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

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:
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
项目状态:
未结题
起止时间:
2022-07-01 至 2025-06-30

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中文摘要
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英文摘要
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.
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CAREER: Advancing Knowledge of Atomization: Numerical Methods, Physics Extraction, and Reduced-Order Models
  • 批准号:
    1749779
  • 项目类别:
    Standard Grant
  • 资助金额:
    $50.0万
  • 财政年份:
    2018
  • 负责人:
    Mark Owkes
  • 依托单位:
UNS: multiphase-UQ: Uncertainty Quantification Framework for Multiphase Flow Simulations
  • 批准号:
    1511325
  • 项目类别:
    Standard Grant
  • 资助金额:
    $27.64万
  • 财政年份:
    2015
  • 负责人:
    Mark Owkes
  • 依托单位:
海外基金