# Impact of HPC and Automated CFD Simulation Processes on Virtual Product Development--A Case Study
## 1 Introduction
### Background  
The complexity of product development is constantly increasing due to more disciplines being involved, such as mechanics, electrical engineering and information technology. For managing the interdisciplinary nature of product development, the approach of systems engineering (SE) has been developed over the years and established in both academia and industry [2]. The basic idea is to subsequently reduce complex systems into smaller and more manageable subsystems and define their interfaces in advance [3,4]. 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]. However, 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.  
According to VDI 2206, product development begins with the requirements specification in the left branch of the \"V\" and is continuously enriched and detailed until the requirements for all subassemblies and components are specified and a final design is available (lower tip of the \"V\"). The right branch covers the validation and verification of the design proposals. For example, simulations or bench tests validate the required properties on the different abstraction levels. In this context, it is essential to consider the dependencies between the (sub)systems. In addition to straightforward validation, one must also successfully carry out integration tests in the higher-level system structure. The right branch usually concludes with a simulation of the overall system. If one of the tests fails and components must be modified or optimized, this leads to new validation and verification test cycles [7]. In simulation-based product development, this results in a large number of simulations, which, depending on the type of analysis, can result in a high computing load, especially if many engineering disciplines are involved, as is now common. If product development includes very elaborate simulations, such as computational fluid dynamics (CFD), single simulations can already be so time-consuming that only a few designs or optimization iterations for the overall system are possible to meet a given time-to-market. Reducing the accuracy of simulation models to save computational load is not worthwhile in many use cases. Especially for iterative developments, the use of high-resolution simulation models is beneficial, as shown, for example, in [8].  
Possibilities to speed up complex simulation-based development processes are the increased use of HPC systems to accelerate simulations, the automation of simulation and optimization processes or a combined approach. Unfortunately, the automation of optimization processes highly depends on the underlying model and is usually associated with a high initial effort. In [9], for example, an approach to an automated CFD-based optimization is shown. With the rapid increase in performance of processor and memory technologies and current research in the HPC domain [10], further increases in efficiency and cost reductions are highly probable. Combined with progressive development of computational methodologies [11; 12], this opens new potential for product development [13].  
Unfortunately, the tendency of SMEs to use HPC is low. This is partly due to the comparatively high cost and knowledge required to integrate HPC into existing processes and the poor quantifying value of HPC for SMEs. We want to address the last obstacle by providing insights in HPC-based product development to show its effects and value. However, first, we will examine the challenges of integrating HPC in the following subsection, focusing on an automated CFD workflow as an example.