Sprache: Englisch
Verlag: Creative Media Partners, LLC Mai 2025, 2025
ISBN 10: 1025130103 ISBN 13: 9781025130101
Anbieter: AHA-BUCH GmbH, Einbeck, Deutschland
Taschenbuch. Zustand: Neu. Neuware - Fuel-air mixing analysis of scramjet aircraft is often performed through experimental research or computational -uid dynamics (cfd) algorithms. Design optimization with these approaches is often impossible under a limited budget due to their high cost per run. This investigation uses jetpen, a known inexpensive analysis tool, to build upon a previous case study of scramjet design optimization. Mixed Variable Pattern Search (mvps) is compared to evolutionary algorithms in the optimization of two scramjet designs. The rst revisits the previously studied approach and compares the quality of mvps to prior results. The second applies mvps to a new scramjet design in support of the Hypersonic International Flight Research Experimentation (hifire). The results demonstrate the superiority of mvps over evolutionary algorithms and paves the way for design optimization with more expensive approaches.
Sprache: Englisch
Verlag: Creative Media Partners, LLC Mai 2025, 2025
ISBN 10: 1025124820 ISBN 13: 9781025124827
Anbieter: AHA-BUCH GmbH, Einbeck, Deutschland
Buch. Zustand: Neu. Neuware - Fuel-air mixing analysis of scramjet aircraft is often performed through experimental research or computational -uid dynamics (cfd) algorithms. Design optimization with these approaches is often impossible under a limited budget due to their high cost per run. This investigation uses jetpen, a known inexpensive analysis tool, to build upon a previous case study of scramjet design optimization. Mixed Variable Pattern Search (mvps) is compared to evolutionary algorithms in the optimization of two scramjet designs. The rst revisits the previously studied approach and compares the quality of mvps to prior results. The second applies mvps to a new scramjet design in support of the Hypersonic International Flight Research Experimentation (hifire). The results demonstrate the superiority of mvps over evolutionary algorithms and paves the way for design optimization with more expensive approaches.