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Experimental and Computational Investigation of the Dynamics of Fluctuation Suppression by Controlled Flow Shear

Experimental and Computational Investigation of the Dynamics of Fluctuation Suppression by Controlled Flow Shear
受控流剪切抑制脉动动力学的实验和计算研究
批准号:
0903879
负责人:
Mark Gilmore
金额:
$30.0万
依托单位:
依托单位国家:
美国
项目类别:
Continuing Grant
财政年份:
2009
资助国家:
美国
项目状态:
已结题
起止时间:
2009-09-01 至 2013-08-31

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中文摘要
翻译
这项研究的目的是在受控的实验室环境中详细地研究不稳定漂移涨落(包括宽带湍流)和涨落抑制态之间的跃迁动力学。这些实验将通过与非线性流体湍流程序的直接比较来补充,该程序特别适用于模拟这次实验。拟议的实验将在新墨西哥大学(UNM)的双源HELCAT(螺旋阴极)装置中进行。HELCAT是一种灵活的设备,它提供了对这些实验非常重要的独特功能。这两个等离子体源--独立运行或同时运行--可以产生边缘起伏的等离子体,范围从单一漂移模式到宽带漂移湍流。此外,已经证实了等离子体偏置对Er×Bz流动分布的影响,而碰撞对漂移波衰减的重要影响已经改变了一个数量级以上。由阿拉斯加大学费尔班克斯分校的合作者PI开发的数值代码,是一个静电波动的2-D流体板模型,具有详细的诊断方法,以了解波动模式之间相互作用的动力学,将进行修改,以允许驱动器模拟实验驱动器。该代码有一个外部流动,可以打开它来观察流动对波动模式的影响。研究设施非常适合培训学生从事聚变能源职业或研究等离子体中的湍流输运,这一过程在空间和天体物理等离子体以及磁约束实验室等离子体中很重要。这项研究可能会对建立等离子体中湍流传输的预测模型的努力产生重大影响。这项研究涉及基础等离子体物理、复杂动力学、空间等离子体和磁约束等离子体。这项建议提交给NSF-DOE在等离子体科学和工程合作伙伴08-589联合征集。该奖项由数学和物理科学局物理司资助。
英文摘要
The goal of this research is to investigate experimentally the detailed dynamics of transitions between states of unstable drift fluctuations (including broadband turbulence), and fluctuation-suppressed states in a controlled laboratory environment. These experiments will be complemented by direct comparisons with a nonlinear fluid turbulence code, adapted specifically to model this experiment. The proposed experiments will take place in the dual-source HELCAT (HELicon-CAThode) device at the University of New Mexico (UNM). HELCAT is a flexible device that provides unique capabilities important to these experiments. The two plasma sources- operated independently or simultaneously - can generate plasmas with edge fluctuations ranging from single drift modes to broadband drift turbulence. Additionally, plasma biasing to affect Er × Bz flow profiles has been demonstrated, and collisionality, important in drift wave damping, has been varied by more than an order of magnitude. The numerical code developed by the co-PI at the University of Alaska Fairbanks, a 2-D fluid slab model of electrostatic fluctuations with detailed diagnostics to understand the dynamics of the interaction between the fluctuating modes, will be modified to allow the drive to mimic the experimental drive. The code has an external flow that can be turned on to look at the impact of flow on the fluctuating modes.The research facility is well suited for training students for careers in fusion energy or studying turbulent transport in plasmas, a process important in space and astrophysical plasma as well as magnetically confined laboratory plasmas. The research could have a significant impact on efforts to create predictive models for turbulent transport in plasmas. This research is relevant to basic plasma physics, complex dynamics, space plasmas and magnetically confined plasmas.This proposal was submitted to the NSF-DoE Partnership in Plasma Science and Engineering joint solicitation 08-589. This award is being funded by the Division of Physics of the Mathematical and Physical Sciences Directorate.
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会议论文
Investigation of the Dynamics of Interacting Magnetized Plasmas Through Experiments and Extended MHD Modeling
  • 批准号:
    2308849
  • 项目类别:
    Standard Grant
  • 资助金额:
    $56.12万
  • 财政年份:
    2023
  • 负责人:
    Mark Gilmore
  • 依托单位:
Turbulence Dynamics in the Presence of Flow Shear in a Collisional Plasma: Experiment-Model Cross-Validation
  • 批准号:
    1500423
  • 项目类别:
    Standard Grant
  • 资助金额:
    $20.0万
  • 财政年份:
    2015
  • 负责人:
    Mark Gilmore
  • 依托单位:
Investigation of Turbulence Dynamics in the Presence of Flow Shear, Electrode Biasing, Magnetic Shear and X-Points
  • 批准号:
    1201995
  • 项目类别:
    Continuing Grant
  • 资助金额:
    $34.5万
  • 财政年份:
    2012
  • 负责人:
    Mark Gilmore
  • 依托单位:
Collaborative Research on the Complex Dynamics of Turbulence and Structure in Magnetized Plasmas
  • 批准号:
    0317238
  • 项目类别:
    Continuing Grant
  • 资助金额:
    $41.55万
  • 财政年份:
    2003
  • 负责人:
    Mark Gilmore
  • 依托单位:
国内基金
海外基金
Computational Methods for Analyzing Toponome Data