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A special issue of Nanomaterials (ISSN 2079-4991). This special issue belongs to the section "Theory and Simulation of Nanostructures".

Deadline for manuscript submissions: closed (30 November 2022) | Viewed by 11881

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Special Issue Editor

Dr. Malik Zaka Ullah

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Guest Editor

Department of Mathematics, Faculty of Science, King Abdulaziz University, Jeddah 21589, Saudi Arabia
Interests: nanofluids flow; hybrid and ternary hybrid nanofluids; nanofluids used as a medication; heat and mass transfer in nanofluids

Special Issue Information

Dear Colleagues,

This Special Issue of Nanomaterials will cover the advancement of nanofluids for the enhancement of heat transfer and drug delivery applications. Nanofluids are an advanced form of energy resource and are used to control energy consumption. The thermal conductivity of base fluids (water, engine oil, ethylene glycol, etc.) is comparatively smaller, and they need extra energy and time for use in industrial applications. Therefore, small-sized nanoparticles (1–100 nanometers of metal oxides and carbides) are stably dispersed in the base solvents to enhance the thermal efficiency of the base fluids. These nanofluids are used in energy devices such as solar collectors, heat exchangers, heat pipes, and so on.

Furthermore, nanofluids are working as a medication for various diseases, such as cancer therapy. For example, copper oxide, titanium oxide, silver, and gold nanoparticles are working as medications. Modeling is one of the important phenomena in the field of science.

Mathematical models are required for the transportation of the nanofluids in various devices including, closed channels, free surfaces, disks, cones, cylinders, and so on. Due to these important applications, this Special Issue calls for research and review papers on the application of nanofluids flow for heat transfer enhancement applications and medication. The researchers are welcome to submit research articles.

Dr. Malik Zaka Ullah
Guest Editor

Manuscript Submission Information

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Keywords

nanofluids
hybrid and ternary hybrid nanofluids
heat and mass transfer
magnetic field
porous medium
thermal radiations
nanofluids simulations
analytical and numerical methods for nanofluids

Published Papers (7 papers)

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Research

13 pages, 3170 KiB

Open AccessArticle

Irreversibility Marangoni Tri-Hybrid Nanoflow Analysis for Thermal Enhancement Applications

by Malik Zaka Ullah

Nanomaterials 2023, 13(3), 423; https://doi.org/10.3390/nano13030423 - 19 Jan 2023

Cited by 2 | Viewed by 1051

Abstract

Increasing heat transfer is an important part of industrial, mechanical, electrical, thermal, and biological sciences. The aim of this study is to increase the thermal competency of a conventional fluid by using a ternary hybrid nanofluid. A magnetic field and thermal radiation are used to further improve the thermal conductivity of the base fluid. Irreversibility is analyzed under the influence of the embedded parameters. The basic equations for the ternary hybrid nanofluids are transformed from Partial Differential Equations (PDEs) to Ordinary Differential Equations (ODEs) using the similarity concept. The Marangoni convection idea is used in the mathematical model for the temperature difference between the two media: the surface and fluid. The achieved results are provided and discussed. The results show that ternary hybrid nanofluids are more suitable as heat-transmitted conductors than conventional fluids. Full article

(This article belongs to the Special Issue Advances in Modeling and Simulation of Nanofluid Flows)

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22 pages, 1277 KiB

Open AccessArticle

Coupled Effects of Using Magnetic Field, Rotation and Wavy Porous Layer on the Forced Convection of Hybrid Nanoliquid Flow over 3D-Backward Facing Step

by Kaouther Ghachem, Fatih Selimefendigil, Badr M. Alshammari, Chemseddine Maatki and Lioua Kolsi

Nanomaterials 2022, 12(14), 2466; https://doi.org/10.3390/nano12142466 - 18 Jul 2022

Cited by 1 | Viewed by 1244

Abstract

In the present study, the effects of using a corrugated porous layer on the forced convection of a hybrid nanofluid flow over a 3D backward facing step are analyzed under the coupled effects of magnetic field and surface rotation. The thermal analysis is conducted for different values of the Reynolds number (Re between 100 and 500), the rotational Reynolds number (Rew between 0 and 2000), the Hartmann number (Ha between 0 and 15), the permeability of the porous layer (the Darcy number, Da between

10^{- 5}

and

10^{- 2}

) and the amplitude (ax between 0.01 ap and 0.7 ap) and wave number (N between 1 and 16) of the porous layer corrugation. When rotations are activated, the average Nusselt number (Nu) and pressure coefficient values rise, while the increment of the latter is less. The increment in the average Nu is higher for the case with a higher permeability of the layer. When the corrugation amplitude and wave number are increased, favorable impacts of the average Nu are observed, but at the same time pressure coefficients are increased. Successful thermal performance estimations are made by using a neural-based modeling approach with a four input-two output system. Full article

