11 citations · 15 across the 9 of their papers we have counts for
5 papers · 1 filter
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…
Toward accurate RUL and SoH estimation using reinforced graph-based physics-informed neural networks enhanced with dynamic weights
Mohamadreza Akbari Pour, Ali Ghasemzadeh, Mohamad Ali Bijarchi +1
Accurate estimation of Remaining Useful Life (RUL) and State of Health (SoH) is essential for reliable Prognostics and Health Management (PHM), supporting timely maintenance and de…
FlexPINN: Modeling Fluid Dynamics and Mass Transfer in 3D Micromixer Geometries Using a Flexible Physics-Informed Neural Network
Meraj Hassanzadeh, Ehsan Ghaderi, Mohamad Ali Bijarchi
In this study, fluid flow and concentration distribution inside a 3D T-shaped micromixer with various fin shapes and configurations are investigated using a Flexible Physics-Inform…