Article
Mathematics
Nurul Amira Zainal, Roslinda Nazar, Kohilavani Naganthran, Ioan Pop
Summary: In this study, the impact of magnetic field on the unsteady separated stagnation-point flow of hybrid nanofluid is numerically investigated, taking into account viscous dissipation and Joule heating. A new mathematical model for hybrid nanofluid is developed, and similarity solutions in the form of ordinary differential equations are obtained. The findings show that the skin friction coefficient and heat transfer rate of the fluid increase with the nanoparticle volume fraction and unsteadiness parameter. The magnetic and acceleration parameters also have a significant effect on the heat transfer performance.
Article
Multidisciplinary Sciences
Senthil Jayanthi, Hari Niranjan
Summary: This study investigates the flow of magnetohydrodynamic (MHD) nanofluid through a stretching vertical surface influenced by various factors such as Joule heating, chemical reaction, viscosity dissipation, thermal radiation, and activation energy. By using the similarity technique and symmetry analysis, the complicated boundary layer equations for motion, energy, solute, and nanoparticle concentration are simplified. The altered equations are then solved using the shooting technique with Matlab bvp4c. The results show that the Schmidt number, Biot number, and thermal radiation have significant effects on temperature, concentration, local Nusselt number, local Sherwood number, and skin friction.
Article
Materials Science, Multidisciplinary
Muhammad Rooman, Fazal Ur Rehman, Zahir Shah, Mansoor Alshehri, Ahmed Alshehri
Summary: This study investigates the heat-transferring properties of engine oil with MHD effects using Ellis nanofluid, which contains copper (Cu) and Titanium oxide (TiO2) nanoparticles. The movement of engine oil is influenced by the presence of Cu and TiO2. Various factors such as viscous dissipation, thermal radiation, heat flux model, joule heating, and heat generation affect the energy equation. Mathematical representations are used to describe permeability, entropy creation, and a flat moving surface with non-uniform elongating velocity. The numerical technique bvp4c is employed to solve complex differential equations and analyze the flow and heat-transferring facets of Cu-TiO2. The study concludes that temperature and heat transfer rate decrease due to certain limitations, but these fluids can be used with caution in applications requiring heat transfer control. The findings contribute to the understanding of engine and generator cooling systems, aircraft refrigeration systems, nuclear cooling systems, and other technologies.
JOURNAL OF MAGNETISM AND MAGNETIC MATERIALS
(2023)
Article
Computer Science, Artificial Intelligence
Iskandar Waini, Anuar Ishak, Ioan Pop
Summary: This study investigates the radiative and magnetohydrodynamic micropolar fluid flow over a stretching/shrinking sheet consisting of Al2O3 and Cu nanoparticles. Numerical results show that two solutions are obtained for a limited range, with one solution being physically reliable and stable.
NEURAL COMPUTING & APPLICATIONS
(2022)
Article
Thermodynamics
Tahir Naseem, Urooj Fatima, Mohammad Munir, Azeem Shahzad, Nasreen Kausar, Kottakkaran Sooppy Nisar, C. Ahamed Saleel, Mohamed Abbas
Summary: This study investigates the MHD boundary layer flow past a flat plate with radiation, joule heating, and viscous dissipation effects, considering variable temperature. The temperature variations and characteristics in the fluid are analyzed, and the impacts of temperature power coefficient, Prandtl number, Eckert number, and magnetic parameter are graphically presented.
CASE STUDIES IN THERMAL ENGINEERING
(2022)
Article
Mathematics, Applied
M. Ijaz Khan, Faris Alzahrani
Summary: This study focuses on the optimization of nanoparticles in thermal applications, with an emphasis on the impact of curvature and slip parameters on velocity changes and Bejan number increases.
APPLIED MATHEMATICS AND COMPUTATION
(2022)
Article
Thermodynamics
Haroun Ragueb, Antar Tahiri, Dounya Behnous, Belkacem Manser, Kamel Rachedi, Kacem Mansouri
Summary: This study investigates heat transfer and entropy generation in a microchannel subjected to differential heating, viscous dissipation, and Joule heating within a magnetohydrodynamic (MHD) fluid flow. The research findings reveal the discrepancy in Nusselt numbers and the impact of control parameters on entropy generation, providing important insights for heat transfer studies in microchannels.
