An extension of the modified constitutive relation error concept for the robust multi-physics offshore wind turbine model calibration from in situ data

An extension of the modified constitutive relation error concept for the robust multi-physics offshore wind turbine model calibration from in situ data | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article An extension of the modified constitutive relation error concept for the robust multi-physics offshore wind turbine model calibration from in situ data Antoine Roussel, Ludovic Chamoin, Jean-Philippe Argaud, Pierre Bousseau This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7768773/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 29 Apr, 2026 Read the published version in Advanced Modeling and Simulation in Engineering Sciences → Version 1 posted 9 You are reading this latest preprint version Abstract In order to address health monitoring issues on offshore wind turbines, while taking into account engineering know-how and constraints, we propose a robust model identification procedure based on reliability of information for such structures. The procedure leans on the modified Constitutive Relation Error concept, which naturally considers sensing and modeling uncertainties. The concept is here extended to a multi-physics framework involving nonlinear fluid-structure interactions. In this framework, each individual interface is seen as a specific and potentially nonlinear constitutive relation, assumed unreliable and relaxed in the identification process, with suited error metric. Parameters associated to these constitutive relations are then identified to close at best the gap between operational observations and model predictions, and to detect modeling incompatibilities by means of error indicators. Considering classical engineering modeling and simulation approaches dedicated to offshore wind turbines, the performance of the approach is numerically shown first on academic examples with synthetic data, then in a more practical context by processing real in situ measurements coming from an industrial demonstrator equipped with various multiphysic sensors. Model Calibration Multi-physics problems Inverse problems Fluid-structure interactions Structural dynamics Constitutive Relation Error In situ data Offshore wind turbines Digital twins Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 29 Apr, 2026 Read the published version in Advanced Modeling and Simulation in Engineering Sciences → Version 1 posted Editorial decision: Revision requested 24 Nov, 2025 Reviews received at journal 22 Nov, 2025 Reviews received at journal 09 Nov, 2025 Reviewers agreed at journal 12 Oct, 2025 Reviewers agreed at journal 06 Oct, 2025 Reviewers invited by journal 06 Oct, 2025 Editor assigned by journal 03 Oct, 2025 Submission checks completed at journal 03 Oct, 2025 First submitted to journal 02 Oct, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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