Viscosity of nanofluids based on an artificial intelligence model

Mehrabi, Mehdi; Sharifpur, Mohsen; Meyer, Josua P.

doi:10.1016/j.icheatmasstransfer.2013.02.008

Cited by 60 publications

(13 citation statements)

References 39 publications

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“…It is reported by Mehrabi et al [38] that no model is able to predict the viscosity of nanofluids precisely in a broad range of nanoparticle volume fractions. [39,40] The recent study by Mehrabi et al [38] shows that the Brinkman relation [37] predicted the viscosity close to the experimental results as compared to the Abu-Nada et al [41] Figure 5 shows comparison of the different viscosity correlations with experimental results reported in the literature. [39,40] The recent study by Mehrabi et al [38] shows that the Brinkman relation [37] predicted the viscosity close to the experimental results as compared to the Abu-Nada et al [41] Figure 5 shows comparison of the different viscosity correlations with experimental results reported in the literature.…”

Section: Thermo-physical Properties Of Nanofluidsmentioning

confidence: 98%

The thermal and transport characteristics of nanofluids in a novel three‐dimensional device

2014

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The augmentation in heat transfer can be achieved by improving either transport phenomena with geometry perturbation or thermal conductivity of the fluid itself. In the present study, the simultaneous effects of both the geometry and improved thermal conductivity have been tried on heat transfer enhancement by using two different nanofluids (Al 2 O 3 -water and TiO 2 -water). An innovative three-dimensional device called a coiled flow inverter (CFI) is proposed for the process intensification. The CFI is made up of helical coiled tube, which is bent periodically to 90 8 at equidistant length. In addition to a CFI, the performance characteristics of helical coil and straight tube have been investigated. The Reynolds numbers are in the range of 25-4000, while the nanoparticle volume fraction varied from 0.25-4 %. It was noted that the heat transfer in a CFI improved considerably as compared to helical coil and straight tube of same dimension. The Nusselt number in helical coil augments by 2.5 times to that of straight tube. In the CFI, the Nusselt number further enhanced by 23-35 % as compared to helical coil, with 0-4 % increase in the nanoparticle volume fractions. The new correlations are developed to predict the Nusselt number and friction factor for the flow of nanofluids in the CFI. The number of merit in the CFI to that of straight tube are 1.6-1.8 times, with 0-4 % nanoparticle volume fractions. The present study may motivate the design and development of novel compact heat exchangers as well as a new-generation microfluidic device.

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Section: Thermo-physical Properties Of Nanofluidsmentioning

confidence: 98%

The thermal and transport characteristics of nanofluids in a novel three‐dimensional device

2014

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“…Viscosity plays a major role in determining pumping power requirement of any heat exchanger, thus, precise knowledge of the nanofluids' viscosity behaviour is important [15]. Also, a key problem with nanofluid's research is the estimation of the effective viscosity of nanofluids.…”

Section: Nanofluid Is a Modified Heat Transfer Fluid Produced By Homomentioning

confidence: 99%

Experimental investigation and model development for effective viscosity of MgO–ethylene glycol nanofluids by using dimensional analysis, FCM-ANFIS and GA-PNN techniques

Adio

Mehrabi

Sharifpur

et al. 2016

International Communications in Heat and Mass Transfer

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Desirable effective viscosity behaviour is an essential transport property required for the effective utilisation of nanofluids in industrial systems as well as other applications. Viscosity influences significantly the pumping power and heat transfer effectiveness in a thermal system since Reynolds and Prandtl numbers are functions of viscosity. In this study, the optimum energy required for the preparation of MgO-ethylene glycol (MgO-EG) nanofluids was determined by varying the ultrasonication energy input into the preparation process. The uniformly dispersed nanofluids were characterised and the viscosity measurements were carried out as a function of temperature (20 to Therefore, new correlation is proposed using the method of dimensional analysis and considering essential factors, including nanoparticle size, volume fraction temperature, capping layer thickness, viscosity of the base fluid, the density of base fluid and the density of nanofluid as input parameters.Furthermore, genetic algorithm-polynomial neural network (GA-PNN) and fuzzy C-means clusteringbased adaptive neuro-fuzzy inference system (FCM-ANFIS) was used to model the effective viscosity of the MgO-EG nanofluids considering the parameters mentioned above. The results of all the modelling techniques showed good agreement with the experimental data.

