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Uharek, Sebastian Alexander [Author]; Harries, Stefan [Author]; Cura Hochbaum, Andrés [Author] ; Technische Universität Hamburg Institut für Fluiddynamik und Schiffstheorie, Technische Universität Hamburg Institut für Fluiddynamik und Schiffstheorie, Technische Universität Hamburg Institut für Fluiddynamik und Schiffstheorie, Technische Universität Hamburg, International Workshop on Ship and Marine Hydrodynamics 11. 2019 Hamburg

Fully automatic design space exploration by RANS computations

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  • Media type: E-Book
  • Title: Fully automatic design space exploration by RANS computations
  • Contributor: Uharek, Sebastian Alexander [VerfasserIn]; Harries, Stefan [VerfasserIn]; Cura Hochbaum, Andrés [VerfasserIn]
  • Corporation: Technische Universität Hamburg, Institut für Fluiddynamik und Schiffstheorie ; Technische Universität Hamburg
  • Event: International Workshop on Ship and Marine Hydrodynamics
  • imprint: Hamburg: Technische Universität Hamburg, Institut für Fluiddynamik und Schiffstheorie, [Sept-2019]
  • Extent: 1 Online-Ressource (8 Seiten); Illustrationen, Diagramme
  • Language: English
  • DOI: 10.15480/882.3359
  • Identifier:
  • Keywords: CAESES ; Design space exploration ; RANS ; Response surface
  • Origination:
  • Footnote: Sonstige Körperschaft: Technische Universität Hamburg
    Sonstige Körperschaft: 11th International Workshop on Ship and Marine Hydrodynamics, 2019, Hamburg
  • Description: The present paper presents the result of a design space exploration study for three design variables performed for a twin screw ROPAX ship performed with the Computer Aided Engineering (CAE) software CAESES and the RANS code Neptuno using the meshing software GridPro for the automatic generation of the computational grid for each design iteration step. The design space exploration is carried out using an ensemble design engine, which performs a systematic variation of the parameters in the desired design space. After the exploration, the results are used to set up a surrogate model for a subsequent fast optimization. It can be shown that the current approach allows an easy and fully automatic generation of a reliable surrogate model once the parametric model, the grid topology and the numerical computations are set up.
  • Access State: Open Access
  • Rights information: In Copyright