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'Smart Rocks' for Debris-Flow Landslide Research

'Smart Rocks' for Debris-Flow Landslide Research
用于泥石流滑坡研究的“智能岩石”
批准号:
0927496
负责人:
Barry Fussell
金额:
$25.17万
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
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英文摘要
Debris flows are a particularly destructive class of landslide, in that large volumes of wet soil and rock can move as liquefied masses at very high velocity, and with little warning. Debris flows may be triggered by earthquakes, volcanic eruptions, or rising groundwater. Because of their rapid motion, they can result in a large number of fatalities; an extreme example is the destruction of San Salvador?s suburb of Santa Tecla by an earthquake-triggered debris flow in 2001, resulting in over 700 deaths. The US has not experienced such a devastating event, but flow slides triggered by rainfall or earthquakes have caused significant material damage, and a number of fatalities, particularly in densely-populated areas of California. Both human and material losses are expected to rise with climate change, and as urbanization of landslide-prone areas continues.Debris flows have the particular feature of being able to run out for long distances over very flat slopes. In order to define high-hazard zones and plan possible defensive measures, it is necessary to calculate potential slide velocities and run-out lengths. Modeling these slides is difficult; when the slide is triggered, the sliding material is observed to liquefy, i.e. high internal water pressures force the soil grains apart, and the mass behaves as a heavy viscous fluid. However, as the slide moves down-slope, it segregates into a drained ?snout? of coarser material which could be expected to brake the flow, and a still-liquefied interior, where the finer portion of the soil mass pushes the slide forward. How these two zones interact, so that the overall mass maintains a high ?efficiency? which allow it to travel long distances even on flat slopes, is not well understood, although it is obviously related to the slides? capacity to maintain high internal fluid pressures over a long runout. In many cases this seems surprising, since the grain size distribution of even the interior, liquefied, sliding material would suggest a relatively rapid dissipation of the water pressures required to maintain the soil in a liquefied condition. Sophisticated numerical models for debris flow motion have been developed, but a fundamental problem is that they require, as input, a prediction of the internal water pressures during sliding.In order to clarify this basic problem, this project will develop two sizes of instrumented ?smart rocks? using recently-developed MEMS instrumentation: a ?smart pebble? of golf-ball size to measure how the interior particles vibrate, and how water pressure develop and dissipate in the liquefied interior of the sliding mass; and a ?smart cobble? of soft-ball size, more heavily instrumented, so as to also be capable of tracking how coarser particles move towards the landslide snout during sliding. Both will be ovoid in shape, to simulate natural rocks, and have metal casings to make them easier to find at the end of the slide, using a metal detector. The first two years of the project will be spent in design and extensive laboratory testing of the smart rocks, by a team which will include graduate students from mechanical and civil engineering as well as civil, mechanical and electrical engineering undergraduates. In the third year, the smart rocks will be deployed in large-scale artificial flow slides at the USGS experimental landslide flume in the Willamette National Forest, Oregon; the research team which operates the flume is highly supportive of this project. Results from these tests will be used by the project team to calibrate and refine existing models of debris flows in a way which has not been possible to date. Further, a well-established partnership program with local middle and high schools will seek to involve students and teachers as observers and participants in designing the smart rocks and interpreting the results.
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Minimization of Force Model Uncertainty for CNC Milling Process Improvement
  • 批准号:
    0928602
  • 项目类别:
    Standard Grant
  • 资助金额:
    $20.0万
  • 财政年份:
    2009
  • 负责人:
    Barry Fussell
  • 依托单位:
Feedrate Selection for Numerically Controlled Machining Based on Part Tolerance
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    9622612
  • 项目类别:
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  • 资助金额:
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  • 财政年份:
    1996
  • 负责人:
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Research Initiation: Computer Generated Computer NumericallyControlled Machining Feedrates with In-Process Tuning
  • 批准号:
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  • 项目类别:
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  • 资助金额:
    $6.5万
  • 财政年份:
    1991
  • 负责人:
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  • 批准号:
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  • 项目类别:
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  • 批准年份:
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