SIGNIFICANCE AND CORRELATION OF NUSSELT NUMBER (Nu), PRANDTL NUMBER (Pr) AND STANTON NUMBER (St) WITH VOLUME FRACTION OF VAPOUR IN A PHASE CHANGE SITUATION AROUND A CYLINDER IN STAGGERED ARRANGEMENT

2019 ◽  
Vol 23 (1) ◽  
pp. 45-67
Author(s):  
Ravi Pullepudi
Keyword(s):  
Nusselt Number ◽  
Prandtl Number ◽  
Phase Change ◽  
Volume Fraction ◽  
Stanton Number ◽  
Staggered Arrangement

scholarly journals Flow and Heat Transfer in Micro Pin Fin Heat Sinks With Nano-Encapsulated Phase Change Materials

2016 ◽  
Vol 138 (6) ◽  
Author(s):  
Bahram Rajabifar ◽  
Hamid Reza Seyf ◽  
Yuwen Zhang ◽  
Sanjeev K. Khanna
Keyword(s):  
Heat Transfer ◽  
Nusselt Number ◽  
Phase Change ◽  
Wall Temperature ◽  
Phase Change Materials ◽  
Euler Number ◽  
Volume Fraction ◽  
Inlet Velocity ◽  
Pin Fin ◽  
Flow And Heat Transfer

In this paper, a 3D-conjugated heat transfer model for nano-encapsulated phase change materials (NEPCMs) cooled micro pin fin heat sink (MPFHS) is presented. The governing equations of flow and heat transfer are solved using a finite volume method based on collocated grid and the results are validated with the available data reported in the literature. The effect of nanoparticles volume fraction (C = 0.1, 0.2, and 0.3), inlet velocity (Vin = 0.015, 0.030, and 0.045 m/s), and bottom wall temperature (Twall = 299.15, 303.15, 315.15, and 350.15 K) is studied on Nusselt and Euler numbers as well as temperature contours in the system. The results indicate that significant heat transfer enhancement is achieved when using the NEPCM slurry as an advanced coolant. The maximum Nusselt number when NEPCM slurry (C = 0.3) with Vin = 0.015, 0.030, and 0.045 (m/s) is employed is 2.27, 1.81, and 1.56 times higher than the ones with base fluid, respectively. However, with increasing bottom wall temperature, the Nusselt number first increases then decreases. The former is due to higher heat transfer capability of coolant at temperatures over the melting range of phase change material (PCM) particles due to partial melting of nanoparticles in this range. However, the latter phenomenon is due to the lower capability of the NEPCM particles and consequently coolant in absorbing heat at coolant temperatures is higher than the temperature correspond to fully melted NEPCM. It was observed that the NEPCM slurry has a drastic effect on the Euler number, and with increasing volume fraction and decreasing inlet velocity, the Euler number increases accordingly.

Numerical simulation of the effect of using nanofluid in phase change process of cooling fluid

2019 ◽  
Vol 30 (6) ◽  
pp. 2913-2934 ◽  
Author(s):  
Farzad Pourfattah ◽  
Saeid Yousefi ◽  
Omid Ali Akbari ◽  
Mahsa Adhampour ◽  
Davood Toghraie ◽  
...  
Keyword(s):  
Heat Transfer ◽  
Nusselt Number ◽  
Phase Change ◽  
Vapor Phase ◽  
Change Process ◽  
Volume Fraction ◽  
Cooling Fluid ◽  
Content Type ◽  
Phase Change Process ◽  
Boiling Process

Purpose The purpose of this paper is to numerically simulate the nanofluid boiling inside a tube in turbulent flow regime and to investigate the effect of adding volume faction of CuO nanoparticles on the boiling process. Design/methodology/approach To make sure the accuracy of the obtained numerical results, the results of this paper have been compared with the experimental results and an acceptable coincidence has been achieved. In the current paper, by Euler–Euler method, the phase change of boiling phenomenon has been modeled. The presented results are the local Nusselt number distribution, temperature distribution of wall, the distribution of volume fraction of vapor phase and fluid temperature at the center of the tube. Findings The obtained results indicate that using nanofluid is very effective in the postponement of the boiling process. Hence, by change the amount of volume fraction of nanoparticles in base fluid, the location of phase change and bubble creation are changed. Also, at the Reynolds numbers of 50,000, 100,000 and 150,000 with the volume fraction of 2 per cent, the beginning locations of phase change process are, respectively, 2D, 10D and 13D, and for the volume fraction of 4 per cent, the beginning locations of phase change are 4D, 18D and 19D, respectively. These results indicate that, as the volume fraction of nanoparticles increases, the location of the start of the phase change process is postponed that this issue causes the increment of heat transfer from wall to fluid and the reduction of wall temperature. In general, it can be stated that, in boiling flows, using nanofluid because of the delay in boiling phenomenon has a good effect on heat transfer enhancement of heated walls. Also, the obtained results show that, by increasing Reynolds number, the created vapor phase reduces that leads to increase of the Nusselt number. Originality/value The paper investigates the effect of using nanofluid in phase change process of cooling fluid.