INTERNATIONAL COMMUNICATIONS IN HEAT AND MASS TRANSFER
(2023)
Article
Thermodynamics
Wasim Jamshed, S. R. Mishra, P. K. Pattnaik, Kottakkaran Sooppy Nisar, S. Suriya Uma Devi, M. Prakash, Faisal Shahzad, Majid Hussain, V. Vijayakumar
Summary: This study investigated the heat transfer characteristics of Second grade fluid model in nanofluid flow using a single-phase model. The addition of nanoparticle volume fraction can affect the fluid temperature and entropy values. The heavier density of copper nanoparticles impedes the flow profile while also increasing the fluid temperature.
CASE STUDIES IN THERMAL ENGINEERING
(2021)
Article
Computer Science, Artificial Intelligence
Najiyah Safwa Khashi'ie, Nur Syahirah Wahid, Norihan Md Arifin, Ioan Pop
Summary: This paper investigates the MHD stagnation-point flow of Cu-Al2O3/H2O hybrid nanofluid on a convectively heated shrinking disk, taking into account suction, Joule heating, and viscous dissipation effects. Numerical solutions reveal the existence of two solutions, with the first solution being physically stable. The results show that an increase in suction and magnetic parameters enhances the heat transfer performance, while the Eckert and Biot numbers have no effect on the critical value. The temperature profile decreases with an increase in the velocity ratio parameter, Eckert and Biot numbers, while the velocity increases with an increase in the velocity ratio and magnetic parameters.
NEURAL COMPUTING & APPLICATIONS
(2022)
Article
Thermodynamics
Muhammad Rooman, Muhammad Jameel, Asifa Tassaddiq, Zahir Shah, Ahmed Alshehri, Poom Kumam
Summary: This study evaluates the flow of Cu-Water nanofluid across gradually stratified paraboloids of revolution and investigates the influence of various fluid properties and important factors on the flow. Heat transfer equations consider stratification, thermal emission, viscous and joule dissipation, while mass transfer equation investigates chemical reaction. The mathematical model and graphical results demonstrate the relationship between flow characteristics and several important parameters.
INTERNATIONAL COMMUNICATIONS IN HEAT AND MASS TRANSFER
(2022)
Article
Physics, Applied
Farhan Ahmed, Mazhar Iqbal
Summary: This study investigates the effects of viscous dissipation and Joule heating on electrically conducting MHD forced convection non-Newtonian power law nanofluid flow through an annular sector duct using a mathematical model and numerical simulation. The novelty of this study lies in considering the effects of Joule heating and viscous dissipation in the flow of power law nanofluid through an annular sector duct. The main objective is to explore the influence of Joule heating and viscous dissipation on hydro-thermal power law nanofluid.
INTERNATIONAL JOURNAL OF MODERN PHYSICS B
(2023)
Article
Engineering, Multidisciplinary
Bushra Khatoon Siddiqui, Samina Batool, Qazi Mahmood ul Hassan, M. Y. Malik
Summary: This research investigates the behavior of MHD two dimensional flow of Maxwell nanofluid with a focus on heat transfer phenomena. The analysis reveals that entropy generation increases with certain parameters during the flow.
AIN SHAMS ENGINEERING JOURNAL
(2021)
Article
Thermodynamics
Aamir Ali, A. Noreen, S. Saleem, A. F. Aljohani, M. Awais
Summary: The study investigates the influence of Cu-Al2O3MHD hybrid nanofluid on heat transfer and flow through mathematical modeling and computations, revealing a decrease in temperature and an increase in fluid velocity with increasing volume fraction. Additionally, the change in fluid temperature under heat source/sink conditions was examined.
