scholarly journals INVESTIGATION OF HEAT TRANSFER ON TWO ADJACENT NARROW PLATES WITH NATURAL CONVECTION

2021 ◽  
Vol 9 (11) ◽  
pp. 302-312
Author(s):  
Md. Aamir Sohail ◽  
◽  
Ravi Kulkarni H. ◽  
P. Rathnakumar ◽  
Faheem Akthar ◽  
...  
Keyword(s):  
Heat Transfer ◽  
Heat Transfer Coefficient ◽  
Natural Convection ◽  
Transfer Coefficient ◽  
Graphical Representation ◽  
Vertical Channel ◽  
Reynolds Numbers ◽  
Thin Plates ◽  
Cfd Modeling ◽  
Convection Flow

Natural convection flow in a vertical channel containing inside objects exists in a number of advance technological applications, including heat transfer from electronic circuits, refrigerators, heat exchangers, power station, fueling components, chillers, and residential ventilation, etc. In this thesis the model is created in CREO, and then imported into ANSYS to simulate air flow through vertical thin plates. The focus of the thesis will be on thermal and CFD modeling of vertical thin plates with variable Reynolds numbers (2×106& 4×106) and at angles (0°,30°&60°) respectively. Thermal analysis was performed on vertical thin narrow plates made up of steel, aluminium, and copper at various heat transfer coefficient rates.Modeling and analysis of the narrow vertical plate is demonstrated utilising the data books details and design formulary.CFD analysis results tabulated at different Reynolds number, pressure, velocity, heat transfer coefficient, mass flow rate and heat transfer and also which is drawn into graphical representation.3D modelling was done in the parametric application Pro-Engineer, and analysis is performed in ANSYS.

Bouyancy Effect on Forced Convection in Vertical Tubes at High Reynolds Numbers

2010 ◽  
Vol 2 (4) ◽  
Author(s):  
LiDong Huang ◽  
Kevin J. Farrell
Keyword(s):  
Heat Transfer ◽  
Heat Transfer Coefficient ◽  
Natural Convection ◽  
Mixed Convection ◽  
Transfer Coefficient ◽  
Flow Regime ◽  
Forced Convection ◽  
Reynolds Numbers ◽  
Buoyancy Effect ◽  
Vertical Tubes

The complex interaction of forced and natural convections depends on flow regime and flow direction. Aiding flow occurs when both driving forces act in the same direction (heating upflow fluid and cooling downflow fluid), opposing flow occurs when they act in different directions (cooling upflow fluid and heating downflow fluid). To evaluate mixed convection methods, Heat Transfer Research, Inc. (HTRI) recently collected water and propylene glycol data in two vertical tubes of different tube diameters. The data cover wide ranges of Reynolds, Grashof, and Prandtl numbers and differing ratios of heated tube length to diameter in laminar, transition, and turbulent forced flow regimes. In this paper, we focus the buoyancy effect on forced convection of single-phase flows in vertical tubes with Reynolds numbers higher than 2000. Using HTRI data and experimental data in literature, we demonstrate that natural convection can greatly increase or decrease the convective heat transfer coefficient. In addition, we establish that natural convection should not be neglected if the Richardson number is higher than 0.01 or the mixed turbulent parameter Ra1/3/(Re0.8 Pr0.4) is higher than 0.05 even in forced turbulent flow with Reynolds numbers greater than 10,000. High resolution Reynolds-averaged Navier–Stokes simulations of several experimental conditions confirm the importance of the buoyancy effect on the production of turbulence kinetic energy. We also determine that flow regime maps are required to predict the mixed convection heat transfer coefficient accurately.

Mixed Convection in Vertical Tubes: High Reynolds Number

2010 ◽  
Author(s):  
LiDong Huang ◽  
Kevin J. Farrell
Keyword(s):  
Heat Transfer ◽  
Heat Transfer Coefficient ◽  
Natural Convection ◽  
Mixed Convection ◽  
Transfer Coefficient ◽  
Flow Regime ◽  
Reynolds Numbers ◽  
Tube Length ◽  
Buoyancy Effect ◽  
Vertical Tubes

