Article
Mathematics, Applied
Dipunja Gohain, Bijoy Krishna Taid, Nazibuddin Ahmed
Summary: In this study, the MHD water-based nanofluid flow past an impulsively started infinite vertical plate embedded in a porous medium is investigated, considering ramped velocity and concentration, as well as the presence of Hall effect, thermal radiation, chemical reaction, heat source/sink, and thermal diffusion. The governing equations are solved using the Laplace transform method, and the effects of various embedded parameters on velocity, temperature, and concentration profiles are analyzed through graphical interpretation. The variations of the Nusselt number, Sherwood number, and skin friction are also studied. It is found that higher nanoparticle volume fractions lead to reduced primary and secondary velocities and concentration, while increasing the temperature. Thermal diffusion increases the fluid concentration, and the rate of momentum transfer decreases with an increase in the Hall current parameter.
ZAMM-ZEITSCHRIFT FUR ANGEWANDTE MATHEMATIK UND MECHANIK
(2023)
Article
Thermodynamics
Yundong Tang, Rodolfo C. C. Flesch, Tao Jin, Minhua He
Summary: Magnetic hyperthermia has the potential to induce apoptosis in malignant cells while ensuring the safety of normal cells by exposing bio-tissue containing magnetic nanoparticles to a specific treatment temperature range under a magnetic field. This paper develops a theoretical and mathematical model to evaluate apoptosis behavior in a proposed geometric model for therapy, considering the impact of magnetic and concentration fields on heat production of MNPs and subsequent apoptosis in tumor regions. The study suggests that the proposed approach can effectively predict the apoptosis situation of malignant cells by coupling different physical fields during therapy, and may have implications for the planning of nanofluid hyperthermia.
INTERNATIONAL JOURNAL OF HEAT AND MASS TRANSFER
(2021)
Article
Multidisciplinary Sciences
Muhammad Awais, Saeed Ehsan Awan, Muhammad Asif Zahoor Raja, Muhammad Shoaib
Summary: Analysis was conducted on the nonuniform heat immersion phenomenon in bio-convective rheology of nanoparticles combined with gyro-tactic microorganisms, incorporating inclined magnetic field effects, heat and mass transfer effects. Mathematical modeling was used for analysis, with error analysis and verification of results. Numerical values of various physical quantities were presented in tabular and chart form.
ARABIAN JOURNAL FOR SCIENCE AND ENGINEERING
(2021)
Article
Thermodynamics
Lei Shi, Wenliang Tao, Nianben Zheng, Tian Zhou, Zhiqiang Sun
Summary: This study focuses on the thermal and fluidic properties of magnetic nanofluid and analyzes the coupling factors between magnetic field, thermal exchange, fluidity, and nanoparticle concentration. The results show that the magnetic field-enhanced method can improve the thermal exchange efficiency, while entropy generation is also enhanced. This study is significant for the convection performance of magnetic nanofluid.
INTERNATIONAL JOURNAL OF THERMAL SCIENCES
(2023)
Article
Engineering, Multidisciplinary
Yundong Tang, Jian Zou, Rodolfo C. C. Flesch, Tao Jin
Summary: This study develops a poroelastic model to evaluate the effect of syringe needle size and infusion rate on backflow. The results demonstrate that tissue deformation and infusion pressure are the fundamental reasons for obtaining an irregular solution distribution.
APPLIED MATHEMATICAL MODELLING
(2023)
Article
Multidisciplinary Sciences
Fuzhang Wang, Shafiq Ahmad, Qasem Al Mdallal, Maha Alammari, Muhammad Naveed Khan, Aysha Rehman
Summary: This article mainly focuses on the influence of chemical reaction slip condition on the unsteady three-dimensional Maxwell bio-convective nanomaterial liquid flow towards an exponentially expanding surface. The study examines the changes in temperature, velocity, microorganism, and concentration field through numerical calculations and graphical evaluation. The results show that the involvement of unsteadiness parameter restricts the transition from laminar to turbulent flow, while the velocity slip parameter has a decreasing effect on velocity components.
