Collaborative Research: ABR: Multiscale Dynamics in Explosive Volcanic Eruptions

合作研究：ABR：火山喷发的多尺度动力学

• 批准号: 1144198
• 负责人: Michael Manga
• 金额: $ 18万
• 依托单位: University of California-Berkeley
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2012
• 资助国家: 美国
• 起止时间: 2012-07-01 至 2016-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1144198&HistoricalAwards=false
• 关键词: Collaborative; Research; ABR; Multiscale; Dynamics

Explosive volcanic eruptions are some of the most energetic granular flows on the planet, the largest of which can have global impact. Even the more common, smaller, events encompass scales of several kilometers. However, mass and energy transfer in these flows are fundamentally controlled by processes at much smaller spatial and temporal scales, where individual particles interact with each other, with gas, or with the surface over which the flows travel. Our past work on steam explosions, ash production, and heat transfer have shown that subgrid models developed from experiments can be coupled to large-scale numerical simulations. More importantly, these subgrid relations are critical for predicting the dynamics reflected in volcanic deposits and in ash dispersal patterns; models that neglect subgrid processes can fail to produce the energy transfer manifest in volcanic deposits by several orders of magnitude. Our ability to predict large-scale behavior of volcanic flows can ultimately be limited by our understanding of very small-scale, or microphysical, processes. In this study, the investigators will examine a suite of particle-scale mass and energy transfer mechanisms in the laboratory with the aim of understanding the physics of these processes and to incorporate them into large-scale simulations of explosive volcanic eruptions. This project will support an ongoing effort in predictive computational volcanology. Specifically they team will focus on 1) heat transfer between particles and gas at high Reynolds numbers and using clast cooling proxies to examine entrainment in pyroclastic density currents, 2) particle deposition and resuspension, including the role of particle impacts in generating depositional features, 3) large-scale experiments of gas-particle density driven flows, and 4) and the production of fine ash particles in the conduit and in pyroclastic density currents. All these processes contribute to production and dispersal of ash and larger pyroclasts to the immediate environment of the volcanic edifice and also to the wider dispersal of ash in the atmosphere. Understanding the physics of these processes is crucial in determining the potential aviation, climactic, and local hazards of eruptions. All of the proposed experiments will be conducted with materials and at conditions similar to those in natural flows, minimizing the potential difficulties with scaling to large-scale multiphase flows. In the methodology proposed, the numerical models are integrally connected to the experimental data. The strength of numerical models is the ability to solve non-linear, complexly coupled equations and determine emergent behavior, and the strength of the experiments is to understand in detail the physical processes operating at small scales.

火山爆发是地球上最具活力的颗粒流之一，其中最大的一次可以产生全球影响。即使是更常见、更小的事件，规模也有几公里。然而，这些流动中的质量和能量传递基本上是由小得多的空间和时间尺度上的过程控制的，在这些过程中，单个粒子彼此相互作用，与气体相互作用，或者与流动所经过的表面相互作用。我们过去在蒸汽爆炸、灰烬产生和传热方面的工作表明，从实验中开发的亚网格模型可以与大规模数值模拟相结合。更重要的是，这些次网格的关系是至关重要的预测反映在火山沉积物和火山灰扩散模式的动态，忽略次网格过程的模型可能无法产生几个数量级的火山沉积物中的能量转移表现。我们预测火山流大规模行为的能力最终会受到我们对非常小规模或微物理过程的理解的限制。在这项研究中，研究人员将在实验室中研究一套粒子尺度的质量和能量转移机制，目的是了解这些过程的物理学，并将其纳入爆炸性火山爆发的大规模模拟中。该项目将支持预测计算火山学的持续努力。具体来说，他们的团队将专注于1）在高雷诺数下颗粒和气体之间的热传递，并使用碎屑冷却代理来检查火山碎屑密度流中的夹带，2）颗粒沉积和再悬浮，包括颗粒撞击在生成沉积特征中的作用，3）气体颗粒密度驱动流的大规模实验，和4）以及在管道和火山碎屑密度流中产生细灰颗粒。所有这些过程都有助于火山灰和较大的火山碎屑的产生和散布到火山建筑物的直接环境中，也有助于火山灰在大气中更广泛的散布。了解这些过程的物理特性对于确定火山爆发的潜在航空、气候和局部危害至关重要。 所有拟议的实验都将使用与自然流动相似的材料和条件进行，最大限度地减少了缩放到大规模多相流的潜在困难。在所提出的方法中，数值模型是完整地连接到实验数据。数值模型的优势在于能够求解非线性、复杂耦合的方程并确定涌现行为，而实验的优势在于能够详细了解小尺度下的物理过程。