IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v520y2019icp275-288.html
   My bibliography  Save this article

Hydrothermal analysis of turbulent boehmite alumina nanofluid flow with different nanoparticle shapes in a minichannel heat exchanger using two-phase mixture model

Author

Listed:
  • Alsarraf, Jalal
  • Moradikazerouni, Alireza
  • Shahsavar, Amin
  • Afrand, Masoud
  • Salehipour, Hamzeh
  • Tran, Minh Duc

Abstract

Exploring the effect of nanoparticle shape on the fluid flow characteristics of boehmite alumina nanofluid in a horizontal double-pipe minichannel heat exchanger is the goal of this study. The proposed boehmite alumina nanofluid could consist of dispersed cylindrical, brick, blade, platelet, and spherical shape nanoparticles in a mixture of water/ethylene glycol. In this study, the water and nanofluid pass through the annulus and tube side of the heat exchanger, respectively. To accurately simulate the behavior of nanofluid, the two phase mixture model is utilized in the simulation. In this investigation, the effect of different Reynolds numbers, nanoparticle concentrations and shapes versus important hydrothermal properties are investigated. The results show that, the spherical and platelet shape lead to the highest and lowest performance index of heat exchanger, respectively. Moreover, it is found that the rates of heat transfer, overall heat transfer coefficient, pressure drop, and pumping power increases with increase in Reynolds number and nanoparticle concentration, while the opposite trend is observed for performance index of the heat exchanger. For instance, at the Reynolds number of 20000, by boosting the nanoparticle concentration from 0.5 to 2%, the performance index for nanofluid containing platelet shape and spherical shape nanoparticles reduces by 130.63 and 3.88%, respectively.

Suggested Citation

  • Alsarraf, Jalal & Moradikazerouni, Alireza & Shahsavar, Amin & Afrand, Masoud & Salehipour, Hamzeh & Tran, Minh Duc, 2019. "Hydrothermal analysis of turbulent boehmite alumina nanofluid flow with different nanoparticle shapes in a minichannel heat exchanger using two-phase mixture model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 520(C), pages 275-288.
  • Handle: RePEc:eee:phsmap:v:520:y:2019:i:c:p:275-288
    DOI: 10.1016/j.physa.2019.01.021
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378437119300214
    Download Restriction: Full text for ScienceDirect subscribers only. Journal offers the option of making the article available online on Science direct for a fee of $3,000