scholarly journals Effect of using RT-44 as phase-change material in the porous microchannel

2021 ◽  
Author(s):  
Mahdi Alibeigi ◽  
Mohammadreza Sabzeali
Keyword(s):  
Porous Media ◽  
Nusselt Number ◽  
Phase Change ◽  
Phase Change Material ◽  
Volume Fraction ◽  
Bulk Temperature ◽  
Micro Channel ◽  
Nano Fluid ◽  
Result Show ◽  
Change Material

Abstract In this paper, the influence of the utilizing RT-44 which, knows as a phase-change material (PCM) has used in an overall porous layer channel or optional additive nano particle of water/ZnO with three injecting fluid from its lower wall is investigated. The boundary condition slip-walls for the lower and higher walls of the micro-channel as insulation and constant temperature is considered. respectively, for assessment of PCM and nanoparticles consequences, the volume fraction of 0,2% and 5% determined for both of nanofluid and PCM. The result show that the Nusselt number increased with adding PCM to the porous media and decreasing with adding nanoparticles. When volume fraction of nano fluid is 5% the relative Nusselt number was calculated for PCM volume fraction of 1%,2% and 5% with amount of \(N{u^*}=0.9607\),\(N{u^*}=0.9710\)and\(N{u^*}=0.9869\).respectively, for more supplementary the microchannel has levelized in two stage and three stage. The bulk temperature calculated for three stages for each level, at first stage was 299.90 K, at second stage was 302.38 K and 302.72 K at third stage. For considering the geometric parameters effect an optimization with monte Carlo(MC) method has been simulated in terms of maximizing Nusselt number ,it approved the relative Nusselt number Nusselt 1.026 and it increasing 0.26 K at the end of micro channel. Finally, the Additive PCM to porous material purposed for heating and additive nanofluid to the porous media purposed for cooling as well, the multistage channel purposed for heating at the latest stage.

Effect of Nanofluid on Heat Transfer Enhancement for Mixed Convection Flow Over a Corrugated Surface

2020 ◽  
Vol 45 (4) ◽  
pp. 373-383
Author(s):  
Nepal Chandra Roy ◽  
Sadia Siddiqa
Keyword(s):  
Heat Transfer ◽  
Boundary Layer ◽  
Nusselt Number ◽  
Mixed Convection ◽  
Local Nusselt Number ◽  
Richardson Number ◽  
Thermal Boundary Layer ◽  
Volume Fraction ◽  
Convection Flow ◽  
Mixed Convection Flow

AbstractA mathematical model for mixed convection flow of a nanofluid along a vertical wavy surface has been studied. Numerical results reveal the effects of the volume fraction of nanoparticles, the axial distribution, the Richardson number, and the amplitude/wavelength ratio on the heat transfer of Al2O3-water nanofluid. By increasing the volume fraction of nanoparticles, the local Nusselt number and the thermal boundary layer increases significantly. In case of \mathrm{Ri}=1.0, the inclusion of 2 % and 5 % nanoparticles in the pure fluid augments the local Nusselt number, measured at the axial position 6.0, by 6.6 % and 16.3 % for a flat plate and by 5.9 % and 14.5 %, and 5.4 % and 13.3 % for the wavy surfaces with an amplitude/wavelength ratio of 0.1 and 0.2, respectively. However, when the Richardson number is increased, the local Nusselt number is found to increase but the thermal boundary layer decreases. For small values of the amplitude/wavelength ratio, the two harmonics pattern of the energy field cannot be detected by the local Nusselt number curve, however the isotherms clearly demonstrate this characteristic. The pressure leads to the first harmonic, and the buoyancy, diffusion, and inertia forces produce the second harmonic.

