Extreme natural events (e.g. earthquakes, floods, fire) are the major sources of threat to society and infrastructure. Communities that are able to absorb the impacts, recover quickly after disasters, and adapt to adverse events are fairly resilient communities. Economic and public health consequences from natural disasters have increased over time and motivated discussion of a new resilience management worldwide. The key parameter to estimate the resilience of buildings and infrastructures is the downtime (DT). Several strategies have been investigated to reduce disaster risk and evaluate the recovery time of buildings and infrastructures following dangerous events. However, the estimation of the DT is still challenging due to the uncertainty and vagueness of the data available. This paper introduces a method to predict the DT of buildings and infrastructures following earthquakes through a Fuzzy Logic hierarchical scheme. The use of expert-based systems can be helpful to deal with uncertainties, randomness, and limited data availability in the context of risk analysis and management. Fuzzy theory describes the behavior of a complex system through linguistic variables and it is based on deterministic functions. Two different DT models are introduced in this work for residential buildings and infrastructures, since different are the input parameters involved in the estimation process. In the first model, the DT can be divided into three main components: downtime due to the actual damage (DT1); downtime caused by irrational delays (DT2); and downtime due to utilities disruption (DT3). DT1 is evaluated by relating the building damageability to given repair times of the building’s components. A rapid visual screening survey is filled out by an expert to acquire information about the analyzed building. Then, fuzzy logic is implemented to determine the building vulnerability, which is combined with a given earthquake intensity to obtain the building damageability. DT2 and DT3 are estimated using the REDITM Guidelines. DT2 considers irrational components through a specific sequence, which defines the order of components repair, while DT3 depends on the site seismic hazard and on the infrastructure vulnerability. The downtime of the building is finally estimated by combining the three components above, identifying three recovery states: re-occupancy, functional recovery, and full recovery. For estimating the recovery time of buried infrastructures, 31 indicators have been selected from previous publications and studies referring to programs and policies intending to reduce risk and increase recovery. The DT model is designed by aggregating four downtime indices: exposed infrastructure, earthquake intensity, human resources, and infrastructure type. The collected information on the potentially damaged lifelines are aggregated into a fuzzy hierarchical scheme and combined to obtain the DT. The methodology can be used to effectively support decision-makers in managing and minimizing the impacts of earthquakes and to recover damaged infrastructure promptly.

Downtime Estimation of Buildings and Infrastructures Using Fuzzy Logic / De Iuliis, Melissa; Cimellaro, Gian Paolo; Domaneschi, Marco; Tesfamariam, Solomon. - ELETTRONICO. - (2021), pp. 1-12. ((Intervento presentato al convegno The 17th World Conference on Earthquake Engineering tenutosi a Sendai, Japan nel September 27 to October 2, 2021.

Downtime Estimation of Buildings and Infrastructures Using Fuzzy Logic

De Iuliis, Melissa;Cimellaro, Gian Paolo;Domaneschi, Marco;
2021

Abstract

Extreme natural events (e.g. earthquakes, floods, fire) are the major sources of threat to society and infrastructure. Communities that are able to absorb the impacts, recover quickly after disasters, and adapt to adverse events are fairly resilient communities. Economic and public health consequences from natural disasters have increased over time and motivated discussion of a new resilience management worldwide. The key parameter to estimate the resilience of buildings and infrastructures is the downtime (DT). Several strategies have been investigated to reduce disaster risk and evaluate the recovery time of buildings and infrastructures following dangerous events. However, the estimation of the DT is still challenging due to the uncertainty and vagueness of the data available. This paper introduces a method to predict the DT of buildings and infrastructures following earthquakes through a Fuzzy Logic hierarchical scheme. The use of expert-based systems can be helpful to deal with uncertainties, randomness, and limited data availability in the context of risk analysis and management. Fuzzy theory describes the behavior of a complex system through linguistic variables and it is based on deterministic functions. Two different DT models are introduced in this work for residential buildings and infrastructures, since different are the input parameters involved in the estimation process. In the first model, the DT can be divided into three main components: downtime due to the actual damage (DT1); downtime caused by irrational delays (DT2); and downtime due to utilities disruption (DT3). DT1 is evaluated by relating the building damageability to given repair times of the building’s components. A rapid visual screening survey is filled out by an expert to acquire information about the analyzed building. Then, fuzzy logic is implemented to determine the building vulnerability, which is combined with a given earthquake intensity to obtain the building damageability. DT2 and DT3 are estimated using the REDITM Guidelines. DT2 considers irrational components through a specific sequence, which defines the order of components repair, while DT3 depends on the site seismic hazard and on the infrastructure vulnerability. The downtime of the building is finally estimated by combining the three components above, identifying three recovery states: re-occupancy, functional recovery, and full recovery. For estimating the recovery time of buried infrastructures, 31 indicators have been selected from previous publications and studies referring to programs and policies intending to reduce risk and increase recovery. The DT model is designed by aggregating four downtime indices: exposed infrastructure, earthquake intensity, human resources, and infrastructure type. The collected information on the potentially damaged lifelines are aggregated into a fuzzy hierarchical scheme and combined to obtain the DT. The methodology can be used to effectively support decision-makers in managing and minimizing the impacts of earthquakes and to recover damaged infrastructure promptly.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11583/2940896