Use of artificial neural network in the estimation of detonation velocity for tetranitromethane-nitrobenzene mixture

Detonation velocity or rate of energy release is an important property to consider when rating an explosive. It is a critical parameter used for estimating explosive performance as it can indicate the intensity of detonation. The purpose of this research study is to propose an artificial neural netw...

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Main Authors:	Evangelista, Danielle Grace, Rhay Vicerra, Ryan, Bandala, Argel A.
Format:	text
Published:	Animo Repository 2019
Subjects:	Explosives Neural networks (Computer science) Force and energy Manufacturing
Online Access:	https://animorepository.dlsu.edu.ph/faculty_research/1908
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Institution:	De La Salle University

id	oai:animorepository.dlsu.edu.ph:faculty_research-2907
record_format	eprints
spelling	oai:animorepository.dlsu.edu.ph:faculty_research-29072021-07-30T02:45:35Z Use of artificial neural network in the estimation of detonation velocity for tetranitromethane-nitrobenzene mixture Evangelista, Danielle Grace Rhay Vicerra, Ryan Bandala, Argel A. Detonation velocity or rate of energy release is an important property to consider when rating an explosive. It is a critical parameter used for estimating explosive performance as it can indicate the intensity of detonation. The purpose of this research study is to propose an artificial neural network model that would aid in the estimation of detonation velocities of a high explosive specifically, tetranitromethane-nitrobenzene (TNM/NB) mixture, with varying parameters. © 2019 IEEE. 2019-11-01T07:00:00Z text https://animorepository.dlsu.edu.ph/faculty_research/1908 Faculty Research Work Animo Repository Explosives Neural networks (Computer science) Force and energy Manufacturing
institution	De La Salle University
building	De La Salle University Library
continent	Asia
country	Philippines Philippines
content_provider	De La Salle University Library
collection	DLSU Institutional Repository
topic	Explosives Neural networks (Computer science) Force and energy Manufacturing
spellingShingle	Explosives Neural networks (Computer science) Force and energy Manufacturing Evangelista, Danielle Grace Rhay Vicerra, Ryan Bandala, Argel A. Use of artificial neural network in the estimation of detonation velocity for tetranitromethane-nitrobenzene mixture
description	Detonation velocity or rate of energy release is an important property to consider when rating an explosive. It is a critical parameter used for estimating explosive performance as it can indicate the intensity of detonation. The purpose of this research study is to propose an artificial neural network model that would aid in the estimation of detonation velocities of a high explosive specifically, tetranitromethane-nitrobenzene (TNM/NB) mixture, with varying parameters. © 2019 IEEE.
format	text
author	Evangelista, Danielle Grace Rhay Vicerra, Ryan Bandala, Argel A.
author_facet	Evangelista, Danielle Grace Rhay Vicerra, Ryan Bandala, Argel A.
author_sort	Evangelista, Danielle Grace
title	Use of artificial neural network in the estimation of detonation velocity for tetranitromethane-nitrobenzene mixture
title_short	Use of artificial neural network in the estimation of detonation velocity for tetranitromethane-nitrobenzene mixture
title_full	Use of artificial neural network in the estimation of detonation velocity for tetranitromethane-nitrobenzene mixture
title_fullStr	Use of artificial neural network in the estimation of detonation velocity for tetranitromethane-nitrobenzene mixture
title_full_unstemmed	Use of artificial neural network in the estimation of detonation velocity for tetranitromethane-nitrobenzene mixture
title_sort	use of artificial neural network in the estimation of detonation velocity for tetranitromethane-nitrobenzene mixture
publisher	Animo Repository
publishDate	2019
url	https://animorepository.dlsu.edu.ph/faculty_research/1908
_version_	1707059171822665728

Use of artificial neural network in the estimation of detonation velocity for tetranitromethane-nitrobenzene mixture

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