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Physics-informed machine learning for reliability and systems safety applications: State of the art and challenges
The computerized simulations of physical and socio-economic systems have proliferated in
the past decade, at the same time, the capability to develop high-fidelity system predictive …
the past decade, at the same time, the capability to develop high-fidelity system predictive …
Big data and its applications in smart real estate and the disaster management life cycle: A systematic analysis
Big data is the concept of enormous amounts of data being generated daily in different fields
due to the increased use of technology and internet sources. Despite the various …
due to the increased use of technology and internet sources. Despite the various …
Urban resilience assessment from the multidimensional perspective using dynamic Bayesian network: A Case Study of Fujian Province, China
Pursuing the high-quality urbanisation and improving urban system reliability are the current
goal of urban development. Urban resilience reflects the reliability of a city in co** with …
goal of urban development. Urban resilience reflects the reliability of a city in co** with …
Mathematical modeling of interdependent infrastructure: An object-oriented approach for generalized network-system analysis
Risk and resilience analysis research has favored simpler models such as topological
connectivity and maximum flow algorithm to model infrastructure performance. However …
connectivity and maximum flow algorithm to model infrastructure performance. However …
[HTML][HTML] Functional connectivity analysis for modeling flow in infrastructure
The performance loss of infrastructure caused by hazards can disrupt economic activities,
obstruct emergency responses, and be detrimental to society's well-being and recovery …
obstruct emergency responses, and be detrimental to society's well-being and recovery …
[HTML][HTML] Exploring innovative techniques for damage control during natural disasters
The study critically examines the principles, mechanisms, and effectiveness of different
damage control techniques in dealing with natural disasters, emphasizing their pivotal role …
damage control techniques in dealing with natural disasters, emphasizing their pivotal role …
Generating network representations of small‐scale infrastructure using generally available data
Risk analysis (including resilience analysis) of infrastructure requires models that describe
the connection of components and subsequent flow dynamics. However, the detailed …
the connection of components and subsequent flow dynamics. However, the detailed …
Which consequences matter in risk analysis and disaster assessment?
Extreme events (like earthquakes, hurricanes, wildfires) can create significant physical
damage to structures and infrastructure, downtime and business interruptions, economic …
damage to structures and infrastructure, downtime and business interruptions, economic …
Empirical predictive modeling approach to quantifying social vulnerability to natural hazards
Conventionally, natural hazard scholars quantify social vulnerability based on social
indicators to manifest the extent to which locational communities are susceptible to adverse …
indicators to manifest the extent to which locational communities are susceptible to adverse …
Review on modeling the societal impact of infrastructure disruptions due to disasters
Infrastructure systems play a critical role in providing essential products and services for the
functioning of modern society; however, they are vulnerable to disasters and their service …
functioning of modern society; however, they are vulnerable to disasters and their service …