Experimental investigation of the thermal performance of closed loop flat plate oscillating heat pipe

Mehta, Kamlesh; Mehta, Nirvesh; Patel, Vivek

doi:10.1080/08916152.2020.1718802

Cited by 22 publications

(4 citation statements)

References 67 publications

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“…In this juncture, Pathak et al [3] and Dave et al [4] in separate studies altered the working fluid, wick structure, and reported that the applied heat flux is the principal factor influencing the thermal performance of a heat pipe. On the contrary, Mehta et al [5] altered geometric variables (channel size and shape), in a heat pipe, and concluded that the thermal resistance strongly depends on geometrical parameters. Likewise, Chernysheva et al [6] analyzed the effect of external factors (device orientation, condenser cooling temperature, and condition of heat exchange with the surroundings), on the operating performance of a heat pipe.…”

Section: Introductionmentioning

confidence: 99%

Performance evaluation of hybrid nanofluid-filled cylindrical heat pipe by machine learning algorithms

Kumararaja,

Sıvaraman,

Saravanan

2024

Journal of Thermal Engineering

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The current study attempts to predict the outlet temperature of a hybrid nanofluid heat pipe using three machine learning models, namely Extra Tree Regression (ETR), CatBoost Re-gression (CBR), and Light Gradient Boosting Machine Regression (LGBMR), in the Python environment. Based on 7000 experimental data (various heat input, inclination angle, flow rate, and fluid ratio), different training (95%–5%) and testing (5%–95%) split sizes, a closer prediction was attained at 85:15. The three attempted machine learning models are capable of predicting the outlet temperature, as evidenced by the less than 5% deviation from the experi-mental results. Of the three attempted machine learning models, the ETR model outperforms the other two with a higher accuracy (98%). Further, the sensitivity analysis indicates the ab-sence of data overfitting in the attempted models.

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Section: Introductionmentioning

confidence: 99%

Performance evaluation of hybrid nanofluid-filled cylindrical heat pipe by machine learning algorithms

Kumararaja,

Sıvaraman,

Saravanan

2024

Journal of Thermal Engineering

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“…Neethu et al (2021) analytically and statistically analyzed the magnetic field flow of the nanofluid passing between perpendicular porous plates moving in opposite directions. Mehta et al (2021) experimentally studied the effects of different parameters on the thermal efficiency of closed-loop flat-plate oscillating heat pipe.…”

Section: Introductionmentioning

confidence: 99%

Stacked Heterogeneous Ensemble Learning Model in Mixed Convection Heat Transfer from a Vertically Oscillating Flat Plate

Akçay

Buyrukoğlu

Akdag

2023

Osmaniye Korkut Ata Üniversitesi Fen Bilimleri Enstitüsü Dergisi

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In this study, the effects of mixed convection heat transfer from a moving vertical flat plate with an experimental and stacked heterogeneous ensemble learning approach are analyzed. In the experimental work, the effects on both natural and forced convection of dimensionless oscillation amplitude (Ao), dimensionless oscillation frequency (Wo) and Rayleigh number (Ra) are investigated. In the experiments, the vertical movement of the plate is provided by a flywheel-motor assembly. The average Nusselt numbers (Nu) on the fixed plate and the moving plate surface were obtained. Additionally, this study is focused on the prediction of heat transfer of a moving flat plate using single-based algorithms (Gradient Boosting, AdaBoost, Multilayer Per-ceptron) and a stacked heterogeneous ensemble learning model. The statistical per-formance of the single-based algorithms and the stacked ensemble model is meas-ured in the prediction of mixed convection heat transfer. The results show that the stacked-based ensemble learning model yielded the MSE = 2.01, RMSE = 1.42, MAE = 1.1 and R2 = 0.99 values. Overall, this study reveals that the proposed stacked en-semble machine learning model can be used successfully for modeling convection heat transfer of a moving plate.

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“…The heat transfer mechanism is complicated, and many factors affect heat transfer power. Mehta et al [17] studied the optimal filling ratio and inclination angle of a flat-plate CLPHP using the acetone as a working fluid through visual experiments. It is concluded that when the filling ratio is less than 30%, a dry-out phenomenon occurs in the evaporation section and the heat transfer performance is poor.…”

Section: Introductionmentioning

confidence: 99%

Experimental Investigation on the Operating Characteristics of Flat-Plate CLPHP for PEMFC Cooling

Li¹,

Chang²,

Zhao³

2021

WEVJ

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Proton exchange membrane fuel cell (PEMFC) generates electricity through hydrogen and oxygen chemical reaction with the generation of much heat. According to the working temperature of PEMFC, the thermal resistance and internal relative pressure change of the flat-plate micro closed-loop pulsating heat pipe (CLPHP) are tested and analyzed at different filling ratios, vacuum degrees, and inclination angles, whose working medium is binary methanol-deionized water with a mass ratio of 5:1. The experiment results show that the higher the vacuum degree is, the better the startup and heat transfer performance of CLPHP become; the thermal resistance is less sensitive to inclination angle except for horizontal placement; the 40% volume-filling ratio can effectively avoid dry-out at high temperature. When 80 °C is the ideal working temperature of PEMFC, the thermal resistance of CLPHP is 0.093°C/W; the heat transfer heat flux is 1.59 W/cm2, and the temperature fluctuation is small. Therefore, flat-plate CLPHP has great application potential for PEMFC cooling.

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Experimental investigation of the thermal performance of closed loop flat plate oscillating heat pipe

Cited by 22 publications

References 67 publications

Performance evaluation of hybrid nanofluid-filled cylindrical heat pipe by machine learning algorithms

Performance evaluation of hybrid nanofluid-filled cylindrical heat pipe by machine learning algorithms

Stacked Heterogeneous Ensemble Learning Model in Mixed Convection Heat Transfer from a Vertically Oscillating Flat Plate

Experimental Investigation on the Operating Characteristics of Flat-Plate CLPHP for PEMFC Cooling

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