Stability of thermocapillary flows in non-cylindrical liquid bridges

2002 ◽  
Vol 458 ◽  
pp. 35-73 ◽  
Author(s):  
CH. NIENHÜSER ◽  
H. C. KUHLMANN
Keyword(s):  
Reynolds Number ◽  
Prandtl Number ◽  
Critical Reynolds Number ◽  
Volume Fraction ◽  
Thermocapillary Flow ◽  
Surface Shape ◽  
Liquid Bridges ◽  
Gravity Level ◽  
Neutral Curves ◽  
Prandtl Numbers

The thermocapillary flow in liquid bridges is investigated numerically. In the limit of large mean surface tension the free-surface shape is independent of the flow and temperature fields and depends only on the volume of liquid and the hydrostatic pressure difference. When gravity acts parallel to the axis of the liquid bridge the shape is axisymmetric. A differential heating of the bounding circular disks then causes a steady two-dimensional thermocapillary flow which is calculated by a finite-difference method on body-fitted coordinates. The linear-stability problem for the basic flow is solved using azimuthal normal modes computed with the same discretization method. The dependence of the critical Reynolds number on the volume fraction, gravity level, Prandtl number, and aspect ratio is explained by analysing the energy budgets of the neutral modes. For small Prandtl numbers (Pr = 0.02) the critical Reynolds number exhibits a smooth minimum near volume fractions which approximately correspond to the volume of a cylindrical bridge. When the Prandtl number is large (Pr = 4) the intersection of two neutral curves results in a sharp peak of the critical Reynolds number. Since the instabilities for low and high Prandtl numbers are markedly different, the influence of gravity leads to a distinctly different behaviour. While the hydrostatic shape of the bridge is the most important effect of gravity on the critical point for low-Prandtl-number flows, buoyancy is the dominating factor for the stability of the flow in a gravity field when the Prandtl number is high.

Study of the boundary layer heat transfer of nanofluids over a stretching sheet: Passive control of nanoparticles at the surface

2015 ◽  
Vol 93 (7) ◽  
pp. 725-733 ◽  
Author(s):  
M. Ghalambaz ◽  
E. Izadpanahi ◽  
A. Noghrehabadi ◽  
A. Chamkha
Keyword(s):  
Heat Transfer ◽  
Thermal Conductivity ◽  
Boundary Layer ◽  
Nusselt Number ◽  
Heat Transfer Enhancement ◽  
Base Fluid ◽  
Stretching Sheet ◽  
Volume Fraction ◽  
Enhancement Ratio ◽  
Transfer Enhancement

The boundary layer heat and mass transfer of nanofluids over an isothermal stretching sheet is analyzed using a drift-flux model. The relative slip velocity between the nanoparticles and the base fluid is taken into account. The nanoparticles’ volume fractions at the surface of the sheet are considered to be adjusted passively. The thermal conductivity and the dynamic viscosity of the nanofluid are considered as functions of the local volume fraction of the nanoparticles. A non-dimensional parameter, heat transfer enhancement ratio, is introduced, which shows the alteration of the thermal convective coefficient of the nanofluid compared to the base fluid. The governing partial differential equations are reduced into a set of nonlinear ordinary differential equations using appropriate similarity transformations and then solved numerically using the fourth-order Runge–Kutta and Newton–Raphson methods along with the shooting technique. The effects of six non-dimensional parameters, namely, the Prandtl number of the base fluid Prbf, Lewis number Le, Brownian motion parameter Nb, thermophoresis parameter Nt, variable thermal conductivity parameter Nc and the variable viscosity parameter Nv, on the velocity, temperature, and concentration profiles as well as the reduced Nusselt number and the enhancement ratio are investigated. Finally, case studies for Al2O3 and Cu nanoparticles dispersed in water are performed. It is found that increases in the ambient values of the nanoparticles volume fraction cause decreases in both the dimensionless shear stress f″(0) and the reduced Nusselt number Nur. Furthermore, an augmentation of the ambient value of the volume fraction of nanoparticles results in an increase the heat transfer enhancement ratio hnf/hbf. Therefore, using nanoparticles produces heat transfer enhancement from the sheet.

