Schedule
Day 1 (7/30/2022)
Time |
Lectures |
Offline readings |
See Lecture Notes |
8:00-8:30 am EST |
Opening remarks and logistics (Sun) |
8:30-9:30 am EST |
Lecture 1: Graph-based learning and knowledge representation for solid mechanics ( Sun) |
9:30-9:45 am EST |
Break |
9:45-10:45 am EST |
Lecture 2: Manifold based learning and data-driven computing for nonlinear solid mechanics: dimensional reduction and thermodynamics (Chen) |
10:45-11:00 am EST |
Break |
11:00-12:30 pm EST |
Lab Session 1: Artificial Neural Network for Prediction of Failure Envelope of Carbon/Epoxy Composites (UCSD) [Colab] |
Day 2 (7/31/2022)
Time |
Lectures |
8:00 - 9:00 am EST |
Lecture 3: Deep reinforcement learning for adversarial training of constitutive laws (Sun) |
9:00-9:15 am EST |
Break |
9:15 - 10:15 am EST |
Lecture 4: Machine learning for digital twins: an example on musculoskeletal digital twin (Chen) |
10:15 - 10:30 am EST |
Break |
10:30 - 12:00 pm EST |
Lab Session 2: Design of experiments with deep reinforcement learning (Columbia) [Colab] |