    File URL: https://libkey.io/10.1016/j.physa.2019.01.021?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Ahmadi Balootaki, Azam & Karimipour, Arash & Toghraie, Davood, 2018. "Nano scale lattice Boltzmann method to simulate the mixed convection heat transfer of air in a lid-driven cavity with an endothermic obstacle inside," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 508(C), pages 681-701.
    2. Mamourian, Mojtaba & Milani Shirvan, Kamel & Mirzakhanlari, Soroush, 2016. "Two phase simulation and sensitivity analysis of effective parameters on turbulent combined heat transfer and pressure drop in a solar heat exchanger filled with nanofluid by Response Surface Methodol," Energy, Elsevier, vol. 109(C), pages 49-61.
    3. Hemmat Esfe, Mohammad & Kamyab, Mohammad Hassan & Afrand, Masoud & Amiri, Mahmoud Kiannejad, 2018. "Using artificial neural network for investigating of concurrent effects of multi-walled carbon nanotubes and alumina nanoparticles on the viscosity of 10W-40 engine oil," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 510(C), pages 610-624.
    4. Karimipour, Arash & D’Orazio, Annunziata & Goodarzi, Marjan, 2018. "Develop the lattice Boltzmann method to simulate the slip velocity and temperature domain of buoyancy forces of FMWCNT nanoparticles in water through a micro flow imposed to the specified heat flux," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 509(C), pages 729-745.
    5. Karimipour, Arash & Hemmat Esfe, Mohammad & Safaei, Mohammad Reza & Toghraie Semiromi, Davood & Jafari, Saeed & Kazi, S.N., 2014. "Mixed convection of copper–water nanofluid in a shallow inclined lid driven cavity using the lattice Boltzmann method," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 402(C), pages 150-168.
    6. Goodarzi, Marjan & D’Orazio, Annunziata & Keshavarzi, Ahmad & Mousavi, Sayedali & Karimipour, Arash, 2018. "Develop the nano scale method of lattice Boltzmann to predict the fluid flow and heat transfer of air in the inclined lid driven cavity with a large heat source inside, Two case studies: Pure natural ," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 509(C), pages 210-233.
    7. Safaei, Mohammad Reza & Karimipour, Arash & Abdollahi, Ali & Nguyen, Truong Khang, 2018. "The investigation of thermal radiation and free convection heat transfer mechanisms of nanofluid inside a shallow cavity by lattice Boltzmann method," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 509(C), pages 515-535.
    8. Alipour, Pedram & Toghraie, Davood & Karimipour, Arash & Hajian, Mehdi, 2019. "Modeling different structures in perturbed Poiseuille flow in a nanochannel by using of molecular dynamics simulation: Study the equilibrium," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 515(C), pages 13-30.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Fatih Selimefendigil & Furkan Dilbaz & Hakan F. Öztop, 2023. "Combined Utilization of Cylinder and Different Shaped Alumina Nanoparticles in the Base Fluid for the Effective Cooling System Design of Lithium-Ion Battery Packs," Energies, MDPI, vol. 16(9), pages 1-17, May.
    2. Ma, Yulin & Shahsavar, Amin & Moradi, Iman & Rostami, Sara & Moradikazerouni, Alireza & Yarmand, Hooman & Zulkifli, Nurin Wahidah Binti Mohd, 2021. "Using finite volume method for simulating the natural convective heat transfer of nano-fluid flow inside an inclined enclosure with conductive walls in the presence of a constant temperature heat sour," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 580(C).
    3. Ruiqing Du & Dandan Jiang & Yong Wang, 2020. "Numerical Investigation of the Effect of Nanoparticle Diameter and Sphericity on the Thermal Performance of Geothermal Heat Exchanger Using Nanofluid as Heat Transfer Fluid," Energies, MDPI, vol. 13(7), pages 1-18, April.
    4. Sumera Dero & Azizah Mohd Rohni & Azizan Saaban & Ilyas Khan, 2019. "Dual Solutions and Stability Analysis of Micropolar Nanofluid Flow with Slip Effect on Stretching/Shrinking Surfaces," Energies, MDPI, vol. 12(23), pages 1-20, November.
    5. Khan, Kashif Ali & Seadawy, Aly R. & Raza, Nauman, 2022. "The homotopy simulation of MHD time dependent three dimensional shear thinning fluid flow over a stretching plate," Chaos, Solitons & Fractals, Elsevier, vol. 157(C).
    6. Zeeshan & Attaullah & N. Ameer Ahammad & Nehad Ali Shah & Jae Dong Chung, 2023. "A Numerical Framework for Entropy Generation Using Second-Order Nanofluid Thin Film Flow over an Expanding Sheet: Error Estimation and Stability Analysis," Mathematics, MDPI, vol. 11(5), pages 1-26, February.
    7. Chen, Zhixiong & Ashkezari, Abbas Zarenezhad & Tlili, Iskander, 2020. "Applying artificial neural network and curve fitting method to predict the viscosity of SAE50/MWCNTs-TiO2 hybrid nanolubricant," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 549(C).
    8. Sarafraz, M.M. & Tlili, I. & Tian, Zhe & Bakouri, Mohsen & Safaei, Mohammad Reza, 2019. "Smart optimization of a thermosyphon heat pipe for an evacuated tube solar collector using response surface methodology (RSM)," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 534(C).
    9. Shafee, Ahmad & Arabkoohsar, A. & Sheikholeslami, M. & Jafaryar, M. & Ayani, M. & Nguyen-Thoi, Trung & Basha, D. Baba & Tlili, I. & Li, Zhixiong, 2020. "Numerical simulation for turbulent flow in a tube with combined swirl flow device considering nanofluid exergy loss," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 542(C).
    10. Moghadam, Iman Panahi & Afrand, Masoud & Hamad, Samir M. & Barzinjy, Azeez A. & Talebizadehsardari, Pouyan, 2020. "Curve-fitting on experimental data for predicting the thermal-conductivity of a new generated hybrid nanofluid of graphene oxide-titanium oxide/water," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 548(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Shahsavar, Amin & Bagherzadeh, Seyed Amin & Mahmoudi, Boshra & Hajizadeh, Ahmad & Afrand, Masoud & Nguyen, Truong Khang, 2019. "Robust Weighted Least Squares Support Vector Regression algorithm to estimate the nanofluid thermal properties of water/graphene Oxide–Silicon carbide mixture," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 525(C), pages 1418-1428.
    2. Xiaohong, Dai & Huajiang, Chen & Bagherzadeh, Seyed Amin & Shayan, Masoud & Akbari, Mohammad, 2020. "Statistical estimation the thermal conductivity of MWCNTs-SiO2/Water-EG nanofluid using the ridge regression method," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 537(C).