SCIENTIFIC REPORTS
(2022)
Article
Multidisciplinary Sciences
Adnan, Sheikh Irfan Ullah Khan, Umar Khan, Naveed Ahmed, Syed Tauseef Mohyud-Din, Ilyas Khan, Kottakkaran Sooppy Nisar
Summary: Aluminum Alloys AA7072 and AA705 have significant thermal, physical, and mechanical characteristics, making them widely used in aerospace, aircraft parts, and building testing. The study analyzed methanol suspended in AA7072 and AA7075 alloys under various physical flow conditions using RK and shooting algorithm, with reliable results obtained.
SCIENTIFIC REPORTS
(2021)
Article
Thermodynamics
Yun-Dong Tang, Jian Zou, Rodolfo C. C. Flesch, Tao Jin
Summary: Magnetic hyperthermia is an alternative cancer treatment method that involves controlling treatment temperature to damage malignant cells. This study proposes three injection strategies with low rate to improve the distribution of magnetic nanoparticles and enhance the treatment temperature distribution and thermal damage inside malignant tissue. The simulation results demonstrate the effectiveness of these injection strategies in improving physical field distribution for nanofluid concentration, treatment temperature, and thermal damage inside malignant tissue.
INTERNATIONAL COMMUNICATIONS IN HEAT AND MASS TRANSFER
(2022)
Article
Engineering, Mechanical
Priyajit Mondal, T. R. Mahapatra
Summary: This study investigates the double diffusive, MHD, mixed convection flow of Al2O3-water nanofluid in a trapezoidal enclosure, considering various inclination angles and aspect ratios. The research focuses on entropy generation related to heat transfer and mass transfer, finding that lower Richardson numbers lead to reduced entropy generation.
INTERNATIONAL JOURNAL OF MECHANICAL SCIENCES
(2021)
Article
Thermodynamics
Taher Halawa, Andrew S. Tanious
Summary: Numerical simulations were conducted to find the best magnetic field arrangement for maximizing heat exchange performance of Fe3O4-water magnetic nanofluid. The orientation, number, and distribution of magnetic field were studied, and the optimum design was tested under different conditions. Results showed that placing N-N oriented magnets and increasing magnetic flux density between magnets achieved the best design. Increasing magnetic flux density resulted in higher average Nusselt number and pressure drop. The effect of increasing magnetic nanoparticles volume fraction was more significant at low Reynolds number. The optimum design with an average magnetic flux density of 1000 Gauss and magnetic nanoparticles volume fraction of 4% achieved a 16.44%-24.46% increase in average Nusselt number compared to the design without magnetic field.
INTERNATIONAL JOURNAL OF THERMAL SCIENCES
(2023)
Article
Engineering, Chemical
Rasool Alizadeh, Javad Mohebbi Najm Abad, Abolfazl Fattahi, Mehrdad Mesgarpour, Mohammad Hossein Doranehgard, Qingang Xiong, Nader Karimi
Summary: This study investigates transport phenomena in a hybrid or single-particle nanofluid over a conical body embedded inside a porous medium. Using a similarity technique, the researchers simulated transport processes including mixed convection, species transfer, and cell transfer. Machine learning was applied to predict a wide range of parametric variations, and the simulation data were used to build an intelligent tool based on an artificial neural network. The findings demonstrate the abilities of combining numerical simulations with machine learning to significantly extend and enrich analysis of problems with large numbers of variables.
INDUSTRIAL & ENGINEERING CHEMISTRY RESEARCH
(2022)
Article
Thermodynamics
Xiangman Zhou, Zichuan Fu, Xing Zhou, Xingwang Bai, Qihua Tian, Junjian Fu, Haiou Zhang
Summary: This study introduced an external deflection magnetic field into the wire arc additive manufacturing process and conducted a numerical simulation to investigate its effect on the morphology of the deposition layer and the overlapping flatness. The results showed that the external magnetic field can improve the deposition morphology and the overlapping flatness.