JOURNAL OF THERMAL ANALYSIS AND CALORIMETRY
(2021)
Article
Engineering, Mechanical
M. Riaz Khan, Awatef Abidi, Jamel Madiouli, Kamel Guedri, A. M. Al-Bugami, T. H. Al-arabi, Zeyad Al-Zhour, Ahmed M. Galal
Summary: This study investigates the two-dimensional magnetohydrodynamics incompressible flow of nanofluid around a stretching surface, considering the impact of viscous dissipation and Joule heating. The results show that the increase in nanoparticles concentration and suction parameter decreases the velocity and temperature distribution, while the enhancement of Hartman number and nanoparticles concentration leads to a decrease in Nusselt number and skin friction coefficient.
PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART E-JOURNAL OF PROCESS MECHANICAL ENGINEERING
(2021)
Article
Engineering, Multidisciplinary
Khadija Rafique, Zafar Mahmood, Haifa Alqahtani, Sayed M. Eldin
Summary: The research aimed to investigate the impact of different shapes of nanoparticles on the entropy production of a water-alumina nanofluid. The results showed that the wall shear stress increases by almost 6.3% for increases in the volume fraction of nanoparticles from 0% to 2% and by 12.6% for increases from 0% to 4% in the region behind a stretching sheet. When the magnetic effect accounts for roughly 5 percent of the boundary layer flow, there is an approximately 16.4 percent increase in the rate of convective heat transfer. The frictional force and thermal entropy produced by nanofluids with blade-, brick-, and Os-shaped NPs were lower than that produced by nanofluids with platelet-shaped NPs. On the cold fluid side, the nanofluid with Os-shaped NPs develops thermal entropy at a faster rate than those with brick-, blade-, cylinder-, and platelet-shaped NPs.
ALEXANDRIA ENGINEERING JOURNAL
(2023)
Article
Physics, Multidisciplinary
Xiaoyu Shi, Jian Zhang, Xia Jiang, Juan Chen, Wei Hao, Bo Wang
Summary: This study presents a novel framework using offline reinforcement learning to improve energy consumption in road transportation. By leveraging real-world human driving trajectories, the proposed method achieves significant improvements in energy consumption. The offline learning approach demonstrates generalizability across different scenarios.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2024)
Article
Physics, Multidisciplinary
Junhyuk Woo, Soon Ho Kim, Hyeongmo Kim, Kyungreem Han
Summary: Reservoir computing (RC) is a new machine-learning framework that uses an abstract neural network model to process information from complex dynamical systems. This study investigates the neuronal and network dynamics of liquid state machines (LSMs) using numerical simulations and classification tasks. The findings suggest that the computational performance of LSMs is closely related to the dynamic range, with a larger dynamic range resulting in higher performance.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2024)
Article
Physics, Multidisciplinary
Yuwei Yang, Zhuoxuan Li, Jun Chen, Zhiyuan Liu, Jinde Cao
Summary: This paper proposes an extreme learning machine (ELM) algorithm based on residual correction and Tent chaos sequence (TRELM-DROP) for accurate prediction of traffic flow. The algorithm reduces the impact of randomness in traffic flow through the Tent chaos strategy and residual correction method, and avoids weight optimization using the iterative method. A DROP strategy is introduced to improve the algorithm's ability to predict traffic flow under varying conditions.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2024)
Article
Physics, Multidisciplinary
Chengwei Dong, Min Yang, Lian Jia, Zirun Li
Summary: This work presents a novel three-dimensional system with multiple types of coexisting attractors, and investigates its dynamics using various methods. The mechanism of chaos emergence is explored, and the periodic orbits in the system are studied using the variational method. A symbolic coding method is successfully established to classify the short cycles. The flexibility and validity of the system are demonstrated through analogous circuit implementation. Various chaos-based applications are also presented to show the system's feasibility.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2024)
Article
Physics, Multidisciplinary
Viorel Badescu
Summary: This article discusses the maximum work extraction from confined particles energy, considering both reversible and irreversible processes. The results vary for different types of particles and conditions. The concept of exergy cannot be defined for particles that undergo spontaneous creation and annihilation. It is also noted that the Carnot efficiency is not applicable to the conversion of confined thermal radiation into work.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2024)
Article
Physics, Multidisciplinary
P. M. Centres, D. J. Perez-Morelo, R. Guzman, L. Reinaudi, M. C. Gimenez
Summary: In this study, a phenomenological investigation of epidemic spread was conducted using a model of agent diffusion over a square region based on the SIR model. Two possible contagion mechanisms were considered, and it was observed that the number of secondary infections produced by an individual during its infectious period depended on various factors.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2024)
