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Effects of dispersed added Graphene Oxide-Silicon Carbide nanoparticles to present a statistical formulation for the mixture thermal properties

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  • Mahyari, Amirhossein Ansari
  • Karimipour, Arash
  • Afrand, Masoud

Abstract

This study experimentally investigated the preparation method, stability, measurement, and modeling of the thermal conductivity of water/graphene oxide-silicon carbide nanofluid. In this study, the nanofluid was prepared via a two-stage method. Moreover, the SEM and XRD tests were used to investigate surface and atomic structure of nanoparticles. A probe-type ultrasonic stirrer was used to achieve stability and homogenized distribution of particles in the base fluid. Then, the nanofluid stability was assessed using the DLS test. According to the results, the base fluid contained nano-sized particles. Moreover, the thermal conductivity measurement of the hybrid nanofluid was carried out in the temperature and volume concentration ranges of 25–50 °C and 0.05–1 vol%, respectively. The experimental variables were the nanofluid’s temperature and volume concentration. Results showed that the thermal conductivity of the nanofluid increased with increasing volume concentration and temperature. Although nanoparticle concentration has a greater impact than temperature, changes in thermal conductivity are greater at higher temperatures. The greatest increase in thermal conductivity of nanofluid was 33.2% at the concentration of 1 vol% and temperature of 50 °C. To calculate thermal conductivity of this nanofluid, a highly accurate experimental equation was developed using the laboratory data curve fitting method.

Suggested Citation

  • 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.
  • Handle: RePEc:eee:phsmap:v:521:y:2019:i:c:p:98-112
    DOI: 10.1016/j.physa.2019.01.035
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    1. 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.
    2. 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.
    3. M. Goodarzi & M. R. Safaei & A. Karimipour & K. Hooman & M. Dahari & S. N. Kazi & E. Sadeghinezhad, 2014. "Comparison of the Finite Volume and Lattice Boltzmann Methods for Solving Natural Convection Heat Transfer Problems inside Cavities and Enclosures," Abstract and Applied Analysis, Hindawi, vol. 2014, pages 1-15, February.
    4. Hemmat Esfe, Mohammad & Hajmohammad, Hadi & Toghraie, Davood & Rostamian, Hadi & Mahian, Omid & Wongwises, Somchai, 2017. "Multi-objective optimization of nanofluid flow in double tube heat exchangers for applications in energy systems," Energy, Elsevier, vol. 137(C), pages 160-171.
    5. Toghraie, Davood & Karimipour, Arash & Safaei, Mohammad Reza & Goodarzi, Marjan & Alipour, Habibollah & Dahari, Mahidzal, 2016. "Investigation of rib's height effect on heat transfer and flow parameters of laminar water–Al2O3 nanofluid in a rib-microchannelAuthor-Name: Akbari, Omid Ali," Applied Mathematics and Computation, Elsevier, vol. 290(C), pages 135-153.
    6. 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.
    7. Khodabandeh, Erfan & Safaei, Mohammad Reza & Akbari, Soheil & Akbari, Omid Ali & Alrashed, Abdullah A.A.A., 2018. "Application of nanofluid to improve the thermal performance of horizontal spiral coil utilized in solar ponds: Geometric study," Renewable Energy, Elsevier, vol. 122(C), pages 1-16.
    8. Saidur, R. & Leong, K.Y. & Mohammad, H.A., 2011. "A review on applications and challenges of nanofluids," Renewable and Sustainable Energy Reviews, Elsevier, vol. 15(3), pages 1646-1668, April.
    9. 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.
    10. Nemati, Maedeh & Shateri Najaf Abady, Ali Reza & Toghraie, Davood & Karimipour, Arash, 2018. "Numerical investigation of the pseudopotential lattice Boltzmann modeling of liquid–vapor for multi-phase flows," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 489(C), pages 65-77.
    11. Murshed, S.M. Sohel & Nieto de Castro, C.A., 2016. "Conduction and convection heat transfer characteristics of ethylene glycol based nanofluids – A review," Applied Energy, Elsevier, vol. 184(C), pages 681-695.
    12. Leong, K.Y. & Ku Ahmad, K.Z. & Ong, Hwai Chyuan & Ghazali, M.J. & Baharum, Azizah, 2017. "Synthesis and thermal conductivity characteristic of hybrid nanofluids – A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 75(C), pages 868-878.
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    5. 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).
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