Statistics – Computation
Scientific paper
Jan 1995
adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=1995phdt.........5f&link_type=abstract
Thesis (PH.D.)--THE UNIVERSITY OF TEXAS AT AUSTIN, 1995.Source: Dissertation Abstracts International, Volume: 56-10, Section: B,
Statistics
Computation
1
Thermal Radiation, Ray Tracing
Scientific paper
The complexities inherent in analysis of radiative heat transfer in participating media often dictate the use of Monte Carlo ray tracing methods. However, the statistical uncertainty of the results produced by this type of method and its voracious appetite for computer time detract from its attractiveness as a general use tool. This research examines various approaches to overcome these disadvantages and improve the general utility of the Monte Carlo ray tracing method for this application. The research examined various Monte Carlo ray tracing algorithms to determine if particular algorithms exhibited reduced uncertainty or computer usage. The performance of selected alternatives under different media conditions was compared. The pathlength based methods offered the best performance in the media tested. In addition, a finite element modeling technique was employed to facilitate the creation of media geometric models and improve the flexibility and speed of the ray tracing algorithms. The research identified and compared several techniques for analyzing particular complexities in participating media that often cause problems for other analysis methods. These complexities included anisotropic scattering, inhomogeneous radiative properties, and spectrally dependent properties. Some suggestions are made based on the quantitative and qualitative comparisons of these techniques. An alternative approach investigated the performance improvements obtained by combining the Monte Carlo methods with other analysis methods. In particular, a Monte Carlo method was combined with a diffusion method to create a hybrid that performs more efficiently in optically thick media. The improvements in performance obtained by this hybrid were demonstrated and some potential limitations were discussed. The formulation and performance of a Monte Carlo-exchange factor hybrid were also described. Another approach examined in the research was to utilize parallel processing to improve the speed of solution. The improvement in computation capabilities of recent parallel processing machines seems well suited to Monte Carlo ray tracing algorithms. The speed improvements obtained by parallelizing the Monte Carlo algorithms described in this research were demonstrated and some limitations were identified.
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