Monocolumn composite bucket foundation is a new type of offshore wind energy foundation.Its bearing characteristics under shallow bedrock conditions and complex geological conditions have not been extensively studied....Monocolumn composite bucket foundation is a new type of offshore wind energy foundation.Its bearing characteristics under shallow bedrock conditions and complex geological conditions have not been extensively studied.Therefore,to analyze its bearing characteristics under complex conditions-such as silty soil,chalky soil,and shallow bedrock-this paper employs finite element software to establish various soil combination scenarios.The load-displacement curves of the foundations under these scenarios are calculated to subsequently evaluate the horizontal ultimate bearing capacity.This study investigates the effects of shallow bedrock depth,the type of soil above the bedrock,the thickness of layered soil,and the quality of layered soil on the bearing characteristics of the monocolumn composite bucket foundation.Based on the principle of single-variable control,the ultimate bearing capacity characteristics of the foundation under different conditions are compared.The distribution of soil pressure inside and outside the bucket wall on the compressed side of the foundation,along with the plastic strain of the soil at the base of the foundation,is also analyzed.In conclusion,shallow bedrock somewhat reduces foundation bearing capacity.Under shallow bedrock conditions,the degree of influence on foundation bearing capacity characteristics can considerably vary on different upper soils.The thickness of each soil layer and the depth to bedrock in stratified soils also affect the bearing capacity of the foundation.The findings of this paper provide a theoretical reference for related foundation design and construction.In practice,the bearing performance of the foundation can be enhanced by improvingthe soil quality in the bucket,adjusting the penetration depth,adjusting the percentage of different types of soil layers in the bucket,and applying other technical construction methods.展开更多
During the hoisting process of the offshore substation,changes in the hoisting speed can affect the hoisting system.Therefore,this study set four different speed conditions for the lifting and lowering stages of the i...During the hoisting process of the offshore substation,changes in the hoisting speed can affect the hoisting system.Therefore,this study set four different speed conditions for the lifting and lowering stages of the installation process,and studied the impact of different lifting and lowering speeds on the hoisting system under the same environmental conditions through numerical simulation.The results show that during the lifting operation,as the lifting speed increases,the swing motion of the substation and the installation vessel tends to decrease,and the faster the hoisting speed,the more obvious the swing suppression of the substation and the installation vessel,and the smaller the fluctuation in the tension amplitude of the slings and mooring lines.In contrast,during the lowering operation,as the lowering speed increases,the swing motion of the substation and the installation vessel tends to increase,and the faster the lowering speed,the more obvious the swing amplification effect of the substation and the installation vessel.Therefore,during hoisting operations,increasing the lifting speed and reducing the lowering speed can mitigate the motion performance of the hoisting coupling system,reduce the tension amplitude variation of the sling and mooring,and ensure the smooth progress of the hoisting operation.展开更多
针对目前海上风电出力预测方法精度较低的问题,提出一种基于词向量化和长短期记忆网络(word to vector long short-term memory,Word2vec-LSTM)与聚类修正的海上风电出力预测方法。对Word2vec方法进行改进来提取时间序列数据特征,实现...针对目前海上风电出力预测方法精度较低的问题,提出一种基于词向量化和长短期记忆网络(word to vector long short-term memory,Word2vec-LSTM)与聚类修正的海上风电出力预测方法。对Word2vec方法进行改进来提取时间序列数据特征,实现数据信息的高效利用;在长短期记忆神经网络的预测模型基础上,研究了一种基于k-shape聚类结果的预测结果修正算法,对预测结果距离聚类中心超过阈值的数值判定为预测误差偏大的数据并向簇中心进行修正。最后,基于江苏某海上风电场的真实数据进行测试,结果表明,基于Word2vec-LSTM与聚类修正的海上风电出力预测方法的平均绝对误差(mean absolute error,MAE)和均方根误差(root mean square error,RMSE)达到5.04和5.42,相比传统LSTM预测模型的误差平均降低了11.10%和12.25%,为海上风电并网与电网调控提供了技术支持。展开更多
文摘Monocolumn composite bucket foundation is a new type of offshore wind energy foundation.Its bearing characteristics under shallow bedrock conditions and complex geological conditions have not been extensively studied.Therefore,to analyze its bearing characteristics under complex conditions-such as silty soil,chalky soil,and shallow bedrock-this paper employs finite element software to establish various soil combination scenarios.The load-displacement curves of the foundations under these scenarios are calculated to subsequently evaluate the horizontal ultimate bearing capacity.This study investigates the effects of shallow bedrock depth,the type of soil above the bedrock,the thickness of layered soil,and the quality of layered soil on the bearing characteristics of the monocolumn composite bucket foundation.Based on the principle of single-variable control,the ultimate bearing capacity characteristics of the foundation under different conditions are compared.The distribution of soil pressure inside and outside the bucket wall on the compressed side of the foundation,along with the plastic strain of the soil at the base of the foundation,is also analyzed.In conclusion,shallow bedrock somewhat reduces foundation bearing capacity.Under shallow bedrock conditions,the degree of influence on foundation bearing capacity characteristics can considerably vary on different upper soils.The thickness of each soil layer and the depth to bedrock in stratified soils also affect the bearing capacity of the foundation.The findings of this paper provide a theoretical reference for related foundation design and construction.In practice,the bearing performance of the foundation can be enhanced by improvingthe soil quality in the bucket,adjusting the penetration depth,adjusting the percentage of different types of soil layers in the bucket,and applying other technical construction methods.
基金support from the National Natural Science Foundation of China(No.52271287)funding from the State Key Laboratory of Hydraulic Engineering Intelligent Construction and Operation,Tianjin University。
文摘During the hoisting process of the offshore substation,changes in the hoisting speed can affect the hoisting system.Therefore,this study set four different speed conditions for the lifting and lowering stages of the installation process,and studied the impact of different lifting and lowering speeds on the hoisting system under the same environmental conditions through numerical simulation.The results show that during the lifting operation,as the lifting speed increases,the swing motion of the substation and the installation vessel tends to decrease,and the faster the hoisting speed,the more obvious the swing suppression of the substation and the installation vessel,and the smaller the fluctuation in the tension amplitude of the slings and mooring lines.In contrast,during the lowering operation,as the lowering speed increases,the swing motion of the substation and the installation vessel tends to increase,and the faster the lowering speed,the more obvious the swing amplification effect of the substation and the installation vessel.Therefore,during hoisting operations,increasing the lifting speed and reducing the lowering speed can mitigate the motion performance of the hoisting coupling system,reduce the tension amplitude variation of the sling and mooring,and ensure the smooth progress of the hoisting operation.
文摘针对目前海上风电出力预测方法精度较低的问题,提出一种基于词向量化和长短期记忆网络(word to vector long short-term memory,Word2vec-LSTM)与聚类修正的海上风电出力预测方法。对Word2vec方法进行改进来提取时间序列数据特征,实现数据信息的高效利用;在长短期记忆神经网络的预测模型基础上,研究了一种基于k-shape聚类结果的预测结果修正算法,对预测结果距离聚类中心超过阈值的数值判定为预测误差偏大的数据并向簇中心进行修正。最后,基于江苏某海上风电场的真实数据进行测试,结果表明,基于Word2vec-LSTM与聚类修正的海上风电出力预测方法的平均绝对误差(mean absolute error,MAE)和均方根误差(root mean square error,RMSE)达到5.04和5.42,相比传统LSTM预测模型的误差平均降低了11.10%和12.25%,为海上风电并网与电网调控提供了技术支持。
