Optimal design of geometrical parameters and flow characteristics for Al2O3/water nanofluid inside corrugated heat exchangers by using entropy generation minimization and genetic algorithm methods

Ebrahimi‐Moghadam, Amir; Moghadam, Ali Jabari

doi:10.1016/j.applthermaleng.2018.12.068

Cited by 53 publications

(7 citation statements)

References 37 publications

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“…(This content can be seen in Fig. 6a-c and is consistent with previous research findings in the field [17,29,39].) Figure 6a shows the variation of against Re number for various nanoparticle concentrations (φ).…”

Section: Thermodynamics Sensitivity Analysissupporting

confidence: 90%

“…Consequently, a reduction and increment trend is, respectively, observed before and after this specific Re number. This behavior is consistent with the findings of Prof. Bejan and the other researchers in this regard [29,37,39,55].…”

Section: Thermodynamics Sensitivity Analysismentioning

confidence: 98%

“…Several investigations have been carried out on the optimization of the geometry factors and fluid flow parameters in different HEs and other energy systems by the method of EGM [26][27][28]. In one of the recently published studies, Ebrahimi-Moghadam et al [29] prepared a comprehensive sensitivity analysis and also an optimization of entropy generation for Al 2 O 3 /water nano-fluid flow inside wavy wall HEs. In other work, Ebrahimi-Moghadam et al [30] applied a multi-objective genetic algorithm (GA) optimization method for optimizing flow charactristicts and geometrical parameters of the Fe 3 O 4 /water flow inside U-bend HEs with longitudinal strip inserts.…”

Section: Introductionmentioning

confidence: 99%

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A comprehensive thermo-hydraulic analysis and optimization of turbulent TiO2/W-EG nano-fluid flow inside double-pipe heat exchangers with helical coil inserts

Ebrahimi‐Moghadam

Gohari

Hoseinzade

et al. 2020

J Braz. Soc. Mech. Sci. Eng.

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The main aim in current work is to optimize TiO 2 /W-EG nano-fluid (with 60 vol% of water and 40 vol% of ethylene glycol) flow within the inner tube of the double-pipe heat exchangers with helical coil inserts. The entropy generation is selected as the target function and is to be minimized. To reach this goal, at the first step, a comprehensive sensitivity analysis is carried out taking into account all of the nano-fluid flow conditions (including nanoparticle volume fraction , Reynolds number Re and Prandtl number Pr) and geometric parameters of the helical coil inserts (including thepitch-to-diameter ratio of coil Π). Afterward, the genetic algorithm (GA) is utilized in the optimization process. The results of sensitivity analysis reveal that and Π , respectively, have the highest and lowest impact on the thermodynamics characteristics. Also, the addition of up to 0.02 vol% nanoparticles leads to a maximum of 13.93% improvement in dimensionless entropy generation (DEG). The outputs of the GA are opt = 0.0198%, Re opt = 8421.173, Pr opt = 32.833, Π opt = 2.437 and DEG opt = 0.005086. Furthermore, based on the optimization results, a useful correlation is proposed to find the optimum geometry of the helical coil based on the nano-fluid flow conditions.

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Section: Thermodynamics Sensitivity Analysissupporting

confidence: 90%

Section: Thermodynamics Sensitivity Analysismentioning

confidence: 98%

Section: Introductionmentioning

confidence: 99%

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A comprehensive thermo-hydraulic analysis and optimization of turbulent TiO2/W-EG nano-fluid flow inside double-pipe heat exchangers with helical coil inserts

Ebrahimi‐Moghadam

Gohari

Hoseinzade

et al. 2020

J Braz. Soc. Mech. Sci. Eng.

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“…A common application of genetic algorithm is using it as an optimizer function. Genetic algorithm is a useful tool in the pattern recognition, feature selection, image understanding and machine learning [64,65]. In genetic algorithms, the genetic evolution manner of the living creatures is simulated.…”

Section: Hybrid Modelingmentioning

confidence: 99%

A hybrid genetic–BP algorithm approach for thermal conductivity modeling of nanofluid containing silver nanoparticles coated with PVP

Paknezhad

Vakili

Bozorgi

et al. 2020

J Therm Anal Calorim

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Since nanoparticles play a significant role in increasing the thermal conductivity of fluids, the present study aims to predict the thermal conductivity of silver nanofluid coated with polyvinylpyrrolidone (PVP) by the combinational model of multilayer perceptron artificial neural network and genetic algorithm. For modeling, the results of experimental measurements have been used for thermal conductivity of nanofluid containing PVP-coated silver nanoparticle-based deionized water at 25-55 °C in volume fraction of 250 ppm, 500 ppm and 1000 ppm. Henceforth, genetic algorithm is applied to improve learning process in the artificial neural network. It is in this way that the masses were chosen for each neuron's communications as well as their bias happens according to optimization performed by the genetic algorithm. To evaluate the accuracy of the model in predicting thermal conductivity of nanofluid, mean absolute percentage error, root mean square error, coefficient of determination (R 2 ) and mean bias error have exerted indices which are 1.202, 0.345, 0.989 and − 0.016, respectively. The results of the indices and predictions, compared to the experimental results, show high accuracy and reliable combinational model of artificial neural network and genetic algorithm.

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“…In recent years, the energy crisis and its related problems has become an important issue in the world, and the supply of energy resources and power generation methods are one of the most important issues in each country and have overwhelmed all political and economic issues. The limitation of fossil fuels, environmental problems, population growth, economic growth, and consumption ratios are critical issues that require appropriate solutions …”

Section: Introductionmentioning

confidence: 99%

Experimental and numerical investigations of a novel chimney system for power generation using the combination of fossil fuel power plant exhaust gases and ambient air

Shahdost

Astaraei

Ebrahimi‐Moghadam

et al. 2019

Energy Science & Engineering

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Fossil fuel power plants, one of the main sources of power generation, are the major emitters of exhaust gases into the environment at relatively high temperature and significant energy. One way to utilize these hot gases is to use wind turbines in the path of fluid flow that created by buoyancy (like a solar chimney). In this paper, the power generation from the gas of the power plant's chimney based on the buoyancy phenomenon using the combination of the power plant's hot output with ambient air is modeled and investigated at different discharge rates and temperatures of the power plant's hot output on a pilot scale. An experimental model, at the same scale of modeling, is constructed and used to validate the modeling results. The obtained results showed that due to the buoyancy phenomenon the combination of the power plant's exhaust gases with the ambient air creates a higher volume of the fluid with a good velocity inside the chimney compared with the exhaust gases of the power plant only. At the temperature of 350 K and velocity of 1 m/s for the hot inlet, the velocity of the fluid resulting from the buoyancy would be greater than 1 m/s for the air which enters the chimney's foot and its gas.

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Optimal design of geometrical parameters and flow characteristics for Al2O3/water nanofluid inside corrugated heat exchangers by using entropy generation minimization and genetic algorithm methods

Cited by 53 publications

References 37 publications

A comprehensive thermo-hydraulic analysis and optimization of turbulent TiO2/W-EG nano-fluid flow inside double-pipe heat exchangers with helical coil inserts

A comprehensive thermo-hydraulic analysis and optimization of turbulent TiO2/W-EG nano-fluid flow inside double-pipe heat exchangers with helical coil inserts

A hybrid genetic–BP algorithm approach for thermal conductivity modeling of nanofluid containing silver nanoparticles coated with PVP

Experimental and numerical investigations of a novel chimney system for power generation using the combination of fossil fuel power plant exhaust gases and ambient air

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