Predicting and improvising the performance of rocket nozzle throat using machine learning algorithms

Title

Predicting and improvising the performance of rocket nozzle throat using machine learning algorithms

Creator

Krishna A.V.N.

Description

This paper is a study of one dimensional heat conduction with thermo physical properties like K, row, Cp of a material varying with temperature. The physical problem is characterized by a cylinder of infinite length and thickness L, imposed with a net heat flux at x= 0, with the other end being insulated. The temperatures at the insulate end are measured by placing thermocouples. As the temperatures at the other end are very high, it is not possible to measure temperatures by keeping thermocouples which will burn away. So the problem is initialized with known sensor values near insulated end. By proper predicting values by ARIMA Model, the temperature distribution in Rocket Nozzle throat system (RNT) is calculated. The outcome of the work is processed with Machine Learning algorithm like Genetic algorithm in identifying the optimal location of sensor position which helps in improvising the performance of RNT. 2020, Institute of Advanced Scientific Research, Inc. All rights reserved.

Source

Journal of Advanced Research in Dynamical and Control Systems, Vol-12, No. 4 Special Issue, pp. 16-20.

Date

2020-01-01

Publisher

Institute of Advanced Scientific Research, Inc.

Subject

Machine Learning Algorithms; Rocket Nozzle Throat

Coverage

Krishna A.V.N., CSE, CHRIST (Deemed to BE University), Bengaluru, India

Rights

Restricted Access

Relation

ISSN: 1943023X

Format

Online

Language

English

Type

Article

Identifier

https://doi.org/10.5373/JARDCS/V12SP4/20201461

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