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Gallagher R.S. (Ed.). Computer Visualization: Graphics Techniques for Engineering and Scientific Analysis

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Gallagher R.S. (Ed.). Computer Visualization: Graphics Techniques for Engineering and Scientific Analysis
CRC Press, 1994. — 336 p. ISBN: 978-0849390500.
Technology, at its most basic level, seeks to understand how the world behaves. Over the past three decades, computer graphics methods have fueled a growing understanding of physical phenomena, which in turn have helped scientists and engineers substantially improve the quality of life.
The growth of these graphics techniques for scientific behavior developed in spurts over the past twenty
years—some might say in fits and starts, as the field has grown rapidly from an area of academic research to a commercial field, accounting for sales of hundreds of millions of US dollars per year in the early 1990s. The first spurt came in the 1960s, when digital numerical simulation techniques became popular, and the need to graphically display their output on at least a pen plotter became immediately apparent. The next spurt came in the 1970s, when techniques were developed for the display of states of behavior using methods such as color-coding, contour displays, and vector symbols. Most of these techniques shared a common purpose of representing behavior on the outside visible surfaces of a model. In the late 1980s these same techniques remained the norm for displays of behavior.
Today the relatively new field of 3-D scientific visualization has made a major impact on the display of
behavior. Originally developed to address large-scale visualization needs such as medical imaging, real-time data reduction, and satellite imagery, the techniques of scientific visualization are now being applied to numerical analysis and simulation to understand complex volumetric, multidimensional or time-dependent behavior. More important, numerical methods such as finite element analysis and computational fluid dynamics have begun over the last few years to make a substantial impact in the development of algorithmic visualization techniques. This harks back to the situation in the early days of computer graphics, when graphics techniques for design and analysis applications made a central impact on the computer graphics field as a whole. In applying this new and developing area of technology, the student or practitioner of 3-D visualization techniques has frequently needed to refer to such source materials as computer graphics journals or published collections of papers. A reference work to summarize developments in this field for those who wish to understand and apply them is clearly required. Computer Visualization represents a single, unified collection of computer graphics techniques for the Title scientific visualization of behavior. It is a reference work for professionals who use computing techniques to visualize data, and for the academic and software communities who support them. The book combines a basic overview of the fundamentals of computer graphics with a practitioner oriented review of the latest 3-D graphics display and visualization techniques, as they are applied to science and engineering. All of its chapters are written by key researchers or experts in their specialties. Section One reviews how computer graphics visualization techniques have evolved to work with digital numerical analysis methods. Its introductory chapter examines the growth of computer visualization from the perspective of my own profession of computer-aided engineering. This section also introduces the fundamentals of computer graphics which apply to the visualization of analysis data.
The chapters of Section Two contain a detailed review of the algorithms and techniques used to visualize
behavior in 3-D, as static, interactive or animated imagery. This section begins with a discussion of the
mathematics of engineering data for visualization, and then covers the current methods used for the display of scalar, vector and tensor fields. Another chapter examines the more general issues of visualizing a continuum volume field, and the section ends with a chapter on animating the dimensions of time and motion in a state of behavior. The final section is particularly useful for those implementing production visualization capabilities, including the practical computational aspects of visualization such as user interfaces, database architecture and interaction with a model. The concluding chapters outline successful practical applications of visualization, and future trends in scientific visualization.
To produce things better, faster, and less expensively than before, visualization tools have evolved to help scientists and engineers understand more about how things behave. In the process we have gained an insight into a whole new realm of information which has heretofore been hidden from us.
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