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Adjoint-based Aerodynamic Design Optimization for Centrifugal Compressor with Structural Constraints

Schaffrath, Robert und Backhaus, Jan und Voß, Christian und Nicke, Eberhard (2025) Adjoint-based Aerodynamic Design Optimization for Centrifugal Compressor with Structural Constraints. In: 70th ASME Turbo Expo 2025: Turbomachinery Technical Conference and Exposition, GT 2025. 70th ASME Turbo Expo 2025: Turbomachinery Technical Conference and Exposition, GT 2025, 2025-06-16 - 2025-06-20, Memphis, Tennessee, USA.

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Kurzfassung

Simulation based optimizations play an increasingly important role in the design of turbomachinery to meet challenging design goals within short design cycles. These optimizations are multi-disciplinary. In addition to computational fluid dynamics (CFD) to calculate aerodynamical performance parameters, computational structural mechanics (CSM) is needed to ensure that material limits are not exceeded. These optimizations are characterized by a large number of free variables. Consequently gradient-enhanced methods should have significant advantages over gradient-free approaches in terms of required iterations and computational costs. An optimization is presented in which the gradient information from CFD and CSM is used to train a gradient-enhanced Gaussian process regression surrogate model. The gradients are efficiently calculated for the CFD and CSM discipline with a discrete adjoint method. This approach is compared to a gradient-free optimization and to an optimization in which gradients are only used for the objective function (CFD) but not for the constraints (CSM). The methods are applied on a centrifugal compressor geometry with splitter-blades which consists of impeller and diffusor and uses water vapor as working medium. The design objective is reaching a high isentropic efficiency at the aerodynamic design point (ADP). Constraints are the restriction of the mass flow and a limit for the maximal stress in the solid material. By using the gradients for the training of the surrogate models the number of required iterations could be significantly reduced to 140. The gradient-free benchmark optimization with an ordinary kriging surrogate model required 350 iteration. Besides the satisfaction of the constraints, the optimized geometry has an increased isentropic efficiency of 3.2% compared to the baseline.

elib-URL des Eintrags:https://elib.dlr.de/216457/
Dokumentart:Konferenzbeitrag (Vortrag)
Titel:Adjoint-based Aerodynamic Design Optimization for Centrifugal Compressor with Structural Constraints
Autoren:
AutorenInstitution oder E-Mail-AdresseAutoren-ORCID-iDORCID Put Code
Schaffrath, RobertRobert.Schaffrath (at) dlr.dehttps://orcid.org/0000-0001-8487-8299NICHT SPEZIFIZIERT
Backhaus, Janjan.backhaus (at) dlr.dehttps://orcid.org/0000-0003-1951-3829192638635
Voß, ChristianChristian.Voss (at) dlr.dehttps://orcid.org/0009-0007-0504-495X192638638
Nicke, EberhardEberhard.Nicke (at) dlr.deNICHT SPEZIFIZIERTNICHT SPEZIFIZIERT
Datum:2025
Erschienen in:70th ASME Turbo Expo 2025: Turbomachinery Technical Conference and Exposition, GT 2025
Referierte Publikation:Ja
Open Access:Nein
Gold Open Access:Nein
In SCOPUS:Ja
In ISI Web of Science:Nein
Status:veröffentlicht
Stichwörter:Aerodynamic Optimization, Adjoint Computational Fluid Dynamics, Adjoint Computational Structural Simulation, Gradient Enhanced Surrogate Models, Radial Compressor, Water Vapor
Veranstaltungstitel:70th ASME Turbo Expo 2025: Turbomachinery Technical Conference and Exposition, GT 2025
Veranstaltungsort:Memphis, Tennessee, USA
Veranstaltungsart:internationale Konferenz
Veranstaltungsbeginn:16 Juni 2025
Veranstaltungsende:20 Juni 2025
Veranstalter :ASME: The American Society of Mechanical Engineers
HGF - Forschungsbereich:Energie
HGF - Programm:Materialien und Technologien für die Energiewende
HGF - Programmthema:Thermische Hochtemperaturtechnologien
DLR - Schwerpunkt:Energie
DLR - Forschungsgebiet:E SP - Energiespeicher
DLR - Teilgebiet (Projekt, Vorhaben):E - Dekarbonisierte Industrieprozesse
Standort: Zittau
Institute & Einrichtungen:Institut für CO2-arme Industrieprozesse
Institut für Antriebstechnik > Numerische Methoden
Institut für Antriebstechnik > Fan- und Verdichter
Hinterlegt von: Schaffrath, Robert
Hinterlegt am:24 Sep 2025 16:21
Letzte Änderung:24 Sep 2025 16:21

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