Configurational optimizer of combined cycle propulsion using genetic programming

Alessandro Mogavero

doi:10.1109/SSCI.2016.7850102

Configurational optimizer of combined cycle propulsion using genetic programming

Alessandro Mogavero

Mechanical And Aerospace Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution book

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Abstract

In most engineering applications the optimization is employed after the conceptual design is already frozen with the only purpose of perfecting it. Although optimization algorithms capable of optimizing the configuration exist, their application is limited to electronics or control design, while for complex systems the conceptual design is often performed with manual trade off analyses among few options.

Original language	English
Title of host publication	2016 IEEE Symposium Series on Computational Intelligence, (SSCI)
Place of Publication	Piscataway
ISBN (Electronic)	9781509042401
DOIs	https://doi.org/10.1109/SSCI.2016.7850102
Publication status	Published - 13 Feb 2017
Event	2016 IEEE Symposium Series on Computational Intelligence, SSCI 2016 - Royal Olympic Hotel, Athens, Greece Duration: 6 Dec 2016 → 9 Dec 2016 http://ssci2016.cs.surrey.ac.uk/

Conference

Conference	2016 IEEE Symposium Series on Computational Intelligence, SSCI 2016
Abbreviated title	SSCI 2016
Country	Greece
City	Athens
Period	6/12/16 → 9/12/16
Internet address	http://ssci2016.cs.surrey.ac.uk/

Keywords

combined cycle
propulsion system modelling
genetic programming
automated design
engines
optimization
object oriented modeling
rockets

Access to Document

10.1109/SSCI.2016.7850102

Mogavero-SSCI-2016-Configurational-optimizer-of-combined-cycle-propulsion-using-genetic-programmingAccepted author manuscript, 256 KB

Link to publication in Scopus

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Cite this

Mogavero, A. (2017). Configurational optimizer of combined cycle propulsion using genetic programming. In 2016 IEEE Symposium Series on Computational Intelligence, (SSCI) [7850102]. https://doi.org/10.1109/SSCI.2016.7850102

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