Effect of Nozzle Spacing on Heat Transfer and Fluid Flow Characteristics of an Impinging Circular Jet in Cooling of Electronic Components

Anwarullah, M.; Rao, V. Srinivasa; Sharma, K.V.

doi:10.5383/ijtee.04.01.002

Cited by 15 publications

(7 citation statements)

References 23 publications

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“…The coefficients a 4,j (related to H/d) and a 5,j (related to S/d) presented negative values. This negative nature was found in literature for the case of a 4,j in systems with impinging single and multiple jets on flat surfaces and cylinder arrays and H/d > 5 (Chang et al, 1995;Webb and Ma, 1995;Anwarullah et al, 2011), and for impinging array of jets on flat surfaces in the case of a 5,j (Huber and Viskanta, 1994). It is noteworthy to mention that the coefficients a 2,ave , a 4,ave and a 5,ave of Eq.…”

Section: Nusselt Correlationsupporting

confidence: 59%

Effect of the number of orifices and operative variables on the heat and mass transfer in a hydrofluidization system with static spheres

Belis

Zorrilla

Peralta

2015

Journal of Food Engineering

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Section: Nusselt Correlationsupporting

confidence: 59%

Effect of the number of orifices and operative variables on the heat and mass transfer in a hydrofluidization system with static spheres

Belis

Zorrilla

Peralta

2015

Journal of Food Engineering

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“…Correlations related impinging jets cooling have been extensively explored in earlier research. Anwarullahet al [15] created a correlation for the stagnation Nusselt number of an impinging air jet that was submerged, which could be applied for cooling electronic components. They investigated the effects of Reynolds number (6000-23000) and jet plate distance (2-8 jet diameters) on the local Nusselt number.…”

Section: Introductionmentioning

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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“…While only a few studies evaluate the effect of water jet height on the Jominy end quench test, there are many studies on impinging jets because they are encountered in many industrial cooling processes. For instance, several researchers [20][21][22] have studied the influence of the distance between the nozzle and object on the local Nusselt number by impinging jets. Their results indicate that the local heat transfer decreases when the distance increases, which means that the cooling rate will increase with an increase in the water jet height during the Jominy end quench test.…”

Section: Introductionmentioning

confidence: 99%

Effects of Water Jet Height and End Dipping on the Cooling Rate and Hardenability in the Jominy End Quench Test

Hwang

2021

Processes

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The effects of water jet height and end dipping on cooling rate and hardenability in the Jominy end quench test were investigated to understand the Jominy test in more detail. Experimental tests were conducted under end dipping cooling condition as well as for specific water jet heights of 35, 65, and 100 mm. The thermal behavior and mechanical properties of the Jominy specimen with region were evaluated using thermocouples and hardness measurements, respectively. The effect of the water jet height on the thermal and hardness behaviors was not large; especially, the influence of water jet height was negligible when the water jet height was over 50 mm. These observations indicate that the uncertainty of the water jet height is not important during the standard Jominy end quench test. Meanwhile, during the standard Jominy test, we cannot neglect the heat flow along the radial direction of the specimen because the temperature difference between the center and surface area was not small; the maximum temperature difference was approximately 50 °C. Based on the comparative study between the standard Jominy cooling and the end dipping cooling processes, the thermal gradient along the radial direction of the specimen can be reduced with the more stable cooling condition on the Jominy end. However, the effect of temperature deviation along the radial direction of the Jominy specimen on the hardness distribution along the longitudinal direction was not large, which shows the high reliability of the Jominy end quench test.

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Effect of Nozzle Spacing on Heat Transfer and Fluid Flow Characteristics of an Impinging Circular Jet in Cooling of Electronic Components

Cited by 15 publications

References 23 publications

Effect of the number of orifices and operative variables on the heat and mass transfer in a hydrofluidization system with static spheres

Effect of the number of orifices and operative variables on the heat and mass transfer in a hydrofluidization system with static spheres

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

Effects of Water Jet Height and End Dipping on the Cooling Rate and Hardenability in the Jominy End Quench Test

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