INTERNATIONAL JOURNAL OF HEAT AND MASS TRANSFER
(2024)
Article
Engineering, Multidisciplinary
M. M. Abdullah, Hasan B. Albargi, Emad Hasani Malekshah, Mohsen Sharifpur
Summary: In this study, the mixed convection of nanofluid flow in a closed enclosure is analyzed using the Lattice Boltzmann method. The effects of the magnetic field and wall baffles on the flow and heat transfer are investigated. The results show that increasing the Richardson number weakens the vortex inside the enclosure and reduces the Nusselt number, while increasing the wall baffles enhances the Nusselt number on the upper wall but weakens the vortex inside. In addition, enhancing the Hartmann number weakens the vortex and reduces the heat transfer on both walls, and increasing the angle of the magnetic field improves the heat transfer rate in the enclosure.
ENGINEERING ANALYSIS WITH BOUNDARY ELEMENTS
(2023)
Review
Chemistry, Multidisciplinary
Hengwei Wang, Keliang Wang, Yayu Zuo, Manhui Wei, Pucheng Pei, Pengfei Zhang, Zhuo Chen, Nuo Shang
Summary: Metal-air batteries are considered as a promising source of electrochemical energy due to their excellent characteristics and low cost. However, commercialization is hindered by slow kinetics, corrosion, and dendrite growth. The use of magnetic fields has shown promise in improving the performance of these batteries by enhancing mass transfer, charge transfer, and electrocatalysis.
ADVANCED FUNCTIONAL MATERIALS
(2023)
Article
Green & Sustainable Science & Technology
Zhigang Liu, Youwen Yang, Cijun Shuai, Chongxian He
Summary: Magnetic field treatment of Fe-Ga alloy can influence its degradation behavior, resulting in faster corrosion rate and lower corrosion resistance.
SUSTAINABLE MATERIALS AND TECHNOLOGIES
(2023)
Article
Computer Science, Interdisciplinary Applications
Zulqurnain Sabir, Muhammad Asif Zahoor Raja, Muhammad Shoaib, R. Sadat, Mohamed R. Ali
Summary: The current study aims to present a novel design of a sixth-order nonlinear Emden-Fowler system and provides detailed characteristics for each type of the system. Examples of the designed system are solved using a supervised neural network approach, and a reference dataset is established. The results of the study show that the proposed method is efficient, correct, and effective in reducing mean square error and improving correlation.
ENGINEERING WITH COMPUTERS
(2023)
Article
Mathematics, Applied
Yu-Ming Chu, Seemab Bashir, Muhammad Ramzan, Muhammad Yousaf Malik
Summary: This study examines the impact of unsteady viscous flow in a squeezing channel and investigates the flow and heat transfer mechanism of different shapes of silver-gold hybrid nanofluid particles in the base fluid. The numerical solution and parameter analysis reveal that the Yamada-Ota model of the Hybrid nanofluid has a higher temperature and velocity profile, and the performance of hybrid nanoparticles is superior to that of common nanofluids.
MATHEMATICAL METHODS IN THE APPLIED SCIENCES
(2023)
Article
Multidisciplinary Sciences
Ammara Mehmood, Muhammad Asif Zahoor Raja
Summary: The application of evolutionary computing paradigm-based heuristics for system modeling and parameter estimation of complex nonlinear systems has been widely explored. This study investigates the use of weighted differential evolution (WDE) in estimating the parameters of Hammerstein-Wiener model (HWM) and compares it with state-of-the-art methods. The HWM parameters are estimated using the WDE and genetic algorithms (GAs) heuristics, and the worth and value of the designed WDE algorithm is demonstrated through extensive graphical and numerical comparisons.
JOURNAL OF ADVANCED RESEARCH
(2023)
Article
Computer Science, Artificial Intelligence
Zulqurnain Sabir, Mohamed R. Ali, Muhammad Asif Zahoor Raja, R. Sadat, Dumitru Baleanu
Summary: The present study introduces a novel heuristic computing design for solving the second kind of Three-point singular boundary value problems (TPS-BVPs) by combining Feed forward Gudermannian neural networks (GNN) with Genetic algorithms (GA) and Active-set method (ASM). The proposed intelligent computing solver, FF-GNN-GAASM, is integrated into the hidden layer structure of FF-GNN systems, optimizing the error based Merit function (MF) with the hybrid-combined heuristics of GAASM. The performance of FF-GNN-GAASM is evaluated through statistical assessments, demonstrating consistent stability, accuracy, and convergence.
