Numerical Study of the Solid Volume Fraction and Pressure Drop of Fibrous Media by Response Surface Methodology

2013 ◽  
Vol 36 (5) ◽  
pp. 788-794 ◽  
Author(s):  
X. Zhu ◽  
F. Qian ◽  
J. Lu ◽  
H. Zhang
Keyword(s):  
Response Surface Methodology ◽  
Pressure Drop ◽  
Response Surface ◽  
Volume Fraction ◽  
Numerical Study ◽  
Solid Volume Fraction ◽  
Fibrous Media

scholarly journals Numerical analysis of mixed convection characteristics inside a ventilated cavity including the effects of nanoparticle suspensions

2017 ◽  
Vol 21 (5) ◽  
pp. 2205-2215
Author(s):  
Ehsan Sourtiji ◽  
Mofid Gorji-Bandpy
Keyword(s):  
Heat Transfer ◽  
Nusselt Number ◽  
Pressure Drop ◽  
Mixed Convection ◽  
Volume Fraction ◽  
Numerical Study ◽  
Solid Volume Fraction ◽  
Maximum Heat ◽  
Outlet Port ◽  
Maximum Heat Transfer

A numerical study of mixed convection flow and heat transfer inside a square cavity with inlet and outlet ports is performed. The position of the inlet port is fixed but the location of the outlet port is varied along the four walls of the cavity to investigate the best position corresponding to maximum heat transfer rate and minimum pressure drop in the cavity. It is seen that the overall Nusselt number and pressure drop coefficient vary drastically depending on the Reynolds and Richardson numbers and the position of the outlet port. As the Richardson number increases, the overall Nusselt number generally rises for all cases investigated. It is deduced that placing the outlet port on the right side of the top wall is the best position that leads to the greatest overall Nusselt number and lower pressure drop coefficient. Finally, the effects of nanoparticles on heat transfer are investigated for the best position of the outlet port. It is found that an enhancement of heat transfer and pressure drop is seen in the presence of nanoparticles and augments with solid volume fraction of the nanofluid. It is also observed that the effects of nanoparticles on heat transfer at low Richardson numbers is more than that of high Richardson numbers. <br><br><font color="red"><b> This article has been retracted. Link to the retraction <u><a href="http://dx.doi.org/10.2298/TSCI190625278E">10.2298/TSCI190625278E</a><u></b></font>

Pareto Optimal Design of Thermal Conductivity and Viscosity of NDCo3O4 Nanofluids by MOPSO and NSGA II Using Response Surface Methodology

2017 ◽  
Vol 14 (1) ◽  
pp. 62-70 ◽  
Author(s):  
Mohammad Hemmat Esfe ◽  
Mohammad Hadi Hajmohammad ◽  
Somchai Wongwises
Keyword(s):  
Thermal Conductivity ◽  
Response Surface Methodology ◽  
Response Surface ◽  
Volume Fraction ◽  
Solid Volume Fraction ◽  
Particle Swarm ◽  
Target Function ◽  
Maximum Temperature ◽  
Particle Swarm Algorithm ◽  
Multi Objective

Background: Achieving a nanofluid with optimal thermal conductivity and viscosity is one of the main problems of applications of nanofluids in industries. Methods: There are experimental and theoretical methods to reach an applicable nanofluids with mentioned characteristics. Surely, experimental methods are not optimal in time and cost($) aspects. So, in the present study multi-objective optimization of nanofluids ND-Co3O4 is done to find the optimal solid volume fraction for having maximum thermal conductivity and minimum viscosity. The response surface methodology (RSM) is used to model target functions using empirical data. The improved non- dominated sorting method and multi-objective particle swarm optimization are used as powerful tools for optimization. In order to implement the optimization process, the obtained target function model is joined to multi-objective particle swarm algorithm and it is used in each step of the target function evaluation. Results: The obtained results of these two algorithms are presented in the form of Pareto front. Also, a comparison between them is provided. According to the optimal results, MOPSO has a better performance that the other one. Conclusion: It will be shown that the highest thermal conductivity and the lowest viscosity occur at the maximum temperature. By investigating obtained optimum results, the optimal point with highest thermal conductivity and lowest viscosity was found at about 60 °C and 0.1 to 0.11 of solid volume fraction.

