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Grain size distribution uncertainty quantification in volcanic ash dispersal and deposition from weak plumes

机译:弱烟羽中火山灰散布和沉积的粒度分布不确定性量化

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摘要

We present the results of uncertainty quantification and sensitivity analysis applied to volcanic ash dispersal from weak plumes with focus on the uncertainties associated to the original grain size distribution of the mixture. The Lagrangian particle model Lagrangian Particles Advection Code is used to simulate the transport of inertial particles under the action of realistic atmospheric conditions. The particle motion equations are derived by expressing the particle acceleration as the sum of forces acting along its trajectory, with the drag force calculated as a function of particle diameter, density, shape, and Reynolds number. Simulations are representative of a weak plume event of Mount Etna (Italy) and aimed at quantifying the effect on the dispersal process of the uncertainty in the mean and standard deviation of a lognormal function describing the initial grain size distribution and in particle sphericity. In order to analyze the sensitivity of particle dispersal to these uncertain variables with a reasonable number of simulations, response surfaces in the parameter space are built by using the generalized polynomial chaos expansion technique. The mean diameter and standard deviation of particle size distribution, and their probability density functions, at various distances from the source, both airborne and on ground, are quantified. Results highlight that uncertainty ranges in these quantities are drastically reduced with distance from source, making them largely dependent just on the location. Moreover, at a given distance from source, the distribution is mostly controlled by particle sphericity, particularly on the ground, whereas in air also mean diameter and sorting play a main role.
机译:我们介绍了不确定性量化和敏感性分析的结果,这些结果适用于弱烟羽散发的火山灰散发,重点是与混合物原始粒度分布相关的不确定性。拉格朗日粒子模型拉格朗日粒子对流代码用于模拟惯性粒子在现实大气条件下的传输。通过将粒子加速度表示为沿其轨迹作用的力之和,并根据颗粒直径,密度,形状和雷诺数来计算阻力,从而得出粒子运动方程。模拟代表了埃特纳火山(意大利)的微弱羽流事件,旨在量化描述初始粒度分布和颗粒球形度的对数正态函数的均值和标准差的不确定性对分散过程的影响。为了通过合理数量的模拟来分析粒子扩散对这些不确定变量的敏感性,使用广义多项式混沌展开技术在参数空间中构建了响应面。量化了从源头到空中和地面的各种距离下的粒径分布的平均直径和标准偏差及其概率密度函数。结果表明,这些数量的不确定性范围会随着距源的距离而大大减少,从而使其很大程度上取决于位置。此外,在距源一定距离的情况下,分布主要受粒子球形度控制,尤其是在地面上,而在空气中,平均直径和分类也起着主要作用。

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