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Papers by mohammad jadidi

Proceedings of the World Congress on Momentum, Heat and Mass Transfer, Apr 1, 2024

Turbulence modelling in porous media presents challenges in Computational Fluid Dynamics (CFD). W... more Turbulence modelling in porous media presents challenges in Computational Fluid Dynamics (CFD). While various modelling approaches have been employed to analyze turbulent flow properties, achieving both precision and cost-effectiveness remains a significant hurdle. In recent years, Deep Learning (DL), with its capacity for solving nonlinear model, has emerged as a promising solution to address these challenges. The advent of Physics-Informed Neural Networks (PINN) has expanded the scope of Deep learning applications in turbulent flow modelling. However, applying PINN to complex flow physics within porous media remains an underexplored territory. This study employs PINN to solve the Reynolds-Averaged Navier-Stokes (RANS) equations in a composite porous-fluid system, guided by supervised learning and penalized by the RANS equation to ensure fidelity to flow physics. The research aims to enhance flow prediction accuracy and explore the influence of data distribution on PINN performance in complex flow scenarios in composite porous-fluid systems. Results showed that using porous-fluid interface training data provides better accuracy, with improvements of 40% and 2% in second-order statistics. This research contributes to advancing our understanding of turbulent flows in porous media and highlights the potential of PINN as a valuable tool for exploring complex flow physics.

Efficient implementation of masked AES on Side-Channel Attack Standard Evaluation Board

2015 International Conference on Information Society (i-Society), 2015

In this paper, we present a practical smart card implementation of AES-128 combined with a simple... more In this paper, we present a practical smart card implementation of AES-128 combined with a simple yet effective masking scheme. The proposed method has advantage of easy software implementation, low memory and clock cycle requirement, and most importantly, it provides enough robustness against first-order Differential Power Analysis (DPA)attacks and removes the correlation between power consumption and hamming weight of sensitive data. The experimental results from implementation on Side-Channel Attack Standard Evaluation Board (SASEBO-W) verifies the effectiveness of both implementation and the masking algorithm that has already been implemented on the smartcard.

Physics of Fluids

In the present paper, turbulent flow in a composite porous-fluid system including a permeable sur... more In the present paper, turbulent flow in a composite porous-fluid system including a permeable surface-mounted bluff body immersed in a turbulent channel flow is investigated using pore-scale large eddy simulation. The effect of Reynolds number (Re) on the flow leakage from porous to non-porous regions, Kelvin-Helmholtz (K-H) instabilities, as well as coherent structures over the porous-fluid interface are elaborated. Results show that more than 52% of the fluid entering the porous blocks leaks from the first half of the porous region to the non-porous region through the porous-fluid interface. As the Re number increases, the flow leakage decreases by 24%. Flow visualization shows that the Re number affects the size of counter-rotating vortex pairs and coherent hairpin structures above the porous block. Moreover, turbulence statistics show that by reducing the Re number, turbulence production is delayed downstream; at the Re=14400, it begins from the leading edge of the porous block ...

Large eddy simulation of thermal stratification effect on convective and turbulent diffusion fluxes concerning gaseous pollutant dispersion around a high-rise model building

Journal of Building Performance Simulation

Module 01: Large Eddy Simulation (LES) and Other Scale Resolving Simulation (SRS) Models

Module 02: Setting Up LES-type Simulations

Hairpin turbulent structure downstream of hemisphere Laminar flow (Re D =1000) Top view Iso-metric view

Computational Fluid Dynamics (Session #6)

Introduction to Reactive Flows modeling using ANSYS FLUENT Equations governing reacting flows

Computational Fluid Dynamics (Session #4)

Computational Fluid Dynamics (Session #7)

Introduction to Multiphase Flows-Part # 2 Fundamental Definitions & Choosing a Multiphase Model

Introduction to Reactive Flows modeling using ANSYS FLUENT (Part #2 – Rev00) Finite-Rate Formulation for Reaction Modeling

Computational Fluid Dynamics (Session #14) Solution algorithms for pressure--velocity coupling in steady flows- SIMPLE Algorithm

Computational Fluid Dynamics (Session #5)

Computational Fluid Dynamics (Session #3)

Computational Fluid Dynamics Session #1

Computational Fluid Dynamics (Session #18) The finite volume method for unsteady flows-part II