RT Journal Article
T1 Prevention of Hazards Induced by a Radiation Fireball through Computational Geometry and Parametric Design
A1 Cabeza Laínez, Jose M.
A1 Salguero Andújar, Francisco Jesús
A1 Rodríguez Cunil, Inmaculada
AB Radiation fireballs are singular phenomena which involve severe thermal radiation and,consequently, they need to be duly assessed and prevented. Although the radiative heat transferproduced by a sphere is relatively well known, the shadowing measures implemented to controlthe fireball’s devastating effects have frequently posed a difficult analytical instance, mainly dueto its specific configuration. The objective of this article is to develop a parametric algorithm thatprovides the exact radiative configuration factors for the most general case in which the fireball islocated at any distance and height above the ground, partially hidden by a protective wall over anaffected area at different positions with respect to the said fireball. To this aim we use methods basedon Computational Geometry and Algorithm-Aided Design; tools that, departing from the projectedsolid-angle principle, provide exact configuration factors, in all cases, even if they do not presenta definite analytical solution. This implies dealing with spatially curved radiative sources whichhad not been addressed formerly in the literature due to their mathematical difficulties. Adequateapplication of this method may improve the safety of a significant number of facilities and reducethe number casualties among persons exposed to such risks. As a similar radiative problem appearsin volcanic explosions; we hope that further extensions of the method can be adapted to the issuewith advantage
PB MDPI
SN 2227-7390 (electrónico)
YR 2022
FD 2022
LK http://hdl.handle.net/10272/20714
UL http://hdl.handle.net/10272/20714
LA eng
NO Cabeza-Lainez, J. M., Salguero-Andújar, F., & Rodríguez-Cunill, I. (2022). Prevention of Hazards Induced by a Radiation Fireball through Computational Geometry and Parametric Design. In Mathematics (Vol. 10, Issue 3, p. 387). MDPI AG. https://doi.org/10.3390/math10030387
NO F.S.-A. would like to dedicate this work to his beloved son Enrique SalgueroJiménez from whom he learned all he knows about Grasshopper®. J. C-L. recognizes TomomiOdajima for strategic support and Juan Manuel Bonilla for his technical vision and contribution
DS Repositorio Institucional de la Universidad de Huelva
RD 30 may 2026