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Application of an Algorithmically Differentiated Turbomachinery Flow Solver to the Optimization of a Fan Stage

Backhaus, Jan and Schmitz, Andreas and Frey, Christian and Mann, Sebastian and Nagel, Marc and Sagebaum, Max and Gauger, Nicolas (2017) Application of an Algorithmically Differentiated Turbomachinery Flow Solver to the Optimization of a Fan Stage. In: AIAA JOURNAL. 18th AIAA/ISSMO Multidisciplinary Analysis and Optimization Conference, 05.-09. Jun. 2017, Denver, USA.

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The adjoint method has already proven its potential to reduce the computational effort for optimizations of turbomachinery components based on flow simulations. However, the transfer of the adjoint-based optimization methods to industrial design problems turns out to pose specific requirements to both the adjoint solver as well as the optimization algorithms which utilize the gradient information. While the construction of the adjoint solver through algorithmic differentiation is described in a parallel publication, we focus here on the robust application of the gradient information in a high-dimensional multi-objective op- timization with several constraints including non-differentiated mechanical constraints. We describe the optimization methods, which comprise the use of gradient-enhanced Kriging meta-models, and subsequently apply these to the design optimization of a contra-rotating fan stage. The results show that through the described combination of methods the adjoint method can be used in practical design optimizations of turbomachinery components.

Item URL in elib:https://elib.dlr.de/112832/
Document Type:Conference or Workshop Item (Speech)
Additional Information:AIAA-2017-3997 This project has received funding from the Clean Sky 2 Joint Undertaking under the European Unions Horizon 2020 research and innovation programme under grant agreement No CS2-Engines ITD-2014-2015- 01.
Title:Application of an Algorithmically Differentiated Turbomachinery Flow Solver to the Optimization of a Fan Stage
AuthorsInstitution or Email of AuthorsAuthor's ORCID iD
Backhaus, Janjan.backhaus (at) dlr.dehttps://orcid.org/0000-0003-1951-3829
Schmitz, AndreasAndreas.Schmitz (at) dlr.deUNSPECIFIED
Frey, ChristianChristian.Frey (at) dlr.deUNSPECIFIED
Mann, SebastianSebastian.Mann (at) mtu.deUNSPECIFIED
Nagel, MarcMarc.Nagel (at) mtu.deUNSPECIFIED
Sagebaum, Maxmax.sagebaum (at) scicomp.uni-kl.deUNSPECIFIED
Gauger, Nicolasnicolas.gauger (at) scicomp.uni-kl.deUNSPECIFIED
Date:7 June 2017
Journal or Publication Title:AIAA JOURNAL
Refereed publication:Yes
Open Access:Yes
Gold Open Access:No
In ISI Web of Science:Yes
Keywords:adjoint, optimization, meta-modelling, kriging, contra rotating fan
Event Title:18th AIAA/ISSMO Multidisciplinary Analysis and Optimization Conference
Event Location:Denver, USA
Event Type:international Conference
Event Dates:05.-09. Jun. 2017
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Aeronautics
HGF - Program Themes:fixed-wing aircraft
DLR - Research area:Aeronautics
DLR - Program:L AR - Aircraft Research
DLR - Research theme (Project):L - Simulation and Validation (old)
Location: Köln-Porz
Institutes and Institutions:Institute of Propulsion Technology > Numerical Methodes
Deposited By: Backhaus, Jan
Deposited On:02 Jul 2017 12:44
Last Modified:20 Jun 2021 15:49

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