SCREMS: Visualization of Complex Spatio-Temporal Multiscale Fluid Dynamic Phenomena

近年来，亚利桑那州立大学的流体动力学社区一直在开发用于流体动力学模拟的强大而有效的数值代码，这些代码涵盖了与不稳定性和过渡到湍流有关的基本基本问题，以及在几何简单的几何形状中对这种过渡的控制，到微观的大规模海洋和大气流动模拟，中期和全球范围，并制定战略，使不同层次相互联系。 亚利桑那州立大学已作出了严重的承诺，高性能计算与建立高性能计算计划（HPCI）。虽然我们的计算服务器的需求目前正在满足ASU HPCI设施，一个严重的瓶颈，我们充分利用这一资源是我们缺乏的设施，以交互方式可视化和分析的大型数据集，从我们的湍流模拟结果。 这将通过获取交互式可视化集群来解决。将大型复杂时空数据集的交互式图形询问和分析集成到高性能计算范式中，将导致湍流研究方式的转变。可视化集群将使我们能够以非常容易的方式增强流场的传统统计力学分析，这些分析依赖于涉及空间和时间平均值的措施，直接分析湍流相干结构如何演变和相互作用。这种四维数据集（三维空间加时间）的分析，不仅速度和温度场，而且涡度和其他相关的流量，如螺旋度，目前只能从大规模的直接数值模拟。4D模拟数据的可视化查询和分析将在改变我们对复杂时空流的理解方面发挥关键作用。由具有数十年跨学科研究经验的导师对研究生进行跨学科培训是本提案的核心目标。我们的REU参与将继续由CSUMS（计算科学培训本科生在数学科学）计划在亚利桑那州立大学，在本提案中描述的各个项目的方面将被隔离到适合本科生的项目。对于更广泛的社区，我们提出的可视化集群以及我们将如何利用它将提供一个交互式图形可视化和大型时空数据集分析的范例模型。

In recent years, the fluid dynamics community at ASU has been developing robust and efficient numerical codes for fluid dynamics simulations that span from basic fundamental problems concerned with instabilities and transitions to turbulence, and the control of such transitions, in geometrically simple geometries, to large scale oceanographic and atmospheric flow simulations at the micro, meso and global scales and developing strategies to intermesh the different levels. ASU has made a serious commitment to high performance computing with the establishment of the High Performance Computing Initiative (HPCI). While our compute-server needs are presently being met by the ASU HPCI facility, a serious bottleneck to our taking full advantage of this resource is our lack of facilities to interactively visualize and analyze the large data sets that result from our turbulent flow simulations. This is to be addressed with the acquisition of an interactive visualization cluster. The integration of interactive graphical interrogation and analysis of large complex spatio-temporal data sets into the high-performance computing paradigm will lead to a transformation in the way turbulent flows are studied. The visualization cluster will allow us, in a very accessible fashion, to augment the traditional statistical mechanics analyses of the flow fields, which rely on measures involving spatial and temporal averages, with direct analysis of how turbulent coherent structures evolve and interact. The analysis of such 4D data sets (3D spatial plus time) of not only velocity and temperature fields, but also vorticity and other relevant flow quantities such as helicity, is presently only available from large-scale direct numerical simulations. The visual interrogation and analysis of 4D simulation data will play a critical role in transforming our understanding of complex spatio-temporal flows.The interdisciplinary training of graduate students by mentors who have decades of interdisciplinary research experience between them is a core objective of this proposal. Our REU involvement will be continued by the CSUMS (Computational Science Training for Undergraduates in the Mathematical Sciences) program at ASU, where aspects of the various individual projects described in this proposal will be isolated into projects suitable for undergraduates. For the broader community, our proposed visualization cluster and how we will be utilizing it will provide a paradigm model for interactive graphical visualization and analysis of large spatio-temporal data sets.