Article
Physics, Multidisciplinary
Zuan Jin, Minghui Ma, Shidong Liang, Hongguang Yao
Summary: This study proposes a differential variable speed limit (DVSL) control strategy considering lane assignment, which sets dynamic speed limits for each lane to attract vehicle lane-changing behaviors before the bottleneck and reduce the impact of traffic capacity drop. Experimental results show that the proposed DVSL control strategy can alleviate traffic congestion and improve efficiency.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2024)
Article
Physics, Multidisciplinary
Matthew Dicks, Andrew Paskaramoorthy, Tim Gebbie
Summary: In this study, we investigate the learning dynamics of a single reinforcement learning optimal execution trading agent when it interacts with an event-driven agent-based financial market model. The results show that the agents with smaller state spaces converge faster and are able to intuitively learn to trade using spread and volume states. The introduction of the learning agent has a robust impact on the moments of the model, except for the Hurst exponent, which decreases, and it can increase the micro-price volatility as trading volumes increase.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2024)
Article
Physics, Multidisciplinary
Zhouzhou Yao, Xianyu Wu, Yang Yang, Ning Li
Summary: This paper developed a cooperative lane-changing decision system based on digital technology and indirect reciprocity. By introducing image scoring and a Q-learning based reinforcement learning algorithm, drivers can continuously evaluate gains and adjust their strategies. The study shows that this decision system can improve driver cooperation and traffic efficiency, achieving over 50% cooperation probability under any connected vehicles penetration and traffic density, and reaching 100% cooperation probability under high penetration and medium to high traffic density.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2024)
Article
Physics, Multidisciplinary
Josephine Nanyondo, Henry Kasumba
Summary: This paper presents a multi-class Aw-Rascle (AR) model with area occupancy expressed in terms of vehicle class proportions. The qualitative properties of the proposed equilibrium velocity and the stability conditions of the model are established. The numerical results show the effect of proportional densities on the flow of vehicle classes, indicating the realism of the proposed model.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2024)
Article
Physics, Multidisciplinary
Oliver Smirnov
Summary: This study proposes a new method for simultaneously estimating the parameters of the 2D Ising model. The method solves a constrained optimization problem, where the objective function is a pseudo-log-likelihood and the constraint is the Hamiltonian of the external field. Monte Carlo simulations were conducted using models of different shapes and sizes to evaluate the performance of the method with and without the Hamiltonian constraint. The results demonstrate that the proposed estimation method yields lower variance across all model shapes and sizes compared to a simple pseudo-maximum likelihood.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2024)
Article
Physics, Multidisciplinary
Przemyslaw Chelminiak
Summary: The study investigates the first-passage properties of a non-linear diffusion equation with diffusivity dependent on the concentration/probability density through a power-law relationship. The survival probability and first-passage time distribution are determined based on the power-law exponent, and both exact and approximate expressions are derived, along with their asymptotic representations. The results pertain to diffusing particles that are either freely or harmonically trapped. The mean first-passage time is finite for the harmonically trapped particle, while it is divergent for the freely diffusing particle.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2024)
Article
Physics, Multidisciplinary
Hidemaro Suwa
Summary: The choice of transition kernel is crucial for the performance of the Markov chain Monte Carlo method. A one-parameter rejection control transition kernel is proposed, and it is shown that the rejection process plays a significant role in determining the sampling efficiency.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2024)
Article
Physics, Multidisciplinary
Xudong Wang, Yao Chen
Summary: This article investigates the joint influence of expanding medium and constant force on particle diffusion. By starting from the Langevin picture and introducing the effect of external force in two different ways, two models with different force terms are obtained. Detailed analysis and derivation yield the Fokker-Planck equations and moments for the two models. The sustained force behaves as a decoupled force, while the intermittent force changes the diffusion behavior with specific effects depending on the expanding rate of the medium.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2024)