Date Approved

12-31-2004

Embargo Period

4-27-2016

Document Type

Thesis

Degree Name

M.S. in Engineering

Department

Electrical & Computer Engineering

College

Henry M. Rowan College of Engineering

First Advisor

Mandayam, Shreekanth

Subject(s)

Computer algorithms; Data structures (Computer science); Virtual reality

Disciplines

Electrical and Computer Engineering

Abstract

Virtual reality (VR) has emerged as a powerful visualization tool for design, simulation, and analysis in modem complex industrial systems. The primary motivation for this thesis is to develop a framework for the effective use of VR in design-simulation-analysis cycles, particularly in situations involving large, complex, multi-dimensional data-sets. This thesis develops a framework that is intended to support not only the integration of such data for visual, interactive, and immersive displays, but also provides a method for performing risk analysis. Previously "static" VR environments are enhanced with time-evolutionary capabilities. Four candidate algorithms are evaluated for this purpose – deterministic modeling, auto-regressive moving average modeling, genetic algorithm modeling, and hidden Markov modeling. Benefits, drawbacks, and trade-offs are evaluated with reference to their suitability for development in a VR environment. The methods developed in this research work are demonstrated by applying them to multi-sensor data obtained during the in-line, nondestructive evaluation of gas transmission pipelines.

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