Probabilistic surrogate modeling of offshore wind-turbine loads with chained Gaussian processes
نویسندگان
چکیده
Abstract Heteroscedastic Gaussian process regression, based on the concept of chained processes, is used to build surrogates predict site-specific loads an offshore wind turbine. Stochasticity in inflow turbulence and irregular waves results load responses that are best represented as random variables rather than deterministic values. Moreover, effect these stochastic sources depends strongly mean environmental conditions - for instance, at low speeds, produces much less variability high speeds. Statistically, this known heteroscedasticity . Deterministic most do not account heteroscedastic noise, giving incomplete potentially misleading picture structural response. In paper, we draw recent advancements statistical inference train a surrogate model noisy database conditional pdf The informed via 10-minute statistics IEA-10MW-RWT subject both aero- hydrodynamic loads, simulated with OpenFAST. Its performance assessed against standard regression. predicted similar models, but approximates large-scale variance significantly better.
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ژورنال
عنوان ژورنال: Journal of physics
سال: 2022
ISSN: ['0022-3700', '1747-3721', '0368-3508', '1747-3713']
DOI: https://doi.org/10.1088/1742-6596/2265/3/032070