11 citations · 15 across the 9 of their papers we have counts for
9 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…
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…
Novel Magnetic Actuation Strategies for Precise Ferrofluid Marble Manipulation in Magnetic Digital Microfluidics: Position Control and Applications
Mohammad Hossein Sarkhosh, Mohammad Hassan Dabirzadeh, Mohamad Ali Bijarchi +1
Precise manipulation of liquid marbles has significant potential in various applications such as lab-on-a-chip systems, drug delivery, and biotechnology and has been a challenge fo…
Deformation and breakup of a ferrofluid compound droplet migrating in a microchannel under a magnetic field: A phase-field-based multiple-relaxation time lattice Boltzmann study
Parham Poureslami, Mohammad Majidi, Javad Ranjbar Kermani +1
Though ubiquitous in many engineering applications, including drug delivery, the compound droplet hydrodynamics in confined geometries have been barely surveyed. For the first time…
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…
Enhancing Convergence Speed with Feature-Enforcing Physics-Informed Neural Networks: Utilizing Boundary Conditions as Prior Knowledge for Faster Convergence
Mahyar Jahaninasab, Mohamad Ali Bijarchi
This study introduces an accelerated training method for Vanilla Physics-Informed-Neural-Networks (PINN) addressing three factors that imbalance the loss function: initial weight s…