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Symmetry
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Advances in Heat and Mass Transfer with Symmetry
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Advances in Heat and Mass Transfer with Symmetry

A special issue of Symmetry (ISSN 2073-8994). This special issue belongs to the section "Engineering and Materials".

Deadline for manuscript submissions: closed (31 March 2024) | Viewed by 7417

Special Issue Editors

Dr. Liaqat Ali

E-Mail Website
Guest Editor
School of Sciences, Xi’an Technological University, Xi’an 710021, China
Interests: computational fluid dynamics; applied thermodynamics; nanofluids; hybrid nanofluid; Newtonian fluids; non-Newtonian fluids; heat and mass transfer; finite element method; Runge–Kutta method and numerical methods
Special Issues, Collections and Topics in MDPI journals
Dr. Bagh Ali

E-Mail Website
Guest Editor
Faculty of Computer Science and Information Technology, Superior University, Lahore 54000, Pakistan
Interests: Newtonian and non-Newtonian fluid flows; mono and hybrid nanofluids; computational fluid dynamics; finite element method
Dr. Dumitru Vieru

E-Mail Website
Guest Editor
Department of Theoretical Mechanics, Technical University of Iasi, Iasi, Romania
Interests: dynamics; dynamic analysis; nonlinear analysis; fluid-applied mathematics; piezoelectricity; convection
Dr. Nehad Ali Shah

E-Mail Website
Guest Editor
Department of Mechanical Engineering, Sejong University, Seoul 05006, Republic of Korea
Interests: fluid dynamics; fractional PDEs; heat and mass transfer; nanofluids; nonlinear analysis
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The development of nanostructured fluid flow has received a lot of interest recently due to its excellent potential for enhancing the photocatalytic efficiency of semiconductor nanomaterials. These hybrid nanostructured materials combine polymers with other innovative 2-dimensional nanosheet materials, such as MXene and black phosphorus (BP), as well as carbon nanomaterials including graphene, GO, CNT, carbon quantum dots, and carbon nitride. The duration of the charge separation state, catalytic activity, and selectivity all significantly increase when nanomaterials are combined with molecular structures. The subjects that are solicited for this Special Issue include (but are not limited to) the design, characterization, and application of the inventive nanostructured photocatalysts mentioned above. All submissions should be in the scope of Symmetry.

Dr. Liaqat Ali
Dr. Bagh Ali
Dr. Dumitru Vieru
Dr. Nehad Ali Shah
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Symmetry is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • nanomaterials
  • solar energy 
  • hybridization 
  • effect of nanoparticles on fluid flow 
  • environmental remediation 
  • advanced oxidation processes 
  • water purification 
  • adsorption 
  • multifunctional nanomaterials 
  • magnetic nanoparticles

Published Papers (5 papers)

