SBIR PHASE I: A New Approach to Particle Characterization - The Probability Density Function Propagation (PDFP) Model

SBIR 阶段 I：粒子表征的新方法 - 概率密度函数传播 (PDFP) 模型

• 批准号: 0060298
• 负责人: David Black
• 金额: $ 10万
• 依托单位: CFD RESEARCH CORPORATION
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2001
• 资助国家: 美国
• 起止时间: 2001-01-01 至 2001-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0060298&HistoricalAwards=false
• 关键词: SBIR; PHASE; New; Approach; Particle

This Small Business Innovation Research (SBIR) Phase I project will develop an innovative particle transport and dispersion model called the Probability Density Function Propagation (PDFP) models, and implements the model into a commercial code. The PDFP model tracks the Probability Density Function (PDF) of particle position as a function of space and time. Only one trajectory for each class of particle size or type needs to be calculated, as compared to the 2000 to 6000 trajectories needed in current state-of-the-art particulate models. This makes the PDFP model very computationally efficient, which is important for simulations with large numbers of particles where the particle calculations take a significant percentage of the CPU time. From the particle PDF's calculated in the model, the properties of the dispersed phase (solid or liquid) can be calculated anywhere in the model, providing a complete statistical representation of the particle behavior. The combination of computational speed and capability to completely describe the particles (solid or liquid) will make the PDFP model a valuable tool for engineers analyzing two-phase flows. In Phase I, the feasibility of the model will be demonstrated by comparing predictions with published data.The Probability Density Function Propagation (PDFP) model will be developed and implemented in a commercial code. The capability will be implemented in an existing commercial code and will provide the capability to easily simulate two-phase flows that are difficult or very time consuming using current state-of-the-art particle models. Examples of applications where the PDFP model can be used include characterizing nonreacting sprays for ignition calculations, atmospheric dispersion, pneumatic transport, spray cooling, and any other application where large number of particles must be modeled.

这个小企业创新研究（SBIR）第一阶段项目将开发一个创新的粒子传输和扩散模型，称为概率密度函数传播（PDFP）模型，并将该模型实现为商业代码。PDFP模型跟踪粒子位置的概率密度函数（PDF）作为空间和时间的函数。与目前最先进的颗粒模型所需的2000至6000个轨迹相比，每类颗粒大小或类型只需计算一个轨迹。这使得PDFP模型的计算效率非常高，这对于具有大量粒子的模拟非常重要，其中粒子计算占用了CPU时间的很大比例。根据模型中计算的颗粒PDF，可以在模型中的任何位置计算分散相（固体或液体）的性质，从而提供颗粒行为的完整统计表示。计算速度和完全描述颗粒（固体或液体）的能力的结合将使PDFP模型成为工程师分析两相流的有价值的工具。在第一阶段，我们会将预测结果与已发表的数据作比较，以证明模式的可行性。我们会发展概率密度函数传播模式，并以商用程式实施。该能力将在现有的商业代码中实现，并将提供使用当前最先进的粒子模型轻松模拟两相流的能力。可以使用PDFP模型的应用示例包括表征用于点火计算的非反应喷雾、大气扩散、气动输送、喷雾冷却以及必须对大量颗粒进行建模的任何其他应用。