The complex interaction of forced and natural convection depends on flow regime and flow direction. Aiding flow occurs when both driving forces act in the same direction (heating upflow fluid and cooling downflow fluid); opposing flow occurs when they act in different directions (cooling upflow fluid and heating downflow fluid). This paper discusses the buoyancy effect on forced convection for single-phase flows in vertical tubes. To evaluate mixed convection methods, Heat Transfer Research, Inc. (HTRI) recently collected water and propylene glycol data in two vertical tubes of different tube diameters. The data cover wide ranges of Reynolds, Grashof, and Prandtl numbers and differing ratios of heated tube length to diameter in laminar, transition, and turbulent forced flow regimes. In this paper, we focus on mixed convection with Reynolds numbers higher than 2000. Using HTRI data and experimental data in literature, we demonstrate that natural convection can greatly increase or decrease the convective heat transfer coefficient. In addition, we establish that natural convection should not be neglected if the Richardson number is higher than 0.01 or the mixed turbulent parameter Ra1/3/(Re0.8 Pr0.4) is higher than 0.05 even in forced turbulent flow with Reynolds numbers greater than 10000. High resolution Reynolds-Averaged Navier-Stokes (RANS) simulations of several experimental conditions confirm the importance of the buoyancy effect on the production of turbulence kinetic energy. We also determine that flow regime maps are required to predict the mixed convection heat transfer coefficient accurately.

Local Heat Transfer Measurements in Turbulent Flow Around a 180-deg Pipe Bend

1987 ◽  
Vol 109 (1) ◽  
pp. 43-48 ◽  
Author(s):  
J. W. Baughn ◽  
H. Iacovides ◽  
D. C. Jackson ◽  
B. E. Launder
Keyword(s):  
Heat Transfer ◽  
Heat Transfer Coefficient ◽  
Turbulent Flow ◽  
Transfer Coefficient ◽  
Secondary Flow ◽  
Local Heat Transfer ◽  
Reynolds Numbers ◽  
Local Heat ◽  
Pipe Bend ◽  
Streamline Curvature

The paper reports extensive connective heat transfer data for turbulent flow of air around a U-bend with a ratio of bend radius:pipe diameter of 3.375:1. Experiments cover Reynolds numbers from 2 × 104 to 1.1 × 105. Measurements of local heat transfer coefficient are made at six stations and at five circumferential positions at each station. At Re = 6 × 104 a detailed mapping of the temperature field within the air is made at the same stations. The experiment duplicates the flow configuration for which Azzola and Humphrey [3] have recently reported laser-Doppler measurements of the mean and turbulent velocity field. The measurements show a strong augmentation of heat transfer coefficient on the outside of the bend and relatively low levels on the inside associated with the combined effects of secondary flow and the amplification/suppression of turbulent mixing by streamline curvature. The peak level of Nu occurs halfway around the bend at which position the heat transfer coefficient on the outside is about three times that on the inside. Another feature of interest is that a strongly nonuniform Nu persists six diameters downstream of the bend even though secondary flow and streamline curvature are negligible there. At the entry to the bend there are signs of partial laminarization on the inside of the bend, an effect that is more pronounced at lower Reynolds numbers.

scholarly journals Experimental and Theoretical Investigation of the Natural Convection Heat Transfer Coefficient in Phase Change Material (PCM) Based Fin-and-Tube Heat Exchanger

Energies ◽  
2021 ◽  
Vol 14 (3) ◽  
pp. 716
Author(s):  
Saulius Pakalka ◽  
Kęstutis Valančius ◽  
Giedrė Streckienė
Keyword(s):  
Heat Transfer ◽  
Heat Transfer Coefficient ◽  
Natural Convection ◽  
Energy Storage ◽  
Heat Exchanger ◽  
Transfer Coefficient ◽  
Convection Heat Transfer ◽  
Natural Convection Heat Transfer ◽  
Convection Heat ◽  
Convection Heat Transfer Coefficient

Latent heat thermal energy storage systems allow storing large amounts of energy in relatively small volumes. Phase change materials (PCMs) are used as a latent heat storage medium. However, low thermal conductivity of most PCMs results in long melting (charging) and solidification (discharging) processes. This study focuses on the PCM melting process in a fin-and-tube type copper heat exchanger. The aim of this study is to define analytically natural convection heat transfer coefficient and compare the results with experimental data. The study shows how the local heat transfer coefficient changes in different areas of the heat exchanger and how it is affected by the choice of characteristic length and boundary conditions. It has been determined that applying the calculation method of the natural convection occurring in the channel leads to results that are closer to the experiment. Using this method, the average values of the heat transfer coefficient (have) during the entire charging process was obtained 68 W/m2K, compared to the experimental result have = 61 W/m2K. This is beneficial in the predesign stage of PCM-based thermal energy storage units.

