An official website of the United States government
This paper introduces the multihazard optimization-based probabilistic scenario (multihazard OPS) method to create an ensemble of multihazard scenarios that can be used for efficient evaluation of spatially distributed infrastructure. Each multihazard scenario is a map depicting a possible realization of the co-occurring multiple hazard effects associated with a single earthquake, including ground motion intensity contours, liquefaction potential contours, and locations of surface fault rupture. Together, when the small set of multihazard scenarios are combined with their computed weights, they represent the probabilistic hazard in a way that captures spatial correlation, includes multiple hazards, and is computationally efficient. In demonstrating the method for Los Angeles, California, we find a set of 350 multihazard scenarios matches the regional hazard and damage with errors small enough for most practical purposes. Further reduction is possible depending on the desired tradeoff between acceptable errors and computational efficiency. A sensitivity analysis suggests it is important to consider each hazard type in determining the multihazard scenarios, although the outcome is not sensitive to the precision of the weights.
more »
« less
Selection of multihazard-based damage scenarios for the Los Angeles water supply network
Earthquake damage scenarios are required to support design and analysis of spatially distributed infrastructure systems. In this paper we develop a computationally efficient set of damage scenarios for the Los Angeles water transmission system that considers ground motion and liquefaction. Each damage scenario describes one possible realization of damage to the pipe network and includes the corresponding multihazard scenario and an associated adjusted annual occurrence probability. Each damage scenario, which specifies the damage state of each pipe in the network, is defined to be physically realistic and consistent with the associated multihazard scenario. Together, when probabilistically combined, the set of damage scenarios with their occurrence probabilities matches the probabilistic hazard and component damage distributions. The scenarios are selected to be small in number so that subsequent analysis is efficient. We combine ideas from recently developed methods to generate sets of multihazard scenarios and damage scenarios for analysis of spatially distributed infrastructure systems. The method applied in this paper involves simulating multihazard, and a number of respective damage scenarios, and using an optimization to select a subset of damage scenarios and assign adjusted occurrence probabilities.
more »
« less
- Award ID(s):
- 1735407
- PAR ID:
- 10338504
- Date Published:
- Journal Name:
- 2021 ASCE Lifelines Conference
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
More Like this
-
-
This paper develops a probabilistic earthquake risk assessment for the electric power transmis- sion system in the City of Los Angeles. Via a dc load flow analysis of a suite of damage scenarios that reflect the seismic risk in Los Angeles, we develop a probabilistic representation for load shed during the restoration process. This suite of damage scenarios and their associated annual probabilities of occurrence are developed from 351 risk-adjusted earthquake scenarios using ground motion that collectively represent the seismic risk in Los Angeles at the census tract level. For each of these 351 earthquake scenarios, 12 damage scenarios are developed that form a probabilistic representation of the consequences of the earthquake scenario on the components of the transmission system. This analysis reveals that substation damage is the key driver of load shed. Damage to generators has a substantial but still secondary impact, and damage to transmission lines has significantly less impact. We identify the census tracts that are substantially more vulnerable to power transmission outages during the restoration process. Further, we explore the impact of forecasted increases in penetration of residential storage paired with rooftop solar. The deployment of storage paired with rooftop solar is represented at the census tract level and is assumed to be able to generate and store power for residential demand during the restoration process. The deployment of storage paired with rooftop solar reduces the load shed during the restoration process, but the distribution of this benefit is correlated with household income and whether the dwelling is owned or rented.more » « less
-
The objective of this paper is to model and characterize the percolation dynamics in road networks during a major fluvial flooding event. First, a road system is modelled as planar graph, then, using the level of co-location interdependency with flood control infrastructure as a proxy to the flood vulnerability of the road networks, it estimated the extent of disruptions each neighborhood road network experienced during a flooding event. Second, percolation mechanism in the road network during the flood is captured by assigning different removal probabilities to nodes in road network according to a Bayesian rule. Finally, temporal changes in road network robustness were obtained for random and weighted-adjusted node-removal scenarios. The proposed method was applied to road flooding in a super neighborhood in Houston during hurricane Harvey. The result shows that, network percolation due to fluvial flooding, which is modelled with the proposed Bayes rule based node-removal scheme, causes the decrease in the road network connectivity at varying rate.more » « less
-
Critical infrastructure is the backbone of modern societies. To meet increasing demand under resource-constrained and multihazard conditions, policy-makers are tapping into infrastructure resiliency: its capacity to withstand and recover from disruptions. Thus, resiliency-aware uncertainty quantification is key to identify tipping points, yet it remains computationally inaccessible. This paper maps resiliency measures to well understood time-dependent reliability computations, porting insights and methods from reliability theory to the service of critical infrastructure resiliency and upkeep efforts. For large-scale applications, we use particle integration methods (PIMs)—a family of sequential Monte Carlo methods with wide-ranging applications—and propose their optimal tuning in terms of their variance and number of limit-state function evaluations. We obtain consistent and unbiased probability estimates in applications to dynamical systems, network reliability, and resilience analysis, demonstrating PIMs as practical yet under-appreciated tools. For example, we obtain probability estimates of order 10−14 in networks with over 10,000 random variables.more » « less
-
This paper is the second of a set presented within the session: Findings from the CFS10 MultiHazard Test Program. The emphasis within this article is to highlight correlations between physical damage to nonstructural components and systems with measured response during a suite of 18 earthquake tests and two subsequent fire tests. This damage was documented within a 10story cold-formed steel-framed building test specimen outfitted with various nonstructural components, including suspended ceilings, architectural finishes, a resilient stair system, windows and doors, pressurized fire sprinkler and gas piping systems, and roof-mounted mechanical equipment. The test building and multi-hazard protocol are described in the session companion paper. This paper provides test observations correlated with measured engineering demand parameters such as floor acceleration, building inter-story drift or peak local temperature responses and offers related literature emerging from the project. Damage data and functionality checks will support development of fragility functions for these nonstructural systems for use in recoverybased frameworks.more » « less
- Free Publicly Accessible Full Text
-
Accepted Manuscript
- Conference Paper:
- The DOI is not currently available.
