4 papers
An Adaptive Physics-Driven Deep Learning Framework for a Two-Phase Stefan Problem
Meraj Hassanzadeh, Ehsan Ghaderi, Fatemeh Fatahi +1
Thermal Energy Storage (TES) using Phase Change Materials (PCMs) represents a critical technology for sustainable energy management and grid stability. This study presents a novel…
Intelligent Optimization of Multi-Parameter Micromixers Using a Scientific Machine Learning Framework
Meraj Hassanzadeh, Ehsan Ghaderi, Mohamad Ali Bijarchi +1
Multidimensional optimization has consistently been a critical challenge in engineering. However, traditional simulation-based optimization methods have long been plagued by signif…
Equation Discovery, Parametric Simulation, and Optimization Using the Physics-Informed Neural Network (PINN) Method for the Heat Conduction Problem
Ehsan Ghaderi, Mohamad Ali Bijarchi, Siamak Kazemzadeh Hannani +1
In this study, the capabilities of the Physics-Informed Neural Network (PINN) method are investigated for three major tasks: modeling, simulation, and optimization in the context o…
Revising the Structure of Recurrent Neural Networks to Eliminate Numerical Derivatives in Forming Physics Informed Loss Terms with Respect to Time
Mahyar Jahani-nasab, Mohamad Ali Bijarchi
Solving unsteady partial differential equations (PDEs) using recurrent neural networks (RNNs) typically requires numerical derivatives between each block of the RNN to form the phy…