Effect of dual flow arrangements on the performance of mini-channel heat sink: numerical study

Tariq, Hussain Ahmed; Anwar, Muhammad Shoaib; Ali, Hafız Muhammad; Ahmed, Jamal Uddin

doi:10.1007/s10973-020-09617-8

Cited by 11 publications

(4 citation statements)

References 48 publications

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“…An advantage of 15.28%, 13.39% and 11.32% as compared to Jajja et al [2] is noted at all the three volumetric flow rates. Numerical outcomes have been compared with Tariq et al [3]. A relative advantage of 5.46%, 3.24% and 2.03% is observed at all the three volumetric flow rates respectively.…”

Section: Resultsmentioning

confidence: 96%

“…3. Considering first the effect of novel header geometry proposed in this work, base temperature outcome at the chosen volumetric concentrations boasts a maximum advantage of 9.41% and 18.58% as compared to straight integral fin mini channel heat sink proposed by Tariq et al [3] and single inlet single outlet flow configuration reported by Jajja et al [2], respectively.…”

Section: Test Setupmentioning

confidence: 84%

“…They reported that by decreasing the fin spacing, the heat transfer increased. Tariq et al [3] performed numerical investigation on mini channel heat sink having 1.5 mm, 1 mm, 0.5 mm and 0.2 mm fin spacing using dual flow configuration. They reported that by using dual flow configuration, better base temperature distribution was observed as compared to single flow configuration.…”

Section: Introductionmentioning

confidence: 99%

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Thermal performance of dual flow slotted fin mini channel heat sink using Al₂O₃-H₂O and TiO₂-H₂O: a numerical and experimental approach

Baig

Adil

Manzoor³

et al. 2023

Nanotechnology

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Water cooled mini channels have gained importance because of high heat generation inside the microprocessors. This generated heat needs to be timely removed for maintaining the durability and performance of the microprocessor. This work proposes a two-pronged strategy for thermal performance enhancement of mini channel heat sinks. Firstly, a novel dual flow slotted fin mini channel heat sink flow configuration is proposed. Secondly, a detailed numerical investigation is performed to assess heat transfer enhancement property of Al2O3-H2O and TiO2-H2O nanofluids. Considering the first step, fin spacing, number of slots, slot thickness and slot angle are investigated in detail yielding to the selection of best structural parameters. Further, numerical assessment of nano fluid behavior is carried out at volumetric concentrations of 0.005% and 0.01%. For the case of novel dual flow slotted fin mini channel heat sink, maximum numerical and experimental reduction in base temperature and thermal resistance is observed for Al2¬O3-H2O nano fluid at volumetric concentration of 0.01%, as compared with water. Increment in the pressure drop is noted with increasing volumetric concentrations.

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Section: Resultsmentioning

confidence: 96%

Section: Test Setupmentioning

confidence: 84%

Section: Introductionmentioning

confidence: 99%

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Thermal performance of dual flow slotted fin mini channel heat sink using Al₂O₃-H₂O and TiO₂-H₂O: a numerical and experimental approach

Baig

Adil

Manzoor³

et al. 2023

Nanotechnology

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“…Computational investigations in particular have become vitally important [24][25][26][27][28][29][30][31][32][33], where many researchers have widely implemented intelligent methods based on neuro-fuzzy neural networks to model many engineering processes [6,[34][35][36][37][38][39] and predict the thermophysical properties of different nanofluids [40][41][42]. In 2013, Salehi et al [43] used an interesting adaptive neuro-fuzzy inference system (ANFIS) modeling technique in a study that set out to predict the heat transfer coefficient of a nanofluid containing Al 2 O 3 under a uniform heat flux condition.…”

Section: Introductionmentioning

confidence: 99%

Estimating the Heat Capacity of Non-Newtonian Ionanofluid Systems Using ANN, ANFIS, and SGB Tree Algorithms

et al. 2020

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This work investigated the capability of multilayer perceptron artificial neural network (MLP–ANN), stochastic gradient boosting (SGB) tree, radial basis function artificial neural network (RBF–ANN), and adaptive neuro-fuzzy inference system (ANFIS) models to determine the heat capacity (Cp) of ionanofluids in terms of the nanoparticle concentration (x) and the critical temperature (Tc), operational temperature (T), acentric factor (ω), and molecular weight (Mw) of pure ionic liquids (ILs). To this end, a comprehensive database of literature reviews was searched. The results of the SGB model were more satisfactory than the other models. Furthermore, an analysis was done to determine the outlying bad data points. It showed that most of the experimental data points were located in a reliable zone for the development of the model. The mean squared error and R2 were 0.00249 and 0.987, 0.0132 and 0.9434, 0.0320 and 0.8754, and 0.0201 and 0.9204 for the SGB, MLP–ANN, ANFIS, and RBF–ANN, respectively. According to this study, the ability of SGB for estimating the Cp of ionanofluids was shown to be greater than other models. By eliminating the need for conducting costly and time-consuming experiments, the SGB strategy showed its superiority compared with experimental measurements. Furthermore, the SGB displayed great generalizability because of the stochastic element. Therefore, it can be highly applicable to unseen conditions. Furthermore, it can help chemical engineers and chemists by providing a model with low parameters that yields satisfactory results for estimating the Cp of ionanofluids. Additionally, the sensitivity analysis showed that Cp is directly related to T, Mw, and Tc, and has an inverse relation with ω and x. Mw and Tc had the highest impact and ω had the lowest impact on Cp.

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Influence of nanoparticles size, per cent mass ratio, and temperature on the thermal properties of water-based MgO–ZnO nanofluid: an experimental approach

Giwa

Momin

Nwaokocha

et al. 2020

J Therm Anal Calorim

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Effect of dual flow arrangements on the performance of mini-channel heat sink: numerical study

Cited by 11 publications

References 48 publications

Thermal performance of dual flow slotted fin mini channel heat sink using Al₂O₃-H₂O and TiO₂-H₂O: a numerical and experimental approach

Thermal performance of dual flow slotted fin mini channel heat sink using Al₂O₃-H₂O and TiO₂-H₂O: a numerical and experimental approach

Estimating the Heat Capacity of Non-Newtonian Ionanofluid Systems Using ANN, ANFIS, and SGB Tree Algorithms

Influence of nanoparticles size, per cent mass ratio, and temperature on the thermal properties of water-based MgO–ZnO nanofluid: an experimental approach

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Effect of dual flow arrangements on the performance of mini-channel heat sink: numerical study

Cited by 11 publications

References 48 publications

Thermal performance of dual flow slotted fin mini channel heat sink using Al2O3-H2O and TiO2-H2O: a numerical and experimental approach

Thermal performance of dual flow slotted fin mini channel heat sink using Al2O3-H2O and TiO2-H2O: a numerical and experimental approach

Estimating the Heat Capacity of Non-Newtonian Ionanofluid Systems Using ANN, ANFIS, and SGB Tree Algorithms

Influence of nanoparticles size, per cent mass ratio, and temperature on the thermal properties of water-based MgO–ZnO nanofluid: an experimental approach

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Product

Resources

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Thermal performance of dual flow slotted fin mini channel heat sink using Al₂O₃-H₂O and TiO₂-H₂O: a numerical and experimental approach

Thermal performance of dual flow slotted fin mini channel heat sink using Al₂O₃-H₂O and TiO₂-H₂O: a numerical and experimental approach