Robust and Expedited Methodologies for Resolving Radiation View Factors

Authors

  • Natan P. Herzog Student
  • Eliana M. Crew
  • Shane P. Riley
  • Matthew M. Barry

DOI:

https://doi.org/10.5195/pur.2024.60

Abstract

The effects of mesh refinement using the distmesh2d algorithm and gaussian integration on the numerical accuracy of the Double Area Integration (DAI) and Single Area Integration (SAI) numerical methods for evaluating the view factor between two surfaces were studied. It was determined that SAI presents an advantage in eliminating the need for mesh refinement of the receiving surface. Gaussian integration proved to dramatically increase numerical accuracy by, in some cases, five orders of magnitude. These results were applied to the evaluation of view factors for the hot shoe array within a General Purpose Heat Source RTG. It was found that the top and bottom rows are dramatically worse-performing than the remaining rows and that the columns facing the corner of the fuel stack have significantly lower view factors than the others.

Author Biography

Matthew M. Barry

Faculty in the Department of Mechanical Engineering and Materials Science

References

https://www.osti.gov/biblio/296824

http://persson.berkeley.edu/distmesh/

https://booksite.elsevier.com/9780123869449/downloads/View3D/NISTIR-6925.pdf

https://archive.org/details/radiativetransfe0000hoyt

https://archive.org/details/heattransferbasi00ozis

https://people.sc.fsu.edu/~jburkardt/datasets/quadrature_rules_tri/quadrature_rules_tri.html

https://rps.nasa.gov/resources/164/perseverance-looks-back-at-wheel-tracks/?category=images

https://rps.nasa.gov/missions/17/transit-iv-a/

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Published

2024-04-12

How to Cite

Natan P. Herzog, Eliana M. Crew, Shane P. Riley, & Matthew M. Barry. (2024). Robust and Expedited Methodologies for Resolving Radiation View Factors. Pittsburgh Undergraduate Review, 3(1). https://doi.org/10.5195/pur.2024.60

Issue

Vol. 3 No. 1 (2024): Pittsburgh Undergraduate Review

Section

Research

License

Copyright (c) 2024 Natan Herzog, Eliana M. Crew, Shane P. Riley, Matthew M. Barry

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