Data-driven mathematical modelling of particle dynamics in opaque fluid flows

不透明流体流动中粒子动力学的数据驱动数学建模

• 批准号: 2445117
• 金额: --
• 依托单位: University of Edinburgh
• 依托单位国家: 英国
• 项目类别: Studentship
• 财政年份: 2020
• 资助国家: 英国
• 起止时间: 2020 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=studentship-2445117
• 关键词: Data; driven; mathematical; modelling; particle

Examining the dispersion of both particles advected by weakly compressible flow, using an either approximation that reduces inertial-particle dynamics to passive advection by a weakly compressible flow or with non-inertial particles in weakly compressible ocean surface flow. The principal aim is characterisation of the clustering of particles from Lagrangian statistics of the flow, using importance sampling methods to allow efficient computation that would otherwise be intractable.

使用将惯性粒子动力学简化为弱可压缩流的被动平流或弱可压缩海洋表面流中的非惯性粒子的近似，检查弱可压缩流中两种粒子的弥散。主要目的是从拉格朗日流统计中描述粒子的聚类，使用重要采样方法来进行有效的计算，否则将是难以处理的。