model will help the road and highway agency in the UAE to efficiently monitor the road pavement assets and establish the necessary maintenance plan for future years, and captures a real system which assists the policy decision makers in their pavement intervention programme.
URI: https://bspace.buid.ac.ae1234/1474
Appears in Collections:Thesis for Project Management

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