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The document presents a study on the Stiff-PINN, a physics-informed neural network designed to address stiff chemical kinetics by incorporating the quasi-steady-state assumption (QSSA) to reduce the stiffness of ordinary differential equations (ODEs). The research highlights the challenges faced by traditional PINNs when applied to stiff systems and demonstrates that the Stiff-PINN can effectively solve these problems, opening new possibilities for modeling complex chemical reaction-diffusion systems. The f

Author

sudhanq8

Language

EN