Comprehensive Eulerian models for electrostatic phenomena in polydisperse gas-particle flows

多分散气体颗粒流中静电现象的综合欧拉模型

• 批准号: 2246481
• 负责人: Alberto Passalacqua
• 金额: $ 41万
• 依托单位: Iowa State University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-07-01 至 2026-06-30
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2246481&HistoricalAwards=false
• 关键词: Comprehensive; Eulerian; models; electrostatic; phenomena

Solid particles in motion in a gas form a gas-particle flow, often encountered in the food, pharmaceutical, and chemical industries. In this flow type, particles repeatedly collide with other particles or walls and become electrically charged. Such charged particles can accumulate in parts of the systems used to produce and process them, degrading performance or preventing correct operations. They can also cause sparks, leading to explosions, such as those that happen when emptying corn silos, with serious safety implications for workers and infrastructure. This award will develop computer models to better predict when electric charge accumulates on solid particles and how it affects the behavior of gas-particle flows. These predictions will allow hazardous conditions or situations adverse to the process under consideration to be mitigated at the design stage, potentially reducing design costs, and improving system performance and safety. Graduate and undergraduate students will be trained as part of the award, contributing to education and workforce development. In addition to disseminating the results through scientific publications and conferences, a short course targeting the relevant industry sectors will be organized to facilitate knowledge transfer.A comprehensive Eulerian multiphase model for electrostatic charging in granular and gas-particle flows will be formulated. Kinetic theory closures for the hydrodynamic properties and electrostatic charging will be derived, accounting for finite contact time, consistently with the constitutive contact charge model. The experimentally observed normal distribution of charge saturation, currently assumed constant in most computational models, and the dependency of charge saturation on the local temperature and pressure value will be incorporated into the model. Wall boundary conditions accounting for the effect of electric force will be proposed to enable the correct description of charged particles at solid surfaces. Multiphase RANS closures will be formulated to account for the effect of turbulence on particle charging, enabling the application of the newly formulated model to regimes with higher gas flow rates and turbulent behavior, such as those encountered in fluidized bed risers and pneumatic conveying. Validation against experiments and direct numerical simulations from the literature will be performed to establish and demonstrate the predictive capabilities of the newly developed model.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.

在气体中运动的固体颗粒形成气粒流，经常在食品、制药和化学工业中遇到。在这种流动类型中，颗粒反复与其他颗粒或壁碰撞并带电。这些带电粒子可能会积聚在用于生产和处理它们的系统的部件中，降低性能或阻止正确操作。它们还可能引起火花，导致爆炸，例如在清空玉米筒仓时发生的爆炸，对工人和基础设施造成严重的安全影响。该奖项将开发计算机模型，以更好地预测电荷何时在固体颗粒上积累以及它如何影响气体颗粒流动的行为。这些预测将允许在设计阶段减轻对所考虑的过程不利的危险条件或情况，从而可能降低设计成本，并提高系统性能和安全性。研究生和本科生将作为该奖项的一部分接受培训，为教育和劳动力发展做出贡献。除了通过科学出版物和会议传播成果外，还将组织针对相关行业的短期课程，以促进知识转移。将制定颗粒和气体-颗粒流中静电荷的综合欧拉多相模型。动力学理论封闭的流体动力学特性和静电荷将推导出，占有限的接触时间，一致的本构接触电荷模型。实验观察到的电荷饱和度的正态分布，目前假设在大多数计算模型中是恒定的，以及电荷饱和度对局部温度和压力值的依赖性将被纳入模型中。壁边界条件占电力的影响将被提出，使正确的描述带电粒子在固体表面。将制定多相RANS封闭，以考虑湍流对颗粒荷电的影响，使新制定的模型应用于具有较高气体流速和湍流行为的制度，如流化床流化床和气力输送中遇到的情况。验证实验和直接数值模拟从文献中将进行建立和证明的预测能力的新开发的model.This奖项反映了NSF的法定使命，并已被认为是值得通过使用基金会的智力价值和更广泛的影响审查标准进行评估的支持。