High-Efficiency Computing Technology for Thermohydrodynamic Lubrication Analysis

ABSTRACT

Numerical analysis of thermal hydrodynamic (THD) lubrication is complex and time consuming because of the three-dimensional numerical domain of the solution of the energy equation. To reduce the execution time, many methods for determining solutions for bearing design problems are available; parallel computing technology is crucial for achieving high computational capability and involves using workstations equipped with multicore central processing units and many-core graphics processing units (GPUs). High-performance GPUs have emerged as powerful computing tools for modeling purposes in engineering and science. High-level GPUs depend on thousands of shaders, namely, processor cores. In this study, the traditional successive overrelaxation (SOR) method for solving the Reynolds equation and energy equation was replaced with the two- and three-dimensional red–black SOR methods for parallelizing the governing equations of a GPU system. The results show that a high-level GPU can be used to increase the parallel computing speed in the process of solving THD problems.

KEYWORDS:

• Thermal hydrodynamic lubrication
• three-dimensional red–black successive overrelaxation (RBSOR)
• graphics processing unit (GPU)
• compute unified device architecture (CUDA)