Genetic Programming based Drag Model with Improved Prediction Accuracy for Fluidization Systems

2017 ◽  
Vol 15 (2) ◽  
Author(s):  
R. R. Sonolikar ◽  
M. P. Patil ◽  
R. B. Mankar ◽  
S. S. Tambe ◽  
B. D. Kulkarni
Keyword(s):  
Pressure Drop ◽  
Genetic Programming ◽  
Drag Coefficient ◽  
Prediction Accuracy ◽  
Volume Fraction ◽  
Solid Volume Fraction ◽  
Superior Performance ◽  
Momentum Exchange ◽  
Drag Model ◽  
Parameter Ranges

Abstract The drag coefficient plays a vital role in the modeling of gas-solid flows. Its knowledge is essential for understanding the momentum exchange between the gas and solid phases of a fluidization system, and correctly predicting the related hydrodynamics. There exists a number of models for predicting the magnitude of the drag coefficient. However, their major limitation is that they predict widely differing drag coefficient values over same parameter ranges. The parameter ranges over which models possess a good drag prediction accuracy are also not specified explicitly. Accordingly, the present investigation employs Geldart’s group B particles fluidization data from various studies covering wide ranges of Re and εs to propose a new unified drag coefficient model. A novel artificial intelligence based formalism namely genetic programming (GP) has been used to obtain this model. It is developed using the pressure drop approach, and its performance has been assessed rigorously for predicting the bed height, pressure drop, and solid volume fraction at different magnitudes of Reynolds number, by simulating a 3D bubbling fluidized bed. The new drag model has been found to possess better prediction accuracy and applicability over a much wider range of Re and εs than a number of existing models. Owing to the superior performance of the new drag model, it has a potential to gainfully replace the existing drag models in predicting the hydrodynamic behavior of fluidized beds.

Optimization of phenolics and antioxidants extraction from Centaurium erythraea using response surface methodology

2021 ◽  
pp. 6455-6462
Author(s):  
Wissam Zam ◽  
Ali Ali ◽  
Dimah Saleem ◽  
Sahar Alali
Keyword(s):  
Antioxidant Activity ◽  
Response Surface Methodology ◽  
Response Surface ◽  
Volume Fraction ◽  
Quadratic Model ◽  
Natural Food ◽  
Solvent Ratio ◽  
Research Attention ◽  
Experimental Values ◽  
Centaurium Erythraea

In recent years, Centaurium erythraea extracts have attracted much research attention in the context of prevention or treatment of many diseases due to its bioactive compounds content and antioxidant activity. The antioxidants of C. erythraea are very effective as they possess excellent antioxidant activity. Thus, it can be used as a safe and natural food preservative. The aim of this study is to make extracts more effective by optimizing the extraction conditions of the phenolics and antioxidants from C. erythraea using response surface methodology (RSM) based on a central composite design (CCD). Two process variables (Methanol volume fraction and solid - solvent ratio) were evaluated at five levels (13 experimental designs). Multiple regression analyses were performed to obtain quadratic polynomial equations using RSM; each response was fitted by a quadratic model. The adequacy of the models was proven using the analysis of variance (ANOVA). The significant effects of the factors and their interactions on the extraction efficiency were investigated at 95% confidence interval. RSM indicated that the optimal extraction conditions were 71% methanol volume fraction and 2.2:10 solid:solvent ratio. Predicted values thus obtained were close to the experimental values indicating suitability of the model.

scholarly journals Study on filtration performance of elliptical fiber with different arrangements

2020 ◽  
Vol 15 ◽  
pp. 155892501989388
Author(s):  
JiaWei Zhou ◽  
Liang Zhang ◽  
Bo Zhang ◽  
Wei Gong
Keyword(s):  
Quality Factor ◽  
Volume Fraction ◽  
Solid Volume Fraction ◽  
Particle Diameter ◽  
Dense Layer ◽  
Fibrous Media ◽  
Bimodal Structure ◽  
Filtration Performance ◽  
Particle Penetration ◽  
Circular Fiber

The fibrous media composed of elliptical fibers is widely used owing to the high filtration efficiency. However, there are few studies on the arrangement of non-circular fibers, although the single non-circular fiber has been clearly investigated. In this article, two-dimensional numerical geometries of fibrous media with different elliptical fiber arrangements, namely, random distribution structure, dense–sparse structure, and bimodal structure, are developed for studying filtration performance. The results show that the large aspect ratio and solid volume fraction represent low particle penetration. When the particle diameter ( Dp) is small, the quality factor of bimodal structure is higher than the dense–sparse structure, especially at Dp = 50 nm. For the large Dp, the opposite is true. Meanwhile, reducing fiber diameter ( Df) is more significant than increasing solid volume fraction in terms of improving penetration. As for dense–sparse structure, replacing the elliptical fibers in sparse layers with circular fibers can comprehensively improve the quality factor of fibrous media. However, if the replacement between elliptical fiber and circular fiber occurs in dense layer, it will result in high quality factor at Dp ⩽ 500 nm, while low quality factor at Dp > 500 nm.