NUMERICAL SIMULATION OF MARANGONI MAGNETOHYDRODYNAMIC BIO-NANOFLUID CONVECTION FROM A NON-ISOTHERMAL SURFACE WITH MAGNETIC INDUCTION EFFECTS: A BIO-NANOMATERIAL MANUFACTURING TRANSPORT MODEL

2014 ◽  
Vol 14 (03) ◽  
pp. 1450039 ◽  
Author(s):  
O. ANWAR BÉG ◽  
M. FERDOWS ◽  
S. SHAMIMA ◽  
M. NAZRUL ISLAM
Keyword(s):  
Magnetic Field ◽  
Boundary Layer ◽  
Prandtl Number ◽  
Stream Function ◽  
Magnetic Induction ◽  
Body Force ◽  
Volume Fraction ◽  
Solid Volume Fraction ◽  
Convection Boundary Layer ◽  
Force Parameter

Laminar magnetohydrodynamic Marangoni-forced convection boundary layer flow of a water-based biopolymer nanofluid containing nanoparticles from a non-isothermal plate is studied. Magnetic induction effects are incorporated. A variety of nanoparticles are studied, specifically, silver, copper, aluminium oxide and titanium oxide. The Tiwari–Das model is utilized for simulating nanofluid effects. The normalized ordinary differential boundary layer equations (mass, magnetic field continuity, momentum, induced magnetic field and energy conservation) are solved subject to appropriate boundary conditions using Maple shooting quadrature. The influence of Prandtl number (Pr), magnetohydrodynamic body force parameter (β), reciprocal of magnetic Prandtl number (α) and nanofluid solid volume fraction (φ) on velocity, temperature and magnetic stream function distributions is investigated in the presence of strong Marangoni effects (ξ i.e., Marangoni parameter is set as unity). Magnetic stream function is accentuated with body force parameter. The flow is considerably decelerated as is magnetic stream function gradient, with increasing nanofluid solid volume fraction, whereas temperatures are significantly enhanced. Interesting features in the flow regime are explored. The study finds applications in the fabrication of complex biomedical nanofluids, biopolymers, etc.

scholarly journals Phase-Transition Thermal Charging of a Channel-Shape Thermal Energy Storage Unit: Taguchi Optimization Approach and Copper Foam Inserts

Molecules ◽  
2021 ◽  
Vol 26 (5) ◽  
pp. 1235
Author(s):  
Mohammad Ghalambaz ◽  
Seyed Abdollah Mansouri Mehryan ◽  
Ahmad Hajjar ◽  
Obai Younis ◽  
Mikhail A. Sheremet ◽  
...  
Keyword(s):  
Energy Storage ◽  
Phase Change ◽  
Thermal Energy ◽  
Thermal Energy Storage ◽  
Metal Foam ◽  
Volume Fraction ◽  
Foam Layer ◽  
Storage Unit ◽  
Energy Storage Unit ◽  
Copper Foam

Thermal energy storage is a technique that has the potential to contribute to future energy grids to reduce fluctuations in supply from renewable energy sources. The principle of energy storage is to drive an endothermic phase change when excess energy is available and to allow the phase change to reverse and release heat when energy demand exceeds supply. Unwanted charge leakage and low heat transfer rates can limit the effectiveness of the units, but both of these problems can be mitigated by incorporating a metal foam into the design of the storage unit. This study demonstrates the benefits of adding copper foam into a thermal energy storage unit based on capric acid enhanced by copper nanoparticles. The volume fraction of nanoparticles and the location and porosity of the foam were optimized using the Taguchi approach to minimize the charge leakage expected from simulations. Placing the foam layer at the bottom of the unit with the maximum possible height and minimum porosity led to the lowest charge time. The optimum concentration of nanoparticles was found to be 4 vol.%, while the maximu possible concentration was 6 vol.%. The use of an optimized design of the enclosure and the optimum fraction of nanoparticles led to a predicted charging time for the unit that was approximately 58% shorter than that of the worst design. A sensitivity analysis shows that the height of the foam layer and its porosity are the dominant variables, and the location of the porous layer and volume fraction of nanoparticles are of secondary importance. Therefore, a well-designed location and size of a metal foam layer could be used to improve the charging speed of thermal energy storage units significantly. In such designs, the porosity and the placement-location of the foam should be considered more strongly than other factors.

