CDS&E: Extracting Physics from High-Fidelity Simulations of Atomization using Geometric and Topological Data Analysis

CDS

• 批准号: 2152737
• 负责人: Mark Owkes
• 金额: $ 37.53万
• 依托单位: Montana State University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-07-01 至 2025-06-30
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2152737&HistoricalAwards=false
• 关键词: CDS&E; Extracting; Physics; Fidelity; Simulations

Many applications simulate atomizing sprays that are found in engines, fire sprinklers, spray painting systems, and manufacturing processes. These simulations produce massive datasets that fully describe the spray. However, the design of these systems is hindered by the lack of knowledge and physics-based models of the atomization process. This work will combine geometric and topological data analysis with these rich simulations results to create new knowledge on how the liquid in a spray breaks up and ultimately lead to improved atomization models. The project includes the development of a teaching module that will bring geometric technics into undergraduate and graduate numerical methods courses which will expose future engineers to ideas from different disciplines. The goal of the project is to leverage advances in geometric and topological data analysis combined with high-fidelity simulation results to quantify how atomization occurs. The first objective will add extraction algorithms into an advance computational fluid dynamics code to produce a database of atomization events including the shape of and flow field around liquid structures. The second objective will extend geometric and topological descriptors to quantify the shapes of liquid structures and local flow fields. The descriptors will provide a way to index and search for quantitatively similar breakup events within the precomputed database from the high-fidelity simulations. The third objective will develop physics­based, reduced­order models using new knowledge on the process of atomization. At a high level, the work couples geometric and topological analysis with high­fidelity simulation results to provide a new perspective on a process. With this view, the work will allow for advances in a wide range of fields that involve the evolution of objects with changing shape.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.

许多应用程序模拟在发动机、消防喷头、喷漆系统和制造过程中发现的雾化喷雾。这些模拟产生了大量的数据集，完全描述了喷雾。然而，由于缺乏雾化过程的知识和基于物理的模型，这些系统的设计受到阻碍。这项工作将几何和拓扑数据分析与这些丰富的模拟结果相结合，以创造关于喷雾中液体如何分解的新知识，并最终导致改进的雾化模型。该项目包括开发一个教学模块，将几何技术引入本科生和研究生的数值方法课程，使未来的工程师接触到不同学科的想法。该项目的目标是利用几何和拓扑数据分析方面的进步，结合高保真模拟结果来量化雾化是如何发生的。第一个目标是将提取算法添加到高级计算流体动力学代码中，以产生一个雾化事件数据库，包括液体结构的形状和周围的流场。第二个目标将扩展几何和拓扑描述符，以量化液体结构和局部流场的形状。描述符将提供一种从高保真模拟中索引和搜索预计算数据库内定量相似的分手事件的方法。第三个目标将利用雾化过程的新知识开发基于物理的降阶模型。在高层次上，这项工作将几何和拓扑分析与高保真模拟结果结合在一起，为工艺提供了一个新的视角。根据这一观点，这项工作将允许在涉及不断变化的形状的物体的演变的广泛领域取得进展。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。