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Keivan Ardam
Keivan Ardam
Department of Energy Engineering, Politecnico di Milano
在 mail.polimi.it 的电子邮件经过验证
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Machine learning based models for pressure drop estimation of two-phase adiabatic air-water flow in micro-finned tubes: Determination of the most promising dimensionless …
B Najafi, K Ardam, A Hanušovský, F Rinaldi, LPM Colombo
Chemical Engineering Research and Design 167, 252-267, 2021
212021
Machine learning based pressure drop estimation of evaporating R134a flow in micro-fin tubes: Investigation of the optimal dimensionless feature set
K Ardam, B Najafi, A Lucchini, F Rinaldi, LPM Colombo
International Journal of Refrigeration 131, 20-32, 2021
152021
Heat transfer estimation in flow boiling of R134a within microfin tubes utilizing physics-inspired machine learning
S Milani, K Ardam, B Najafi, LPM Colombo, A Lucchini, F Rinaldi
Available at SSRN 4175964, 2022
22022
Application of machine learning in frictional pressure drop estimation of two-phase flow: a dimensionless approach
K ARDAM
Politecnico di Milano, 2018
2018
Reproducible Machine Learning/Physical Based Models for Pressure Drop Estimation in Two-Phase Adiabatic Flows in Smooth Tubes
K Ardam, B Najafi, A Hanusovsky, P Vega Pinchet Domecq, F Rinaldi, ...
Physical Based Models for Pressure Drop Estimation in Two-Phase Adiabatic …, 0
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