Research

As part of my undergraduate research project (August 2009 – August 2010), I worked on the design, simulation, and fabrication of an air-based ejector, integrating computational and experimental approaches to optimize its performance. The project aimed to understand the hydrodynamic behavior of fluid flow and the impact of geometric parameters on ejector efficiency.

Key Contributions & Industry-Relevant Skills

• Computational Fluid Dynamics (CFD) Simulation: Modeled two-phase turbulent flow inside the ejector to analyze energy efficiency based on the first and second laws of thermodynamics.

• Experimental Validation & Prototyping: Designed and fabricated a functional ejector, which was later incorporated into the fluid mechanics laboratory for student training.

• Optimization of Ejector Performance: Investigated key geometrical and thermofluidic parameters affecting ejector efficiency, improving its practical application in fluid transport systems.

• Collaboration & Research Dissemination: Presented findings at the September 2011 MIC conference in the paper:
  📄 "Investigating Effective Parameters in the Design of an Ejector for an Underwater Sediment Remover."

In later research, I collaborated with Gholamabbas Sadeghi and Roya Rouhollahi, contributing to a thermofluidic and energy-exergy analysis of an air-based ejector. This work was published in:
📑 "Experimental and Numerical Thermofluidic Assessments of an Air-Based Ejector Regarding Energy and Exergy Analyses," (International Communications in Heat and Mass Transfer, July 2020).

This experience strengthened my expertise in fluid mechanics, CFD modeling, experimental testing, and energy-efficient system design, all of which are directly applicable to engineering roles in R&D, energy systems, and industrial fluid applications.

Three-dimensional model of the ejector used in experimental validation (a) nozzle, (b) suction chamber, (c) mixing section and diffuser, (d) assembled ejector

First and second law efficiencies of the designed air ejector for different primary pressures, and different exit nozzle positions

As a graduate student, I conducted a macro-scale computational study on the influence of magnetic fields on blood flow, simulating a blood artery in a two-dimensional straight tube. The study explored how Reynolds number, magnetic field strength, and wall infiltration velocity affect the surface concentration of low-density lipoprotein (LDL), a key macromolecule in blood circulation.

Key Findings & Industry Applications

• Biomedical & Engineering Applications: Investigated the potential of magnetic fields to control blood flow, relevant to targeted drug delivery, biofluid transport, and cardiovascular disease studies.

• Flow Optimization & Shear Stress Control: Extended the study to 2D axial-symmetric stenosis and a 3D S-shaped tube, revealing how non-uniform magnetic fields influence vortex formation, wall shear stress, and lipid accumulation.

• Porous Media & Diffusion Enhancement: Modeled the blood vessel wall as a porous structure, assessing the diffusion rate of macromolecules under magnetic field effects, with implications for biomedical device design and fluid filtration technologies.

• Computational & Simulation Expertise: Applied advanced numerical modeling using CFD and magnetohydrodynamics (MHD) to analyze fluid-magnetic field interactions.

This research was published in the Journal of Magnetism and Magnetic Materials and presented at international conferences, where I engaged with experts in biomedical simulations and fluid mechanics.

Schematic diagram of the geometry and the approximate location of the wire that contains electric current

Emulsions are complex fluids widely used in enhanced oil recovery (EOR) due to the presence of interfacial-active oil constituents, such as asphaltene molecules. Understanding their behavior at the oil-water interface is key to optimizing recovery efficiency and interfacial tension control.

In this project, we extended the NAMD molecular dynamics (MD) package by modifying the Velocity Verlet algorithm to incorporate magnetic fields as external forces. This allowed us to investigate how magnetic fields affect the interfacial tension of a water-toluene system in the presence of asphaltene molecules.

Key Innovations & Findings

• Magnetic Field Implementation in Molecular Dynamics: Developed a customized version of NAMD (v2.12) with a magnetic field feature, using C++ scripting for force implementation and Fortran programming to calculate viscosity from MD outputs.

• Aggregation & Interfacial Tension Control: Simulated toluene-water interfaces under varying magnetic field strengths, showing that magnetic fields alter hydrogen bonding and influence asphaltene aggregation, potentially improving fluid stability in oil recovery applications.

• Potential Industry Impact: Findings suggest that magnetic field application could be used to optimize oil recovery techniques by modifying interfacial tension and controlling the behavior of interfacial-active oil constituents in emulsions.

• Computational & Simulation Expertise: Applied advanced molecular dynamics (MD), interfacial fluid modeling, and custom numerical implementations to address energy sector challenges.

The results of this study were published in:
📑 Fluid Phase Equilibria (2020)
📑 Journal of Molecular Modeling (2020)

The modified source code is available on GitHub, and the findings were presented at international conferences, contributing to advancements in computational fluid dynamics, enhanced oil recovery, and energy-efficient materials research.

Molecular representation of the PAP asphaltene model molecule: white: hydrogen, red: oxygen, cyan: carbon, blue: nitrogen.

Adding the magnetic field force into the velocity Verlet algorithm. q is the charge, and B is the magnetic intensity

The rotation of charged particle in the presence ofmagnetic field; left: B = (0, 0, 1e+5) T, right: B = (0, 0, 1) T

In collaboration with Mitsui Chemicals, we developed a Fortran-based simulation framework integrating the Lattice Boltzmann Method (LBM) and Brownian dynamics to study polymer-fluid interactions in lubrication systems. The model was further extended to include thermal coupling, allowing us to analyze temperature fields in polymer-enhanced lubricants—a crucial factor in optimizing thermal stability and viscosity performance in industrial applications.

Key Contributions & Industry Applications

• Thermal Effects in Lubrication: Incorporated thermal coupling into the LBM framework to simulate temperature variations in lubricants containing polymers, enhancing insights into heat dissipation, viscosity modulation, and tribological efficiency.

• Polymer Influence on Flow Behavior: Evaluated the effects of polymer additives on velocity fields, polymer conformation (radius of gyration), center of mass movement, and bulk flow energy, contributing to next-generation lubricant formulations.

• Advanced Computational Techniques: Implemented LBM for fluid modeling, Brownian dynamics for polymer behavior, and thermal coupling mechanisms, integrating Fortran-based solvers with Python and ParaView for result visualization.

• Biomedical Applications: Extended the study to model the von Willebrand Factor (VWF) protein in flow fields during early thrombus formation, providing insights into biomedical device performance and blood flow regulation.

This work bridges materials science, computational fluid dynamics, and biomedical research, demonstrating how multiscale modeling can optimize polymer-lubricant interactions for both industrial and biomedical applications.