Numerical Study of Forced Convection of Nanofluids in a Microchannel Heat Sink

2008 ◽  
Author(s):  
Parisa Vaziee ◽  
Omid Abouali
Keyword(s):  
Heat Transfer ◽  
Pressure Drop ◽  
Heat Sink ◽  
Volume Fraction ◽  
Numerical Study ◽  
Heat Removal ◽  
Al2o3 Nanoparticles ◽  
Microchannel Heat Sink ◽  
Particle Volume ◽  
Volume Fractions

Effectiveness of the microchannel heat sink cooled by nanofluids with various particle volume fractions is investigated numerically using the latest theoretical models for conductivity and viscosity of the nanofluids. Both laminar and turbulent flows are considered in this research. The model of conductivity used in this research accounts for the fundamental role of Brownian motion of the nanoparticles which is in good agreement with the experimental data. The changes in viscosity of the nanofluid due to temperature variation are considered also. Final results are compared with the experimental measurements for heat transfer coefficient and pressure drop in microchannel. Enhancement in heat transfer is achieved for laminar flow with increasing of volume fraction of Al2O3 nanoparticles. But for turbulent flow an enhancement of heat removal was not seen and using higher volume fractions of nanoparticles increases the maximum substrate temperature. Pressure drop is increased with using nanofluids because of the augmentation in the viscosity and this increase is more noticeable in higher Reynolds numbers.

Numerical Simulation of Nanofluid-Cooling Enhancement of Three Fins Mounted in a Horizontal Channel

2016 ◽  
Vol 138 (9) ◽  
Author(s):  
Moussa Khentoul ◽  
Rachid Bessaïh
Keyword(s):  
Volume Fraction ◽  
Numerical Study ◽  
Solid Volume Fraction ◽  
Horizontal Channel ◽  
Thermal Fields ◽  
Nusselt Numbers ◽  
Simpler Algorithm ◽  
Laminar Mixed Convection ◽  
Cooling Enhancement ◽  
Volume Method

This article presents a numerical study of two-dimensional laminar mixed convection in a horizontal channel. The upper horizontal wall of the channel is insulated. The governing equations were solved by using the finite volume method based on the simpler algorithm. Comparisons with previous results were performed and found to be in excellent agreement. The results were presented in terms of streamlines, isotherms, local and average Nusselt numbers for the Richardson number (0 ≤ Ri ≤ 10), Reynolds number (5 ≤ Re ≤ 100), solid volume fraction of nanoparticles (0 ≤ ϕ ≤ 0.10), and the type of nanofluids (Cu, Ag, Al2O3, and TiO2). The results show that the previous parameters have considerable effects on the flow and thermal fields. It was found that the heat transfer increases with increasing of Ra, Re, and ϕ.

scholarly journals Optimization of electro-Fenton oxidation of carbonated soft drink industry wastewater using response surface methodology

2020 ◽  
Vol 39 (2) ◽  
pp. 129
Author(s):  
Reza Davarnejad ◽  
Jamal Azizi ◽  
Amir Joodaki ◽  
Sepideh Mansoori
Keyword(s):  
Response Surface Methodology ◽  
Response Surface ◽  
Current Density ◽  
Volume Fraction ◽  
Soft Drink ◽  
Oxygen Demand ◽  
Volume Ratio ◽  
Organic Pollution ◽  
Molar Ratio ◽  
The Impact

The immense volume of highly polluted organic wastewater continuously generated in the beverage industry urges the design of new types of wastewater treatment plants. This study aimed to evaluate the applicability of the electro-Fenton (EF) technique to reduce organic pollution of real effluent from a carbonated soft drink factory. The impact of various process variables like pH, time, current density, H2O2/Fe2+ molar ratio, and the volume ratio of H2O2/soft drink wastewater (SDW) was analyzed using response surface methodology (RSM). The observed responses were in good agreement with predicted values obtained through optimization. The optimum conditions showed a chemical oxygen demand (COD) removal efficiency of 73.07 %, pH of 4.14, time of 41.55 min, current density of 46.12 mA/cm2, H2O2/Fe2+ molar ratio of 0.9802, and H2O2/SDW volume fraction of 2.74 ml/l. The EF process was able to effectively diminish the organic pollution, reduce the residence time and, therefore, the operating costs.

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