Heat transfer enhancement in natural convection between vertical and downward inclined wall and air by pulsating jets

Baffigi, F.; Bartoli, Carlo

doi:10.1016/j.expthermflusci.2010.02.011

Cited by 10 publications

(2 citation statements)

References 16 publications

(34 reference statements)

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“…The unit of nozzles is positioned using a multi-axis precision positioning stage with a spatial resolution of 0.01 mm in both the horizontal and vertical planes. As a result, the jet to plate spacing may be controlled very precisely [26]. The impingement plate is mounted between two copper bus bars and is made of a stainless steel sheet that is 325 mm by 525 mm and 0.5 mm thick.…”

Section: Experimental Methodsmentioning

confidence: 99%

Artificial Neural Networks Application on Average and Stagnation Nusselt Number Prediction for Impingement Cooling of Flat Plate With Helically Coiled Air Jet

Fawaz,

Osama,

Maghrabie

2023

Journal of Thermal Science and Engineering Applications

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In order to estimate the average and stagnation Nusselt numbers for turbulent flow for impingement cooling of a flat plate with a helically coiled air jet, a new artificial neural network (ANN) model is presented in the present study. A new dataset of stagnation and average Nusselt numbers as a function of Reynolds number (Re) varied from 5000 to 30,000, nozzle plate spacing ratio changed from 2 to 8, and jet helical angles of 0 deg, 20 deg, 30 deg, 40 deg, and 60 deg was created based on an experimental investigation. The ANN structure is composed of three layers with hidden neurons of 14–10–8. The training process comprises feed-forward propagation of the selected input parameters, back-propagation with biases and weight adjustments, and loss function evaluation for the training and validation datasets. The activation function of the output layer is a linear function, and the rectified linear unit activation function is utilized in the hidden layers. The adaptive moment estimation algorithm is employed to minimize the loss function to accelerate the ANN training. To prevent an increase in training time caused by the marked discrepancy in the gradients of loss function considering the values of the weights, the “MinMax” normalization strategy was used. For the ANN model, the mean absolute percent error values were 2.35% for the average Nusselt number and 2.52% for the stagnation Nusselt number. According to the comparison of projected data with the outcomes of earlier experiments, the derived model’s performance was validated and the findings showed outstanding accuracy.

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Section: Experimental Methodsmentioning

confidence: 99%

Artificial Neural Networks Application on Average and Stagnation Nusselt Number Prediction for Impingement Cooling of Flat Plate With Helically Coiled Air Jet

Fawaz,

Osama,

Maghrabie

2023

Journal of Thermal Science and Engineering Applications

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show abstract

“…Results showed that the heat transfer enhancement factor can be larger than 1.2. Many other valuable experimental studies reported an enhancement in heat transfer due to the pulsation (Zohir et al 2006, Ji et al 2008, Baffigi and Bartoli 2010. However, some studies such as Elsayed et al's work (Elshafei et al 2008), reported the pulsation would downgrade the heat transfer compared to that in steady flow.…”

Section: Introductionmentioning

confidence: 99%

Numerical Investigation of Heat Transfer and Fluid Flow around the Rectangular Flat Plane Confined by a Cylinder under Pulsating Flow

Zheng

Yang

et al. 2016

JAFM

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Fluid flow around and heat transfer from a rectangular flat plane with constant uniform heat flux in laminar pulsating flows is studied, and compared with our experimental data. Quantitatively accurate, second-order schemes for time, space, momentum and energy are employed, and fine meshes are adopted. The numerical results agree well with experimental data. Results found that the heat transfer enhancement is caused by the relative low temperature gradient in the thermal boundary layer, and by the lower surface temperature in pulsating flows. In addition, the heat transfer resistance is much lower during reverse flow period than that during forward flow period. The flow reversal period is about 180 degree behind the pulsating pressure waves. Besides, spectrum results of the simulated averaged surface temperature showed that the temperature fluctuates in multiple-peaked modes when the amplitude of the imposed pulsations is larger, whereas the temperature fluctuates in a single-peaked mode when the amplitude of the imposed pulsation is small.

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Lattice Boltzmann simulation to laminar pulsating flow past a circular cylinder with constant temperature

Zheng

Guo

et al. 2017

Heat Mass Transfer

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Heat transfer enhancement in natural convection between vertical and downward inclined wall and air by pulsating jets

Cited by 10 publications

References 16 publications

Artificial Neural Networks Application on Average and Stagnation Nusselt Number Prediction for Impingement Cooling of Flat Plate With Helically Coiled Air Jet

Artificial Neural Networks Application on Average and Stagnation Nusselt Number Prediction for Impingement Cooling of Flat Plate With Helically Coiled Air Jet

Numerical Investigation of Heat Transfer and Fluid Flow around the Rectangular Flat Plane Confined by a Cylinder under Pulsating Flow

Lattice Boltzmann simulation to laminar pulsating flow past a circular cylinder with constant temperature

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