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Abstract
High-performance computing (HPC) enables both academia and industry to accelerate simulation-driven product development processes by providing a massively parallel computing infrastructure. In particular, the automation of high-fidelity computational fluid dynamics (CFD) analyses aided by HPC systems can be beneficial since computing time decreases while the number of significant design iterations increases. However, no studies have quantified these effects from a product development point of view yet. This article evaluates the impact of HPC and automation on product development by studying a formula student racing team as a representative example of a small or medium-sized company. Over several seasons, we accompanied the team, and provided HPC infrastructure and methods to automate their CFD simulation processes. By comparing the team’s key performance indicators (KPIs) before and after the HPC implementation, we were able to quantify a significant increase in development efficiency in both qualitative and quantitative aspects. The major aerodynamic KPI increased up to 115%. Simultaneously, the number of expedient design iterations within one season increased by 600% while utilizing HPC. These results prove the substantial benefits of HPC and automation of numerical-intensive simulation processes for product development.
Highlights
High-performance computing (HPC) accelerates product development by decreasing the computing time of numerical-intensive simulations, such as computational fluid dynamics (CFD) analyses, and allows for an increase in design iterations
After describing the implementation of the automated CFD process on HPC systems in the previous section, this section will present the implications for product development
A formula student team as an object of research is interesting because there are short development cycles and often fewer restrictions compared to most industrial projects, which opens new possibilities for innovations based on high-fidelity
Summary
High-performance computing (HPC) accelerates product development by decreasing the computing time of numerical-intensive simulations, such as CFD analyses, and allows for an increase in design iterations. Automating the simulation-driven optimization processes can further increase the efficiency of product development. There has been a great deal of interest in outlining the advantages of HPC and automation for simulation and optimization processes. The complexity of product development is constantly increasing due to more disciplines being involved, such as mechanics, electrical engineering and information technology. A widely used SE model is the V-model (see Figure 1), which classifies the technical work stages in product development processes and defines responsibilities. One of the first works addressing product development according to the V-model was published in 1991 [5]. The model has been adapted in multiple ways, and enhanced and implemented in guidelines, such as VDI 2206 [6], which is widely used in German-speaking countries
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