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Research

32 pages, 6823 KiB  
Article
Numerical and Machine Learning Approach for Fe3O4-Au/Blood Hybrid Nanofluid Flow in a Melting/Non-Melting Heat Transfer Surface with Entropy Generation
by Shaik Jakeer, Sathishkumar Veerappampalayam Easwaramoorthy, Seethi Reddy Reddisekhar Reddy and Hayath Thameem Basha
Symmetry 2023, 15(8), 1503; https://doi.org/10.3390/sym15081503 - 28 Jul 2023
Cited by 1 | Viewed by 1076
Abstract
The physiological system loses thermal energy to nearby cells via the bloodstream. Such energy loss can result in sudden death, severe hypothermia, anemia, high or low blood pressure, and heart surgery. Gold and iron oxide nanoparticles are significant in cancer treatment. Thus, there [...] Read more.
The physiological system loses thermal energy to nearby cells via the bloodstream. Such energy loss can result in sudden death, severe hypothermia, anemia, high or low blood pressure, and heart surgery. Gold and iron oxide nanoparticles are significant in cancer treatment. Thus, there is a growing interest among biomedical engineers and clinicians in the study of entropy production as a means of quantifying energy dissipation in biological systems. The present study provides a novel implementation of an intelligent numerical computing solver based on an MLP feed-forward backpropagation ANN with the Levenberg–Marquard algorithm to interpret the Cattaneo–Christov heat flux model and demonstrate the effect of entropy production and melting heat transfer on the ferrohydrodynamic flow of the Fe3O4-Au/blood Powell–Eyring hybrid nanofluid. Similarity transformation studies symmetry and simplifies PDEs to ODEs. The MATLAB program bvp4c is used to solve the nonlinear coupled ordinary differential equations. Graphs illustrate the impact of a wide range of physical factors on variables, including velocity, temperature, entropy generation, local skin friction coefficient, and heat transfer rate. The artificial neural network model engages in a process of data selection, network construction, training, and evaluation through the use of mean square error. The ferromagnetic parameter, porosity parameter, distance from origin to magnetic dipole, inertia coefficient, dimensionless Curie temperature ratio, fluid parameters, Eckert number, thermal radiation, heat source, thermal relaxation parameter, and latent heat of the fluid parameter are taken as input data, and the skin friction coefficient and heat transfer rate are taken as output data. A total of sixty data collections were used for the purpose of testing, certifying, and training the ANN model. From the results, it is found that the fluid temperature declines when the thermal relaxation parameter is improved. The latent heat of the fluid parameter impacts the entropy generation and Bejan number. There is a less significant impact on the heat transfer rate of the hybrid nanofluid over the sheet on the melting heat transfer parameter. Full article
(This article belongs to the Special Issue Advances in Heat and Mass Transfer with Symmetry)
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13 pages, 636 KiB  
Article
Ternary Hybrid Nanofluid Flow Emerging on a Symmetrically Stretching Sheet Optimization with Machine Learning Prediction Scheme
by P. Priyadharshini, M. Vanitha Archana, Nehad Ali Shah and Mansoor H. Alshehri
Symmetry 2023, 15(6), 1225; https://doi.org/10.3390/sym15061225 - 08 Jun 2023
Cited by 4 | Viewed by 1722
Abstract
Nanofluids holding three distinct sorts of nanosized particles suspended in base fluid possess excellent thermal performance. In light of this novel use in coolant applications, the current work dealt with the optimal design and performance estimation of a ternary hybrid nanofluid, based on [...] Read more.
Nanofluids holding three distinct sorts of nanosized particles suspended in base fluid possess excellent thermal performance. In light of this novel use in coolant applications, the current work dealt with the optimal design and performance estimation of a ternary hybrid nanofluid, based on a modern machine learning prediction technique. The synthesis of (Cu), (TiO2), and (SiO2) ternary hybrid nanoparticles suspended in water over a symmetrically stretching sheet was scrutinized. The flow over a stretching sheet is the most noteworthy symmetry analysis for momentum and thermal boundary layers, due to the implications of heat transfer, and is applied in various industries and technological fields. The governing equations were transformed to a dimension-free series of ODEs, by handling similarity transformable with symmetry variables, after which, the series of ODEs were treated scientifically, with the help of the Wolfram Language tool. The precision of the current estimates was assessed by comparison to existing research. Moreover, the natures of the physical phenomena were forecast by designing a support vector machine algorithm with an emphasis on machine learning, which delivers a robust and efficient structure for every fluid application that infers physical influences. To validate the proposed research, some of the statistical metrics were taken for error assessment between true and anticipated values. It was revealed that the presented approach is the best strategy for predicting physical quantities. This investigation established that ternary hybrid nanofluid possesses excellent thermal performance, greater than that of hybrid nanofluid. The current optimization process delivers a new beneficial viewpoint on the production of polymer sheets, glass fiber, petroleum, plastic films, heat exchangers, and electronic devices. Hence, the obtained results are recommended for the development of industrial devices setups. Full article
(This article belongs to the Special Issue Advances in Heat and Mass Transfer with Symmetry)
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26 pages, 12128 KiB  
Article
Cubic Chemical Autocatalysis and Oblique Magneto Dipole Effectiveness on Cross Nanofluid Flow via a Symmetric Stretchable Wedge
by Nor Ain Azeany Mohd Nasir, Tanveer Sajid, Wasim Jamshed, Gilder Cieza Altamirano, Mohamed R. Eid and Fayza Abdel Aziz ElSeabee
Symmetry 2023, 15(6), 1145; https://doi.org/10.3390/sym15061145 - 24 May 2023
Cited by 8 | Viewed by 1079
Abstract
