The average product development cycle spans 3-5 years, involving extensive virtual and physical testing of the machine. Advances in simulation tools have significantly enhanced our ability to identify product solutions early in the design phase. Tools like 1D KULI and Creo Flow Analysis (CFA) offer faster solutions in less time, thereby accelerating the product development cycle.
Cooling systems are crucial components of off-highway tractor machines, directly affecting engine efficiency and overall machine functionality. An optimized cooling system ensures the engine operates within safe temperature ranges, preventing overheating and potential damage. Thus, designing an effective cooling system is a vital aspect of machine engineering.
3D Computational Fluid Dynamics (CFD) simulations are essential for evaluating cooling system performance. These high-fidelity simulations provide detailed insights into fluid flow and heat transfer, enabling engineers to predict and enhance cooling efficiency. However, 3D CFD simulations require significant manual effort for preprocessing and postprocessing, as well as substantial computational resources, making them time-consuming and costly.
Low-fidelity solvers, such as 1D KULI analysis and Creo Flow, offer practical alternatives for analyzing cooling systems in the early design phase. These tools can correlate well with predictions from traditional 3D CFD software, providing accurate results with reduced computational effort. By transitioning from 3D to lite 3D and 1D simulations, engineers can save considerable time and money on preprocessing, postprocessing, and high-performance computing (HPC) costs. This paper focuses on the correlation practices between traditional 3D software and low-fidelity solvers, highlighting various methods that impact the lead time for product development.