CDS&E: Collaborative Research: Fast Numerical Simulations of Low Void Fraction Disperse Multiphase Systems using Event-Triggered Communication

分散流涉及多相流体，其中一相由悬浮在另一连续相中的颗粒（包括气泡和液滴）组成。 在工程和自然环境中，许多有实际意义的问题都会遇到弥散流。 直接数值模拟（DNS）已被证明是不可或缺的理解这样的流动。 然而，对于具有更集中颗粒（即低空隙率）的流动，模拟颗粒之间的相互作用在计算上变得昂贵。即使是最先进的模拟也需要很长时间才能变得司空见惯。本项目将根据控制理论的思想开发新的计算方法，以加速此类模拟，并使用它们对低空隙率的分散多相系统进行深入研究。该项目的主要智力价值在于使用计算算法，减少多个处理元件之间的通信，以进行大规模的非均相多相系统模拟-特别是低空隙率分散系统，其中包含许多颗粒需要大的计算域和长的计算时间来收集收敛的统计量。这样的平均数据是至关重要的，用于工业预测的降阶模型的建设。该项目将有助于更好地理解在能源转换，材料加工，化学工业，大气过程和生命系统中至关重要的多相流和系统，并开发基于处理器之间事件触发通信的新型计算策略，以提高并行计算的效率。此外，人们将在其开发和使用方面受到教育，并将开发旨在降低新研究人员进入门槛的教育材料。该奖项反映了NSF的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

Disperse flows involve multiphase fluids where one phase consists of particles, including bubbles and drops, suspended in another contiguous phase. Disperse flows arise in many problems of practical interest in engineering and the natural environment. Direct numerical simulations (DNS) have proven to be indispensable in understanding such flows. However, for flows with more concentrated particles (i.e. low void fractions), it becomes computationally expensive to simulate interactions between particles. Even state-of-the-art simulations take much too long for them to become commonplace. This project will develop new computational methods, based on ideas from control theory, to speed up such simulations and use them to conduct an in-depth study of disperse multiphase systems with low void fractions. The primary intellectual merit of the project lies in using computation algorithms that reduce communication among multiple processing elements for conducting large-scale simulations of heterogeneous multiphase systems - in particular, low void fraction disperse systems where the inclusion of many particles requires large computational domains and long computational times to collect converged statistical quantities. Such averaged data is critical for the construction of reduced order models used for industrial predictions. This project will aid in better understanding of multiphase flows and systems that are critical in energy conversion, material processing, the chemical industry, atmospheric processes, and living systems, as well as develop novel computational strategies based on event-triggered communications between processors to improve the efficiency of parallel computations. Further, people will be educated in both their development and use, and educational material aimed at lowering the barrier to entry for new researchers will be developed.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.