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An experimental investigation on long-term performance of the wide-shallow bucket foundation model for offshore wind turbine in saturated sand

机译:饱和砂中近海风力涡轮机宽浅桶基础模型长期性能的实验研究

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摘要

The bucket foundation is considered as a promising alternative to conventional foundations for offshore wind turbines (OWTs) due to its cost-effectiveness and high-reliability. The behavior of bucket foundation under static loading has been extensively investigated, while its long-term performance induced by the cyclic loading under the surrounding soil influence lack of study. This study aims to investigate the influence of one-way cyclic horizontal loading on the long-term performance of the wide-shallow bucket foundation (WSBF) model for offshore wind turbine in saturated sand by using single-gravity (1-g) model tests. Specifically, a series of cyclic experiments with varied loading conditions including load magnitude (P), load frequency (f), excitation height (H) and cycle number (N) were conducted to reveal the influence of loading conditions on dynamic characteristics and accumulated rotation of the WSBF model. Furthermore, the regression analysis method based on artificial neural network (ANN) model is proposed to determine the relationship between loading conditions and the long-term performance of the WSBF model. It is shown that the natural frequency rises and damping ratio decreases with the increase of cyclic loading number during the early cyclic stage. Afterwards, there is a declining or stable trend for the natural frequency and a rising trend for the damping ratio of the WSBF model. As for the accumulated rotation, more than 80% foundation rotation occurs in the first hundred cycles, whereas accumulated rotation for rest cycles tends to be small. Finally, multiple regression analysis and sensitivity analysis based on the ANN model are demonstrated to evaluate and predict the changes in long-term performance of the WSBF model with high accuracy in this study.
机译:由于其成本效益和高可靠性,铲斗基础被认为是对海上风力涡轮机(OWTS)的常规基础的有前途的替代品。静电负荷下铲斗基础的行为得到了广泛研究,而周围土壤循环载荷诱导的长期性能影响缺乏研究。本研究旨在探讨单重循环水平加载单循环水平加载对饱和砂中饱和砂宽浅桶基础(WSBF)模型的长期性能的影响。具体地,进行了一系列具有变化的负载条件的循环实验,包括负载幅度(P),负载频率(F),激发高度(H)和循环编号(N),以揭示负载条件对动态特性和累积旋转的影响WSBF模型。此外,提出了基于人工神经网络(ANN)模型的回归分析方法来确定加载条件与WSBF模型的长期性能之间的关系。结果表明,自然频率上升和阻尼比随着早期循环阶段期间的循环负载数的增加而降低。之后,对WSBF模型的阻尼比的矛盾趋势下降或稳定趋势。至于累积的旋转,在前一百个循环中发生超过80%的基础旋转,而静止循环的累积旋转趋于小。最后,证明了基于ANN模型的多元回归分析和敏感性分析,以评估和预测本研究高精度的WSBF模型的长期性能变化。

著录项

  • 来源
    《Ocean Engineering》 |2021年第15期|108921.1-108921.14|共14页
  • 作者单位

    Tianjin Univ State Key Lab Hydraul Engn Simulat & Safety Tianjin 300072 Peoples R China|Tianjin Univ Sch Civil Engn 135 Yaguan Rd Tianjin 300072 Peoples R China|Hebei Univ Engn Sch Water Conservancy & Hydropower Handan 056038 Peoples R China;

    Tianjin Univ State Key Lab Hydraul Engn Simulat & Safety Tianjin 300072 Peoples R China|Tianjin Univ Sch Civil Engn 135 Yaguan Rd Tianjin 300072 Peoples R China|PowerChina Huadong Engn Corp Ltd Hangzhou 311122 Peoples R China;

    Tianjin Univ State Key Lab Hydraul Engn Simulat & Safety Tianjin 300072 Peoples R China|Tianjin Univ Sch Civil Engn 135 Yaguan Rd Tianjin 300072 Peoples R China;

    Tianjin Univ State Key Lab Hydraul Engn Simulat & Safety Tianjin 300072 Peoples R China|Tianjin Univ Sch Civil Engn 135 Yaguan Rd Tianjin 300072 Peoples R China;

    Tianjin Univ State Key Lab Hydraul Engn Simulat & Safety Tianjin 300072 Peoples R China|Tianjin Univ Sch Civil Engn 135 Yaguan Rd Tianjin 300072 Peoples R China;

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  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Offshore wind turbine (OWT); Wide-shallow bucket foundation (WSBF); 1-G model tests; Long-term performance; Artificial neural network (ANN);

    机译:海上风力涡轮机(OWT);宽浅桶基础(WSBF);1-G型试验;长期性能;人工神经网络(ANN);

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