EVOLUTIONARY INTELLIGENCE
(2023)
Article
Engineering, Multidisciplinary
Qiliang Chen, Zulqurnain Sabir, Muhammad Asif Zahoor Raja, Wei Gao, Haci Mehmet Baskonus
Summary: The purpose of this investigation is to numerically study the fractional order economic and environmental mathematical model (FO-EEMM). The study aims to find more realistic results of the FO-EEMM with non-integer and fractional order derivatives. The FO-EEMM is divided into three aspects: control accomplishment cost, capability of manufacturing elements, and diagnostics cost of technical exclusion. The FO-EEMM's solution is presented numerically using scaled conjugate gradient neural networks (SCGNNs). Three cases based on the FO-EEMM have been examined to evaluate numerical performances.
ALEXANDRIA ENGINEERING JOURNAL
(2023)
Article
Thermodynamics
Zeeshan Ikram Butt, Iftikhar Ahmad, Muhammad Shoaib, Hira Ilyas, Muhammad Asif Zahoor Raja
Summary: This study investigates the magnetohydrodynamic effects and radiation effects on two-dimensional nanofluid boundary layer flow in a porous medium using inverse multiquadric radial basis neural networks (IMQ-RBNNs). A new computational approach combining artificial neural networks (ANNs) with genetic algorithms (GAs) and sequential quadratic programming (SQP) is used. The dynamical properties of the nanofluid, including velocity, temperature, and mass concentration, are analyzed by varying physical parameters. The numerical results obtained through the IMQ-RBNNs based solver optimized with GASQP algorithm are validated through graphical illustrations and tables.
INTERNATIONAL COMMUNICATIONS IN HEAT AND MASS TRANSFER
(2023)
Article
Chemistry, Physical
Zeeshan Ikram Butt, Iftikhar Ahmad, Hira Ilyas, Muhammad Shoaib, Muhammad Asif Zahoor Raja
Summary: This research investigates the magnetohydrodynamics (MHD) Casson nanofluid flow in a porous medium along a stretchable surface with different slips using artificial neural networks (ANNs) and inverse multiquadric (IMQ) radial basis function (RBF) as an activation function. The effects of various parameters on the velocity, temperature, and nanofluid concentration are analyzed through graphs. The proposed solver is validated through boxplot analysis, histograms, and cumulative distribution function (CDF) plots.
INTERNATIONAL JOURNAL OF HYDROGEN ENERGY
(2023)
Article
Physics, Applied
Syed Ali Asghar, Shafaq Naz, Muhammad Asif Zahoor Raja
Summary: The purpose of this research is to utilize a Bayesian solver with neural networks to determine numerical solutions of functional differential equations arising in quantum calculus models. The difficulty in solving functional differential equations with discrete versions is overcome by converting them into recurrence relations and generating datasets for neural networks. The proposed technique is confirmed to be accurate and stable through comprehensive statistical analysis, including mean squared error and regression analysis. The convergence and reliability of the technique are further supported by histogram, training state, and correlation plots, as well as by comparison with a reference solution and absolute error analysis.
INTERNATIONAL JOURNAL OF MODERN PHYSICS B
(2023)
Article
Mathematics, Applied
Ajed Akbar, Hakeem Ullah, Kottakkaran Sooppy Nisar, Muhammad Asif Zahoor Raja, Muhammad Shoaib, Saeed Islam
Summary: This study examines the Buongiorno model for the MHD nano-fluid flow through a rotating disk under the influence of partial slip effects using the LMB-NNS technique. The recommended approach demonstrates high accuracy and has various applications.
ZAMM-ZEITSCHRIFT FUR ANGEWANDTE MATHEMATIK UND MECHANIK
(2023)
Article
Physics, Multidisciplinary
Saeed Ehsan Awan, Muhammad Awais, Muhammad Asif Zahoor Raja, Saeed ur Rehman, Chi-Min Shu
Summary: Artificial intelligence techniques are widely used in engineering and technology to enhance efficiency in business and society. This study explores the application of AI-based numerical computing to investigate the heat and mass transport improvement of nanofluids. Mathematical modeling and numerical simulations are conducted to analyze the effect of various parameters on temperature and velocity fields. Bayesian regularization knack-based networks are designed and evaluated for their accuracy and performance in approximating the solution dynamic of nanofluidic models.
