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A Quasi-Dimensional Engine Model Using Fractal Geometry

A Quasi-Dimensional Engine Model Using Fractal Geometry
使用分形几何的准维发动机模型
批准号:
8807169
负责人:
Ronald Matthews
金额:
$22.98万
依托单位国家:
美国
项目类别:
Continuing Grant
财政年份:
1988
资助国家:
美国
项目状态:
已结题
起止时间:
1988-08-15 至 1992-01-31

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中文摘要
翻译
分形几何是对粗糙表面几何的一种数学处理,最近已被应用于描述一般的湍流火焰。作者认为,该方法为四冲程均质充气火花点火(SI)活塞式发动机的应用提供了一个模型突破的机制。与以前的准维发动机程序中使用的燃速模型不同,所提出的湍流燃速模型不需要对可调的模拟常数进行实验标定。模型预报对各种模拟参数的敏感性,如分维和大涡的尺度,将被考察。模型预测将与现有的实验数据进行对比测试。基于分形的湍流扩散模型的可获得性将使设计者能够用比目前的模型更简单和更通用的模型来预测燃烧现象。目前对猜测和实验检查的需要将在很大程度上被消除,计算机性能可以专门用于发动机燃烧的其他方面(例如几何方面),目前使用现有的笨重的湍流模型无法管理。
英文摘要
Fractal geometry is a mathematical treatment of the geometry of rough surfaces that has been applied recently to describe a generic turbulent flame. The proposers believe this method may provide a mechanism for a modeling breakthrough for the 4-stroke homogeneous charge spark-ignition (SI) piston engine application. Unlike the burning rate models used in previous quasi-dimensional engine codes, the proposed model for the turbulent burning rate will not require experimental calibration of adjustable modeling constants. The sensitivity of the model predictions to various modeling parameters, such as the fractal dimension and the scale of the large eddies, will be investigated. The model predictions will be tested against available experimental data. The availability of a fractal based turbulent diffusion model would enable designers to predict combustion phenomena with a model both simpler and more generic than the current ones. The current need for guessing and experimental checking would be largely eliminated, and computer performance could be dedicated to other aspects of engine combustion (e.g. geometrical aspects) not currently manageable with the existing unwieldy turbulence models.
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IUCRC Phase II UT Austin Site: Center for Efficient Vehicles and Sustainable Transportation Systems (EVSTS)
  • 批准号:
    2137274
  • 项目类别:
    Continuing Grant
  • 资助金额:
    $50.0万
  • 财政年份:
    2022
  • 负责人:
    Ronald Matthews
  • 依托单位:
Phase I I/UCRC University of Texas at Austin: Center for Efficient Vehicles and Sustainable Transportation Systems (EV-STS)
  • 批准号:
    1650483
  • 项目类别:
    Continuing Grant
  • 资助金额:
    $60.0万
  • 财政年份:
    2017
  • 负责人:
    Ronald Matthews
  • 依托单位:
Research Initiation - Experimental and Theoretical Investigation of Synthetic Polymer Ignition
  • 批准号:
    8019539
  • 项目类别:
    Standard Grant
  • 资助金额:
    $2.5万
  • 财政年份:
    1980
  • 负责人:
    Ronald Matthews
  • 依托单位:
Research Initiation - Experimental and Theoretical Investigation of Synthetic Polymer Ignition
国内基金
海外基金
Scalable Learning and Optimization: High-dimensional Models and Online Decision-Making Strategies for Big Data Analysis