A novel comprehensive experimental study concerned synthesizes and prepare liquid paraffin-Fe3O4 mixture to develop models for both thermal conductivity &amp; viscosity: A new approach of GMDH type of neural network

Shahsavar, Amin; Khanmohammadi, Shoaib; Karimipour, Arash; Goodarzi, Marjan

doi:10.1016/j.ijheatmasstransfer.2018.11.069

Cited by 138 publications

(33 citation statements)

References 61 publications

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“…On the other hand, smart computational techniques have emerged and evolved as powerful and advanced approaches that can resolve highly complex relatedmodeling topics (Amirian, Dejam, & Chen, 2018;Hemmati-Sarapardeh, Ghazanfari, Ayatollahi, & Masihi, 2016;Hemmati-Sarapardeh et al, 2018;Hobold & da Silva, 2019;Nait Amar & Zeraibi, 2018;Nait Amar, Zeraibi, & Redouane, 2018a;Nait Amar, Zeraibi, & Redouane, 2018b;Redouane, Zeraibi, & Amar, 2018;Shahsavar, Khanmohammadi, Karimipour, & Goodarzi, 2019;Xi, Gao, Xu, Zhao, & Li, 2018). Among the successful examples of soft computing techniques applications, we can cite production forcasting in thermal enhanced oil recovery (Amirian, Leung, Zanon, & Dzurman, 2015;Amirian, Fedutenko, Yang, Chen, & Nghiem, 2018), optimization of enhanced oil recovery techniques (Nait Amar & Zeraibi 2019), reservoir flood control (Chuntian & Chau, 2002), hydrology (Chau, 2017;Wu & Chau, 2011;Yaseen, Sulaiman, Deo, & Chau, 2019), and meteorology related topics (Ali Ghorbani, Kazempour, Chau, Shamshirband, & Ghazvinei, 2018;Moazenzadeh, Mohammadi, Shamshirband, & Chau, 2018).…”

Section: Modelmentioning

confidence: 99%

Modeling temperature dependency of oil - water relative permeability in thermal enhanced oil recovery processes using group method of data handling and gene expression programming

Menad

Zerhouni

Hemmati-Sarapardeh

et al. 2019

Engineering Applications of Computational Fluid Mechanics

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In the implementation of thermal enhanced oil recovery (TEOR) techniques, the temperature impact on relative permeability in oil-water systems (K rw and K ro ) is of special concern. Hence, developing a fast and reliable tool to model the temperature effect on K rw and K ro is still a major challenge for precise studying of TEOR processes. To reach the goal of this work, two promising soft-computing algorithms, namely Group Method of Data Handling (GMDH) and Gene Expression Programming (GEP) were employed to develop reliable and simple to use paradigms to predict the temperature dependency of K rw and K ro . To do so, a large database encompassing wide-ranging temperatures and fluids/rock parameters, was considered to establish these correlations. Statistical results and graphical analyses disclosed the high degree of accuracy for the proposed correlations in emulating the experimental results. In addition, GEP correlations were found to be the most consistent with root mean square error (RMSE) values of 0.0284 and 0.0636 for K rw and K ro , respectively. Lastly, the performance comparison against the preexisting correlations indicated the large superiority of the newly introduced correlations. The findings of this study can help for better understanding the temperature dependency of K rw and K ro in TEOR. ARTICLE HISTORY

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Section: Modelmentioning

confidence: 99%

Modeling temperature dependency of oil - water relative permeability in thermal enhanced oil recovery processes using group method of data handling and gene expression programming

Menad

Zerhouni

Hemmati-Sarapardeh

et al. 2019

Engineering Applications of Computational Fluid Mechanics

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“…Besides, nanofluids' novel characteristics can be used in a wide range of applications, especially heat transfer, electronics, biomedicine, and food (Sarfaraz 2018 , 2019a ; b ). Besides, nanofluids exhibit enhanced thermal conductivity and convective heat transfer as compared with other kinds of fluids (Shahsavar 2019 ; Akbari 2016 ; Bahmani 2018 ; Nazari 2020 ). Among all nanofluids, ferrofluids containing MNPs exhibit high nanoparticle stability with biomedical applications.…”