EUROPEAN PHYSICAL JOURNAL PLUS
(2023)
Article
Computer Science, Interdisciplinary Applications
Nabeela Anwar, Iftikhar Ahmad, Adiqa Kausar Kiani, Muhammad Shoaib, Muhammad Asif Zahoor Raja
Summary: In this article, the dynamics of the non-linear tumor-immune delayed (TID) model is analyzed using neural networks with back propagation Levenberg Marquardt approach (NNLMA). The model captures the interaction among tumor cells and the immune system, with delays representing various factors including molecule formation, cell growth, segregation, and transportation. The solution of the model is determined through the use of explicit Runge-Kutta method (RKM) and randomized data samples for training and testing.
COMPUTER METHODS IN BIOMECHANICS AND BIOMEDICAL ENGINEERING
(2023)
Article
Mathematics, Interdisciplinary Applications
Muhammad Shoaib, Rafia Tabassum, Kottakkaran Sooppy Nisar, Muhammad Asif Zahoor Raja, Farooq Ahmed Shah, Mohammed S. Alqahtani, C. Ahamed Saleel, H. M. Almohiy
Summary: This study investigates the pine wilt disease model (PWDM) using a hybrid bio-inspired algorithm. The artificial neural networks-based genetic algorithm (ANNs-GA) is used for global search, and sequential quadratic programming (SQP) serves as the local search framework. The model consists of two populations, host (h) and vector (v), each having different classes. The proposed ANNs-GASQP solver shows stability, robustness, and effectiveness with high accuracy.
FRACTALS-COMPLEX GEOMETRY PATTERNS AND SCALING IN NATURE AND SOCIETY
(2023)
Article
Computer Science, Information Systems
Narongsak Yotha, Qusain Hiader, Zulqurnain Sabir, Muhammad Asif Zahoor Raja, Salem Ben Said, Qasem Al-Mdallal, Thongchai Botmart, Wajaree Weera
Summary: This study aims to solve the nonlinear fractional-order mathematical model of myeloma bone disease (MBD) by using the normal and dysregulated bone remodeling. Fractional-order derivatives are used to numerically solve the disease model for more accurate performance. The focus of the model is on the interactions between bone resorption or osteoclasts (OC) and bone formation or osteoblasts (OB).
CMC-COMPUTERS MATERIALS & CONTINUA
(2023)
Article
Computer Science, Information Systems
Sakda Noinang, Zulqurnain Sabir, Muhammad Asif Zahoor Raja, Soheil Salahshour, Wajaree Weera, Thongchai Botmart
Summary: The investigations aim to solve the fractional order HBV differential infection system (FO-HBV-DIS) with the response of antibody immune using the optimization based stochastic schemes of the Levenberg-Marquardt backpropagation neural networks (LMBNNs). The FO-HBV-DIS with the response of antibody immune is categorized into five dynamics: healthy hepatocytes, capsids, infected hepatocytes, free virus, and antibodies. Through numerical tests with three different fractional order variants, the nonlinear FO-HBV-DIS with the response of antibody immune is solved. The stochastic LMBNNs procedures in conjunction with the Adams-Bashforth-Moulton approach are utilized for numerical simulations and comparison of the results.
CMC-COMPUTERS MATERIALS & CONTINUA
(2023)
Article
Engineering, Multidisciplinary
Li Yan, Zulqurnain Sabir, Esin Ilhan, Muhammad Asif Zahoor Raja, Wei Gao, Haci Mehmet Baskonus
Summary: This study presents a computational heuristic design based on the nonlinear Lienard model, using the efficiency of artificial neural networks (ANNs) and the hybridization procedures of global and local search approaches. The designed procedures of ANNs along with GA-SQPS are applied for three highly nonlinear differential models. The outcomes of the designed procedures are compared to verify their correctness, viability and efficacy.
CMES-COMPUTER MODELING IN ENGINEERING & SCIENCES
(2023)
