Modeling Fluid and Granular Flow using Mesh-free Particle Method

使用无网格粒子法模拟流体和颗粒流

• 批准号: RGPIN-2022-03432
• 负责人: Jin, YeeChung
• 金额: $ 2.62万
• 依托单位: University of Regina
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2022
• 资助国家: 加拿大
• 起止时间: 2022-01-01 至 2023-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=753115
• 关键词: Modeling; Fluid; Granular; Flow; using

Effective predictions of natural flow dynamics and regimes require an in-depth understanding of computational fluid concepts. To simply transient flow regimes, single phase modeling is often applied to represent the complex flow phenomena. The majority of the natural hazards belong to the mixture of the phases of matter. To address the complexities of fluid flow within the modeling framework, the classical application of fixed spatial grids where the physical properties at fixed locations are considered in the model domain. Although the application of using fixed mesh approach has been historically successful in representing fluid flow, recent studies have highlighted some of the shortcomings with grid-based modeling methods. The drawbacks of these grid-based approaches include inaccuracies due to complex flow boundaries, interfaces, free surfaces, and its difficulty in mass conservation.     The development and application of mesh-free methods has allowed for accurate representation of complex flow regimes and in solving fluid flow problems numerically. One prominent and promising mesh-free method is the Moving Particle Semi-implicit (MPS) method. The MPS method uses a set of arbitrarily distributed particles as opposed to a fixed mesh grid layout to solve governing equations for diverse boundaries and interfaces. Each particle possesses a set of field variables such as mass, concentration and momentum. Although significant improvements have been made to the modeling efforts, fluid incompressibility remains the most time-consuming part of the original MPS approach when many particles are required.     The initial focus of the research is improvement of MPS shallow water model and development of a hybrid model using 2D MPS with incorporation of a 1D shallow water equation. The hybrid MPS will reduce computation time in accurately representing real world engineering applications. The newly developed model will also be expanded to study flow with non-hydrostatic pressure, flow in porous media and in complex granular flow scenarios. The positive outcomes of these investigations can be used to identify the risks from natural disasters. These simulated outcomes can be used as tools to identify potential damage to engineering infrastructure from landslides, debris flow, avalanches, and pyroclastic flows, and in construction and manufacturing industries. The second part of the program is to use quasi-static state of granular materials with the integration of rheology model in the MPS model framework in developing a multiphase model for more complicate engineering cases. Accuracy and stability improvement will be incorporated into the MPS model in engineering application and case studies. The outcome of the program will highlight the varied applications of the MPS method such that it is not only a numerical method but also a useful approach that is complimentary to physical models.

自然流动动力学和流态的有效预测需要对计算流体概念的深入理解，为了简化瞬态流态，通常采用单相建模来表示复杂的流动现象。大多数自然灾害属于混合流。为了解决建模空间框架内流体流动的复杂性，固定网格的经典应用是在模型域中考虑固定位置的物理属性，尽管使用固定网格方法的应用历史上已经取得了成功。代表流体流动，最近的研究强调了一些基于网格的建模方法的缺点这些基于网格的方法的缺点包括由于复杂的流动边界、界面、自由表面以及质量守恒的困难而导致的不准确。移动粒子半隐式 (MPS) 方法是一种突出且有前景的无网格方法，该方法使用一组任意分布的粒子，而不是固定的网格。每个粒子都拥有一组场变量，例如质量、浓度和动量，尽管建模工作已取得重大改进，但流体不可压缩性仍然是原始模型中最耗时的部分。需要许多粒子时的 MPS 方法 ​研究的最初重点是改进 MPS 浅水模型并开发使用 2D MPS 并结合 1D 浅水方程的混合模型，混合 MPS 将准确地减少计算时间。新开发的模型还将扩展到研究非静水压力下的流动、多孔介质中的流动以及复杂颗粒流动场景中的流动，这些研究的积极成果可用于识别自然灾害的风险。这些模拟结果可用作识别山体滑坡、泥石流、雪崩和火山碎屑流对工程基础设施造成的潜在损害的工具，以及在建筑和制造业中的应用。将流变学模型集成到 MPS 模型框架中的颗粒材料，为更复杂的工程案例开发多相模型，其准确性和稳定性的改进将被纳入 MPS 模型的工程应用和案例研究中。 MPS 方法的应用使其不仅是一种数值方法，而且是一种与各种物理模型互补的有用方法。