A COMPARATIVE STUDY OF MULTIPLE REGRESSION AND MACHINE LEARNING TECHNIQUES FOR PREDICTION OF NANOFLUID HEAT TRANSFER

2021 ◽  
pp. 1-22
Author(s):  
Eyup Kocak ◽  
Ulku Ece Ayli ◽  
Hasmet Turkoglu
Keyword(s):  
Heat Transfer ◽  
Nusselt Number ◽  
Multiple Regression ◽  
Volume Fraction ◽  
Particle Diameter ◽  
Machine Learning Techniques ◽  
Exponential Factor ◽  
Nano Fluid ◽  
Neuro Fuzzy ◽  
Interface System

Abstract The aim of this paper is to introduce and discuss prediction power of the multiple regression technique, Artificial Neural Network (ANN) and Adaptive Neuro-Fuzzy Interface System (ANFIS) methods for predicting the forced convection heat transfer characteristics of a turbulent nano fluid flow a pipe. Water and Al2O3 mixture is used as the nano fluid. Utilizing FLUENT software, numerical computations were performed with volume fraction ranging between 0.3% and 5%, particle diameter ranging between 20 and 140 nm and Reynolds number ranging between 7000 and 21000. Based on the computationally obtained results, a correlation is developed for Nusselt number using the multiple regression method. Also, based on the CFD results different ANN architectures with different number of neurons in the hidden layers and several training algorithms (Levenberg-Marquardt, Bayesian Regularization, Scaled Conjugate Gradient) are tested to find the best ANN architecture. In addition, Adaptive Neuro-fuzzy Interface System (ANFIS) is also used to predict the Nusselt number. In the ANFIS, number of clusters, exponential factor and Membership Function (MF) type are optimized. The results obtained from multiple regression correlation, ANN and ANFIS were compared. According to the obtained results, ANFIS is a powerful tool with a R2 of 0.9987 for predictions.

Thermo-Solutal Convection of a Nanofluid Utilizing Fourier’s-Type Compass Conditions

2020 ◽  
Vol 9 (4) ◽  
pp. 362-374
Author(s):  
J. C. Umavathi ◽  
Ali J. Chamkha
Keyword(s):  
Brownian Motion ◽  
Prandtl Number ◽  
Boundary Conditions ◽  
Volume Fraction ◽  
Temperature Fields ◽  
Physical Parameters ◽  
Surface Boundary ◽  
Perturbation Scheme ◽  
Runge Kutta ◽  
The Impact

Nanotechnology has infiltrated into duct design in parallel with many other fields of mechanical, medical and energy engineering. Motivated by the excellent potential of nanofluids, a subset of materials engineered at the nanoscale, in the present work, a new mathematical model is developed for natural convection in a vertical duct containing nanofluid. Numerical scrutiny for the double-diffusive free and forced convection within a duct encumbered with nanofluid is performed. Buongiorno’s model is deployed to define the nanofluid. Robin boundary conditions are used to define the surface boundary conditions. Thermal and concentration equations envisage the viscous, Brownian motion, thermosphores of the nanofluid, Soret and Dufour effects. Using the Boussi-nesq approximation the solutal buoyancy effect as a result of gradients in concentration are incorporated. The conservation equations which are nonlinear are numerically estimated using fourth order Runge-Kutta methodology and analytically ratifying regular perturbation scheme. The mass, heat, nanoparticle concentration and species concentration fields on eight dimensionless physical parameters such as thermal and mass Grashof numbers, Brownian motion parameter, thermal parameter, Prandtl number, Eckert number, Schmidt parameter, and Soret parameter are calculated. The impact of these parameters are outlined pictorially. The velocity and temperature fields are boosted with the thermal Grashof number. The Soret and the Schemidt parameters reduces the nanoparticle volume fraction but it heightens the momentum, temperature and concentration. At the cold wall thermal and concentration Grashof numbers reduces the Nusselt values but they increase the Nusselt values at the hot wall. The reversal consequence was attained at the hot plate. The perturbation and Runge-Kutta solutions are equal in the nonappearance of Prandtl number. The (E. Zanchini, Int. J. Heat Mass Transfer 41, 3949 (1998)). results are restored for the regular fluid. The heat transfer rate is high for nanofluid when matched with regular fluid.

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