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“…Mehrabi et al [236] developed four different models for the prediction of nanofluid viscosities for four different water-based nanofluids (Al2O3, CuO, TiO2 and SiO2) based on the FCM-based adaptive neuro-fuzzy inference system. The results of the respective models were compared with the experimental data points and some prominent correlations from the literature.…”

mentioning

confidence: 99%

The Viscosity of Nanofluids: A Review of the Theoretical, Empirical, and Numerical Models

Meyer

Adio

Sharifpur

et al. 2015

Heat Transfer Engineering

198

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The enhanced thermal characteristics of nanofluids have made it one of the fastest-growing research areas in the last decade. Numerous researches have shown the merits of nanofluids in heat transfer equipment. However, one of the problems is the increase in viscosity due to the suspension of nanoparticles. This viscosity increase is not desirable in the industry, especially when it involves flow, such as in heat exchanger or micro-channel applications INTRODUCTIONColloidal suspension dates back to Maxwell's study in 1873 [1]. Though the idea behind his study was vivid, the imposed problems were too enormous for profitable engineering solutions [2]. In 1995, Choi [3] came up with a pioneering idea based on Maxwell's study and suspended ultrafine particles (nanoparticles) in conventional heat transfer fluids. His invention has opened up a myriad of opportunities in research and development. Nanofluids descriptively are colloidal suspensions containing metallic (Ag, Au, Al, Cu, Ni, etc.), non-metallic (single-and multi-wall carbon nanotube (SWCNT and MWCNT), Si, Graphene, etc.), metallic oxide (Al2O3, CuO, NiO2,TiO2, etc.) and oxides of non-metals (SiO2, SiC, MgO, CaCO3, etc.) nanoparticles suspended in conventional heat transfer fluids such as water, engine oil, ethylene glycol, transformer oil, gear oil or mixture of two or more heat transfer fluids [2,3]. When compared with previous microparticle suspensions in conventional heat transfer fluids, it is a special type of fluid with numerous applications potentials because of its enhanced thermal conductivity, stability and homogeneity [3,4]. Microscale particles in suspensions lead to abrasion, clogging of flow paths, pressure drop and high pumping power requirements, therefore, its sustainability was impossible. Besides, nanofluids can reduce the pumping power in engineering equipment significantly and do not pose the problem of clogging and abrasion of equipment flow paths [5][6][7][8]. Therefore, the design and engineering of physical systems are now being tailored towards using nanofluid as working fluid.The impact of colloidal suspension cuts across the fields of science, biological science, medical, pharmaceutical and engineering. In the context of sustainable energy development and thermal management, nanofluids are becoming more and more significant as the need for efficient thermal management is of paramount importance. Moreover, the level of miniaturisation of devices today as technology advances is overwhelming. Devices such as microprocessors, microelectromechanical systems (MEMS), nanoelectromechanical systems (NEMS), microchannels and lab-on-chips come with high-density heat flux that needs quick heat removal for 3 efficient performance, stability and durability, which, from all indications, could be provided by nanofluids for now [9][10][11][12]. The following are also emerging areas of applications of nanoparticles and nanofluids: (i) they could be useful in medicine in the targeted treatment of malignant cells without damaging healthy tis...

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Viscosity of nanofluids based on an artificial intelligence model

Cited by 60 publications

References 39 publications

The thermal and transport characteristics of nanofluids in a novel three‐dimensional device

The thermal and transport characteristics of nanofluids in a novel three‐dimensional device

Experimental investigation and model development for effective viscosity of MgO–ethylene glycol nanofluids by using dimensional analysis, FCM-ANFIS and GA-PNN techniques

The Viscosity of Nanofluids: A Review of the Theoretical, Empirical, and Numerical Models

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