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: 2018
• 资助国家: 加拿大
• 起止时间: 2018-01-01 至 2019-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=663603
• 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.******The following novel work will be carried out in this research program: Development of numerical and analytical techniques to quantify compressibility and slip in complex flow geometries; development of numerical techniques for multiparticle collision dynamics (MPCD) flow through domains with porous walls; development of reactive MPCD simulations of reactive or multiphase flow and biochemical networks; development of analytical and numerical techniques for compressible flow problems.******Compressibility effects have recently been observed when using particle-based methods to simulate flow through a local constriction, as well as non-equilibrium effects. Making use of the built-in compressibility in MPCD flow, a number of numerical and theoretical investigations will be carried out in order to quantify and control the compressibility if desired. The research program will lead to important contributions in: flows of chemically reactive media for which low concentration chemical species exist, compressible flows, improved numerical/theoretical estimates for viscosity expressions in MPCD flow in non-equilibrium conditions, MPCD flow through complex flow domains with applications to blood flow and microfluidics, and numerical simulations of biologically relevant biochemical networks. The HQP trained under this program will obtain highly desirable mathematical modeling skills, programming experience, dissemination experience, and refereed journal publications, which are highly desirable skills/milestones for industry and academia alike.**

基于粒子的方法是一种流行的仿真工具，它提供了一个更精确的系统动力学，能够捕获和探索不能用微分方程建模的系统动力学。 最近的技术进步允许基于粒子的方法应用到广泛的问题，包括基于粒子的流动模型和生物化学网络。 最近的结果表明，在应用粒子为基础的方法来模拟通过局部收缩流动的粒子为基础的方法的可压缩性。在模拟不可压缩或弱可压缩流体（如血液）的流动时，必须小心控制并尽量减少这种影响。 血流的真实流域，例如通过收缩的动脉的流动，或通过分支血管的流动，自然会产生压缩性效应，对于这种特定的应用，需要对其进行量化和控制。 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，将反应并入基于颗粒的方法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，例如大肠杆菌的趋化反应。例如大肠杆菌细胞。本研究计划将开展以下新的工作：发展数值和分析技术，以量化复杂流动几何形状中的压缩性和滑移;发展多粒子碰撞动力学（MPCD）流经多孔壁域的数值技术;发展反应或多相流和生物化学网络的反应MPCD模拟;发展可压缩流动问题的分析和数值技术。**最近，当使用基于粒子的方法来模拟通过局部收缩的流动时，已经观察到可压缩性效应以及非平衡效应。利用MPCD流动中固有的可压缩性，将进行一些数值和理论研究，以量化和控制的可压缩性，如果需要的话。该研究计划将导致重要的贡献：化学反应介质的流动，其中低浓度的化学物种存在，可压缩流，改进的数值/理论估计的粘度表达式在MPCD流在非平衡条件下，MPCD流通过复杂的流动领域与应用程序的血液流动和微流体，和生物相关的生化网络的数值模拟。根据本计划培训的HQP将获得非常理想的数学建模技能，编程经验，传播经验和参考期刊出版物，这些都是行业和学术界非常理想的技能/里程碑。