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Your search keyword '"Andrews, John"' showing total 75 results
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75 results on '"Andrews, John"'

5. Ranking the critical sections of railway networks

Author

Meesit, Ratthaphong and Andrews, John

Subjects
Railway network, Risk-based criticality, Vulnerability analysis, Simulation model, ComputerApplications_COMPUTERSINOTHERSYSTEMS
Abstract

Railway systems are now facing an increasing number of threats such as aging infrastructures and climate changes. The identification of critical network sections provides infrastructure managers with the ability to understand the impact of a disruption and creates a suitable preventive strategy to counter such threats. To this end, various vulnerability analysis methods have been proposed for railway networks. Two main types of methods, network topological analysis and network flow-based analysis, have been developed. Both approaches are constructed based on macroscopic models which take only some railway properties such as network structure, train and passenger flow into account. Thus, the results obtained are high level approximations. This study proposes a new analysis method which is developed based on the stochastic-microscopic railway network simulation model. The method can be applied to identify the critical sections of a railway network. The effect of impact levels and occurrence times of a disruption on the network section criticality are presented. An application of the proposed model is demonstrated using the Liverpool railway network in the UK.

Published
2021

10. Sensor selection for fault diagnostics using performance metric

Author

Reeves, Jack, Remenyte-Prescott, R, Andrews, John, Reeves, J, and Andrews, J

Subjects
Sensor selection, Fault diagnostics, Bayesian Belief Network
Abstract

As technology advances, modern systems are becoming increasingly complex, consisting of large numbers of components, and therefore large numbers of potential component failures. These component failures can result in reduced system performance, or even system failure. The system performance can be monitored using sensors, which can help to detect faults and diagnose failures present in the system. However, sensors increase the weight and cost of the system, and therefore, the number of sensors may be limited, and only the sensors that provide the most useful system information should be selected.In this paper, a novel sensor performance metric is introduced. This performance metric is used in a sensor selection process, where the sensors are chosen based on their ability to detect faults and diagnose failures of components, as well as the effect the component failures have on system performance. The proposed performance metric is a suitable solution for the selection of sensors for fault diagnostics. In order to model the outputs that would be measured by the sensors, a Bayesian Belief Network (BBN) is developed. Sensors are selected using the performance metric, and sensor readings can be introduced in the BBN. The results of the BBN can then be used to rank the component failures in order of likelihood of causing the sensor readings. To illustrate the proposed approach, a simple flow system is used in this paper.

Published
2018

32. West Nile Virus Infection in Free-Ranging Squirrels in Illinois

Author

Heinz-Taheny, Kathleen M., primary, Andrews, John J., additional, Kinsel, Michael J., additional, Pessier, Allan P., additional, Pinkerton, Marie E., additional, Lemberger, Karin Y., additional, Novak, Robert J., additional, Dizikes, George J., additional, Edwards, Eric, additional, and Komar, Nicholas, additional

Published
2004
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47. Preface

Author

Johnson, Barry L., primary, Xintaras, Charles, additional, and Andrews, John S., additional

Published
1997
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