    3. Bagherzadeh, Seyed Amin & D’Orazio, Annunziata & Karimipour, Arash & Goodarzi, Marjan & Bach, Quang-Vu, 2019. "A novel sensitivity analysis model of EANN for F-MWCNTs–Fe3O4/EG nanofluid thermal conductivity: Outputs predicted analytically instead of numerically to more accuracy and less costs," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 521(C), pages 406-415.
    4. Nafchi, Peyman Mirzakhani & Karimipour, Arash & Afrand, Masoud, 2019. "The evaluation on a new non-Newtonian hybrid mixture composed of TiO2/ZnO/EG to present a statistical approach of power law for its rheological and thermal properties," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 516(C), pages 1-18.
    5. Rasti, Ehsan & Talebi, Farhad & Mazaheri, Kiumars, 2019. "Improvement of drag reduction prediction in viscoelastic pipe flows using proper low-Reynolds k-ε turbulence models," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 516(C), pages 412-422.
    6. Tian, Zhe & Arasteh, Hossein & Parsian, Amir & Karimipour, Arash & Safaei, Mohammad Reza & Nguyen, Truong Khang, 2019. "Estimate the shear rate & apparent viscosity of multi-phased non-Newtonian hybrid nanofluids via new developed Support Vector Machine method coupled with sensitivity analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 535(C).
    7. Bahrami, Mehrdad & Akbari, Mohammad & Bagherzadeh, Seyed Amin & Karimipour, Arash & Afrand, Masoud & Goodarzi, Marjan, 2019. "Develop 24 dissimilar ANNs by suitable architectures & training algorithms via sensitivity analysis to better statistical presentation: Measure MSEs between targets & ANN for Fe–CuO/Eg–Water nanofluid," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 519(C), pages 159-168.
    8. Mahyari, Amirhossein Ansari & Karimipour, Arash & Afrand, Masoud, 2019. "Effects of dispersed added Graphene Oxide-Silicon Carbide nanoparticles to present a statistical formulation for the mixture thermal properties," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 521(C), pages 98-112.
    9. Peng, Yeping & Parsian, Amir & Khodadadi, Hossein & Akbari, Mohammad & Ghani, Kamal & Goodarzi, Marjan & Bach, Quang-Vu, 2020. "Develop optimal network topology of artificial neural network (AONN) to predict the hybrid nanofluids thermal conductivity according to the empirical data of Al2O3 – Cu nanoparticles dispersed in ethy," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 549(C).
    10. Al-Rashed, Abdullah A.A.A. & Ranjbarzadeh, Ramin & Aghakhani, Saeed & Soltanimehr, Mehdi & Afrand, Masoud & Nguyen, Truong Khang, 2019. "Entropy generation of boehmite alumina nanofluid flow through a minichannel heat exchanger considering nanoparticle shape effect," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 521(C), pages 724-736.
    11. Karimipour, Arash & Bagherzadeh, Seyed Amin & Taghipour, Abdolmajid & Abdollahi, Ali & Safaei, Mohammad Reza, 2019. "A novel nonlinear regression model of SVR as a substitute for ANN to predict conductivity of MWCNT-CuO/water hybrid nanofluid based on empirical data," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 521(C), pages 89-97.
    12. Alipour, Pedram & Toghraie, Davood & Karimipour, Arash, 2019. "Investigation the atomic arrangement and stability of the fluid inside a rough nanochannel in both presence and absence of different roughness by using of accurate nano scale simulation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 524(C), pages 639-660.
    13. Najafi, Mohammad Javid & Naghavi, Sayed Mahdi & Toghraie, Davood, 2019. "Numerical simulation of flow in hydro turbines channel to improve its efficiency by using of Lattice Boltzmann Method," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 520(C), pages 390-408.
    14. Moradikazerouni, Alireza & Hajizadeh, Ahmad & Safaei, Mohammad Reza & Afrand, Masoud & Yarmand, Hooman & Zulkifli, Nurin Wahidah Binti Mohd, 2019. "Assessment of thermal conductivity enhancement of nano-antifreeze containing single-walled carbon nanotubes: Optimal artificial neural network and curve-fitting," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 521(C), pages 138-145.
    15. Alipour, Pedram & Toghraie, Davood & Karimipour, Arash & Hajian, Mehdi, 2019. "Modeling different structures in perturbed Poiseuille flow in a nanochannel by using of molecular dynamics simulation: Study the equilibrium," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 515(C), pages 13-30.
    16. Zarei, Amir & Karimipour, Arash & Meghdadi Isfahani, Amir Homayoon & Tian, Zhe, 2019. "Improve the performance of lattice Boltzmann method for a porous nanoscale transient flow by provide a new modified relaxation time equation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 535(C).
    17. Wei, Li & Arasteh, Hossein & abdollahi, Ali & Parsian, Amir & Taghipour, Abdolmajid & Mashayekhi, Ramin & Tlili, Iskander, 2020. "Locally weighted moving regression: A non-parametric method for modeling nanofluid features of dynamic viscosity," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 550(C).
    18. Khaje khabaz, Moahamad & Eftekhari, S. Ali & Hashemian, Mohamad & Toghraie, Davood, 2020. "Optimal vibration control of multi-layer micro-beams actuated by piezoelectric layer based on modified couple stress and surface stress elasticity theories," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 546(C).
    19. Afrouzi, Hamid Hassanzadeh & Ahmadian, Majid & Moshfegh, Abouzar & Toghraie, Davood & Javadzadegan, Ashkan, 2019. "Statistical analysis of pulsating non-Newtonian flow in a corrugated channel using Lattice-Boltzmann method," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 535(C).
    20. Alnaqi, Abdulwahab A. & Sayyad Tavoos Hal, Sina & Aghaei, Alireza & Soltanimehr, Mehdi & Afrand, Masoud & Nguyen, Truong Khang, 2019. "Predicting the effect of functionalized multi-walled carbon nanotubes on thermal performance factor of water under various Reynolds number using artificial neural network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 521(C), pages 493-500.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:phsmap:v:520:y:2019:i:c:p:275-288. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/physica-a-statistical-mechpplications/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.