scholarly journals Investigating and Modeling the Factors Affecting Thermal Optimization and Dynamic Viscosity of Water Hybrid Nanofluid/Carbon Nanotubes via MOPSO using ANN

2020 ◽  
Vol 2 (3) ◽  
pp. 108-114
Author(s):  
Amin Moslemi Petrudi ◽  
Ionut Cristian Scurtu
Keyword(s):  
Thermal Conductivity ◽  
Carbon Nanotubes ◽  
Volume Fraction ◽  
Optimization Process ◽  
Hybrid Nanofluid ◽  
Engineering Systems ◽  
Factors Affecting ◽  
Multi Objective ◽  
Ann Modeling ◽  
Artificial Neural Network Ann

Optimization is to find the best answer among existing situations. Optimization is used in the design and maintenance of many engineering systems to minimize costs or maximize profits. Due to the widespread use of optimization in engineering, this topic has grown a lot. In this paper, the optimization of multi-objective of Water Hybrid Nanofluid/Carbon Nanotubes is investigated. Multi-Objective Particle Swarm Optimization (MOPSO) algorithm has been used in order to maximize thermal conductivity and minimum viscosity by changing the temperature (300 to 340 ºk) and the volume fraction (0.01 to 0.4%) of nanofluid. Artificial Neural Network (ANN) modeling of experimental data has been used to obtain the values. Parto fronts, the optimal points and different values are 20 members and 15 iterations, and in order to compare the results optimization process on the first, fifth, tenth fronts, a relation has been proposed to predict the viscosity and Parto fronts in the optimization process. The aim of the study was to optimize nanofluid to reduce viscosity and increase thermal conductivity.

scholarly journals Entropy generation of a hybrid nanofluid on MHD mixed convection is a lid-driven cavity with partial heating having two rounded corners

2021 ◽  
Vol 321 ◽  
pp. 02004
Author(s):  
Zakaria Korei ◽  
Smail Benissaad
Keyword(s):  
Thermal Conductivity ◽  
Reynolds Number ◽  
Mixed Convection ◽  
Entropy Generation ◽  
Volume Fraction ◽  
Object Oriented ◽  
Reynolds Numbers ◽  
Hybrid Nanofluid ◽  
Driven Cavity ◽  
Partial Heating

This research aims to investigate thermal and flow behaviors and entropy generation of magnetohydrodynamic Al2O3-Cu/water hybrid nanofluid in a lid-driven cavity having two rounded corners. A solver based on C ++ object-oriented language was developed where the finite volume was used. Parameter’s analysis is provided by varying Reynolds numbers (Re), Hartmann numbers (Ha), the volume fraction of hybrid nanofluid (ϕ), radii of the rounded corners. The findings show that reducing the radii of the rounded corners minimizes the irreversibility. Furthermore, the thermal conductivity and dynamic viscosity of hybrid nanofluid contribute to increasing the irreversibility. Finally, the entropy generation is decreased by increasing the Hartman number and increases by rising the Reynolds number.

Study on the In Situ Growth of Carbon Nanotubes for the Reinforcement of Cf/SiC Composite Fabricated by CVI+PIP Process

2013 ◽  
Vol 745-746 ◽  
pp. 582-586 ◽  
Author(s):  
Jian Bao Hu ◽  
Shao Ming Dong ◽  
Xiang Yu Zhang ◽  
Zhen Wang ◽  
Hai Jun Zhou ◽  
...  
Keyword(s):  
Thermal Conductivity ◽  
Carbon Nanotubes ◽  
Bonding Strength ◽  
Volume Fraction ◽  
Interfacial Bonding ◽  
Mechanical And Thermal Properties ◽  
Fiber Volume ◽  
Pull Out ◽  
Interfacial Bonding Strength

Cf/SiC composites were fabricated through in situ growth of carbon nanotubes (CNTs) on three-dimensional needle-punched carbon fabric via chemical vapor deposition and polymer impregnation and pyrolysis process. The mechanical and thermal properties of the composites were investigated. The flexural strength and fracture toughness were decreased due to the fiber volume fraction loss and much shorter pull-out length of fibers which was caused by the higher interfacial bonding strength between fiber and matrix after the growth of CNTs. Brittle fracture character of CNTs was observed due to the strong interfacial bonding strength between CNTs and matrix. The parallel thermal conductivity and perpendicular thermal conductivity were improved to 14.5% and 8.0% respectively.

