Experimental investigation of mixed convection heat transfer in a rectangular channel with discrete heat sources at the top and at the bottom

Doğan, Ayla; Sivrioğlu, Mecit; Baskaya, Senol

doi:10.1016/j.icheatmasstransfer.2005.05.003

Cited by 39 publications

(14 citation statements)

References 18 publications

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“…Mixed convection heat transfer in a top and bottom heated rectangular channel with discrete heat sources has been investigated experimentally for air by Dogan et al [6]. Results show that the face temperatures increase with increasing Grashof number.…”

Section: Introductionmentioning

confidence: 99%

Mixed convection air cooling of protruding heat sources mounted in a horizontal channel

Hamouche¹,

Bessaïh²

2009

International Communications in Heat and Mass Transfer

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Section: Introductionmentioning

confidence: 99%

Mixed convection air cooling of protruding heat sources mounted in a horizontal channel

Hamouche¹,

Bessaïh²

2009

International Communications in Heat and Mass Transfer

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“…(1)(2)(3)(4)(5)(6)(7)(8)(9)(10)(11), together with the boundary conditions shown in Fig. 2 are solved using FLUENT 6.3, including the radiation model.…”

Section: Numerical Schemementioning

confidence: 99%

“…The effects of heat flux, coolant flow rates and chip numbers were investigated and a correlation was developed to describe the three modes of convection. Mixed convection heat transfer in a top and bottom heated rectangular channel with discrete heat sources has been investigated experimentally for air by Dogan et al [3]. Bautista and Mendez [4] studied conjugate heat transfer analysis in a discrete heat source with internal heat generation.…”

Section: Introductionmentioning

confidence: 99%

Inverse conjugate mixed convection in a vertical substrate with protruding heat sources: a combined experimental and numerical study

Ahamad

Balaji

2015

Heat Mass Transfer

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heat inputs, CFD simulations were again run to compare the temperature distribution at the back of the PCB board with measurements. List of symbolsa Absorption coefficient (m −1 ) A Area of heat source (m 2 ) B Distance from the edge of the plate to the nearest chip edge (m) C p Specific heat (J/kg k) D Spacing between the heat sources (m) d Height of the heat source (m) Gr Grashof number, Gr = gβ∆TL 3 υ 2 g Acceleration due to gravity (9.81 m/s 2 ) H Height of the duct/channel (m) h Convective heat transfer coefficient (W/m 2 K) I Total radiation intensity (W/m 3 ) k s Thermal conductivity of solid (W/m K) L Characteristic length (height of the heat source in this case) (m) N Length of substrate in Z direction (m) n Refractive index p Pressure (N/m 2 ) S Sum of the residues, as the case may be (Eq. 12) s Direction vector Q Power input (W) Q ANN Heat input value measured by ANN (W) Q Expt Heat input value measured by experiments (W) Re Reynolds number, U α L υ Ri Richardson number, Ri = Gr Re 2 S Spacing between the two walls of the channel (m) t Heat source thickness (m) T Temperature (K) U ∝ Inlet air velocity (m/s) V Velocity vector (m/s) Abstract This paper reports the results of a combined numerical and experimental study to estimate the heat inputs of three protruding heat sources of the same size placed on a vertically placed PCB board of height 150 mm, depth 250 mm, and thickness 5 mm. First, limited measurements of temperatures were recorded at eight locations along the height of the back of the PCB board for different (and known) values of heat inputs of the protruding heat sources and different velocities. These were followed by three-dimensional calculations of fluid flow and conjugate heat transfer for various heat transfer coefficients on the backside of the PCB board. The difference between the CFD predicted and experimentally measured temperature distributions on the back of the PCB board was minimized using least squares and the best value of heat transfer coefficient was obtained. Using this 'data assimilated' CFD model, detailed CFD simulations were done for various values of heat input values and Reynolds numbers (each of these can be different from one another) of the flow. The temperatures at the same eight locations at the back of the PCB board were noted. An artificial neural network was then developed with ten inputs (eight temperatures together with the input velocity and the ambient temperature) to estimate the three outputs (three heat inputs) after carrying out extensive studies on the architecture of the network. This inverse solution was then tested with experiments for validating the ANN approach to solve the inverse conjugate heat transfer problem. Finally, with the ANN estimated

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“…Upon substituting the heat flux distributions obtained from Eqs. (11) and (16) into Eq. (17), the dimensionless total heat transfer rate enhancement resulting from adding an adiabatic spacing is given as:…”

Section: Heat Sources With Uniform Temperaturementioning

confidence: 99%

Constructal placement of unequal heat sources on a plate cooled by laminar forced convection

Hajmohammadi

Shirani

Salimpour

et al. 2012

International Journal of Thermal Sciences

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Experimental investigation of mixed convection heat transfer in a rectangular channel with discrete heat sources at the top and at the bottom

Cited by 39 publications

References 18 publications

Mixed convection air cooling of protruding heat sources mounted in a horizontal channel

Mixed convection air cooling of protruding heat sources mounted in a horizontal channel

Inverse conjugate mixed convection in a vertical substrate with protruding heat sources: a combined experimental and numerical study

Constructal placement of unequal heat sources on a plate cooled by laminar forced convection

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