Particle-based methods for flow applications and biochemical networks

用于流动应用和生化网络的基于粒子的方法

• 批准号: RGPIN-2017-04672
• 负责人: Rohlf, Katrin
• 金额: $ 1.02万
• 依托单位: Ryerson University
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2017
• 资助国家: 加拿大
• 起止时间: 2017-01-01 至 2018-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=635168
• 关键词: Particle; based; methods; flow; applications

Particle-based methods are a popular simulation tool that provide a more refined system dynamics with the ability to capture and explore system dynamics that cannot be modeled by differential equations. Recent technological advances have allowed for applications of particle-based methods to a wide array of problems including particle-based flow models and biochemical networks. Recent results in applying particle-based methods to simulate flow through a local constriction have shown the compressible nature of the particle-based method. Care must be taken to control and to minimize this effect when simulating flows for incompressible, or weakly compressible, fluids such as blood. Realistic flow domains for blood flow, such as flow through a constricted artery, or flow through a branched vessel naturally give rise to compressibility effects that need to be quantified and controlled for this particular application. On the other hand, the built-in compressibility is ideal for exploring a range of compressible flow problems including microfluidics. Additionally, incorporation of reactions into the particle-based method allows for the study of reactive or multiphase flow applications, as well as for simulating spatially distributed biochemical networks such as the chemotactic response of an E. coli cell for example.

基于粒子的方法是一种流行的模拟工具，它提供了一种更精细的系统动力学，能够捕获和探索不能用微分方程建模的系统动力学。最近的技术进步使基于粒子的方法能够应用于一系列广泛的问题，包括基于粒子的流动模型和生化网络。应用基于粒子的方法模拟局部收缩流动的最新结果表明，基于粒子的方法具有可压缩的性质。在模拟不可压缩或弱可压缩流体(如血液)的流动时，必须注意控制并将这种影响降至最低。血液流动的真实流动区域，如通过狭窄动脉的流动，或通过分支血管的流动，自然会产生需要量化和控制的可压缩性效应。另一方面，内置的可压缩性是探索包括微流体在内的一系列可压缩流动问题的理想选择。此外，将反应结合到基于颗粒的方法中，允许研究反应或多相流应用，以及模拟空间分布的生化网络，例如大肠杆菌细胞的趋化反应。