Presentation
Analytically Integratable Zero-restlength Springs for Capturing Dynamic Modes Unrepresented by Quasistatic Neural Networks
SessionTechnical Papers
Event Type
Technical Paper
Research & Education
Virtual
Full Conference Supporter
Full Conference
Virtual Conference Supporter
Virtual Conference
Exhibitor Additional Full Conference
Exhibitor Full Conference
Time
Location
DescriptionWe present a novel paradigm for modeling certain types of dynamic simulation in real-time with the aid of neural networks. Our approach utilizes a data-driven neural network only to capture quasistatic information and an analytically integratable, real-time dynamic simulation layer to augment the quasistatic neural network inference.
