Multiagent Simulation for Complex Adaptive Modeling of Road Infrastructure Resilience to Sea‐Level Rise

Abstract

Infrastructure systems in coastal areas are exposed to episodic flooding exacerbated by sea-level rise stressors. To enable assessing the long-term resilience of infrastructure to such chronic impacts of sea-level rise, the present study created a novel complex system modeling framework that integrates: (i) stochastic simulation of sea-level rise stressors, based on the data obtained from downscaled climate studies pertaining to future projections of sea level and precipitation; (ii) dynamic modeling of infrastructure conditions by considering regular decay of infrastructure, as well as structural damages caused by flooding; and (iii) a decision-theoretic modeling of infrastructure management and adaptation processes based on bounded rationality and regret theories. Using the proposed framework and data collected from a road network in Miami, a multiagent computational simulation model was created to assess the long-term cost and performance of the road network under various sealevel rise scenarios, adaptation approaches, and network degradation effects. The results showed the capabilities of the proposed computational model for robust planning and scenario analysis to enhance the resilience of infrastructure systems to sea-level rise impacts.

Resilience as an emergent property of human-infrastructure dynamics: A multi-agent simulation model for characterizing regime shifts and tipping point behaviors in infrastructure systems

“…Instead a new equilibrium state is attained, as seen in other fields such as ecology and economics which inspired developments in the engineering resilience field [ 18 ]. In the proposed study, grounded theories, measures, and methods related to resilience in complex systems [ 10 , 13 , 18 – 22 ] were utilized to build a long-term resilience framework ( Fig 1 ) for civil infrastructure systems under external stressors. The resilience of civil infrastructure system is contingent upon its transformation and adaptation to evolving conditions in the social and environmental sphere [ 21 ].…”

“…Based on the existing evidence related to resilience in complex systems [ 10 , 13 , 18 – 22 ] this study, as shown in Fig 1 , identified three important characteristics related to long-term resilience of civil infrastructure systems: (i) external stressors, (ii) internal dynamics, and (ii) performance regime shifts. The following sub-sections explain the three mechanisms which characterize the resilience of complex infrastructure systems.…”

“…On the human actor side, two distinct decision-making processes of institutional actors (i.e., infrastructure agencies) can affect the long-term transformation of physical infrastructure. First, actor’s decisions on maintenance, rehabilitation, or reconstruction of assets (referred to as preservation decisions) [ 22 ] influence transformation of physical infrastructure by affecting the degradation rates and renewal of assets. Second, the adaptation decisions of actors affect the vulnerability of assets to external stressors.…”

“…In MAS, an agent has several essential characteristics: active–initiating actions, reactive–responding to external stimulus, and autonomy [ 33 ]. MAS has been shown as an effective simulation approach for analyzing complex processes and interactions in civil infrastructure systems [ 22 , 34 – 36 ]. Many entities within an infrastructure system (e.g., users, human-decision makers, and physical infrastructure) can be viewed and modeled as an agent.…”

Framework for city‐scale building seismic resilience simulation and repair scheduling with labor constraints driven by time–history analysis

“…However, during the 2011 Christchurch earthquake in New Zealand, although the number of collapsed buildings in the central business district of this city was limited, the functionalities of the area were severely disrupted because the buildings sustained irreparable damage (Kam, Pampanin, & Elwood, 2011;Parker & Steenkamp, 2012;Wikipedia, 2012). For this reason, the con-© 2019 Computer-Aided Civil and Infrastructure Engineering cept of urban building seismic resilience has emerged as one of the most notable topics in order to cope with the aforementioned type of problem (Burton, Deierlein, Lallemant, & Lin, 2015;Franchin & Cavalieri, 2015;Kang, 2018;Mahmoud & Chulahwat, 2018;Wang et al, 2017;Xu, Ouyang, Mao, & Xu, 2019), and simulation methods can be useful tools when dealing with community resilience (Batouli & Mostafavi, 2018;Mostafavi & Ganapati, 2019).…”