Geophysical flow dynamics using pulsed Doppler radar

使用脉冲多普勒雷达的地球物理流动力学

• 批准号: NE/F004621/1
• 负责人: Paul Brennan
• 金额: $ 16.85万
• 依托单位: University College London
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2008
• 资助国家: 英国
• 起止时间: 2008 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=NE%2FF004621%2F1
• 关键词: Geophysical; flow; dynamics; using; pulsed

Mass movement flows are a significant natural hazard throughout the world and yet our ability to predict their behaviour and plan for their effects is limited, in part, by our lack of understanding of their flow dynamics. This research will investigate the dynamics of geophysical mass movement flow processes (specifically snow avalanches and pyroclastic flows) by means of carefully-controlled trials at avalanche and volcano test sites. This research will utilise a sophisticated and new Doppler radar imaging instrument, able to form two-dimensional animated images of a variety of geophysical events. This radar has been under development at University College London, supported by the Royal Society, and permits imaging of the dense parts of the flow (often the most important component for risk analyses) by penetrating the suspended matter surrounding snow avalanches and pyroclastic flows. Advanced signal processing algorithms will be used to generate detailed models of the structure and dynamics of the flow. At present, opto-electronic instruments can provide such information at a single point and existing Doppler radar can provide crude images of the flow speed, but averaged over 50 m and only giving an overall measure of the velocity magnitude (with no information on direction). Our instrument will reduce the averaging distance to just 1 m so that, for the first time, information on individual blocks in the flow can be obtained and assessed in relation to their significance for the overall flow dynamics. Thus, we can assess the validity of a variety of flow laws that have been proposed for describing such processes. This will lead to improved models for these flow processes by limiting the values of coefficient in the models to reasonable values and rejecting some proposed flow laws outright. This will lead to more accurate modelling of these processes, which in turn will improve risk analyses and the design of defensive structures. This study will therefore considerably increase our understanding of flow movement and raise the status of UK research in this area to internationally-leading standards.

大规模流动是世界各地的一种重大自然灾害，但我们预测其行为和规划其影响的能力有限，部分原因是我们缺乏对其流动动力学的了解。这项研究将通过在雪崩和火山试验场进行精心控制的试验，调查地球物理物质运动流动过程（特别是雪崩和火山碎屑流）的动力学。这项研究将利用一种先进的新型多普勒雷达成像仪器，能够形成各种地球物理事件的二维动画图像。该雷达在皇家学会的支持下，由伦敦大学学院研制，通过穿透雪崩和火山碎屑流周围的悬浮物质，可以对流动的密集部分（通常是风险分析的最重要组成部分）进行成像。先进的信号处理算法将被用来生成详细的模型的结构和动态的流动。目前，光电仪器可以在一个点提供这种信息，现有的多普勒雷达可以提供流速的粗略图像，但平均超过50米，只能给出速度大小的总体测量（没有方向信息）。我们的仪器将把平均距离减少到1米，这样，第一次可以获得流中各个块体的信息，并根据它们对整体流动动力学的重要性进行评估。因此，我们可以评估的有效性的各种流动的法律，已提出了描述这样的过程。这将导致改进的模型，这些流动过程中的系数值限制在合理的值，并拒绝一些建议的流动定律彻底。这将导致对这些过程进行更准确的建模，从而改善风险分析和防御结构的设计。因此，这项研究将大大增加我们对流动的理解，并将英国在这一领域的研究水平提高到国际领先水平。

项目成果

High-resolution radar measurements of snow avalanches

• DOI: 10.1002/grl.50134
• 发表时间: 2013-02-28
• 期刊: GEOPHYSICAL RESEARCH LETTERS
• 影响因子: 5.2
• 作者: Vriend, N. M.;McElwaine, J. N.;Brennan, P. V.
• 通讯作者: Brennan, P. V.

Looking inside an avalanche using a novel radar system

使用新型雷达系统观察雪崩内部

• DOI: 10.1111/gto.12033
• 发表时间: 2014
• 期刊: Geology Today
• 作者: Keylock C

Two-dimensional radar imaging of flowing avalanches

• DOI: 10.1016/j.coldregions.2014.02.004
• 发表时间: 2014-06-01
• 期刊: COLD REGIONS SCIENCE AND TECHNOLOGY
• 影响因子: 4.1
• 作者: Ash, Matthew;Brennan, Paul V.;Sovilla, Betty
• 通讯作者: Sovilla, Betty

Millimeter-precision range profiling and cross-sectional imaging of ice shelves in Polar regions using phase-sensitive FMCW radar

使用相敏 FMCW 雷达对极地冰架进行毫米级精度范围剖面分析和横截面成像

• DOI: 10.1109/radar.2013.6586055
• 发表时间: 2013
• 作者: Rahman S

Range migration compensation in static digital-beamforming-on-receive radar

静态数字接收波束成形雷达中的距离偏移补偿

• DOI: 10.1049/iet-rsn.2014.0355
• 发表时间: 2015
• 期刊: IET Radar, Sonar & Navigation
• 作者: Brennan P