Advancing Engineering Simulations: The Role of AI in Computational Fluid Dynamics
Maximizing Efficiency and Insight in CFD Simulations Through Artificial Intelligence
In the ever-evolving landscape of engineering simulations, Computational Fluid Dynamics (CFD) stands out as a crucial tool utilized across various industries. From automotive and aerospace to energy and environmental engineering, CFD enables engineers to analyze and optimize fluid flow, heat transfer, and other related phenomena. For example, in automotive design, CFD simulations can assess aerodynamic performance to enhance fuel efficiency and reduce drag, while in aerospace, they aid in optimizing airflow around aircraft components for improved performance and safety.
However, traditional CFD simulations often pose significant challenges in terms of computational resources and time consumption. These simulations can take hours, days, or even weeks to produce results, hindering the iterative design process and delaying critical decision-making. Recognizing this bottleneck, engineers and researchers have turned to artificial intelligence (AI) to accelerate the simulation process and unlock new efficiencies.
Simulations take days to complete. Customers need faster time to insights.
byteLAKE’s CFD Suite represents a paradigm shift in CFD simulations by harnessing the power of AI to expedite results and enhance decision-making. By leveraging AI algorithms, deep learning, and machine learning techniques, the CFD Suite slashes simulation times, minimizes trial-and-error costs, and supercharges decision-making processes. This innovative approach enables engineers to obtain actionable insights faster, empowering them to iterate designs more rapidly and optimize performance across various scenarios.
The core focus of byteLAKE’s CFD Suite lies in accelerating simulations through the innovative application of artificial intelligence. Trained on vast repositories of past simulations, the CFD Suite harnesses AI to expedite the simulation process without altering the underlying CFD solvers. Acting as an external add-on, it seamlessly integrates with existing CFD toolchains, offering a non-intrusive solution for accelerating simulations. Once deployed, the AI Accelerator is supervised by an AI Supervisor that continuously monitors ongoing CFD simulations in real-time. When opportunities for acceleration are identified, the AI Accelerator steps in dynamically, enhancing the simulation speed without compromising accuracy. This tandem approach, where the AI Accelerator and AI Supervisor work together, enables the CFD Suite to achieve remarkable acceleration rates. Research conducted by byteLAKE has demonstrated accelerations of up to 10x with high accuracy levels, even with a limited number of historic simulations used for AI training. Furthermore, results have shown accelerations exceeding 20x and, in some cases, surpassing 40x with reliable predictions, showcasing the immense potential of AI-driven simulation acceleration in advancing engineering workflows.
The image above illustrates the results achieved by AI-accelerating OPENFOAM’s® Motorbike CFD Simulation with byteLAKE’s CFD Suite.
Disclaimers:
This offering is not approved or endorsed by OpenCFD Limited, producer and distributor of the OpenFOAM software via www.openfoam.com, and owner of the OPENFOAM® and OpenCFD® trade marks.
OPENFOAM® is a registered trade mark of OpenCFD Limited, producer and distributor of the OpenFOAM software via www.openfoam.com.
Going beyond AI-accelerated CFD Simulations
byteLAKE’s commitment to bridging the gap between academia and industry is evident in its holistic approach to AI-accelerated simulations. Beyond simply expediting time-to-results, the CFD Suite revolutionizes the entire simulation lifecycle by assisting in preparation, configuration optimization, and result analysis. By analyzing historical data and learning from past simulations, AI guides engineers in prioritizing simulations, reducing trial and error, and optimizing parameters, thereby enhancing efficiency and effectiveness throughout the process.
While the benefits of AI-accelerated simulations are evident in relatively small, steady-state simulations, larger and more complex simulations present a different challenge. However, byteLAKE’s ongoing research endeavors aim to harness AI’s potential to revolutionize CFD simulations holistically. By leveraging historical data and learning from past simulations, AI not only predicts outcomes but also suggests optimal configurations, streamlines workflows, and provides invaluable insights.
Moreover, byteLAKE’s CFD Suite extends beyond accelerating time-to-results for CFD simulations alone. It can be trained for various purposes, such as selecting or prioritizing geometries based on AI-predicted efficiency or optimizing configurations and meshing operations. This multi-purpose training approach enables comprehensive process optimization, leading to faster insights, lower costs, and enhanced efficiency across a wide range of simulation processes.
Looking ahead, the potential applications of AI in the realm of engineering simulations and CAE tools are vast. Beyond CFD simulations, AI could revolutionize areas such as structural analysis, thermal management, and electromagnetics. By incorporating AI-driven enhancements into existing workflows, engineers can achieve faster time-to-market, lower development costs, and superior product performance.
In conclusion, byteLAKE remains at the forefront of AI research efforts, collaborating with academia partners to explore the myriad ways in which AI can elevate engineering simulations to new heights. Through its innovative CFD Suite and ongoing commitment to advancing AI technologies, byteLAKE aims to empower engineers and researchers worldwide to tackle complex engineering challenges with confidence and efficiency.
Learn more:
- CFD Suite blog post series: https://www.bytelake.com/en/AI4CFD-toc
- Product website: https://www.bytelake.com/en/cfdsuite
- Unlocking the Power of AI: Transforming Data into Actionable Insights | by Marcin Rojek | Apr, 2024 | Medium
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