arXiv subjects

Hyung-Jun Park

Publications and source records attributed to Hyung-Jun Park.

4 recordsLinked to original sources

arXiv2025

Graph-Based Learning of Free Surface Dynamics in Generalized Newtonian Fluids using Smoothed Particle Hydrodynamics

In this study, we propose a graph neural network (GNN) model for efficiently predicting the flow behavior of non-Newtonian fluids with free surface dynamics. The numerical analysis of non-Newtonian fluids presents significant challenges, as traditional algorithms designed for Newtonian fluids with constant viscosity often struggle to converge when applied to non-Newtonian cases, where rheological properties vary dynamically with flow conditions. Among these, power-law fluids exhibit viscosity that decreases exponentially as the shear rate increases, making numerical simulations particularly difficult. The complexity further escalates in free surface flow scenarios, where computational challenges intensify. In such cases, particle-based methods like smoothed particle hydrodynamics (SPH) provide advantages over traditional grid-based techniques, such as the finite element method (FEM). Building on this approach, we introduce a novel GNN-based numerical model to enhance the computational efficiency of non-Newtonian power-law fluid flow simulations. Our model is trained on SPH simulation data, learning the effects of particle accelerations in the presence of SPH interactions based on the fluid's power-law parameters. The GNN significantly accelerates computations while maintaining reliable accuracy in benchmark tests, including dam-break and droplet impact simulations. The results underscore the potential of GNN-based simulation frameworks for efficiently modeling non-Newtonian fluid behavior, paving the way for future advancements in data-driven fluid simulations.

physics.flu-dyn↗

arXiv2025

Comparative Analysis of Granular Material Flow: Discrete Element Method and Smoothed Particle Hydrodynamics Approaches

We compare two widely used Lagrangian approaches for modeling granular materials: the Discrete Element Method (DEM) and Smoothed Particle Hydrodynamics (SPH). DEM models individual particle interactions, while SPH treats granular materials as a continuum using constitutive rheological models. In particular, we employ the Drucker Prager viscoplastic model for SPH. By examining key parameters unique to each method, such as the coefficient of restitution in DEM and the dilatancy angle in SPH, we assess their influence on two dimensional soil collapse predictions against experimental results. While DEM requires computationally expensive parameter calibration, SPH benefits from a continuum scale rheological model, allowing most parameters to be directly determined from laboratory measurements and requiring significantly fewer particles. However, despite its computational efficiency, viscoplastic SPH struggles to capture complex granular flow behaviors observed in DEM, particularly in rotating drum simulations. In contrast, DEM offers greater versatility, accommodating a broader range of flow patterns while maintaining a relatively simple model formulation. These findings provide valuable insights into the strengths and limitations of each method, aiding the selection of appropriate modeling techniques for granular flow simulations.

cond-mat.soft↗

arXiv2024

Fast Marching based Rendezvous Path Planning for a Team of Heterogeneous Vehicle

This paper presents a formulation for deterministically calculating optimized paths for a multiagent system consisting of heterogeneous vehicles. The key idea is the calculation of the shortest time for each agent to reach every grid point from its known initial position. Such arrival time map is efficiently computed using the Fast Marching Method (FMM), a computational algorithm originally designed for solving boundary value problems of the Eikonal equation. By leveraging the FMM, we demonstrate that the minimal time rendezvous point and paths for all member vehicles can be uniquely determined with minimal computational overhead. The scalability and adaptability of the present method during online execution are investigated, followed by a comparison with a baseline method that highlights the effectiveness of the proposed approach. Then, the potential of the present method is showcased through a virtual rendezvous scenario involving the coordination of a ship, an underwater vehicle, an aerial vehicle, and a ground vehicle, all converging at the optimal location within the Tampa Bay area in minimal time. The results show that the developed framework can efficiently construct continuous paths of heterogeneous vehicles by accommodating operational constraints via an FMM algorithm

cs.MA↗

arXiv2023

Segment-Based Wall Treatment Model for Heat Transfer Rate in Smoothed Particle Hydrodynamics

In this study, a smoothed particle hydrodynamics (SPH) model that applies a segment-based boundary treatment is used to simulate natural convection. In a natural convection simulated using an SPH model, the wall boundary treatment is a major issue because accurate heat transfer from boundaries should be calculated. The boundary particle method, which models the boundary by placing multiple layers of particles on and behind the wall boundary, is the most widely used boundary treatment method. Although this method can impose accurate boundary conditions, boundary modeling for complex shapes is challenging and requires excessive computational costs depending on the boundary shape. In this study, we utilize a segment-based boundary treatment method to model the wall boundary and apply this method to the energy conservation equation for the wall heat transfer model. The proposed method solves the problems arising from the use of boundary particles and simultaneously provides accurate heat transfer calculation results for the wall. In various numerical examples, the proposed method is verified through a comparison with available experimental results, SPH results using the boundary particle method, and finite volume method (FVM) results.

physics.flu-dyn↗