Development of the multifactorial computational models of the solid propellants combustion by means of data science methods –phase II

Chandrasekaran, N and Oommen, C and Bharath, RS and Abrukov, VS and Lukin, AN and Kiselev, MV and Anufrieva, DA and Sanalkumar, VR (2018) Development of the multifactorial computational models of the solid propellants combustion by means of data science methods –phase II. In: 54th AIAA/SAE/ASEE Joint Propulsion Conference, 2018, 9 - 1 July 2018, Cincinnati.

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Abstract

In the present investigation, we present the results of usage of artificial neural networks (ANN) methodologies, for predicting primary combustion characteristics of solid propellants (SP) combustion. ANN could be considered as a good approximation tool of the experimental functions of several variables, which could provide an affordable way of predicting parameters which otherwise demand hazardous and costly experiments. Two ANN multifactor models dealing with the combustion of AP-HTPB composite propellant are presented. The validated ANN models will be able to predict many unexplored regimes for which experimental data are not available.

Item Type:	Conference Paper
Publication:	2018 Joint Propulsion Conference
Publisher:	American Institute of Aeronautics and Astronautics Inc, AIAA
Additional Information:	The copyright of this article belongs to American Institute of Aeronautics and Astronautics Inc, AIAA.
Keywords:	Combustion; Forecasting; HTPB propellants; Neural networks; Propulsion, Ann models; Computational model; Functions of several variables; Multifactor models; Phase II; Primary combustions; Science methods, Composite propellants
Department/Centre:	Division of Mechanical Sciences > Aerospace Engineering(Formerly Aeronautical Engineering)
Date Deposited:	27 Jul 2022 10:28
Last Modified:	27 Jul 2022 10:29
URI:	https://eprints.iisc.ac.in/id/eprint/75281

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