A Python-Based Learning Tool for Hydrodynamic Journal Bearing: From Reynolds Equation to Simulation

Abstract

Journal bearing analysis is fundamental to machine element design, yet the complexity of the Reynolds equation often creates a gap between theory and practical visualization for students. Furthermore, commercial simulation software can limit pedagogical flexibility due to licensing costs and closed-source architectures. To address this, this study presents a Python-based learning tool to simulate and visualize the hydrodynamic behavior of journal bearings. The model solves the steady-state Reynolds equation using a finite difference method to evaluate pressure distribution, load-carrying capacity, attitude angle, friction force, and power loss. Simulation results demonstrate realistic hydrodynamic behavior, yielding a maximum pressure of 7942.03 Pa, a load-carrying capacity of 62.37 N/m, an attitude angle of 87.62°, a friction force of 126 N/m, and a power loss of 1979.27 W/m. By bridging analytical formulation with interactive visualization, this tool provides an accessible, active-learning platform for teaching tribology.