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Detection of Magma Chamber at Mt. Fuji, Japan

Detection of Magma Chamber at Mt. Fuji, Japan
日本富士山岩浆房的探测
批准号:
0440054
负责人:
Jonathan Lees
金额:
$0.0万
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2005
资助国家:
美国
项目状态:
已结题
起止时间:
2005-07-01 至 2008-06-30

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中文摘要
翻译
我们申请资金拍摄日本富士山下的地壳结构,以限制岩浆储存系统和火山管道的几何形状。富士山目前正由日本合作者进行监测,并在过去20年里积累了大量的地震数据。地震活动和活火山活动在富士山地区特别强烈,提供了一个极好的数据集,数据覆盖范围很广。我们将讨论深部与浅层岩浆储存区、地壳中部分熔融堆积的存在以及岩浆管道的几何形状等问题。利用已建立的三维地震成像方法,利用地震速度、衰减、各向异性和震源相关性等物理参数对管道/岩浆储存区进行照明。高分辨率的事件位置将约束岩浆储存区附近的岩浆搬运模型。约束管道中岩浆和气体通量的流体动力学性质将使用有关谐波震颤与收缩流动的非线性过程进行建模。在富士山下面观测到的深层低频事件将通过矩张量反演与地震成像所描绘的结构特征的相关性来建模。这一建议解决了在俯冲带背景下岩浆储存的问题。对火山形成和演化的分析,需要对深层熔体的积累和运移进行估算。活火山系统的结构分析为火山喷发动力学评估和减灾提供了框架。
英文摘要
We request funds to image crustal structure below Mt. Fuji, Japan, to constrain the geometry of the magma storage system and volcano plumbing. Mt. Fuji is currently being monitored by Japanese collaborators and has an extensive seismic data set accumulated over the last 20 years. Seismicity and active volcanism is particularly intense in the Mt. Fuji region, providing an excellent data set with ample data coverage. We will address the question of deep versus shallow magma storage regions, the presence of partial melt accumulation in the crust and the geometry of magma conduits. Established methods of three-dimensional seismic imaging will be used to illuminate the conduit/magma storage areas using physical parameters such as seismic velocity, attenuation, anisotropy and hypocenter correlation. High resolution event locations will constrain magma transport models near in the magma storage region. Fluid dynamical properties constraining magma and gas flux in the conduits will be modeled using non-linear processes relating harmonic tremor to constricted flow. Deep, low frequency events observed below Mt. Fuji will be modeled by moment tensor inversion for correlation to structural features delineated by seismic imaging.This proposal addresses issues of magma storage in subduction zone settings. Estimation of deep melt accumulation and transport is essential for analysis of volcano formation and evolution. Structural analysis of active volcanic systems provides the framework for assessment of eruption dynamics and hazard mitigation.
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Deep Learning for CAR-T cell therapy optimisation
  • 批准号:
    MR/W003309/2
  • 项目类别:
    Research Grant
  • 资助金额:
    $11.21万
  • 财政年份:
    2022
  • 负责人:
    Jonathan Lees
  • 依托单位:
Deep Learning for CAR-T cell therapy optimisation
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  • 项目类别:
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  • 资助金额:
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  • 财政年份:
    2021
  • 负责人:
    Jonathan Lees
  • 依托单位:
CEDAR: Lower-Upper Atmosphere Coupling via Acoustic Wave Energy
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  • 批准号:
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  • 项目类别:
    数学天元基金项目
  • 资助金额:
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  • 批准年份:
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  • 负责人:
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