TY - GEN
T1 - A cloud-based computational platform to manage risk and resilience of buildings and infrastructure systems
AU - Hackl, Jürgen
N1 - Publisher Copyright:
© ESREL 2021. Published by Research Publishing, Singapore.
PY - 2021
Y1 - 2021
N2 - The primary responsibility of asset managers is to ensure that their assets, such as buildings and infrastructure systems, provide adequate service needed. They have the continuous task of executing interventions to help prevent the loss of service and to restore service after it is lost, which can happen, for example, due to natural hazards such as floods, landslides, and earthquakes. In other words, they have the continuous task of making their assets resilient. To provide optimal mitigation measures, the risk and resilience of buildings and infrastructure systems have to be assessed. Therefore, different computational models from different disciplines have to be executed, and their results have to be brought together in order to make profound quantitative statements. Nonetheless, conducting such assessments can be a particularly challenging task due to numerous scenarios and chains of interrelated events that require considerations, the modelling of these events, the relationships among them, and the availability of support tools to run the models in an integrated way. Cloud-based simulations offer a solution to this problem, by providing almost unlimited storage and computational resources; furthermore, the cloud enables and facilitates collaborative approaches, and provide a Digital Twin of the assets for prediction and disaster management. This paper introduces a computational platform which enables cloud-based simulations to estimate risk and resilience of buildings and infrastructure systems. The setup of the computational platform follows the principles and ideas of systems engineering and allows to incorporate and link different events. The platform is centred on the integration of the spatial and temporal attributes of the events that need to be modelled to estimate the risk and resilience. Furthermore, the platform supports the inclusion of the uncertainty of these events and the propagation of these uncertainties throughout the risk and resilience modelling. Through the modular implementation of the simulation platform, the updating and swapping of computational models from different disciplines-according to the needs of engineers and decision-makers-is supported. The platform enables high-performance computing for simulation-based risk and resilience assessments, considering the occurrence of time-varying multi-hazard events affecting buildings and infrastructure systems. Beyond the modelling of complex scenarios, the proposed computational platform provide technologies and tools to help decision-makers in determining the best mitigation policies. This is reached by collaborative technologies like data sharing, real-time collaboration, a continual process of creating, editing, and commenting, as well as a cheap and easy way of creating visuals and reports.
AB - The primary responsibility of asset managers is to ensure that their assets, such as buildings and infrastructure systems, provide adequate service needed. They have the continuous task of executing interventions to help prevent the loss of service and to restore service after it is lost, which can happen, for example, due to natural hazards such as floods, landslides, and earthquakes. In other words, they have the continuous task of making their assets resilient. To provide optimal mitigation measures, the risk and resilience of buildings and infrastructure systems have to be assessed. Therefore, different computational models from different disciplines have to be executed, and their results have to be brought together in order to make profound quantitative statements. Nonetheless, conducting such assessments can be a particularly challenging task due to numerous scenarios and chains of interrelated events that require considerations, the modelling of these events, the relationships among them, and the availability of support tools to run the models in an integrated way. Cloud-based simulations offer a solution to this problem, by providing almost unlimited storage and computational resources; furthermore, the cloud enables and facilitates collaborative approaches, and provide a Digital Twin of the assets for prediction and disaster management. This paper introduces a computational platform which enables cloud-based simulations to estimate risk and resilience of buildings and infrastructure systems. The setup of the computational platform follows the principles and ideas of systems engineering and allows to incorporate and link different events. The platform is centred on the integration of the spatial and temporal attributes of the events that need to be modelled to estimate the risk and resilience. Furthermore, the platform supports the inclusion of the uncertainty of these events and the propagation of these uncertainties throughout the risk and resilience modelling. Through the modular implementation of the simulation platform, the updating and swapping of computational models from different disciplines-according to the needs of engineers and decision-makers-is supported. The platform enables high-performance computing for simulation-based risk and resilience assessments, considering the occurrence of time-varying multi-hazard events affecting buildings and infrastructure systems. Beyond the modelling of complex scenarios, the proposed computational platform provide technologies and tools to help decision-makers in determining the best mitigation policies. This is reached by collaborative technologies like data sharing, real-time collaboration, a continual process of creating, editing, and commenting, as well as a cheap and easy way of creating visuals and reports.
KW - HPC
KW - cloud computing
KW - computational modelling
KW - digital twin
KW - disaster response
KW - infrastructure management
KW - multi-hazards
KW - natural hazards
KW - resilience
KW - risk
KW - simulation
UR - http://www.scopus.com/inward/record.url?scp=85135436766&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85135436766&partnerID=8YFLogxK
U2 - 10.3850/978-981-18-2016-8_054-cd
DO - 10.3850/978-981-18-2016-8_054-cd
M3 - Conference contribution
AN - SCOPUS:85135436766
SN - 9789811820168
T3 - Proceedings of the 31st European Safety and Reliability Conference, ESREL 2021
SP - 369
BT - Proceedings of the 31st European Safety and Reliability Conference, ESREL 2021
A2 - Castanier, Bruno
A2 - Cepin, Marko
A2 - Bigaud, David
A2 - Berenguer, Christophe
PB - Research Publishing, Singapore
T2 - 31st European Safety and Reliability Conference, ESREL 2021
Y2 - 19 September 2021 through 23 September 2021
ER -