Stochastic dynamic stiffness of a surface footing for offshore wind turbines: Implementing a subset simulation method to estimate rare events |
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| Institution: | 1. Dalhousie University, Halifax, Nova Scotia, Canada;2. Energy Security Studies, Masaryk University, Brno, Czech Republic;3. Mineral Resource Strategy and Policy Research Center, School of Economics and Management, China University of Geosciences, Wuhan 430074, China;1. University of Florence, Department of Civil and Environmental Engineering, Via di S. Marta 3, 50139 Florence, Italy;2. Bergische Universität Wuppertal, Pauluskirchstraße 7, 42285 Wuppertal, Germany;3. Krätzig & Partner, Buscheyplatz 9-13, 44801 Bochum, Germany;4. Niemann & Partner, Universitätstr. 142, 44799 Bochum, Germany;1. Department of Sustainability Engineering, Guglielmo Marconi University, via Plinio 44, Rome 00193, Italy;2. Department of Engineering, University of Perugia, Via G. Duranti, Perugia 06125, Italy;3. Ev-K2-CNR Chartered Association, Via San Bernardino 145, Bergamo 24126, Italy;1. Department of Civil Engineering, Indian Institute of Engineering Science and Technology, Shibpur, Howrah 711103, India;2. Department of Civil, Structural and Environmental Engineering, Trinity College Dublin, Dublin 2, Ireland;1. Department of Mechanical Engineering, Nantong University, No. 9, Seyuan Road, Nantong, Jiangsu, China;2. Jiangsu Engineering Research Center for Wind Energy Application, No. 9, Seyuan Road, Nantong, Jiangsu, China |
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| Abstract: | The purpose of this study, which concerns the stochastic dynamic stiffness of foundations for large offshore wind turbines, is to quantify uncertainties related to the first natural frequency of a turbine supported by a surface footing and to estimate the low event probabilities. Herein, a simple model of a wind turbine structure with equivalent coupled springs at the base is calibrated with the mean soil property values. A semianalytical solution, based on the Green?s function for a layered half-space is utilized for estimation of foundation responses. Soil elastic modulus and layer depth are considered as random variables with lognormal distributions. The uncertainties are quantified, and the estimation of rare events of the first natural frequency is discussed through an advanced reliability approach based on subset simulation. This analysis represents a first step in the estimation of the safety with respect to the failure of a turbine in the fatigue limit state. |
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| Keywords: | Wind turbines Foundations Subset simulation Stochastic analysis Dynamics Monte Carlo |
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