LIST OF EQUATIONS
1. Chapter 1 Introduction
1.2. Research Context and Background Information
Infrastructure is a crucial component for sustainable societies and healthy economies at the worldwide level. The Economic and Social Affairs Department at the United Nations (2014) has projected a world population of 9.7 billion by the middle of the 21st century. It is also expected that 66% of the world's inhabitants will be living in urban areas. Such increases in both urbanisation and population growth draw a completely new set of expectations for infrastructure worldwide (PWC 2014).
Infrastructure is categorised into two areas. Economic infrastructure comprises utilities, energy, transport and telecommunication services. Social infrastructure consists of hospitals, schools and prisons (Panayiotou 2017).
Societies have a growing dependence on transportation infrastructure for their everyday activities, and the capability and ability of the transport system to continuously function to the levels of acceptable service is essential to people’s wellbeing. As individuals, companies, economies and societies evolve, reliable and resilient infrastructures are needed. For example, the national economy depends on transportation networks to support goods and mobility for people. The transportation infrastructure could be roads, bridges or airports. In the United States itself, such infrastructures represent more than 19,000 airports, 600,000 bridges and 4 million miles of roads (USDOT 2016). However, transportation infrastructures are not immune from deterioration.
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Transportation infrastructure is expected to face a series of challenges over the coming decades. Markolf et al. (2019) mentioned that current transportation infrastructure receives insufficient and unstable funding, and is not well designed to cope with changes in external conditions or different utilisation. For instance, among transportation networks in the US, it is estimated that 65% of major roads are evaluated as being below good condition (The White House 2014). Climate change, also known as phenomena that cause destabilising changes in Earth systems, can exacerbate the challenges in current transport infrastructure. Climate change is not a short-term effect; it is a long-term phenomenon with a lot of uncertainty (Bhamidipati 2015), and little research has been conducted on how vulnerable transport infrastructure will be to climate change (Jaroszweski 2010).
Road pavement assets deteriorate over time. Such deterioration is a result of many factors such as asset ageing, traffic loading, environmental effects, construction deficiency and design inadequacy. Roads are usually constructed to have a design life of 20 to 40 years. Pavement scientists and practitioners have focused a great deal of attention on the use of a prediction deterioration model that can be applied to forecast how the future pavement is going to deteriorate. Kobayashi, Do and Han (2010) stated that keeping critical assets functional from an engineering perspective is very challenging. The deterioration rate is considered to be low at the beginning but with time this rate increases, dramatically increasing maintenance costs. Such deterioration occurs due to many factors such as asset ageing, traffic loading, environmental effects, construction deficiency, design inadequacy, etc. Pavement condition surveys of distress are periodically conducted to quantify pavement surface condition at a specific time. Highway agencies need to establish an efficient tool that correctly monitors the pavement performance (Thom 2014). However, funding limitations trigger the need to seek more cost-effective methods of pavement maintenance optimisation (Lamptey, Labi and Sinha 2004). If road assets managers and engineers had prior knowledge of the likely consequences of future climate change, this could help to ensure that maintenance strategies and activities are conducted at the right time with the right cost. Such an approach could lead to robust roads and highways. Anyala (2011) stated that achieving proper maintenance strategies tools that take into consideration key factors such as climate and traffic is possible and such tools will help in understanding the performance of our roads.
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The impacts of climate change shorten such design lives. Mallick et al. (2014) stated that limited research has been conducted in the past to study the impact of climate change on pavement performance. Cechet (2005) stated that, the more knowledge road planners, designers and asset managers have of the expected impacts of future climate change, the better they can plan for such impacts, thus reducing future costs. Climate change impacts contribute to the degradation of infrastructure assets (Meyera and Weigel 2011). Climate change – both extreme and chronically gradual changes in weather events – is likely to threaten transportation infrastructures.
Extreme weather events would cause substantial physical damage to the transportation infrastructure, which can lead to significant economic losses. For example, in New York City itself, $7.5 billion of damage to the transportation system occurred as a result of Hurricane Sandy, according to the United States Department of Commerce (USDOC 2013).
Climate change impacts are unavoidable events and there is a need for resilient transport networks that are able to withstand, mitigate and recover from the consequence of such adverse events. Such events have adversely affected the efficiency of transport systems over recent years (Rashidy 2014). Such catastrophic events trigger the need to enhance the performance of the transportation infrastructure.
For example, some efforts to support the resilience of transportation systems to face the impact of climate change and other threats have started by incorporating robustness factors in such systems (Markolf et al. 2019). A focus on performance analyses with regard to resilience is also essential.
Resilience is not a new topic. In 1973, the first introduction of the resilience concept was made by Holling (1973), who defined resilience in ecological systems as a “measure of perseverance of systems and their capability to absorb changes and disturbances, and still sustain the same relationships between populations or state variables”. It has also been widely used in multiple engineering fields (Bruneau et al.
2003; Cimellaro, Reinhorn and Bruneau 2009). Generally, resilience is the maximum degree of threat mitigation to respond to, minimise or remove long-term impacts to property and humans from hazards and the consequences of such risks (Godschalk 2003). Levina and Tirpak (2006) introduced two main elements of resilience. The first element is to observe a disruptive action without change to the original state of the system. The second element is the system recovering from the potential impact.
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Maguire and Cartwright (2008) categorised resilience into three terminologies:
stability, recovery and transformation. Godschalk (2003) emphasised the importance of measuring resilience to test the ability of the critical infrastructure to withstand and accommodate any change without catastrophic failure.
Freckleton et al. (2012) defined resilience in transportation systems as “The ability for a transportation network to absorb disruptive events gracefully and return itself to a level of service equal to or greater than the pre-disruption level of service within a reasonable time frame”. Resilience analyses can lead to many benefits for the transportation infrastructure, for instance, improving safety relating to mobility and physical operability (Sun, Bocchini and Davison 2018). Moreover, interpretation of the exact characteristics of resilience allows transportation infrastructure managers to effectively draw the hazard line and quantitatively assess potential impacts of investment and policies (Cao 2015).
Disruptions to transportation infrastructures (or networks) trigger the vulnerability of the system, leading to delaying or stopping the movement of people and goods (Bagloee et al. 2017). The consequence of such disruption has become an area of rising concern to governmental institutions, and has led to the need to study the methods that achieve better understanding of these disruptions in order to make the systems more robust, and enable them to recover from disturbance events.
In terms of a safety system, resilience is a crucial indicator which can picture system-resilience measurements and define the roadmap for improving the system at the emergency level, planning level and response level (Zhao, Liu and Zhuo 2017).
Rochas, Kuznecova and Romagnoli (2014) highlighted the main challenges in developing comprehensive resilience measurements, which have different natural inputs and outputs. Such problems include lack of information regarding historical events, different dynamics disruption scenarios, time-varying, interdependent system performance indicators and unknown system consequences.
Although many academics and researchers have conducted many kinds of studies on measuring resilience, a quantitative resilience metric with system performance scenarios still remains unsolved (Zhao, Liu and Zhuo 2017).
Additionally, the current practice for measuring resilience quantitatively or qualitatively exhibits little standardisation and provides unclear guidance to asset
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managers (Francis and Bekera 2014). Bagloee et al. (2017) also added that, in the past, simple heuristic procedures were used to measure resilience for the entire road network. In order to make the measure of the resilience system more transparent and quantifiable, a comprehensive study should be conducted to allow application across a variety of scales (Hughes and Healy 2014).
Thus, the primary challenge is to measure the resilience of pavement infrastructure quantitatively through the concept of pavement performance with consideration of all the risk factors concerning climate change impacts and the consequences of such risk.