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Bubble dynamics during volcanic eruptions: in situ measurements and modelling of physical processes of a rising and exploding gas slug

Bubble dynamics during volcanic eruptions: in situ measurements and modelling of physical processes of a rising and exploding gas slug
火山喷发期间的气泡动力学:气段塞上升和爆炸物理过程的现场测量和建模
批准号:
13799595
负责人:
Professor Dr. Matthias Hort
金额:
$0.0万
依托单位国家:
德国
项目类别:
Research Grants
财政年份:
2006
资助国家:
德国
项目状态:
已结题
起止时间:
2005-12-31 至 2014-12-31

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中文摘要
翻译
在这项研究的最初两年资助期间,我们在瓦努阿图的亚苏尔火山收集了长达16天的多学科数据集,其中包括地震学和声学数据、红外视频片段以及用于量化喷发动力学的多普勒雷达测量,以及用于估计二氧化硫通量的DOAS测量。在此期间,总共观察到了大约26000次喷发,初步数据处理表明,喷发方式从爆炸性的几乎没有火山灰的喷发转变为非常富含火山灰的羽流,然后又回到几乎没有火山灰的喷发。在这项提议的框架内,我们将使用我们的多学科数据集来探索火山喷发方式变化背后的物理原因。特别是,我们将把处理后的地震和声学数据与雷达数据结合起来,以核实亚苏尔火山的哪个喷口是活跃的,并确定喷口出口以下多深处管道中的岩浆水平。利用雷达数据,我们将确定每次爆炸过程中释放的动能,并由此确定气泡超压或气塞体积,而声波和地震数据将为地震和声波能量释放提供证据。这将使人们对活火山的能量收支有更全面的了解。雷达数据还将允许我们定义不同的喷发类型,然后使用神经网络,我们将对所有记录的事件进行分类。这些不同的处理步骤将有助于改进目前的喷发动力学模型。
英文摘要
During the initial two years funding of this research we collected a 16 days long multidisciplinary data set at Yasur volcano, Vanuatu, that includes seismological and acoustic data, infrared video footage, as well as Doppler radar measurements to quantify eruption dynamics, and DOAS measurements for SO2 flux estimation. During this time a total of about 26000 eruptions were observed and initial data processing indicated a transition in eruption style from explosive nearly ash free eruptions to very ash rich plumes and back to nearly ash free eruptions. In the frame of this proposal we will explore the physics behind this change in eruption style using our multidisciplinary data set. In particular we will combine the processed seismic and acoustic data with the radar data to verify which vent of Yasur volcano was active and determine at what depth below the vent exit the magma level in the conduit is located. Exploiting the radar data we will determine the kinetic energy released during each single explosion and from that determine either bubble overpressure or gas slug volume, while the acoustic and seismic data will give us evidences for the seismic and acoustic energy release. This will lead to a more complete understanding of the energy budget at an active volcano. The radar data will also allow us to define different eruption types and using a neuronal network we will then classify all recorded events. These different processing steps will help to improve current models for eruption dynamics.
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Observing conduit flow processes during Strombolian Eruptions using Transient Electromagnetics (TEM): a numerical and field approach
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