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An Advanced Surrogate Model for Predicting the Impact of a SMA Twist System on the Helicopter Performance

Ameduri, Salvatore and Concilio, Antonio and Majeti, Rohin Kumar (2019) An Advanced Surrogate Model for Predicting the Impact of a SMA Twist System on the Helicopter Performance. In: SMASIS2019: Proceedings of the ASME 2019 Conference on Smart Materials, Adaptive Structures, and Intelligent Systems. ASME 2019 Conference on Smart Materials, Adaptive Structures, and Intelligent Systems, SMASIS2019, 09-11. Sept. 2019, Louisville, KY, USA.

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Abstract

The paper at hand focuses on an advanced surrogate predictive model, conceived to estimate the impact on blade twist law of a Shape Memory Alloy actuation system. The basic idea is to integrate the pre-existing blade structure with a pre-twisted SMA tube. Due to the specific property of recovering deformation during phase transition, the SMA element can transmit angular deformations and alter the original twist to improve performance when required. The model at hand includes two main modules. The first one targets the SMA actuator and simulates the transmission of twist against some critical parameters (tube extension and location along the blade span and level of activation). The second module receives as input the modified twist law and the updated mechanical features due to the SMA and gives in output an estimate of the performance produced by the system. After an overview on input and output parameters and their cross link, a description of the SMA predicting core is provided. A parameterization is then organized to illustrate the impact of the morphing system onto the blade and on the twist law. On this basis, an additional parameterization is implemented, now focusing on the effects on performance of the proposed system.

Item URL in elib:https://elib.dlr.de/131717/
Document Type:Conference or Workshop Item (Speech)
Additional Information:SABRE
Title:An Advanced Surrogate Model for Predicting the Impact of a SMA Twist System on the Helicopter Performance
Authors:
AuthorsInstitution or Email of AuthorsAuthors ORCID iD
Ameduri, SalvatoreCIRA, ItalyUNSPECIFIED
Concilio, AntonioCIRA, ItalyUNSPECIFIED
Majeti, Rohin KumarRohin.Majeti (at) dlr.dehttps://orcid.org/0000-0003-0634-8051
Date:14 October 2019
Journal or Publication Title:SMASIS2019: Proceedings of the ASME 2019 Conference on Smart Materials, Adaptive Structures, and Intelligent Systems
Refereed publication:No
Open Access:Yes
Gold Open Access:No
In SCOPUS:No
In ISI Web of Science:No
Status:Published
Keywords:Surrogate model, SMA blade twist, blade morphing
Event Title:ASME 2019 Conference on Smart Materials, Adaptive Structures, and Intelligent Systems, SMASIS2019
Event Location:Louisville, KY, USA
Event Type:international Conference
Event Dates:09-11. Sept. 2019
Organizer:American Society of Mechanical Engineers
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Aeronautics
HGF - Program Themes:rotorcraft
DLR - Research area:Aeronautics
DLR - Program:L RR - Rotorcraft Research
DLR - Research theme (Project):L - The Innovative Rotorcraft
Location: Braunschweig
Institutes and Institutions:Institute of Flight Systems > Rotorcraft
Deposited By: Majeti, Rohin Kumar
Deposited On:14 Jan 2020 18:59
Last Modified:14 Jan 2020 18:59

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