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Reliability Analysis Of Offshore Wind Turbine Foundation Under Wind Loads And Wave Loads

Posted on:2017-11-10Degree:MasterType:Thesis
Country:ChinaCandidate:B W JiangFull Text:PDF
GTID:2322330485981480Subject:Port, Coastal and Offshore Engineering
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Based on the Doctoral Scientific Fund Project of the Ministry of Education of China(No.20125522110004)and the key research project supported by Natural Science Foundation of CSTC(No.cstc2013jjB3002),with the engineering background of Rudong County coastal and tidal zone wind farm construction project in Jiangsu Province,the “reliability analysis of offshore wind turbine foundation under wind loads and wave loads” wasconducted under the guidanceof structural reliability theory based on mathematical statistics.The main research contents and results are as follows:(1)By comparing the accuracy and computational efficiency on wavesimulation of two different theories,the wave loads on wind turbine was calculated with Morison equationaccording toThe fifth order Stokes wave theory.According tothe spectral density function of P-M spectrum and correlation theory of long term statistical distribution of waves,theprobabilitydistribution model of wave height(obeys the Rayleigh distribution)and period(obeys the Gauss distribution)were educed based on the statistical information of Rudong County coastal and tidal zone wind farm construction project in Jiangsu Province.(2)The time history curve of wind velocity on wind turbine hub was educed through calculating the superposition of fluctuating wind velocity and static wind velocity based on the statistical information and linear superposition theory of harmonic wave.According to the Kaimal fluctuating wind power spectrum,the standard deviation of fluctuating wind velocity was calculated and used to educe the time history curve of wind velocity under extreme operating gust.(3)The Hub thrust was calculated respectively on the load effect of “superposition of fluctuating wind and static wind”and extreme operating gust based on design technical data of hub thrust characteristics.By comparing the hub thrust of the two different load effect,the wind velocity model was obtained by superposing the velocity of fluctuating wind and extreme operating gust.Compared with the static wind pressure on the tower,the hub thrust is considered to be the main contributor to the wind load.The probability distribution model of velocity of static wind(obeys the Rayleigh distribution)and velocity of fluctuating wind(obeys the Gauss distribution)were educed based on the statistical characteristics of wind velocity.(4)By means of finite element numerical simulation method,constitutive model of offshore wind turbine structure and nonlinear elastic soil was established.Considered wind loads and wave loads,the static anddynamic responseanalysis of offshore wind turbine was educed respectively.Through contrastingthe displacement and stress in critical points between the two,the probability distribution model of random variable was modified.(5)Considering the conditions of normal operation andturbine-shutdown,the trend analysisaimed atrandom variables and output variableswas done based on Monte Carlo method: The sensitivitiesbetween the output variables and random variables werecalculated to show the correlation;The scattersbetween the output variables and random variables weredrawn to get the function relation;The probability distribution model of load effect(output variable)was obtained.(6)Taking different values of limit displacement and limit stress,failure probabilities of the structure were calculated according to the probability distribution of load effect model.Through failure characteristics analysis,different failure modesunder the conditions of normal operation and turbine-shutdown were summarized.Eventually,some suggestions were put forward on the structure design in the light ofRudong County coastal and tidal zone wind farm construction project in Jiangsu Province.
Keywords/Search Tags:offshore wind turbines, wind loads, wave loads, reliability analysis, Montel Carlo, random variables
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