LIST OF EQUATIONS
2. Chapter 2 Impact of Climate Change on Pavement Resilience Resilience
2.6. Resilience Review
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used to obtain the readings of stress/strain parameters of pavement structures including subgrades.
The strength data obtained from the Falling Weight Deflectometer (FWD) measure the surface deflection. The modified structural number (SNC) has been used to highlight the total strength of both the pavement and the subgrade. Such a combination can easily predict the performance of asphalt pavement structures at a network level (Watanatada et al., 1987). The variable of the SNC is the essential element in the equation of structural component of roughness based on default HDM-4 model. More details are presented in Chapter 6 sections 6.2.1 and 6.3.1.
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Resilience is not a new topic. In 1973, Holling first introduced the resilience concept. During his research, he defined resilience in ecological systems as a “measure of [the] perseverance of systems and their capability to absorb changes and disturbances, and still sustain the same relationships between populations or state variables” (Holling 1973). Resilience can be considered as 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 2003a). The concept of resilience consists of various disciplines which shape the definition of resilient approaches. Levina and Tirpak (2006) introduced two main elements in resilience definitions. First, elements could undergo a disruptive action without change to the original state of the system. Second, features are the system’s ability to recover from the potential impact. Maguire and Cartwright (2008) categorised resilience into three terminologies: stability, recovery and transformation. Hosseini, Barker and Ramirez-Marquez (2016) developed some resilience definitions that present different disciplines from a collection of previous studies. For example, Allenby and Fink (2005) introduced system resilience as the system having the ability to protect itself regarding functionality in case of both internal and external change.
Moreover, system resilience should be graceful enough to adopt such a change when degradation occurs. Pregenzer (2011) defined resilience as the “measure of a system’s ability to absorb continuous and unpredictable change and still maintain its vital functions”. Haimes (2009) explained resilience as a system which has both the ability and capacity to endure significant disruptive events causing accepted degradation parameters and to return to its original state within appropriate risks, time and costs.
Hollnagel and Woods (2006) have also questioned resilience concerning time recovery. They believe that the system should be measured against a timescale for recovery to define how effectively and quickly it can return to its original state after the occurrence of disruption.
Regarding transport networks, the DfT (2014) defined resilience as “the ability of the transport network to withstand the impacts of extreme weather, to operate in the face of such weather and to recover promptly from its effects”. Murray-Tuite (2006)
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presented some essential elements in terms of the efficiency of the road transport network. Those elements depend on certain factors such as speed of recovery (time) and the magnitude of external support. These factors help the system to achieve refunctioning of its original performance.
2.6.2. Resilience Dimensions
Hosseini, Barker and Ramirez-Marquez (2016) summarised the approach suggested by Bruneau et al. (2003) for resilience classification. They proposed four resilience domains, namely social, engineering, economic and organisational. Such designations may differ based on the author's perspective. For example, Kahan, Allen and George (2009) divided resilience dimensions, which focus on organisations and infrastructure, into two fields: ‘hard’ and ‘soft’ resilience. Soft resilience focuses on human requirements, behaviours, relationships, psychology and endeavours. It is related to family, community and society. On the other hand, hard systems cover the area affecting the structural, mechanical and technical infrastructure.
Hughes and Healy (2014) concluded that the four domains (or dimensions) introduced by Bruneau et al. (2003) could not be assessed or evaluated as one component in terms of system performance. It is suggested that an individual study should be applied for each system. There is another classification, made by the US National Infrastructure Advisory Council (NIAC 2010), which establishes the categories of resilience system domains (or dimensions) into fields: practice and process. Practice focuses on people whereas process focuses on the structure of the infrastructure and asset. In their study, Hughes and Healy (2014) mentioned how important the four domains (organisational, engineering, economic and social) of system resilience are. Nevertheless, they concluded that focusing on the area of engineering and organisational system resilience is sufficient in terms of the transport system. The reason behind this approach where both social and economic domains are considered is implicit in the system (engineering and organisational). In this study, resilience is viewed in terms of the engineering dimension only. More details are provided in section 2.6.3.