Section: Introductionmentioning

confidence: 99%

A facile, two-step synthesis and characterization of Fe3O4–LCysteine–graphene quantum dots as a multifunctional nanocomposite

Alaghmandfard

Hosseini

2021

Appl Nanosci

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In this research, a facile, two-step synthesis of Fe 3 O 4 -L Cysteine -graphene quantum dots (GQDs) nanocomposite is reported. This synthesis method comprises the preparation of GQDs via hydrothermal route, which should be conjugated to the L Cysteine functionalized core-shell magnetic structure with the core of about 7.5-nm iron oxide nanoparticle and 3.5-nm L Cysteine shell. L Cysteine, as a biocompatible natural amino acid, was used to link magnetite nanoparticles (MNPs) with GQDs. X-ray powder diffraction, Fourier-transform infrared spectroscopy, X-ray photoelectron spectroscopy, energy dispersive X-ray were used to investigate the presence and formation of MNPs, L Cysteine functionalized MNPs, and final hybrid nanostructure. Morphology and size distribution of nanoparticles were demonstrated by scanning electron microscopy and transmission electron microscopy. Finally, the magnetic and optical properties of the prepared nanocomposite were measured by vibrating sample magnetometer, ultraviolet-visible, and photoluminescence spectroscopy. The results show that Fe 3 O 4 -L Cysteine -GQDs nanocomposite exhibits a superparamagnetic behavior at room temperature with high saturation magnetization and low magnetic coercivity, which are 28.99 emu/g and 0.09 Oe, respectively. This nanocomposite also shows strong and stable emission at 460 nm and 530 nm when it is excited with the 235 nm wavelength. The magnetic GQDs structure also reveals the absorption wavelength at 270 nm. Therefore, Fe 3 O 4 -L Cysteine -GQDs nanocomposite can be considered as a potential multifunctional hybrid structure with magnetic and optical properties simultaneously. This nanocomposite can be used for a wide range of biomedical applications like magnetic resonance imaging (MRI) contrast agents, biosensors, photothermal therapy, and hyperthermia.

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“…Considering these facts, paraffin is a good candidate for using in solar stills. However, its low conductivity problem can be reduced by adding nanoparticles [13,14]. Table 1 shows the synopsis of the investigations about different nano-paraffin composites.…”

Section: Introductionmentioning

confidence: 99%

Solar Still Efficiency Enhancement by Using Graphene Oxide/Paraffin Nano-PCM

2019

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Solar-driven water desalination technologies are rapidly developing with various links to other renewable sources. However, the efficiency of such systems severely depends on the design parameters. The present study focused on using graphene oxide (GO) with the Φ = 0.2, 0.4 and 0.6 wt.% dispersed in paraffin, as phase-change materials (PCMs), to improve the productivity of a solar still for desalination applications. The outcomes showed that by adding more graphene oxide to paraffin, the melting temperature got reduced. Solar still with GO/paraffin showed 25% productivity improvement in comparison with the solar still with only PCM. The obtained Nusselt number during the melting time also represented that free convection heat transfer into the melted region of the solar still has been enhanced by adding dispersed GO to the PCM, compared to the base paraffin. Also, increasing the hot wall temperature augments the Nusselt number. Finally, an empirical equation was derived to correlate the average Nusselt number as a function of Rayleigh number (Ra), the Stefan number (Ste), the subcooling factor (Sb), and the Fourier number (Fo). The obtained correlation depicted that Nusselt number enhancement has a reverse relation with Fourier number.

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A novel comprehensive experimental study concerned synthesizes and prepare liquid paraffin-Fe3O4 mixture to develop models for both thermal conductivity & viscosity: A new approach of GMDH type of neural network

Cited by 138 publications

References 61 publications

Modeling temperature dependency of oil - water relative permeability in thermal enhanced oil recovery processes using group method of data handling and gene expression programming

Modeling temperature dependency of oil - water relative permeability in thermal enhanced oil recovery processes using group method of data handling and gene expression programming

A facile, two-step synthesis and characterization of Fe3O4–LCysteine–graphene quantum dots as a multifunctional nanocomposite

Solar Still Efficiency Enhancement by Using Graphene Oxide/Paraffin Nano-PCM

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