Stiff-PINN: Physics-Informed Neural Network for Stiff Chemical Kinetics
The recently developed physics-informed neural network (PINN) has achieved success in many science and engineering disciplines by encoding physics laws into the loss functions of the neural network such that the network not only conforms to the measurements and initial and boundary conditions but al...
| Main Authors: | , , , , |
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| Other Authors: | |
| Format: | Article |
| Language: | English |
| Published: |
American Chemical Society (ACS)
2021
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| Online Access: | https://hdl.handle.net/1721.1/138718.2 |