In the realm of automotive safety engineering, the demand for efficient and accurate crash simulations is ever-increasing. As finite element (FE) modeling of components becomes increasingly detailed and the availability of advanced material models improves, crash simulations for full vehicles can become time-consuming. Evaluating the crash performance of any vehicle subsystem requires structural simulations at different levels. While the design and configuration phase deals with a local simulation in representative load cases, full vehicle simulations are required later for a final digital proof of achieved requirements and development targets. This paper introduces a novel methodology for replacing full vehicle crash simulations, as required for a local view on the structural load path development, through segment-models. By adapting segment-model simulations, a significant reduction in computational time and resource usage is achieved, thereby optimizing CPU cluster performance and minimizing the effort invested in time and model handling. A closer look at these kinds of representative models can even consider a higher resolution in local regions, necessary to capture the structural behavior through a crash load case much more accurately. The proposed method has been successfully implemented across various scenarios, including full-frontal crash load cases with 100 percent overlap, 40 percent overlap, small overlap crash load cases, side impact, rear impact, underbody impact, and low-speed impact scenarios. The results from these segment-model simulations exhibit strong correlation with full vehicle simulations, ensuring reliability and validity of the presented work. This approach not only enhances simulation efficiency and cluster utilization cost but also offers a scalable solution for future automotive crash evaluation and optimization. The findings underscore the potential for widespread application of segment-models or cut models in the industry as important surrogate models, paving the way for more sustainable and cost-effective crash simulation practices.