Grant: Discovery Grants Program - Individual

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.