Thermal Conductivity Measurement for Carbon-Nanotube Suspensions with 3ω Method

2009 ◽  
Vol 60-61 ◽  
pp. 394-398 ◽  
Author(s):  
Gen Sheng Wu ◽  
Jue Kuan Yang ◽  
Shu Lin Ge ◽  
Yu Juan Wang ◽  
Min Hua Chen ◽  
...  
Keyword(s):  
Thermal Conductivity ◽  
Carbon Nanotubes ◽  
Volume Fraction ◽  
Aqueous Suspension ◽  
Conductivity Measurement ◽  
3Ω Method ◽  
Conductivity Enhancement ◽  
Multi Walled Carbon Nanotubes ◽  
The Stability ◽  
Walled Carbon Nanotubes

The stable and homogeneneous aqueous suspension of carbon nanotubes was prepared in this study. The stability of the nanofluids was improved greatly due to the use of a new dispersant, humic acid. The thermal conductivity of the aqueous suspension was measured with the 3ω method. The experimental results showed that the thermal conductivity of the suspensions increases with the temperature and also is nearly proportional to the loading of the nanoparticles. The thermal conductivity enhancement of single-walled carbon nanotubes (SWNTs) suspensions is better than that of the multi-walled carbon nanotubes (MWNTs) suspensions. Especially for a volume fraction of 0.3846% SWNTs, the thermal conductivity is enhanced by 40.5%. Furthermore, the results at 30°C match well with Jang and Choi’s model.

scholarly journals Synthesis of hybrid nanofluid with two-step method

2018 ◽  
Vol 67 ◽  
pp. 03057 ◽  
Author(s):  
Wayan Nata Septiadi ◽  
Ida Ayu Nyoman Titin Trisnadewi ◽  
Nandy Putra ◽  
Iwan Setyawan
Keyword(s):  
Thermal Conductivity ◽  
Base Fluid ◽  
Volume Fraction ◽  
Heat Transfer Fluid ◽  
Hybrid Nanofluid ◽  
Test Results ◽  
Step Method ◽  
Fluid Mixture ◽  
High Level ◽  
Better Than

Nanofluid is a liquid fluid mixture with a nanometer-sized solid particle potentially applied as a heat transfer fluid because it is capable of producing a thermal conductivity better than a base fluid. However, nanofluids have a weakness that is a high level of agglomeration as the resulting conductivity increases. Therefore, in this study, the synthesis of two nanoparticles into the base fluid called hybrid nanofluids. This study aims to determine the effect of nanoparticle composition on the highest thermal conductivity value with the lowest agglomeration value. This research was conducted by dispersing Al2O3-TiO2 nanoparticles in water with volume fraction of 0.1%, 0.3%, 0.5%, 0.7% in the composition of Al2O3-TiO2 ratio of 75%:25%, 50%:50%, 25%:75%. The synthesis was performed with a magnetic stirrer for 30 minutes. The tests were carried out in three types: thermal conductivity testing with KD2, visual agglomeration observation and absorbance measurements using UV-Vis, wettability testing with HSVC tools and Image applications. The test results showed that the ratio composition ratio of 75% Al2O3-25% TiO2 with a volume fraction of 0.7% resulted in an increase in optimum thermal conductivity with the best wettability and the longest agglomeration level.

Thermal Transport Properties of Nanofluids Containing Carbon Nanotubes

2008 ◽  
Author(s):  
Huaqing Xie ◽  
Lifei Chen ◽  
Yang Li ◽  
Wei Yu
Keyword(s):  
Thermal Conductivity ◽  
Carbon Nanotubes ◽  
Base Fluid ◽  
Volume Fraction ◽  
Thermal Conductivity Enhancement ◽  
Mechanochemical Reaction ◽  
Multiwalled Carbon ◽  
Conductivity Enhancement ◽  
Lower Viscosity ◽  
Potential Applications

Multiwalled carbon nanotubes (CNTs) have been treated by using a mechanochemical reaction method to enhance their dispersibility for producing CNT nanofluids. The thermal conductivity was measured by a short hot wire technique and the viscosity was measured by a rotary viscometer. The thermal conductivity enhancement reaches up to 17.5% at a volume fraction of 0.01 for an ethylene glycol based nanofluid. Temperature variation was shown to have no obvious effects on the thermal conductivity enhancement for the as prepared nanofluids. With an increase in the thermal conductivity of the base fluid, the thermal conductivity enhancement of a nanofluid decreases. At low volume fractions (<0.4 Vol%), nanofluids have lower viscosity than the corresponding base fluid due to lubricative effect of nanoparticles. When the volume fraction is higher than 0.4 Vol%, the viscosity increases with nanoparticle loadings. The prepared nanofluids, with no contamination to medium, good fluidity, stability, and high thermal conductivity, would have potential applications as coolants in advanced thermal systems.

scholarly journals Feasibility of ANFIS-PSO and ANFIS-GA Models in Predicting Thermophysical Properties of Al2O3-MWCNT/Oil Hybrid Nanofluid

Materials ◽  
2019 ◽  
Vol 12 (21) ◽  
pp. 3628 ◽  
Author(s):  
Ibrahim M. Alarifi ◽  
Hoang M. Nguyen ◽  
Ali Naderi Bakhtiyari ◽  
Amin Asadi
Keyword(s):  
Thermal Conductivity ◽  
Thermophysical Properties ◽  
Fuzzy Inference ◽  
Optimization Techniques ◽  
Hybrid Nanofluid ◽  
Inference System ◽  
Laminar And Turbulent Flow ◽  
Input Variables ◽  
Artificial Neural Network Ann ◽  
Thermal Oil

