A Quantitative Framework for Assessing Vulnerability and Redundancy of Freight Transportation Networks

Freight transportation networks are an important component of everyday life in modern society. Disruption to these networks can make peoples’ daily lives extremely difficult as well as seriously cripple economic productivity. This dissertation develops a quantitative framework for assessing vulnerability and redundancy of freight transportation networks. The framework consists of three major contributions: (1) a two- stage approach for estimating a statewide truck origin-destination (O-D) trip table, (2) a decision support tool for assessing vulnerability of freight transportation networks, and (3) a quantitative approach for measuring redundancy of freight transportation networks.The dissertation first proposes a two-stage approach to estimate a statewide truck O-D trip table. The proposed approach is supported by two sequential stages: the first stage estimates a commodity-based truck O-D trip table using the commodity flows derived from the Freight Analysis Framework (FAF) database, and the second stage uses the path flow estimator (PFE) concept to refine the truck trip table obtained from the first stage using the truck counts from the statewide truck count program. The model allows great flexibility of incorporating data at different spatial levels for estimating the truck O- D trip table. The results from the second stage provide us a better understanding of truck flows on the statewide truck routes and corridors, and allow us to better manage the anticipated impacts caused by network disruptions.A decision support tool is developed to facilitate the decision making system through the application of its database management capabilities, graphical user interface, GIS-based visualization, and transportation network vulnerability analysis. The vulnerability assessment focuses on evaluating the statewide truck-freight bottlenecks/chokepoints. This dissertation proposes two quantitative measures: O-D connectivity (or detour route) in terms of distance and freight flow pattern change in terms of vehicle miles traveled (VMT). The case study adopts a “what-if” analysis approach by generating the disruption scenarios of the structurally deficient bridges in Utah due to earthquakes. In addition, the potential impacts of disruptions to multiple bridges in both rural and urban areas are evaluated and compared to the single bridge failure scenarios.This dissertation also proposes an approach to measure the redundancy of freight transportation networks based on two main dimensions: route diversity and network spare capacity. The route diversity dimension is used to evaluate the existence of multiple efficient routes available for users or the degree of connections between a specific O-D pair. The network spare capacity dimension is used to quantify the network- wide spare capacity with an explicit consideration of congestion effect. These two dimensions can complement each other by providing a two-dimensional characterization of freight transportation network redundancy. Case studies of the Utah statewide transportation network and coal multimodal network are conducted to demonstrate the features of the vulnerability and redundancy measures and the applicability of the quantitative assessment methodology

How safe are central counterparties in credit default swap markets?

We propose a general framework for estimating the vulnerability to default by a central counterparty (CCP) in the credit default swaps market. Unlike conventional stress testing approaches, which estimate the ability of a CCP to withstand nonpayment by its two largest counterparties, we study the direct and indirect effects of nonpayment by members and/or their clients through the full network of exposures. We illustrate the approach for the U.S. credit default swaps market under shocks that are similar in magnitude to the Federal Reserve’s stress tests. The analysis indicates that conventional stress testing approaches may underestimate the potential vulnerability of the main CCP for this market

Complex system representation for vulnerability analysis

Many socio-technical systems are endowed of dynamism, self-organization, emergency etc. These attributes make them as complex systems. Because of this complexity, the representation is a crucial step for vulnerability analysis. The objective of this paper is to provide a generic framework of complex systems representation for vulnerability analysis. We used infrastructure network such as power grid, gas and telecommunication system to illustrate our proposal. It is separated in five layers: Spatial framework, Stake, Flow, Environment, and Network structure. The static view consists of a network structure (Nodes and edges). The dynamic view is related to the flow circulation, components’ states variations, and interdependences among them. Characteristics of these factors are described. The environment refers to outside perturbations that could happen. With our proposal it is possible to model many classes of complex system as the basis of vulnerability analysis. For this purpose, some modelling rules are proposed. The result allows performing simulations. Results of the simulation can be used for instance to find out vulnerability model into complex systems, or to validate existing models

Preliminary investigation of multi-hazard resilience analysis for urban transportation networks and data availability for hazard models and vulnerability of physical objects

HUB-Istanbul work package (WP) 2.6 aims to develop tools to analyse the multi-hazard resilience of urban transportation network in complex and evolving metropolitan environment, and propose a demonstrative application to a case study area: Fikirtepe in Istanbul, Turkey. Research outcomes will be conveyed by five deliverables. This document is the first deliverable, summarising the overall framework of analysis and required data for assessing physical vulnerability. Based on the framework, the second deliverable will deal specifically with another type of data required to evaluate traffic functionality of roadways and network performance. Based on the framework and datasets identified in the first two deliverables, the third deliverable will develop a probabilistic model to incorporate multi-layered analysis and data, which will be demonstrated by pilot examples. The fourth deliverable will present a thorough analysis of real-world transportation networks in the case study area, including mapping, network analysis and network performance evaluation. The evaluation results should be used to support decisions through mathematically formulated decision tasks, which will be illustrated in the fifth deliverable. This first deliverable summarises and proposes the research objectives, the framework of multi-hazard disaster resilience analysis of urban transportation networks and data requirement for assessing physical vulnerability, which are accompanied with thorough literature review. Based on the development, major hazard threats and distributions of bridges are identified for the case study area, Fikirtepe in Istanbul, Turkey