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.

火山喷发是地球上最具能量的颗粒流之一，其中最大的颗粒流可能会产生全球影响。即使是更常见、规模较小的事件也涵盖了数公里的规模。然而，这些流中的质量和能量传递从根本上是由更小的空间和时间尺度的过程控制的，其中单个粒子彼此相互作用、与气体或与流行进的表面相互作用。我们过去在蒸汽爆炸、灰烬产生和传热方面的工作表明，通过实验开发的子网格模型可以与大规模数值模拟相结合。更重要的是，这些子网格关系对于预测火山沉积物和火山灰扩散模式所反映的动态至关重要；忽略次网格过程的模型可能无法产生火山沉积物中几个数量级的能量转移。我们预测火山流大规模行为的能力最终可能会受到我们对非常小规模或微观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检查一套粒子尺度的质量和能量传递机制，目的是了解这些过程的物理原理，并将它们纳入火山喷发的大规模模拟中。该项目将支持预测计算火山学方面的持续努力。具体来说，他们的团队将重点关注 1) 高雷诺数下颗粒和气体之间的传热，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，以及 4) 以及管道和火山碎屑中细灰颗粒的产生 密度电流。所有这些过程都有助于产生火山灰和较大的火山碎屑并将其散布到火山建筑物的直接环境中，并促使火山灰在大气中更广泛地扩散。了解这些过程的物理原理对于确定火山喷发的潜在航空、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相似的材料和条件进行，从而最大限度地减少大规模多相流规模化的潜在困难。在所提出的方法中，数值模型与实验数据紧密相连。数值模型的优势在于能够求解非线性、复杂耦合方程并确定突发行为，而实验的优势在于详细了解小尺度下运行的物理过程。