The main purpose of the present paper is to improve the performance of the adaptive neuro-fuzzy inference system (ANFIS) in predicting the thermophysical properties of Al2O3-MWCNT/thermal oil hybrid nanofluid through mixing using metaheuristic optimization techniques. A literature survey showed that the use of an artificial neural network (ANN) is the most widely used method, although there are other methods that showed better performance. Moreover, it was found in the literature that artificial intelligence methods have been widely used for predicting the thermal conductivity of nanofluids. Thus, in the present study, genetic algorithms (GAs) and particle swarm optimization (PSO) have been utilized to search and determine the antecedent and consequent parameters of the ANFIS model. Solid concentration and temperature were considered as input variables, and thermal conductivity, dynamic viscosity, heat transfer performance, and pumping power in both the internal laminar and turbulent flow regimes were the outputs. In order to evaluate and compare the performance of the models, two statistical indices of root mean square error (RMSE) and determination coefficient (R) were utilized. Based on the results, both of the models are able to predict the thermophysical properties appropriately. However, the ANFIS-PSO model had a better performance than the ANFIS-GA model. Finally, the studied thermophysical properties were developed by the trained ANFIS-PSO model.

Bond Line Thickness of Thermal Interface Materials With Carbon Nanotubes

2005 ◽  
Author(s):  
Senthil A. G. Singaravelu ◽  
Xuejiao Hu ◽  
Kenneth E. Goodson
Keyword(s):  
Thermal Conductivity ◽  
Carbon Nanotubes ◽  
Volume Fraction ◽  
Bond Line ◽  
Thermal Interface Materials ◽  
Thermal Interface ◽  
Line Thickness ◽  
Bond Line Thickness ◽  
The Impact ◽  
Interface Materials

Increasing power dissipation in today’s microprocessors demands thermal interface materials (TIMs) with lower thermal resistances. The TIM thermal resistance depends on the TIM thermal conductivity and the bond line thickness (BLT). Carbon Nanotubes (CNTs) have been proposed to improve the TIM thermal conductivity. However, the rheological properties of TIMs with CNT inclusions are not well understood. In this paper, the transient behavior of the BLT of the TIMs with CNT inclusions has been measured under controlled attachment pressures. The experimental results show that the impact of CNT inclusions on the BLT at low volume fractions (up to 2 vol%) is small; however, higher volume fraction of CNT inclusions (5 vol%) can cause huge increase in TIM thickness. Although thermal conductivities are higher for higher CNT fractions, a minimum TIM resistance exists at some optimum CNT fraction for a given attachment pressure.

scholarly journals Mixed convection stagnation point flow of the blood based hybrid nanofluid around a rotating sphere

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Taza Gul ◽  
Basit Ali ◽  
Wajdi Alghamdi ◽  
Saleem Nasir ◽  
Anwar Saeed ◽  
...  
Keyword(s):  
Thermal Conductivity ◽  
Heat Transport ◽  
Stagnation Point ◽  
Volume Fraction ◽  
Excellent Result ◽  
Concentration Field ◽  
Hybrid Nanofluid ◽  
Nanoparticle Volume Fraction ◽  
Nanofluid Flow ◽  
Rotating Sphere

AbstractIn this new world of fluid technologies, hybrid nanofluid has become a productive subject of research among scientists for its potential thermal features and abilities, which provides an excellent result as compared to nanofluids in growing the rate of heat transport. Our purpose here is to introduce the substantial influences of magnetic field on 2D, time-dependent and stagnation point inviscid flow of couple stress hybrid nanofluid around a rotating sphere with base fluid is pure blood, $${\text{TiO}}_{2} \,\,{\text{and}}\,\,{\text{Ag}}$$ TiO 2 and Ag as the nanoparticles. To translate the governing system of partial differential equations and the boundary conditions relevant for computation, some suitable transformations are implemented. To obtain the analytical estimations for the corresponding system of differential expression, the innovative Optimal Homotopy Analysis Method is used. The characteristics of hybrid nanofluid flow patterns, including temperature, velocity and concentration profiles are simulated and analyzed in detail due to the variation in the evolving variables. Detailed research is also performed to investigate the influences of relevant constraints on the rates, momentum and heat transport for both $${\text{TiO}}_{2} + {\text{Ag}} + Blood$$ TiO 2 + Ag + B l o o d and $${\text{TiO}}_{2} + Blood$$ TiO 2 + B l o o d . One of the many outcomes of this analysis, it is observed that increasing the magnetic factor will decelerate the hybrid nanofluid flow velocity and improve the temperature profile. It may also be demonstrated that by increasing the Brownian motion factor, significant improvement can be made in the concentration field of hybrid nanofluid. The increase in the nanoparticle volume fraction from 0.01 to 0.02 in the case of the hybrid nanofluid enhances the thermal conductivity from 5.8 to 11.947% and for the same value of the nanoparticle volume fraction in the case of nanofluid enhance the thermal conductivity from 2.576 to 5.197%.

Sign in / Sign up

Export Citation Format

Share Document