Artificial Intelligence in Numerical Simulations
04.10.2024
Since the mid-20th century, numerical simulations have been crucial for testing, validating, and improving designs across various industries. Numerical simulations are computational methods that use mathematical models to analyze and predict the behavior of complex systems under different conditions. Today, the integration of Artificial Intelligence (AI) with numerical simulations is bringing about revolutionary changes, enabling faster and more accurate simulations. AI and Machine Learning (ML) have evolved from the realm of science fiction into key components of modern technology, significantly enhancing various aspects of daily life, from early disease detection to autonomous driving and optimization of production lines.
Previously, the speed and accuracy of simulations depended on engineers' ability to manually define and run simulations, which often slowed down the process and required significant time, computational, and expertise resources. Now, AI-supported simulations significantly accelerate design, optimization, and the simulation process itself, particularly in industries where accuracy and efficiency are critical, such as automotive, aerospace, and electronics. For instance, the use of ML to optimize geometry in simulation tools allows for the creation of highly accurate models, speeding up and improving the precision of simulations. By leveraging convolutional neural networks, researchers develop models that enhance the way CAD tools represent complex shapes, simplifying spatial representations while maintaining numerical accuracy.
AI also enhances the ease of using simulation tools. For example, large language models (LLMs) like ChatGPT enable users to create simulations by describing desired outcomes in natural language. When specifying requirements in ChatGPT, users receive targeted assistance where AI understands the request and, based on theoretical foundations and internal databases, provides actionable and applicable responses. This technology not only improves geometric modeling but also various aspects of the simulation process, including geometry classification, part connectivity identification, and simulation setup recommendations. Additionally, AI enhances coding and user support by offering efficient coding recommendations and enabling design validation to maximize simulation accuracy.
Distributed by Econ Engineering in the Adriatic region, Ansys®, a leader in numerical simulations, actively integrates AI and ML into its software products, with its latest package, Ansys SimAI™, leveraging these technologies to accelerate simulation solving processes. This cloud-based platform combines the precision of simulation with the speed of generative AI technology, improving model performance by factors of 10 to 100. The software features self-learning capabilities, allowing the system to continuously refine and adapt based on previous data. When 20 models are input into the system, thousands of new variations are automatically generated, utilizing accumulated knowledge and data. Upon introducing the next model, the system provides solutions in the shortest possible period.
As product complexity increases, so does the demand for engineering software that can enhance productivity without compromising accuracy. The integration of advanced AI into design and simulation processes optimizes workflows and adapts to market demands. The synergy between numerical simulations and AI is radically transforming how products are conceived, developed, and brought to market, setting new standards in innovation.
The intersection of AI and simulation technology