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Found 5 papers, 1 papers with code
On using Machine Learning Algorithms for Motorcycle Collision Detection
Impact simulations show that the risk of severe injury or death in the event of a motorcycle-to-car impact can be greatly reduced if the motorcycle is equipped with passive safety measures such as airbags and seat belts.
Multi-Hierarchical Surrogate Learning for Structural Dynamical Crash Simulations Using Graph Convolutional Neural Networks
We thus propose a multi-hierarchical framework for structurally creating a series of surrogate models for a kart frame, which is a good proxy for industrial-relevant crash simulations, at different levels of resolution.
Low-dimensional Data-based Surrogate Model of a Continuum-mechanical Musculoskeletal System Based on Non-intrusive Model Order Reduction
In recent decades, the main focus of computer modeling has been on supporting the design and development of engineering prototyes, but it is now ubiquitous in non-traditional areas such as medical rehabilitation.
Real-time Human Response Prediction Using a Non-intrusive Data-driven Model Reduction Scheme
Recent research in non-intrusive data-driven model order reduction (MOR) enabled accurate and efficient approximation of parameterized ordinary differential equations (ODEs).
Physics-informed Neural Networks-based Model Predictive Control for Multi-link Manipulators
We thus present the idea of enhancing PINNs by adding control actions and initial conditions as additional network inputs.
