Bubble behavior and nucleation site density in subcooled flow boiling using a novel method for simulating the microstructure of surface roughness

Alimoradi, Hasan; Shams, Mehrzad

doi:10.1007/s11814-022-1163-7

Cited by 12 publications

(7 citation statements)

References 39 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The heat transfer coefficient on the surface and in the fluid are also calculated according to Equation (5).…”

Section: Uncertainty Analysismentioning

confidence: 99%

“…In recent years, with the rapid advancement of knowledge frontiers and the consequent production of new products that work with extremely high heat loads, the need for an efficient and small heat exchanger, especially in microelectronic components, has been strongly felt, and this has created a stimulus and motivation [1][2][3]. Boiling helps to develop an effective technique to increase heat transfer, and it is more effective than single-phase heat transfer since the surface on which boiling occurs is in contact with a fluid of high latent heat that cools the surface more evenly and leaves no hot spots on it [4][5][6].…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

An Experimental Study of Heat Transfer in Pool Boiling to Investigate the Effect of Surface Roughness on Critical Heat Flux

Ali

2024

ChemEngineering

View full text Add to dashboard Cite

Utilizing pool boiling as a cooling method holds significant importance within power plant industries due to its ability to effectively manage temperature differentials amidst high heat flux conditions. This study delves into the impact of surface modifications on the pool boiling process by conducting experiments on four distinct boiling surfaces under various conditions. An experimental setup tailored for this investigation is meticulously designed and implemented. The primary objective is to discern the optimal surface configuration capable of efficiently absorbing maximum heat flux while minimizing temperature differentials. In addition, this study scrutinizes bubble dynamics, pivotal in nucleation processes. Notably, surfaces polished unidirectionally (ROD), exhibiting lower roughness, demonstrate superior performance in critical heat flux (CHF) compared to surfaces with circular roughness (RCD). Moreover, the integration of bubble liquid separation methodology along with the introduction of a bubble micro-layer yields a microchannel surface. Remarkably, this modification results in a noteworthy enhancement of 131% in CHF and a substantial 211% increase in the heat transfer coefficient (HTC) without resorting to particle incorporation onto the surface. This indicates promising avenues for enhancing cooling efficiency through surface engineering without additional additives.

show abstract

“…The heat transfer coefficient on the surface and in the fluid are also calculated according to Equation (5).…”

Section: Uncertainty Analysismentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

An Experimental Study of Heat Transfer in Pool Boiling to Investigate the Effect of Surface Roughness on Critical Heat Flux

Ali

2024

ChemEngineering

View full text Add to dashboard Cite

show abstract

“…It is clear that the model captured the problem’s physics and understood the variations in the input parameters. The evaluation of the model was carried out using the mean absolute error and R_squared [ 49 , 50 , 51 , 52 , 53 ]. The model was able to achieve an MAE of 1.98%, and its

was 0.98.…”

Section: Artificial Neural Networkmentioning

confidence: 99%

Thermodynamics Investigation and Artificial Neural Network Prediction of Energy, Exergy, and Hydrogen Production from a Solar Thermochemical Plant Using a Polymer Membrane Electrolyzer

Jery

Salman

Al-Khafaji³

et al. 2023

Molecules

View full text Add to dashboard Cite

Hydrogen production using polymer membrane electrolyzers is an effective and valuable way of generating an environmentally friendly energy source. Hydrogen and oxygen generated by electrolyzers can power drone fuel cells. The thermodynamic analysis of polymer membrane electrolyzers to identify key losses and optimize their performance is fundamental and necessary. In this article, the process of the electrolysis of water by a polymer membrane electrolyzer in combination with a concentrated solar system in order to generate power and hydrogen was studied, and the effect of radiation intensity, current density, and other functional variables on the hydrogen production was investigated. It was shown that with an increasing current density, the voltage generation of the electrolyzer increased, and the energy efficiency and exergy of the electrolyzer decreased. Additionally, as the temperature rose, the pressure dropped, the thickness of the Nafion membrane increased, the voltage decreased, and the electrolyzer performed better. By increasing the intensity of the incoming radiation from 125 W/m2to 320 W/m2, the hydrogen production increased by 111%, and the energy efficiency and exergy of the electrolyzer both decreased by 14% due to the higher ratio of input electric current to output hydrogen. Finally, machine-learning-based predictions were conducted to forecast the energy efficiency, exergy efficiency, voltage, and hydrogen production rate in different scenarios. The results proved to be very accurate compared to the analytical results. Hyperparameter tuning was utilized to adjust the model parameters, and the models’ results showed an MAE lower than 1.98% and an R2 higher than 0.98.

show abstract

“…The use of artificial intelligence in electrocoagulation is overlooked. There is little research using machine learning algorithms to predict a parameter in wastewater treatment, but this trend has changed in the last few years ( Yaqub & Lee, 2022 ; Zaboli, Alimoradi & Shams, 2022 ; Alimoradi & Shams, 2019 ; Alimoradi, Shams & Ashgriz, 2023 , 2022 ). The use of artificial intelligence is becoming more and more common in engineering problems due to its simplicity of application and accuracy.…”

Section: Introductionmentioning

confidence: 99%

Optimization of oil industry wastewater treatment system and proposing empirical correlations for chemical oxygen demand removal using electrocoagulation and predicting the system’s performance by artificial neural network

El Jery,

Salman,

Al-Ansari

et al. 2023

PeerJ

View full text Add to dashboard Cite

The alarming pace of environmental degradation necessitates the treatment of wastewater from the oil industry in order to ensure the long-term sustainability of human civilization. Electrocoagulation has emerged as a promising method for optimizing the removal of chemical oxygen demand (COD) from wastewater obtained from oil refineries. Therefore, in this study, electrocoagulation was experimentally investigated, and a single-factorial approach was employed to identify the optimal conditions, taking into account various parameters such as current density, pH, COD concentration, electrode surface area, and NaCl concentration. The experimental findings revealed that the most favorable conditions for COD removal were determined to be 24 mA/cm2 for current density, pH 8, a COD concentration of 500 mg/l, an electrode surface area of 25.26 cm2, and a NaCl concentration of 0.5 g/l. Correlation equations were proposed to describe the relationship between COD removal and the aforementioned parameters, and double-factorial models were examined to analyze the impact of COD removal over time. The most favorable outcomes were observed after a reaction time of 20 min. Furthermore, an artificial neural network model was developed based on the experimental data to predict COD removal from wastewater generated by the oil industry. The model exhibited a mean absolute error (MAE) of 1.12% and a coefficient of determination (R2) of 0.99, indicating its high accuracy. These findings suggest that machine learning-based models have the potential to effectively predict COD removal and may even serve as viable alternatives to traditional experimental and numerical techniques.

show abstract

Bubble behavior and nucleation site density in subcooled flow boiling using a novel method for simulating the microstructure of surface roughness

Cited by 12 publications

References 39 publications

An Experimental Study of Heat Transfer in Pool Boiling to Investigate the Effect of Surface Roughness on Critical Heat Flux

An Experimental Study of Heat Transfer in Pool Boiling to Investigate the Effect of Surface Roughness on Critical Heat Flux

Thermodynamics Investigation and Artificial Neural Network Prediction of Energy, Exergy, and Hydrogen Production from a Solar Thermochemical Plant Using a Polymer Membrane Electrolyzer

Optimization of oil industry wastewater treatment system and proposing empirical correlations for chemical oxygen demand removal using electrocoagulation and predicting the system’s performance by artificial neural network

Contact Info

Product

Resources

About