PC for Ansys Digital Twin for the automotive industry
PC for Ansys Digital Twin combining physics simulation technology (multiphysics) with AI/machine learning.
Ansys Digital Twin is a technology and solution that combines Ansys's long-standing physical simulation technology (multiphysics) with AI/machine learning to accurately replicate and synchronize real-world products and processes in a virtual space. It is offered through a range of products such as Ansys Twin Builder and Ansys TwinAI, enabling predictive maintenance, performance optimization, and the creation of new services from product design and development to operation and maintenance. It features a "hybrid digital twin" that merges physical models with data models (AI/ML), providing high-precision predictions and real-time insights. Therefore, the performance of CPU, memory, and GPU becomes crucial.
basic information
This model is equipped with an Intel Core Ultra 9 285, featuring 24 cores (P8 + E16), 24 threads, a clock speed of 2.5-5.4GHz, 40MB of L2 cache, and 36MB of L3 cache. It comes with a large memory capacity of 128GB and is equipped with an NVIDIA RTX 5000 Ada 32GB-GDDR6 GPU. These specifications strongly support simulations and AI applications.
Price range
P5
Delivery Time
OTHER
Applications/Examples of results
For Ansys Digital Twin
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News about this product（2）
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[Blog] "The Possibilities of Automotive Development Expanding with LS-DYNA × AI" HPC Supporting Next-Generation CAE
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.
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[Blog] <Technical Explanation> The Cutting Edge of CAE Analysis and Optimization Methods for Achieving Carbon Neutrality
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."
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Applied Corporation is a computer manufacturing company based in Hakata-ku, Fukuoka City, Fukuoka Prefecture, with 65 locations nationwide. We provide the latest business proposals, from cutting-edge computers to the implementation of DX and solutions, for corporate clients across the country.