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Recent advances in the applications of machine learning methods for heat exchanger modeling—a review
Heat exchanger modeling has been widely employed in recent years for performance
calculation, design optimizations, real-time simulations for control analysis, as well as …
calculation, design optimizations, real-time simulations for control analysis, as well as …
Viscosity correlation of CO2, HFCs, HFOs, and their mixtures: review of experimental data and modeling techniques
This work proposes reference viscosity corrections that combine the Peng− Robinson (PR),
Volume− Translated PR (VTPR), and Cubic− Plus− Association (CPA) Equation of State …
Volume− Translated PR (VTPR), and Cubic− Plus− Association (CPA) Equation of State …
[HTML][HTML] Data-driven soft sensors targeting heat pump systems
The development of smart sensors, low cost communication, and computation technologies
enables continuous monitoring and accumulation of tremendous amounts of data for heat …
enables continuous monitoring and accumulation of tremendous amounts of data for heat …
Effect of water absorption on the behavior of jute and sisal fiber biocomposites at different lengths: ANN and RSM modeling
Artificial neural networks (ANN) and response surface method (RSM) modeling were used to
study the effect of water absorption on the behavior of jute (JF/epoxy) and sisal (SF/epoxy) …
study the effect of water absorption on the behavior of jute (JF/epoxy) and sisal (SF/epoxy) …
[HTML][HTML] Dynamic viscosity of low GWP refrigerants in the liquid phase: An empirical equation and an artificial neural network
This study presents a simple correlation for describing the temperature and pressure
dependence of the liquid dynamic viscosity of low GWP refrigerants, namely …
dependence of the liquid dynamic viscosity of low GWP refrigerants, namely …
Water absorption behavior of jute fibers reinforced HDPE biocomposites: Prediction using RSM and ANN modeling
The main objective of the present study was to investigate both the effect of incorporating
Jute Fibers (JF) into the high density polyethylene (HDPE) matrix and to model the water …
Jute Fibers (JF) into the high density polyethylene (HDPE) matrix and to model the water …
Modeling liquid thermal conductivity of low-GWP refrigerants using neural networks
The thermal conductivity of refrigerants is needed to optimize and design the main
components of HVAC&R systems. Consequently, it is crucial to have reliable models that are …
components of HVAC&R systems. Consequently, it is crucial to have reliable models that are …
Water Uptake of HDPE Reinforced with Washingtonia Fibre Biocomposites: Mathematical Modelling using Artificial Neural Network, Response Surface Methodology …
A Belaadi, A Lekrine, M Boumaaza… - Advances in Materials …, 2024 - Taylor & Francis
To research the mechanisms of diffusion and water uptake kinetics biocomposites, various
HDPE materials reinforced by varying quantities of Washingtonia filifera (WF) fibres (10 to 30 …
HDPE materials reinforced by varying quantities of Washingtonia filifera (WF) fibres (10 to 30 …
Modeling of compressed liquid viscosity of hydrofluorocarbons, hydrofluoroolefins, hydrochlorofluoroolefins, hydrochlorofluorocarbons and their mixtures
Y Liu, X Zheng, C Liu, S Lv - Journal of Molecular Liquids, 2022 - Elsevier
In this work, a semi-empirical viscosity model for hydrofluorocarbons (HFCs),
hydrofluoroolefins (HFOs), hydrochlorofluoroolefins (HCFOs), hydrochlorofluorocarbons …
hydrofluoroolefins (HFOs), hydrochlorofluoroolefins (HCFOs), hydrochlorofluorocarbons …
Thermal conductivity prediction of pure refrigerants and mixtures based on entropy-scaling concept
K Kang, X Li, Y Gu, X Wang - Journal of Molecular Liquids, 2022 - Elsevier
The residual entropy scaling (RES) concept builds up connection between the transport
properties and thermodynamic equation of state directly. However, the low-density …
properties and thermodynamic equation of state directly. However, the low-density …