Stormwater Infrastructure Resilience Assessment against Seismic Hazard Using Bayesian Belief Network

Seismic Assessment using a Bayesian Network

This paper presents a framework for seismic vulnerability assessment based on Bayesian Networks. This framework incorporates the HAZUS model, the demand model and the capacity model, which are used to calculate the probabilities of earthquake-induced bridge damage. The framework is here applied to ‘twin’ bridges that are correlated with the demand model and the capacity model. The paper investi...

assessment of the efficiency of s.p.g.c refineries using network dea

data envelopment analysis (dea) is a powerful tool for measuring relative efficiency of organizational units referred to as decision making units (dmus). in most cases dmus have network structures with internal linking activities. traditional dea models, however, consider dmus as black boxes with no regard to their linking activities and therefore do not provide decision makers with the reasons...

A Bayesian Network Methodology for Infrastructure Seismic Risk Assessment and Decision Support

Facilitating Probabilistic Seismic Hazard Analysis Using Bayesian Networks

In probabilistic seismic hazard analysis, one wants to calculate the probability of exceedance of a certain shaking level at a particular site. This requires a good understanding of the parameters that can influence seismic ground-motions. Bayesian networks are used to investigate the probabilistic dependencies between several parameters of the groundmotion domain. Problems specific to the doma...

A Framework for Probabilistic Multi-Hazard Assessment of Rain-Triggered Lahars Using Bayesian Belief Networks

Volcanic water-sediment flows, commonly known as lahars, can often pose a higher threat to population and infrastructure than primary volcanic hazardous processes such as tephra fallout and Pyroclastic Density Currents (PDCs). Lahars are volcaniclastic flows of water, volcanic debris and entrained sediments that can travel long distances from their source, causing severe damage by impact and bu...