(This article belongs to the Special Issue Advances in Modeling and Simulation of Nanofluid Flows)

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18 pages, 1729 KiB

Open AccessArticle

Heat Transfer Analysis of Nanofluid Flow in a Rotating System with Magnetic Field Using an Intelligent Strength Stochastic-Driven Approach

by Kamsing Nonlaopon, Naveed Ahmad Khan, Muhammad Sulaiman, Fahad Sameer Alshammari and Ghaylen Laouini

Nanomaterials 2022, 12(13), 2273; https://doi.org/10.3390/nano12132273 - 1 Jul 2022

Cited by 7 | Viewed by 1582

Abstract

This paper investigates the heat transfer of two-phase nanofluid flow between horizontal plates in a rotating system with a magnetic field and external forces. The basic continuity and momentum equations are considered to formulate the governing mathematical model of the problem. Furthermore, certain similarity transformations are used to reduce a governing system of non-linear partial differential equations (PDEs) into a non-linear system of ordinary differential equations. Moreover, an efficient stochastic technique based on feed-forward neural networks (FFNNs) with a back-propagated Levenberg–Marquardt (BLM) algorithm is developed to examine the effect of variations in various parameters on velocity, gravitational acceleration, temperature, and concentration profiles of the nanofluid. To validate the accuracy, efficiency, and computational complexity of the FFNN–BLM algorithm, different performance functions are defined based on mean absolute deviations (MAD), error in Nash–Sutcliffe efficiency (ENSE), and Theil’s inequality coefficient (TIC). The approximate solutions achieved by the proposed technique are validated by comparing with the least square method (LSM), machine learning algorithms such as NARX-LM, and numerical solutions by the Runge–Kutta–Fehlberg method (RKFM). The results demonstrate that the mean percentage error in our solutions and values of ENSE, TIC, and MAD is almost zero, showing the design algorithm’s robustness and correctness. Full article

(This article belongs to the Special Issue Advances in Modeling and Simulation of Nanofluid Flows)

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21 pages, 3288 KiB

Open AccessArticle

Level-Set Interface Description Approach for Thermal Phase Change of Nanofluids

by Ali Yahyaee, Amir Sajjad Bahman, Klaus Olesen and Henrik Sørensen

Nanomaterials 2022, 12(13), 2228; https://doi.org/10.3390/nano12132228 - 29 Jun 2022

Cited by 2 | Viewed by 1232

Abstract

Simulations of thermally driven phase change phenomena of nanofluids are still in their infancy. Locating the gas–liquid interface location as precisely as possible is one of the primary problems in simulating such flows. The VOF method is the most applied interface description method in commercial and open-source CFD software to simulate nanofluids’ thermal phase change. Using the VOF method directs to inaccurate curvature calculation, which drives artificial flows (numerical non-physical velocities), especially in the vicinity of the gas–liquid interface. To recover accuracy in simulation results by VOF, a solver coupling VOF with the level-set interface description method can be used, in which the VOF is employed to capture the interface since it is a mass conserving method and the level-set is employed to calculate the curvature and physical quantities near the interface. We implemented the aforementioned coupled level-set and VOF (CLSVOF) method within the open-source OpenFOAM

^{®}

framework and conducted a comparative analysis between CLSVOF and VOF (the default interface capturing method) to demonstrate the CLSVOF method’s advantages and disadvantages in various phase change scenarios. Using experimental mathematical correlations from the literature, we consider the effect of nanoparticles on the base fluid. Results shows that the new inferred technique provides more precise curvature calculation and greater agreement between simulated and analytical/benchmark solutions, but at the expense of processing time. Full article

(This article belongs to the Special Issue Advances in Modeling and Simulation of Nanofluid Flows)

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15 pages, 3227 KiB

Open AccessArticle

Hybrid Nanofluid Flow Induced by an Oscillating Disk Considering Surface Catalyzed Reaction and Nanoparticles Shape Factor

by Muhammad Ramzan, Saima Riasat, Saleh Fahad Aljurbua, Hassan Ali S. Ghazwani and Omar Mahmoud

Nanomaterials 2022, 12(11), 1794; https://doi.org/10.3390/nano12111794 - 24 May 2022

