The last two years have witnessed a surge in the acceleration in our ability to generate, curate, and use data for large-scale training of modern physics-AI surrogates. Additionally, physics-AI architectures are rapidly improving in their ability to accurately represent complex, industrially relevant geometries and associated physics. Extrapolating into the future, we must ask ourselves the question: “What does this mean for the future of aerospace engineering?”
During this webinar, Professor Alonso will describe the evolving landscape of artificial intelligence and machine learning methods as they relate to various applications in aerospace engineering, including design space exploration, optimization, uncertainty quantification, and data assimilation for digital twins. For example, Luminary Cloud has developed SHIFT-CCA, a physics-AI model for external aerodynamics (including the flowpath for the propulsion system) for the U.S. Air Force’s Collaborative Combat Aircraft. Using SHIFT-CCA, Professor Alonso will discuss how such models can be used and the potential of Luminary Cloud’s SHIFT models for aerospace applications.
Speaker:
Juan AlonsoCTO and Cofounder, Luminary Cloud; Chair, Department of Aeronautics and Astronautics, Stanford University