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2.6.3. Resilience in the Transport Context
The transportation system is an essential sector of any community. However, risks and uncertainty relating to all types of disruptions can affect transportation systems. For example, both natural disasters and human-made hazards can be the root cause for such disturbances. Natural disasters consist of earthquakes, hurricanes, floods, tsunamis, heavy snow, etc., whilst human-made hazards include terrorist attacks, group events, strikes and system breakdown. All these disturbances may lead to immense economic losses to society (Cao 2015). In terms of the transportation system, it has become increasingly important to integrate sustainability with resilience in management and development of local transport infrastructure (Bouch et al. 2012). To establish the long-term optimisation of engineered structures and efficient management systems, both managerial aspects and physical aspects should be equally taken into account. They are critical elements for a resilient transport infrastructure under different phenomena (Bouch et al. 2012). The more efficient organisational management there is, the more rapid the recovery in the transport system (DfT 2014). Cao (2015) concluded that the interpretation of the specific characteristics of resilience should allow transportation managers to draw the hazard line efficiently. Table 2-8 elaborates on the definition of resilience in terms of the transportation system developed by Cao (2015), who carried out research where he classified such interpretation based on the transportation area.
While a variety of definitions of the term transportation resilience have been suggested, this study will use the definition of Mansouri, Nilchiani and Mostashari (2010). The focus will be on the concept of the function of a system.
Table 2-8: Definition of resilience for different transport contexts, developed by Cao (2015)
Definition of Resilience Source Research
Object The ability of the system to absorb shock as well as
to recover from a disruption so that it can return to its original service delivery level or close to it.
Mayada et al. (2012) Maritime transportation system A function of a system’s vulnerability against
potential disruption, and its adaptive capacity in recovering to an acceptable level of service within a reasonable time frame after being affected by disruption.
Mansouri, Nilchiani and Mostashari
(2010)
Maritime infrastructure and transportation
systems
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Capability of a system to provide and maintain an acceptable level of service in the face of major changes or disruptions to the environment
Mansouri, Nilchiani and Mostashari
(2010)
Port infrastructure systems
“The ability for the system to maintain its demonstrated level of service or to restore itself to that level of service in specified time frame.”
Nayel et al. (2011) Transportation network
“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..
Freckleton et al.
(2012)
Transportation networks
“Both the network’s inherent ability to cope with disruption via its topological and operational attributes and potential actions that can be taken in the immediate aftermath of a disruption or disaster event.”
Miller-Hooks, Zhang and Faturechi (2012)
Freight transportation networks
2.6.4. The Relationship between the Climate Change Risk and Resilience
ISO (2018) defines risk as the: “effect of uncertainty on objectives”. In terms of risk analysis, Khan and Haddara (2003) provide another definition: “Risk analysis is a technique for identifying, characterising, quantifying, and evaluating the loss from an event”. The primary objective of risk analysis concerns the efforts to answer the question of what makes system failure occur. Burnett (2013) highlighted the importance of identifying the critical assets. He also added that this approach will provide support in prioritising and planning a maintenance and rehabilitation plan. Risk consideration should be taken into account in all activities and procedures; thus, the risk can be well controlled. He also stated that there are various methods to measure risk. According to Park et al. (2013), risk analysis, under emergent disruptive events, should be studied with the conjunction of resilience analysis to achieve accepted protection of critical infrastructure systems like a transport network. Rashidy (2014) added that, in terms of resilience, identifying risk and consequences of such risk is a very challenging step in the risk analysis process. She also classified risk into two categories. One is risk in the context of climate change phenomena ( natural impact) and consequent impacts, the other is human-made risk events (for example, terrorist attacks). For this research, the subject of human-made risk is excluded as the study is mainly focusing on the impact of climate change in terms of pavement infrastructure.
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