4 citations · 7 across the 7 of their papers we have counts for
7 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…
On the Non-Markovian Navier-Stokes Framework for Turbulence Modeling -- A Preliminary Analysis
Siamak Kazemzadeh Hannani, Ehsan Ghaderi
This study explores a formulation of the Navier Stokes equations (NSE) using fractional calculus in modeling turbulence. By generalizing the stress strain constitutive relation to…
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…
Evaluating Joule heating influence on heat transfer and entropy generation in MHD channel flow: A parametric study and ill-posed problem solution using PINNs
Ehsan Ghaderi, MohammadAli Bijarchi, Siamak Kazemzadeh Hannani +1
In this study the effects of Joule heating parameter on entropy generation and heat transfer in MHD flow inside a channel is investigated by means of Physics-Informed Neural Networ…
Parametric and inverse analysis of flow inside an obstructed channel under the influence of magnetic field using physics informed neural networks
Ehsan Ghaderi, MohammadAli Bijarchi, Siamak Kazemzadeh Hannani +1
In this study, fluid flow inside of an obstructed channel under the influence of magnetic field has been analyzed using physics informed neural networks(PINNs). Governing equations…