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image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Energyarrow_drop_down
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Energy
Article . 2021 . Peer-reviewed
License: Elsevier TDM
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A GPU-Accelerated ray-tracing method for determining radiation view factors in multi-junction thermoelectric generators

Authors: Asher J. Hancock; Laura B. Fulton; Justin Ying; Corey E. Clifford; Shervin Sammak; Matthew M. Barry;

A GPU-Accelerated ray-tracing method for determining radiation view factors in multi-junction thermoelectric generators

Abstract

Abstract A robust computational framework was developed and implemented to numerically resolve the radiation view factor, F i j , within three-dimensional geometries, and, in particular, thermoelectric generators (TEGs). The proposed numerical methodology utilizes a graphics processing unit-accelerated ray-tracing algorithm to capitalize on the parallel nature of the view factor formulation. The shadow effect, resulting from interference with the TEGs conductive interconnectors and thermoelectric legs, was accounted for via the Moller-Trumbore ray-triangle intersection algorithm with back-face culling enabled. The effect of interconnector thickness, thermoelectric leg height-to-width ratios, TEG packing density, and the number of junctions on F i j is explored for various TEG configurations. Validation is performed against analytical values for planar and non-planar geometries, in addition to a point-in-polygon intersection algorithm for single-junction TEGs. Results indicate that for a constant packing density, F i j asymptotically decreases with increasing distance across the TEG’s hot- and cold-sides. For an increasing packing density and constant distance across the TEG’s junction, F i j decreases. In a multi-junction device, F i j was found to asymptotically increase with junction number, implying that for large multi-junction TEG designs, a simpler model may serve to accurately predict the view factor. The code developed herein is open-source and can be found at https://github.com/AasherH/GPU-Accelerated-View-Factor-Calculator .

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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
7
Top 10%
Average
Top 10%