Towards an improved understanding of tidal turbine dynamics in a turbulent marine environment

提高对湍流海洋环境中潮汐涡轮机动力学的理解

基本信息

  • 批准号:
    1706358
  • 负责人:
  • 金额:
    $ 30.88万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
    Standard Grant
  • 财政年份:
    2017
  • 资助国家:
    美国
  • 起止时间:
    2017-09-01 至 2024-02-29
  • 项目状态:
    已结题

项目摘要

Renewable energy technologies offer the promise of non-polluting and sustainable alternatives to fossil and nuclear-fueled power plants. The objective of this research project is to better understand the interactions between a tidal turbine and the surrounding fluid environment. Tidal turbines are a relatively new class of renewable energy devices that convert the motion of flowing water in rivers or tides into energy.  This research is focused on addressing several outstanding scientific challenges that need to be overcome so that these novel devices can be developed and deployed.  In addition to the scientific discoveries, the educational component of this research project involves training the next generation of engineers and professionals through research, teaching, and outreach activities. The outreach component involves partnering with Lehigh University?s Office of Outreach and Northampton Community College in the STAR (Students That Are Ready) program, which targets economically and academically disadvantaged and/or at-risk 8th to 12th grade students. The social impact of the long-term success of tidal turbine technology is significant. In addition to the continental United States, commercialization of these technologies may directly impact a major fraction of the world population as the majority of large population centers are located either close to major rivers or coastlines. The experimental design in this research project is motivated by the need to couple near and far wake physics to turbine performance at elevated levels of free-stream turbulence. Turbulence generation techniques using active grids are being used to mimic hydraulic and natural in-stream conditions. Diagnostics include a reaction torque-thrust sensor for system analysis and time-resolved stereo particle image velocimetry for flow-field measurements. A detailed understanding of the evolution of the wake is vital when considering design of a tidal farm (similar to wind farms). Designing an optimal farm layout in rivers is challenging as the useful zone for power extraction may be restricted to a small footprint due to navigational requirements. Existing engineering analysis do not fully capture the non-linear interactions that arise due to such closely packed layouts or the associated environmental impact. To enhance the scientific impact, the new data sets are being made available to the scientific community to allow validation and verification of advanced computational fluid dynamics models of flow around tidal turbines.
可再生能源技术为化石和核燃料发电厂提供了无污染和可持续的替代方案。该研究项目的目的是更好地了解潮汐涡轮机和周围流体环境之间的相互作用。潮汐涡轮机是一种相对较新的可再生能源设备,它将河流或潮汐中的流动水的运动转化为能量。这项研究的重点是解决需要克服的几个突出的科学挑战,以便开发和部署这些新颖的设备。除了科学发现,该研究项目的教育部分包括通过研究,教学和外展活动培训下一代工程师和专业人员。外联部分涉及与利哈伊大学合作?的外联办公室和北安普顿社区学院在星星(学生准备)计划,该计划的目标是经济和学术上处于不利地位和/或有风险的8至12年级的学生。 潮汐涡轮机技术的长期成功对社会的影响是巨大的。除了美国大陆,这些技术的商业化可能会直接影响世界人口的主要部分,因为大多数大型人口中心位于主要河流或海岸线附近。本研究项目中的实验设计的动机是需要在自由流湍流水平升高时将近尾流和远尾流物理学与涡轮机性能相结合。使用主动网格的湍流生成技术正被用于模拟水流中的水力和自然条件。诊断包括用于系统分析的反作用扭矩-推力传感器和用于流场测量的时间分辨立体粒子图像测速仪。在考虑潮汐发电场(类似于风力发电场)的设计时,对尾流演变的详细了解至关重要。在河流中设计最佳的农场布局是具有挑战性的,因为由于导航要求,电力提取的有用区域可能被限制在一个小的占地面积内。 现有的工程分析不能完全捕获由于这种紧密堆积的布局或相关的环境影响而产生的非线性相互作用。为了加强科学影响,正在向科学界提供新的数据集,以便验证和核实潮汐涡轮机周围流动的先进计算流体动力学模型。

项目成果

期刊论文数量(7)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
Towards a better understanding of yawed turbine wake for efficient wake steering in tidal arrays
  • DOI:
    10.1016/j.renene.2021.05.152
  • 发表时间:
    2021
  • 期刊:
  • 影响因子:
    8.7
  • 作者:
    P. Modali;A. Vinod;A. Banerjee
  • 通讯作者:
    P. Modali;A. Vinod;A. Banerjee
Performance and near-wake characterization of a tidal current turbine in elevated levels of free stream turbulence
  • DOI:
    10.1016/j.apenergy.2019.113639
  • 发表时间:
    2019-07
  • 期刊:
  • 影响因子:
    11.2
  • 作者:
    A. Vinod;A. Banerjee
  • 通讯作者:
    A. Vinod;A. Banerjee
Influence of yaw misalignment on the propagation of Tidal Turbine wake
偏航不对中对潮汐机尾流传播的影响
  • DOI:
  • 发表时间:
    2019
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Modali, Pranav K;Banerjee, Arindam
  • 通讯作者:
    Banerjee, Arindam
Tidal turbine performance and near-wake characteristics in a sheared turbulent inflow
  • DOI:
    10.1016/j.renene.2021.05.026
  • 发表时间:
    2021-09
  • 期刊:
  • 影响因子:
    8.7
  • 作者:
    A. Vinod;Cong Han;A. Banerjee
  • 通讯作者:
    A. Vinod;Cong Han;A. Banerjee
Performance and wake characteristics of a tidal turbine under yaw
  • DOI:
    10.36688/imej.1.41-50
  • 发表时间:
    2018-09
  • 期刊:
  • 影响因子:
    0
  • 作者:
    P. Modali;Nitin Kolekar;A. Banerjee
  • 通讯作者:
    P. Modali;Nitin Kolekar;A. Banerjee
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Arindam Banerjee其他文献

