Abstract

This research delves into the intricate flow dynamics within a gas pipeline, leveraging the small perturbation equations to elucidate the flow scenario. Utilizing the Python programming language, the study derives the numerical solutions for the governing equations of the pipeline's flow field. This is achieved through the successive over-relaxation (SOR) iterative method in tandem with the Neumann boundary conditions. The flow dynamics are subsequently visualized and analyzed using streamlined diagrams and Mach number cloud representations, facilitating the identification of stress concentration points on the pipeline's inner wall. Such insights significantly affect the pipeline's optimal design and strategic reinforcement. Beyond its immediate application, the methodology presented herein offers a robust framework for addressing diverse fluid mechanics simulation challenges. Its versatility extends to realms such as automotive contour design, pipeline leakage simulations, and engine compressor configurations. When confronted with the need to dissect fluid flow and stress dynamics, professionals can harness the Python-based SOR iteration code to derive governing fluid equations, enabling a graphical interpretation through streamlined and Mach number cloud diagrams. This study, thus, underscores a pivotal toolset for fluid mechanics challenges across various engineering domains.

Full Text
Published version (Free)

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call