General-purpose structural analysis software 'Ansys Mechanical'

In automotive development, CAE (Computer Aided Engineering) is widely used to enhance safety and performance. Among these, "crash analysis," which predicts the deformation, stress, and strain of the vehicle body during a collision, is crucial in the field of crash safety. The representative CAE software LS-DYNA allows for the setting of conditions such as body shape, materials, thickness, and collision speed to analyze the behavior during a crash. On the other hand, automotive development requires not just a single design proposal but also the comparison of numerous candidates, including materials, thickness, component shapes, and reinforcement positions. This is where the focus shifts to utilizing the analysis data accumulated in LS-DYNA to train AI, which can be used for predicting analysis results and screening design candidates. Rather than replacing CAE, combining CAE with AI has the potential to make the design review process more efficient. Furthermore, HPC (High Performance Computing) becomes essential as a foundation supporting CAE analysis, AI learning, and large-scale data processing.

Many people may find it hard to grasp the concept of carbon neutrality (reducing environmental impact) in a nutshell. "The goal is to achieve net-zero greenhouse gas emissions overall by 2050." The government announced this goal in October 2020. Those engaged in the research and development sectors of the manufacturing industry are facing various challenges daily in pursuit of this goal. In the field, CAE (Computer Aided Engineering) is currently evolving from a mere "tool for efficiency" to an "essential sustainable strategy." Why is simulation technology the key to saving the planet? This time, I would like to explore the deep relationship between "carbon neutrality and the power of CAE."