Exploration related to chemical processes in nanomaterial flows contains astonishing features. Nanoparticles have unique physical and chemical properties, so they are continuously used in almost every field of nanotechnology and nanoscience. The motive behind this article is to investigate the Cross nanofluid model [...] Read more.
Exploration related to chemical processes in nanomaterial flows contains astonishing features. Nanoparticles have unique physical and chemical properties, so they are continuously used in almost every field of nanotechnology and nanoscience. The motive behind this article is to investigate the Cross nanofluid model along with its chemical processes via auto catalysts, inclined magnetic field phenomena, heat generation, Brownian movement, and thermophoresis phenomena over a symmetric shrinking (stretching) wedge. The transport of heat via nonuniform heat sources/sinks, the impact of thermophoretic diffusion, and Brownian motion are considered. The Buongiorno nanofluid model is used to investigate the impact of nanofluids on fluid flow. Modeled PDEs are transformed into ODEs by utilizing similarity variables and handling dimensionless ODEs numerically with the adoption of MATLAB’s developed bvp4c technique. This software performs a finite difference method that uses the collocation method with a three-stage LobattoIIIA strategy. Obtained outcomes are strictly for the case of a symmetric wedge. The velocity field lessens due to amplification in the magneto field variable. Fluid temperature is amplified through the enhancement of Brownian diffusion and the concentration field improves under magnification in a homogeneous reaction effect. Full article
(This article belongs to the Special Issue Advances in Heat and Mass Transfer with Symmetry)
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13 pages, 3526 KiB  
Article
Numerical Simulation of the Effects of Reduced Gravity, Radiation and Magnetic Field on Heat Transfer Past a Solid Sphere Using Finite Difference Method
by Amir Abbas, Muhammad Ashraf, Ioannis E. Sarris, Kaouther Ghachem, Taher Labidi, Lioua Kolsi and Hafeez Ahmad
Symmetry 2023, 15(3), 772; https://doi.org/10.3390/sym15030772 - 22 Mar 2023
Cited by 11 | Viewed by 1146
Abstract
The current study deals with the reduced gravity and radiation effects on the magnetohydrodynamic natural convection past a solid sphere. The studied configuration is modeled using coupled and nonlinear partial differential equations. The obtained model is transformed to dimensionless form using suitable scaling [...] Read more.
The current study deals with the reduced gravity and radiation effects on the magnetohydrodynamic natural convection past a solid sphere. The studied configuration is modeled using coupled and nonlinear partial differential equations. The obtained model is transformed to dimensionless form using suitable scaling variables. The finite difference method is adopted to solve the governing equation and determine the velocity and temperature profiles in addition to the skin friction coefficient and Nusselt number. Furthermore, graphic and tabular presentations of the results are made. The verification of the numerical model is performed by comparing with results presented in the literature and a good concordance is encountered. The main objective of this investigation is to study the effect of the buoyancy force caused by the density variation on natural convective heat transfer past a solid sphere. The results show that the velocity increases with the reduced gravity parameter and solar radiation but decreases with Prandtl number and magnetic field parameter. It is also found that the temperature increases the with solar radiation and magnetic field but decreases with the reduced gravity parameter and Prandtl number. Full article
(This article belongs to the Special Issue Advances in Heat and Mass Transfer with Symmetry)
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27 pages, 11537 KiB  
Article
Numerical Simulation on Heat Transfer Augmentation by Using Innovative Hybrid Ribs in a Forward-Facing Contracting Channel
by Hussein Togun, S. Hamidatou, Hayder I. Mohammed, Azher. M. Abed, Husam Abdulrasool Hasan, Raad Z. Homod, Ali Wadi Al-Fatlawi, Mohaimen Al-Thamir and Tuqa Abdulrazzaq
Symmetry 2023, 15(3), 690; https://doi.org/10.3390/sym15030690 - 09 Mar 2023
Cited by 6 | Viewed by 1825
Abstract
This study aims to investigate the thermal behavior and aerodynamic phenomena in a heated channel with varied rib configurations using computational fluid dynamics (CFD) simulations. Incorporating ribs in such systems enhances heat transfer and increases flow resistance and manufacturing costs. Understanding heat exchanger [...] Read more.
This study aims to investigate the thermal behavior and aerodynamic phenomena in a heated channel with varied rib configurations using computational fluid dynamics (CFD) simulations. Incorporating ribs in such systems enhances heat transfer and increases flow resistance and manufacturing costs. Understanding heat exchanger theory, measurement methods, and numerical calculations are crucial for creating efficient heat exchangers. The current research employs numerical analysis to assess the impact of hybrid ribs on heat transfer enhancement in forward-facing contracting channels (FFS). A two-dimensional forced convection heat transfer simulation under turbulent flow conditions was performed, considering the presence and absence of ribs with dimensions of 1 cm by 1 cm and spaced 11 cm apart. The arrangement of the ribs causes symmetrical temperature and flow distribution after and before each rib. The results demonstrate that the use of hybrid ribs outperforms the use of individual rib configurations in terms of thermal performance. This is due to the distinct flow patterns generated as the fluid passes through each rib. The triangle ribs had a more significant impact on the pressure drop than other rib configurations, while the cross ribs showed a lesser effect. The ribs improve the heat transfer coefficient while increasing the pressure drop, and the values of the Reynolds number were found to be directly proportional to the heat transfer coefficient and the pressure drop. The study concludes with a qualitative and quantitative analysis demonstrating the accuracy and coherence of the obtained computational results. Full article
(This article belongs to the Special Issue Advances in Heat and Mass Transfer with Symmetry)
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