A decision support system to improve service quality in multimodal rapid rail systems: A bayesian perspective

Copyright @ 2011 International Conference on Computers and Industrial EngineeringIn this study, the accessibility of the rail transit stations in a multimodal network formed by a trunk line and its feeder lines are defined. Connectivity between lines and the accessibility of the nodes identify the overall spatial structure of the network. The factors influencing the access choices of rail transit stations and satisfaction of transit travelers in rapid rail transit systems are investigated in order to gain insights into the factors and their interrelationships. The quantitative indications of the relationships are produced and the complexity of evaluating the performance of transit services is exhibited. As the interrelationships are mainly stochastic, the problem on hand is treated as a Bayesian Belief Network (BBN). A BBN approach that presents a learning mechanism is employed and is used as an alternative decision making tool to analyze the rapid rail transit services and identify policies to improve the traveler’s level of service

Impact of New Madrid Seismic Zone Earthquakes on the Central USA, Vol. 1 and 2

The information presented in this report has been developed to support the Catastrophic Earthquake Planning Scenario workshops held by the Federal Emergency Management Agency. Four FEMA Regions (Regions IV, V, VI and VII) were involved in the New Madrid Seismic Zone (NMSZ) scenario workshops. The four FEMA Regions include eight states, namely Illinois, Indiana, Kentucky, Tennessee, Alabama, Mississippi, Arkansas and Missouri. The earthquake impact assessment presented hereafter employs an analysis methodology comprising three major components: hazard, inventory and fragility (or vulnerability). The hazard characterizes not only the shaking of the ground but also the consequential transient and permanent deformation of the ground due to strong ground shaking as well as fire and flooding. The inventory comprises all assets in a specific region, including the built environment and population data. Fragility or vulnerability functions relate the severity of shaking to the likelihood of reaching or exceeding damage states (light, moderate, extensive and near-collapse, for example). Social impact models are also included and employ physical infrastructure damage results to estimate the effects on exposed communities. Whereas the modeling software packages used (HAZUS MR3; FEMA, 2008; and MAEviz, Mid-America Earthquake Center, 2008) provide default values for all of the above, most of these default values were replaced by components of traceable provenance and higher reliability than the default data, as described below. The hazard employed in this investigation includes ground shaking for a single scenario event representing the rupture of all three New Madrid fault segments. The NMSZ consists of three fault segments: the northeast segment, the reelfoot thrust or central segment, and the southwest segment. Each segment is assumed to generate a deterministic magnitude 7.7 (Mw7.7) earthquake caused by a rupture over the entire length of the segment. US Geological Survey (USGS) approved the employed magnitude and hazard approach. The combined rupture of all three segments simultaneously is designed to approximate the sequential rupture of all three segments over time. The magnitude of Mw7.7 is retained for the combined rupture. Full liquefaction susceptibility maps for the entire region have been developed and are used in this study. Inventory is enhanced through the use of the Homeland Security Infrastructure Program (HSIP) 2007 and 2008 Gold Datasets (NGA Office of America, 2007). These datasets contain various types of critical infrastructure that are key inventory components for earthquake impact assessment. Transportation and utility facility inventories are improved while regional natural gas and oil pipelines are added to the inventory, alongside high potential loss facility inventories. The National Bridge Inventory (NBI, 2008) and other state and independent data sources are utilized to improve the inventory. New fragility functions derived by the MAE Center are employed in this study for both buildings and bridges providing more regionally-applicable estimations of damage for these infrastructure components. Default fragility values are used to determine damage likelihoods for all other infrastructure components. The study reports new analysis using MAE Center-developed transportation network flow models that estimate changes in traffic flow and travel time due to earthquake damage. Utility network modeling was also undertaken to provide damage estimates for facilities and pipelines. An approximate flood risk model was assembled to identify areas that are likely to be flooded as a result of dam or levee failure. Social vulnerability identifies portions of the eight-state study region that are especially vulnerable due to various factors such as age, income, disability, and language proficiency. Social impact models include estimates of displaced and shelter-seeking populations as well as commodities and medical requirements. Lastly, search and rescue requirements quantify the number of teams and personnel required to clear debris and search for trapped victims. The results indicate that Tennessee, Arkansas, and Missouri are most severely impacted. Illinois and Kentucky are also impacted, though not as severely as the previous three states. Nearly 715,000 buildings are damaged in the eight-state study region. About 42,000 search and rescue personnel working in 1,500 teams are required to respond to the earthquakes. Damage to critical infrastructure (essential facilities, transportation and utility lifelines) is substantial in the 140 impacted counties near the rupture zone, including 3,500 damaged bridges and nearly 425,000 breaks and leaks to both local and interstate pipelines. Approximately 2.6 million households are without power after the earthquake. Nearly 86,000 injuries and fatalities result from damage to infrastructure. Nearly 130 hospitals are damaged and most are located in the impacted counties near the rupture zone. There is extensive damage and substantial travel delays in both Memphis, Tennessee, and St. Louis, Missouri, thus hampering search and rescue as well as evacuation. Moreover roughly 15 major bridges are unusable. Three days after the earthquake, 7.2 million people are still displaced and 2 million people seek temporary shelter. Direct economic losses for the eight states total nearly $300 billion, while indirect losses may be at least twice this amount. The contents of this report provide the various assumptions used to arrive at the impact estimates, detailed background on the above quantitative consequences, and a breakdown of the figures per sector at the FEMA region and state levels. The information is presented in a manner suitable for personnel and agencies responsible for establishing response plans based on likely impacts of plausible earthquakes in the central USA.Armu W0132T-06-02unpublishednot peer reviewe

The safety case and the lessons learned for the reliability and maintainability case

This paper examine the safety case and the lessons learned for the reliability and maintainability case

Simulation modelling and strategic change : creating the sustainable enterprise

Peer reviewedPublisher PD

Probabilistic Reachability Analysis for Large Scale Stochastic Hybrid Systems

This paper studies probabilistic reachability analysis for large scale stochastic hybrid systems (SHS) as a problem of rare event estimation. In literature, advanced rare event estimation theory has recently been embedded within a stochastic analysis framework, and this has led to significant novel results in rare event estimation for a diffusion process using sequential MC simulation. This paper presents this rare event estimation theory directly in terms of probabilistic reachability analysis of an SHS, and develops novel theory which allows to extend the novel results for application to a large scale SHS where a very huge number of rare discrete modes may contribute significantly to the reach probability. Essentially, the approach taken is to introduce an aggregation of the discrete modes, and to develop importance sampling relative to the rare switching between the aggregation modes. The practical working of this approach is demonstrated for the safety verification of an advanced air traffic control example

Mathematical control of complex systems 2013

Mathematical control of complex systems have already become an ideal research area for control engineers, mathematicians, computer scientists, and biologists to understand, manage, analyze, and interpret functional information/dynamical behaviours from real-world complex dynamical systems, such as communication systems, process control, environmental systems, intelligent manufacturing systems, transportation systems, and structural systems. This special issue aims to bring together the latest/innovative knowledge and advances in mathematics for handling complex systems. Topics include, but are not limited to the following: control systems theory (behavioural systems, networked control systems, delay systems, distributed systems, infinite-dimensional systems, and positive systems); networked control (channel capacity constraints, control over communication networks, distributed filtering and control, information theory and control, and sensor networks); and stochastic systems (nonlinear filtering, nonparametric methods, particle filtering, partial identification, stochastic control, stochastic realization, system identification)