A comprehensive review of heat pipe: Its types, incorporation techniques, methods of analysis and applications
Heat pipes are highly efficient thermal devices capable of transferring energy over both short
and long spans. In recent times, heat pipes have aroused to have enormous interest among …
and long spans. In recent times, heat pipes have aroused to have enormous interest among …
Status, challenges, and potential for machine learning in understanding and applying heat transfer phenomena
Abstract Machine learning (ML) offers a variety of techniques to understand many complex
problems in different fields. The field of heat transfer, and thermal systems in general, are …
problems in different fields. The field of heat transfer, and thermal systems in general, are …
Time-series prediction of wind speed using machine learning algorithms: A case study Osorio wind farm, Brazil
Abstract Machine learning algorithms (MLAs) are applied to predict wind speed data for
Osorio wind farm that is located in the south of Brazil, near the Osorio city. Forecasting wind …
Osorio wind farm that is located in the south of Brazil, near the Osorio city. Forecasting wind …
Machine learning algorithms to predict flow boiling pressure drop in mini/micro-channels based on universal consolidated data
Two-phase flow in mini/micro-channels can meet the high heat dissipation requirements of
many state-of-the-art cooling solutions. However, there is lack of accurate universal methods …
many state-of-the-art cooling solutions. However, there is lack of accurate universal methods …
On the prediction of critical heat flux using a physics-informed machine learning-aided framework
The critical heat flux (CHF) corresponding to the departure from nucleate boiling (DNB) crisis
is essential to the design and safety of a two-phase flow boiling system. Despite the …
is essential to the design and safety of a two-phase flow boiling system. Despite the …
Technology development and applications of artificial intelligence for post-combustion carbon dioxide capture: Critical literature review and perspectives
The research conducted in the last five years can potentially paint a picture of the next
generation's research related to solvent development for post-combustion carbon dioxide …
generation's research related to solvent development for post-combustion carbon dioxide …
A neural network model for free-falling condensation heat transfer in the presence of non-condensable gases
Condensation heat transfer has been widely studied for various applications such as power
generation, water desalination, data centers, chemical and pharmaceutical syntheses …
generation, water desalination, data centers, chemical and pharmaceutical syntheses …
An artificial intelligence approach for thermodynamic modeling of geothermal based-organic Rankine cycle equipped with solar system
Geothermal energy is a renewable resource that is constantly available. The low geothermal
well operating lifetime is the main challenge in using this type of renewable energy. This …
well operating lifetime is the main challenge in using this type of renewable energy. This …
Machine-learning-based heat transfer and pressure drop model for internal flow condensation of binary mixtures
Abstract Machine learning regression models were developed to predict the heat transfer
coefficient and frictional pressure gradient during condensation of three zeotropic mixtures …
coefficient and frictional pressure gradient during condensation of three zeotropic mixtures …
Prediction of heat exchanger performance in cryogenic oscillating flow conditions by support vector machine
J Huang, T **, M Liang, H Chen - Applied Thermal Engineering, 2021 - Elsevier
Heat transfer characteristics in cryogenic oscillating flow is essential to the development of
high-efficiency cryocoolers. In this study, the heat exchanger performance in cryogenic …
high-efficiency cryocoolers. In this study, the heat exchanger performance in cryogenic …