Explore the mathematical and computational foundations for enabling predictive digital twins at scale in this comprehensive lecture by Karen Willcox from the University of Texas at Austin. Delve into the concept of digital twins as coupled computational models representing unique physical assets, and discover the growing potential of this technology in revolutionizing decision-making across various fields. Examine a unifying mathematical formulation using probabilistic graphical models to create robust digital twin implementations at scale. Learn about the abstraction of asset-twin systems as coupled dynamical systems and their computational realization as dynamic decision networks. Gain insights into physics-based reduced-order models and their role in enabling digital twins. Follow the demonstration of a structural digital twin for an unmanned aerial vehicle, and understand the importance of combining data with physics-based models in creating effective digital twins. Engage with topics such as historical perspectives, digital twins in economics and aerospace, mathematical foundations, and the critical enablers for digital twin technology. Read more