IEEE

Bootstrap-Driven Adaptive Resampling for Enhanced Solutions of Second-Order Differential Equations in RLC Circuits Using PINNs

Abstract: Physics-informed neural networks (PINNs) offer a flexible framework for solving differential equations using physical constraints and data. This study focuses on second-order ...
IEEE

Waveform relaxation of nonlinear second-order differential equations

Abstract: In this paper, we give a simple theorem on the waveform relaxation (WR) solution for a system of nonlinear second-order differential equations. It is shown that if the norm of certain ...
C&EN

Control of Ethylene Dichloride Cracking Furnace Using an Analytical Model Predictive Control Strategy for a Coupled Partial Differential Equation/Ordinary Differential Equation ...

† Department of Chemical Engineering, Center of Excellence on Petrochemicals and Material Technology, Faculty of Engineering, Kasetsart University, Bangkok 10900, Thailand ‡ The Center for Advanced ...
GitHub

physics-informed-neural-networks

Exploring the concepts of Physics Informed Neural Networks. Coding a Physics Informed Neural Network to simulate a harmonic oscillator and solve a simple first-order ordinary differential equation.
GitHub

harmonic-oscillator

C programs that simulate a damped harmonic oscillator, a fundamental concept in physics and engineering. Data visualisation is done using a Python script with the popular matplotlib library.