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Multi-Fidelity Modeling of Isolated Hovering Rotors

dc.contributor.authorJason Cornelius
dc.contributor.authorNicholas Peters
dc.contributor.authorTove Ågren
dc.contributor.authorHugo Hjelm
dc.contributor.otherAeromechanics Office, NASA Ames Research Center, Mountain View, CA 94035, USA
dc.contributor.otherAeromechanics Office, NASA Ames Research Center, Mountain View, CA 94035, USA
dc.contributor.otherAnalytical Mechanics Associates, NASA Ames Research Center, Mountain View, CA 94035, USA
dc.contributor.otherInternational Internships Program, NASA Ames Research Center, Mountain View, CA 94035, USA
dc.date.accessioned2025-08-27T13:59:21Z
dc.date.accessioned2025-10-08T08:42:55Z
dc.date.available2025-10-08T08:42:55Z
dc.date.issued01-07-2025
dc.identifier.urihttp://digilib.fisipol.ugm.ac.id/repo/handle/15717717/36869
dc.description.abstractSurrogate modeling has been rapidly evolving in the field of aerospace engineering, further reducing the cost of computational analyses. These models often require large amounts of information to learn the underlying process, which is at odds with obtaining and using the highest-fidelity data. This study assesses the efficacy of multi-fidelity modeling (MFM) to improve simulation accuracy while reducing computational cost. A database of hovering rotor simulations with perturbations of the rotor design and operating conditions was first generated using two different fidelity levels of the OVERFLOW 2.4D Computational Fluid Dynamics software. MFM was then used to quantify the effectiveness of this approach for the development of accurate surrogate models. Multi-fidelity models based on Gaussian Process Regression (GPR) were derived for hovering rotor performance prediction given the geometric rotor blade inputs that currently include twist, planform, airfoil, and the collective pitch angle. The MFM approach was consistently more accurate at predicting the hold-out test data than the surrogate model with high-fidelity data alone. An MFM using just 20% of the available high-fidelity training data was as accurate as a solely high-fidelity model trained on 80% of the available data, representing an approximate fourfold reduction in computational cost.
dc.language.isoEN
dc.publisherMDPI AG
dc.subject.lccMotor vehicles. Aeronautics. Astronautics
dc.titleMulti-Fidelity Modeling of Isolated Hovering Rotors
dc.typeArticle
dc.description.keywordsmulti-fidelity modeling
dc.description.keywordsrotorcraft analysis
dc.description.keywordssurrogate modeling
dc.description.keywordscomputational fluid dynamics
dc.description.keywordsrotor conceptual design
dc.description.keywordsrotor performance database
dc.description.doi10.3390/aerospace12080650
dc.title.journalAerospace
dc.identifier.e-issn2226-4310
dc.identifier.oaioai:doaj.org/journal:399a1972bbe54f2fb49c9d727a3256dc
dc.journal.infoVolume 12, Issue 8


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