Investigations on Transient Natural Convection in Boron Nitride-Mineral Oil Nanofluid Systems

2012 ◽  
Author(s):  
Shijo Thomas ◽  
C. B. Sobhan ◽  
Jaime Taha-Tijerina ◽  
T. N. Narayanan ◽  
P. M. Ajayan
Keyword(s):  
Heat Transfer ◽  
Thermal Conductivity ◽  
Heat Transfer Coefficient ◽  
Natural Convection ◽  
Boron Nitride ◽  
Transfer Coefficient ◽  
Convective Heat Transfer ◽  
Convective Heat ◽  
Convective Heat Transfer Coefficient ◽  
Mineral Oil

Nanofluids are suspensions or colloids produced by dispersing nanoparticles in base fluids like water, oil or organic fluids, so as to improve their thermo-physical properties. Investigations reported in recent times have shown that the addition of nanoparticles significantly influence the thermophysical properties, such as the thermal conductivity, viscosity, specific heat and density of base fluids. The convective heat transfer coefficient also has shown anomalous variations, compared to those encountered in the base fluids. By careful selection of the parameters such as the concentration and the particle size, it has been possible to produce nanofluids with various properties engineered depending on the requirement. A mineral oil–boron nitride nanofluid system, where an increased thermal conductivity and a reduced electrical conductivity has been observed, is investigated in the present work to evaluate its heat transfer performance under natural convection. The modified mineral oil is produced by chemically dispersing boron nitride nanoparticles utilizing a one step method to obtain a stable suspension. The mineral oil based nanofluid is investigated under transient free convection heat transfer, by observing the temperature-time response of a lumped parameter system. The experimental study is used to estimate the time-dependent convective heat transfer coefficient. Comparisons are made with the base fluid, so that the enhancement in the heat transfer coefficient under natural convection situation can be estimated.

A Natural Convection Fin with a Solution-Determined Nonmonotonically Varying Heat Transfer Coefficient

1981 ◽  
Vol 103 (2) ◽  
pp. 218-225 ◽  
Author(s):  
E. M. Sparrow ◽  
S. Acharya
Keyword(s):  
Heat Transfer ◽  
Heat Transfer Coefficient ◽  
Natural Convection ◽  
Transfer Coefficient ◽  
First Principles ◽  
Numerical Solutions ◽  
Flow Direction ◽  
Operating Conditions ◽  
Fluid Temperature ◽  
Wide Range

A conjugate conduction-convection analysis has been made for a vertical plate fin which exchanges heat with its fluid environment by natural convection. The analysis is based on a first-principles approach whereby the heat conduction equation for the fin is solved simultaneously with the conservation equations for mass, momentum, and energy in the fluid boundary layer adjacent to the fin. The natural convection heat transfer coefficient is not specified in advance but is one of the results of the numerical solutions. For a wide range of operating conditions, the local heat transfer coefficients were found not to decrease monotonically in the flow direction, as is usual. Rather, the coefficient decreased at first, attained a minimum, and then increased with increasing downstream distance. This behavior was attributed to an enhanced buoyancy resulting from an increase in the wall-to-fluid temperature difference along the streamwise direction. To supplement the first-principles analysis, results were also obtained from a simple adaptation of the conventional fin model.

Measurements and Numerical Simulations of Heat Transfer and Pressure Drop in a Duct With Smooth Walls

2017 ◽  
Author(s):  
Puxuan Li ◽  
Steve J. Eckels
Keyword(s):  
Heat Transfer ◽  
Heat Transfer Coefficient ◽  
Pressure Drop ◽  
Transfer Coefficient ◽  
Numerical Models ◽  
Convective Heat Transfer Coefficient ◽  
Three Dimensional ◽  
Reynolds Numbers ◽  
Inlet Temperature ◽  
Ansys Fluent

Accurate measurements of heat transfer and pressure drop play important roles in thermal designs in a variety of pipes and ducts. In this study, the convective heat transfer coefficient was measured with a semi-local surface average based on Newton’s Law of cooling. Flow and heat transfer data for different Reynolds numbers were collected and compared in a duct with smooth walls. Pressure drop was measured with a pressure transducer from OMEGA Engineering Inc. The experimental results were compared with numerical estimations generated in ANSYS Fluent. Fluent contains the broad physical modeling capabilities needed to model heat transfer and pressure drop in the duct. Thermal conduction and convection in the three-dimensional (3D) duct are simulated together. Special cares for selecting the viscosity models and the near-wall treatments are discussed. The goal of the paper is to find appropriate numerical models for simulating heat conduction, heat convection and pressure drop in the duct with different Reynolds numbers. The relationship between the heat transfer coefficient and Reynolds numbers is discussed. Heat flux and inlet temperature measured in the experiment are applied to the boundary conditions. The study provides the unique opportunity to verify the accuracy of numerical models on heat transfer and pressure drop in ANSYS Fluent.

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