Arc-flash analysis of utility power systems

The electric utility business is an inherently dangerous area to work in with employees exposed to many potential hazards daily. One such hazard is an arc flash. An arc flash is a rapid release of energy, referred to as incident energy, caused by an electric arc. Due to the random nature and occurrence of an arc flash, one can only prepare and minimize the extent of harm to themself, other employees and damage to equipment due to such a violent event. Effective January 1, 2009 the National Electric Safety Code (NESC) requires that an arc-flash assessment be performed by companies whose employees work on or near energized equipment to determine the potential exposure to an electric arc. To comply with the NESC requirement, Minnesota Power’s (MP’s) current short circuit and relay coordination software package, ASPEN OneLinerTM and one of the first software packages to implement an arc-flash module, is used to conduct an arc-flash hazard analysis. At the same time, the package is benchmarked against equations provided in the IEEE Std. 1584-2002 and ultimately used to determine the incident energy levels on the MP transmission system. This report goes into the depth of the history of arc-flash hazards, analysis methods, both software and empirical derived equations, issues of concern with calculation methods and the work conducted at MP. This work also produced two offline software products to conduct and verify an offline arc-flash hazard analysis.

Evaluation of factors affecting speed perception in a driving simulator

The present study was conducted to determine the effects of different variables on the perception of vehicle speeds in a driving simulator. The motivations of the study include validation of the Michigan Technological University Human Factors and Systems Lab driving simulator, obtaining a better understanding of what influences speed perception in a virtual environment, and how to improve speed perception in future simulations involving driver performance measures. Using a fixed base driving simulator, two experiments were conducted, the first to evaluate the effects of subject gender, roadway orientation, field of view, barriers along the roadway, opposing traffic speed, and subject speed judgment strategies on speed estimation, and the second to evaluate all of these variables as well as feedback training through use of the speedometer during a practice run. A mixed procedure model (mixed model ANOVA) in SAS® 9.2 was used to determine the significance of these variables in relation to subject speed estimates, as there were both between and within subject variables analyzed. It was found that subject gender, roadway orientation, feedback training, and the type of judgment strategy all significantly affect speed perception. By using curved roadways, feedback training, and speed judgment strategies including road lines, speed limit experience, and feedback training, speed perception in a driving simulator was found to be significantly improved.