Cited by 14 | Viewed by 2183

Abstract

Lately, a new class of nanofluids, namely hybrid nanofluids, has been introduced that performs much better compared with the nanofluids when a healthier heat transfer rate is the objective of the study. Heading in the same direction, the present investigation accentuates the unsteady hybrid nanofluid flow involving CuO, Al₂O₃/C₂H₆O₂ achieved by an oscillating disk immersed in the porous media. In a study of the homogeneous and heterogeneous reactions, the surface catalyzed reaction was also considered to minimize the reaction time. The shape factors of the nanoparticles were also taken into account, as these play a vital role in assessing the thermal conductivity and heat transfer rate of the system. The assumed model is presented mathematically in the form of partial differential equations. The system is transformed by invoking special similarity transformations. The Keller Box scheme was used to obtain numerical and graphical results. It is inferred that the blade-shaped nanoparticles have the best thermal conductivity that boosts the heat transfer efficiency. The oscillation and surface-catalyzed chemical reactions have opposite impacts on the concentration profile. This analysis also includes a comparison of the proposed model with a published result in a limiting case to check the authenticity of the presented model. Full article

(This article belongs to the Special Issue Advances in Modeling and Simulation of Nanofluid Flows)

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22 pages, 3022 KiB

Open AccessArticle

A Benchmark Evaluation of the isoAdvection Interface Description Method for Thermally–Driven Phase Change Simulation

by Ali Yahyaee, Amir Sajjad Bahman and Henrik Sørensen

Nanomaterials 2022, 12(10), 1665; https://doi.org/10.3390/nano12101665 - 13 May 2022

Cited by 3 | Viewed by 1631

Abstract

A benchmark study is conducted using isoAdvection as the interface description method. In different studies for the simulation of the thermal phase change of nanofluids, the Volume of Fluid (VOF) method is a contemporary standard to locate the interface position. One of the main drawbacks of VOF is the smearing of the interface, leading to the generation of spurious flows. To solve this problem, the VOF method can be supplemented with a recently introduced geometric method called isoAdvection. We study four benchmark cases that show how isoAdvection affects the simulation results and expose its relative strengths and weaknesses in different scenarios. Comparisons are made with VOF employing the Multidimensional Universal Limiter for Explicit Solution (MULES) limiter and analytical data and experimental correlations. The impact of nanoparticles on the base fluid are considered using empirical equations from the literature. The benchmark cases are 1D and 2D boiling and condensation problems. Their results show that isoAdvection (with isoAlpha reconstruct scheme) delivers a faster solution than MULES while maintaining nearly the same accuracy and convergence rate in the majority of thermal phase change scenarios. Full article

(This article belongs to the Special Issue Advances in Modeling and Simulation of Nanofluid Flows)

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22 pages, 1376 KiB

Open AccessArticle

Analysis of Nanofluid Particles in a Duct with Thermal Radiation by Using an Efficient Metaheuristic-Driven Approach

by Naveed Ahmad Khan, Muhammad Sulaiman, Carlos Andrés Tavera Romero and Fahad Sameer Alshammari

Nanomaterials 2022, 12(4), 637; https://doi.org/10.3390/nano12040637 - 14 Feb 2022

Cited by 8 | Viewed by 1793

Abstract

This study investigated the steady two-phase flow of a nanofluid in a permeable duct with thermal radiation, a magnetic field, and external forces. The basic continuity and momentum equations were considered along with the Buongiorno model to formulate the governing mathematical model of the problem. Furthermore, the intelligent computational strength of artificial neural networks (ANNs) was utilized to construct the approximate solution for the problem. The unsupervised objective functions of the governing equations in terms of mean square error were optimized by hybridizing the global search ability of an arithmetic optimization algorithm (AOA) with the local search capability of an interior point algorithm (IPA). The proposed ANN-AOA-IPA technique was implemented to study the effect of variations in the thermophoretic parameter

(N t)

, Hartmann number

(H a)

, Brownian

(N b)

and radiation

(R d)

motion parameters, Eckert number

(E c)

, Reynolds number

(R e)

and Schmidt number

(S c)

on the velocity profile, thermal profile, Nusselt number and skin friction coefficient of the nanofluid. The results obtained by the designed metaheuristic algorithm were compared with the numerical solutions obtained by the Runge–Kutta method of order 4 (RK-4) and machine learning algorithms based on a nonlinear autoregressive network with exogenous inputs (NARX) and backpropagated Levenberg–Marquardt algorithm. The mean percentage errors in approximate solutions obtained by ANN-AOA-IPA are around

10^{- 6}

10^{- 7}

. The graphical analysis illustrates that the velocity, temperature, and concentration profiles of the nanofluid increase with an increase in the suction parameter, Eckert number and Schmidt number, respectively. Solutions and the results of performance indicators such as mean absolute deviation, Theil’s inequality coefficient and error in Nash–Sutcliffe efficiency further validate the proposed algorithm’s utility and efficiency. Full article

(This article belongs to the Special Issue Advances in Modeling and Simulation of Nanofluid Flows)

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