Multidisciplinary Design Optimization and Analysis Using a Hybrid Augmented Lagrangian Genetic Algorithm

Simple item page
dc.contributorMulani, Sameer B
dc.contributorMacPhee, David W
dc.contributor.advisorSu, Weihua
dc.contributor.authorBenabbou, Adam
dc.contributor.otherUniversity of Alabama Tuscaloosa
dc.date.accessioned2022-04-13T20:34:25Z
dc.date.available2022-04-13T20:34:25Z
dc.date.issued2020
dc.descriptionElectronic Thesis or Dissertationen_US
dc.description.abstractA major challenge in the aerospace design process is the balance between simulation fidelity and various types of resource constraints such as financial and computational. To develop new data analytical capabilities and improve the reliability of medium fidelity projects using well selected algorithms and methods, a multidisciplinary simulation and optimization tool is developed using MATLAB. In the process, several key areas of research are identified, investigated and methods of analyses are discussed. Primarily, a novel method for implementing a hybrid augmented Lagrangian genetic algorithm is developed and thoroughly tested using a variety of benchmark problems. The algorithm is then implemented to optimize surrogate models for an MDO case study. This test case is a wing model of size comparable to a Cessna 172, flying at cruising speed. However, the methodology presented in this thesis could be extended beyond subsonic aircraft wing optimization and even outside the realm of aerospace engineering. The study allows for a better understanding of the methods used in multidisciplinary design optimization for conceptual design. The proof-of-concept successfully demonstrates the versatility of the MDO framework and opens the project up to several future avenues of research.en_US
dc.format.mediumelectronic
dc.format.mimetypeapplication/pdf
dc.identifier.otherhttp://purl.lib.ua.edu/182120
dc.identifier.otheru0015_0000001_0004273
dc.identifier.otherBenabbou_alatus_0004M_14261
dc.identifier.urihttps://ir.ua.edu/handle/123456789/8452
dc.languageEnglish
dc.language.isoen_US
dc.publisherUniversity of Alabama Libraries
dc.relation.hasversionborn digital
dc.relation.ispartofThe University of Alabama Electronic Theses and Dissertations
dc.relation.ispartofThe University of Alabama Libraries Digital Collections
dc.rightsAll rights reserved by the author unless otherwise indicated.en_US
dc.subjectcomputational research
dc.subjectdesign engineering
dc.subjectgenetic algorithm
dc.subjectmultidisciplinary
dc.subjectOptimization
dc.subjectrocket science
dc.titleMultidisciplinary Design Optimization and Analysis Using a Hybrid Augmented Lagrangian Genetic Algorithmen_US
dc.typethesis
dc.typetext
etdms.degree.departmentUniversity of Alabama. Department of Aerospace Engineering and Mechanics
etdms.degree.disciplineAerospace Engineering
etdms.degree.grantorThe University of Alabama
etdms.degree.levelmaster's
etdms.degree.nameM.S.

Files

Original bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
u0015_0000001_0004273.pdf
Size:
10.66 MB
Format:
Adobe Portable Document Format
Download

Collections

Theses and Dissertations
Theses and Dissertations - Department of Aerospace Engineering and Mechanics