Passive and reactive scalar measurements in a transient high-Schmidt-number Rayleigh–Taylor mixing layer
  • DOI:
    10.1007/s00348-012-1328-y
  • 发表时间:
    2012-06-05
  • 期刊:
  • 影响因子:
    2.500
  • 作者:
    Arindam Banerjee;Lakshmi Ayyappa Raghu Mutnuri
  • 通讯作者:
    Lakshmi Ayyappa Raghu Mutnuri
Integral Closure of Powers of Edge Ideals of Weighted Oriented Graphs
  • DOI:
    10.1007/s40306-024-00558-0
  • 发表时间:
    2024-10-17
  • 期刊:
  • 影响因子:
    0.300
  • 作者:
    Arindam Banerjee;Kanoy Kumar Das;Sirajul Haque
  • 通讯作者:
    Sirajul Haque
AmbientFlow: Invertible generative models from incomplete, noisy measurements
AmbientFlow:来自不完整、噪声测量的可逆生成模型
  • DOI:
  • 发表时间:
    2023
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Varun A. Kelkar;Rucha Deshpande;Arindam Banerjee;M. Anastasio
  • 通讯作者:
    M. Anastasio
Technology acceptance model and customer engagement: mediating role of customer satisfaction
技术接受模型和客户参与:客户满意度的中介作用
Private equity in developing nations
  • DOI:
    10.1057/jam.2008.12
  • 发表时间:
    2008-06-23
  • 期刊:
  • 影响因子:
    1.400
  • 作者:
    Arindam Banerjee
  • 通讯作者:
    Arindam Banerjee

Arindam Banerjee的其他文献

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{{ truncateString('Arindam Banerjee', 18)}}的其他基金

NRT - Stakeholder Engaged Equitable Decarbonized Energy Futures
NRT - 利益相关者参与的公平脱碳能源期货
  • 批准号:
    2244162
  • 财政年份:
    2023
  • 资助金额:
    $ 30.88万
  • 项目类别:
    Standard Grant
Collaborative Research: Physics-Based Machine Learning for Sub-Seasonal Climate Forecasting
合作研究:基于物理的机器学习用于次季节气候预测
  • 批准号:
    2130835
  • 财政年份:
    2021
  • 资助金额:
    $ 30.88万
  • 项目类别:
    Continuing Grant
III: Small: Stochastic Algorithms for Large Scale Data Analysis
III:小型:大规模数据分析的随机算法
  • 批准号:
    2131335
  • 财政年份:
    2021
  • 资助金额:
    $ 30.88万
  • 项目类别:
    Continuing Grant
PFI-TT: Advancing the Technology Readiness of Pylon Fairings for Tidal Turbines
PFI-TT:推进潮汐涡轮机塔架整流罩的技术准备
  • 批准号:
    1919184
  • 财政年份:
    2019
  • 资助金额:
    $ 30.88万
  • 项目类别:
    Standard Grant
III: Small: Stochastic Algorithms for Large Scale Data Analysis
III:小型:大规模数据分析的随机算法
  • 批准号:
    1908104
  • 财政年份:
    2019
  • 资助金额:
    $ 30.88万
  • 项目类别:
    Continuing Grant
Collaborative Research: Physics-Based Machine Learning for Sub-Seasonal Climate Forecasting
合作研究:基于物理的机器学习用于次季节气候预测
  • 批准号:
    1934634
  • 财政年份:
    2019
  • 资助金额:
    $ 30.88万
  • 项目类别:
    Continuing Grant
III: Medium: Collaborative Research: Bayesian Modeling and Inference for Quantifying Terrestrial Ecosystem Functions
III:媒介:协作研究:量化陆地生态系统功能的贝叶斯建模和推理
  • 批准号:
    1563950
  • 财政年份:
    2016
  • 资助金额:
    $ 30.88万
  • 项目类别:
    Continuing Grant
CAREER: Transition to Turbulence and Mixing for Rayleigh Taylor Instability with Acceleration Reversal
职业生涯:加速反转的瑞利泰勒不稳定性过渡到湍流和混合
  • 批准号:
    1453056
  • 财政年份:
    2015
  • 资助金额:
    $ 30.88万
  • 项目类别:
    Standard Grant
BIGDATA: F: DKA: Collaborative Research: High-Dimensional Statistical Machine Learning for Spatio-Temporal Climate Data
BIGDATA:F:DKA:协作研究:时空气候数据的高维统计机器学习
  • 批准号:
    1447566
  • 财政年份:
    2014
  • 资助金额:
    $ 30.88万
  • 项目类别:
    Standard Grant
EAGER: Collaborative Research: Learning Relations between Extreme Weather Events and Planet-Wide Environmental Trends
EAGER:合作研究:学习极端天气事件与全球环境趋势之间的关系
  • 批准号:
    1451986
  • 财政年份:
    2014
  • 资助金额:
    $ 30.88万
  • 项目类别:
    Standard Grant

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