Multi‐fidelity digital twin structural model for a sub‐scale downwind wind turbine rotor blade. Issue 12 (6th May 2021)

• Record Type: Journal Article
• Authors: Chetan, Mayank; Yao, Shulong; Griffith, D. Todd
• Is Part Of: Wind energy. Volume 24:Issue 12(2021)
• Page Start: 1368
• Page End: 1387
• Publication Date: 2021-05-06
• Subjects: digital twin -- downwind -- extreme‐scale wind turbine -- field‐testing -- multi‐fidelity model; Wind power -- Periodicals; 621.312136
• DOI: 10.1002/we.2636
• Languages: English
• ISSNs: 1095-4244

Abstract

Abstract: This paper presents the development of a multi‐fidelity digital twin structural model (virtual model) of an as‐built wind turbine blade. The goal is to develop and demonstrate an approach to produce an accurate and detailed model of the as‐built blade for use in verifying the performance of the operating two‐bladed, downwind rotor. The digital twin model development methodology, presented herein, involves a novel calibration process to integrate a wide range of information including design specifications, manufacturing information, and structural testing data (modal and static) to produce a multi‐fidelity digital twin structural model: a detailed high‐fidelity model (i.e., 3D finite element analysis [FEA]) and consistent beam‐type models for aeroelastic simulation. A key element is that the multi‐fidelity structural digital twin method follows the rotor from the stages of design, to manufacturing, then to the ground testing and field operation. The result of this comprehensive approach is an accurate multi‐fidelity digital twin structural model for the geometric, structural, and structural dynamic properties of the as‐built blade within a 1% match in mass properties, 3.2% in blade frequencies, and 6% in deflection. The different stages of processing this information within the methodology are discussed. The rotor examined is the SUMR‐Demonstrator (SUMR‐D), which was installed on the Controls Advanced Research Testbed (CART‐2) wind turbine at the National Wind Technology Center. The digital twin model developed here was utilized to design controllers to safely operate SUMR‐D in field tests, which are providing additional data for further evaluation and development of the multi‐fidelity digital twin structural model.