EAGER: Extended Particles in Turbulent Flow: A Grand Computational Challenge

1258398 PI：Prosperetti该项目致力于开发一种灵活而准确的数值方法，名为Physalis，用于模拟颗粒流。迄今为止的工作表明，这种方法比目前使用的其他方法，如格子Boltzmann方法和浸入边界方法，具有显着的优点，因为该方法允许精确满足每个粒子的无滑移条件，并且每个粒子都表示在谱收敛中。 时尚. 这允许模拟涉及1000个颗粒，对于颗粒雷诺数高达约100具有足够高的精度。这里提出的工作的目标是将现有的代码移植到基于GPU的计算机上，目标是实现至少两个数量级的速度提升。 该项目将探索新的方法来并行化的代码和内存管理，以实现这种速度。自然过程和当代技术提供了大量固体颗粒通过流体流动运输的实例：海洋沉积物、重力流、流化床燃烧器、催化油裂解和化学循环燃烧器只是许多实例中的几个。这些系统的可靠的理论理解是必不可少的各种原因，从建模的环境流量碳封存，以开发新的或按比例放大的设计，而无需昂贵的初步实验和许多其他。复杂的数值方法和国家的最先进的计算硬件将在这个项目中采用将有助于推进颗粒系统的理解。

1258398PI: ProsperettiThis project is concerned with the development of a flexible and accurate numerical method, named Physalis, for the simulation of particulate flows. The work to date has shown that this method has significant advantages over the other methods used at present such as the lattice-Boltzmann method and the immersed-boundary methods in that the method permits the exact satisfaction of the no-slip condition on each particle and that each particle is represented in a spectrally convergent fashion. This permits simulations involving 1000 particles with sufficiently high accuracy for particle Reynolds numbers up to about 100. The objective of the work proposed here is to port the existing code to GPU-based computers with the goal of attaining speed up of at least two orders of magnitude. The project will explore novel approaches to the parallelization of the code and memory management to achieve this speed up. The code thus developed will be made available to the research community through the PIs web.Natural processes and contemporary technology offer a wealth of instances in which solid particles are transported by fluid flows: marine sediments, gravity currents, fluidized bed combustors, catalytic oil cracking and chemical looping combustors are just a few examples among many. A reliable theoretical understanding of these systems is essential for a variety of reasons ranging from the modeling of environmental flows to carbon sequestration, to the development of new or scaled-up designs without expensive preliminary experimentation and many others. Sophisticated numerical methods and state-of-the-art computational hardware to be employed in this project will be useful in advancing the understanding of particulate systems.