Particle swarm optimization of air-launch vehicle and trajectory

A preliminary design optimization and trajectory optimization of air launch vehicle (ALV) are conducted using particle swarms. The optimization is conducted in three main steps. First, a mission analysis of ALV is performed using the required Delta-V predicted by trajectory optimization. The initia...

Full description

Bibliographic Details
Main Authors: Aldheeb, M, Kafafy, Raed, Idres, Moumen, Omar, H.
Format: Proceeding Paper
Language:English
Published: 2011
Subjects:
Online Access:http://irep.iium.edu.my/9066/1/ICMAAE-11-162.pdf
_version_ 1825645082454261760
author Aldheeb, M
Kafafy, Raed
Idres, Moumen
Omar, H.
author_facet Aldheeb, M
Kafafy, Raed
Idres, Moumen
Omar, H.
author_sort Aldheeb, M
collection IIUM
description A preliminary design optimization and trajectory optimization of air launch vehicle (ALV) are conducted using particle swarms. The optimization is conducted in three main steps. First, a mission analysis of ALV is performed using the required Delta-V predicted by trajectory optimization. The initial masses estimated are used for the preliminary ALV design to get the performance and geometric parameters. The second step is to optimize the ALV using particle swarm optimization (PSO) for a minimum total initial mass. The range of parameters based on existing ALV is used for the design variables. The third step is to optimize the trajectory for maximum payload mass. It was found that for the selected mission requirements, a maximum payload mass of 203 kg can be carried to a 400-km circular polar orbit using an ALV with minimum total initial mass of 16,453.9 kg.
first_indexed 2024-03-05T22:42:23Z
format Proceeding Paper
id oai:generic.eprints.org:9066
institution International Islamic University Malaysia
language English
last_indexed 2024-03-05T22:42:23Z
publishDate 2011
record_format dspace
spelling oai:generic.eprints.org:90662012-02-02T08:08:46Z http://irep.iium.edu.my/9066/ Particle swarm optimization of air-launch vehicle and trajectory Aldheeb, M Kafafy, Raed Idres, Moumen Omar, H. TJ Mechanical engineering and machinery A preliminary design optimization and trajectory optimization of air launch vehicle (ALV) are conducted using particle swarms. The optimization is conducted in three main steps. First, a mission analysis of ALV is performed using the required Delta-V predicted by trajectory optimization. The initial masses estimated are used for the preliminary ALV design to get the performance and geometric parameters. The second step is to optimize the ALV using particle swarm optimization (PSO) for a minimum total initial mass. The range of parameters based on existing ALV is used for the design variables. The third step is to optimize the trajectory for maximum payload mass. It was found that for the selected mission requirements, a maximum payload mass of 203 kg can be carried to a 400-km circular polar orbit using an ALV with minimum total initial mass of 16,453.9 kg. 2011-05 Proceeding Paper NonPeerReviewed application/pdf en http://irep.iium.edu.my/9066/1/ICMAAE-11-162.pdf Aldheeb, M and Kafafy, Raed and Idres, Moumen and Omar, H. (2011) Particle swarm optimization of air-launch vehicle and trajectory. In: International Conference on Mechanical, Automotive and Aerospace Engineering (ICMAAE' 11), 17-19 May 2011, Kuala Lumpur, Malaysia. (Unpublished) http://www.iium.edu.my/icmaae/2011/
spellingShingle TJ Mechanical engineering and machinery
Aldheeb, M
Kafafy, Raed
Idres, Moumen
Omar, H.
Particle swarm optimization of air-launch vehicle and trajectory
title Particle swarm optimization of air-launch vehicle and trajectory
title_full Particle swarm optimization of air-launch vehicle and trajectory
title_fullStr Particle swarm optimization of air-launch vehicle and trajectory
title_full_unstemmed Particle swarm optimization of air-launch vehicle and trajectory
title_short Particle swarm optimization of air-launch vehicle and trajectory
title_sort particle swarm optimization of air launch vehicle and trajectory
topic TJ Mechanical engineering and machinery
url http://irep.iium.edu.my/9066/1/ICMAAE-11-162.pdf
work_keys_str_mv AT aldheebm particleswarmoptimizationofairlaunchvehicleandtrajectory
AT kafafyraed particleswarmoptimizationofairlaunchvehicleandtrajectory
AT idresmoumen particleswarmoptimizationofairlaunchvehicleandtrajectory
AT omarh particleswarmoptimizationofairlaunchvehicleandtrajectory