Journal ArticleDOI
Dynamic neural networks to analyze the behavior of phase change materials embedded in building envelopes
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TLDR
In this article, the authors used dynamic neural networks to simulate the behavior of a phase change material layer of a building envelope, which typically are under strongly varying conditions, with temperatures and heat fluxes changing at different rates inside a wide range of values.About:
This article is published in Applied Thermal Engineering.The article was published on 2019-07-25. It has received 12 citations till now. The article focuses on the topics: Artificial neural network.read more
Citations
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Journal ArticleDOI
Experimental study and ANN-based prediction of melting heat transfer in a uniform heat flux PCM enclosure
TL;DR: In this paper, a multilayered perceptron feed-forward neural network was used to predict the Nusselt number and the melted volume fraction of n-octadecane phase change material.
Journal ArticleDOI
A state-of-the-art-review on phase change materials integrated cooling systems for deterministic parametrical analysis, stochastic uncertainty-based design, single and multi-objective optimisations with machine learning applications
TL;DR: A state-of-the-art-review on phase change materials for cooling applications is presented, in terms of smart ventilations, intelligent PCMs charging/discharging, deterministic parametrical analysis, stochastic uncertainty-based performance prediction and optimisation.
Journal ArticleDOI
Transient heat transfer analysis of phase change material melting in metal foam by experimental study and artificial neural network
Juan Duan,Fan Li +1 more
TL;DR: In this paper, an artificial neural network (ANN) method is used to study the transient heat transfer process of the phase change material with porous media (PCM-porous) and the experimental results show that porosity of metal foam has a greater influence on the melting and heat transfer of PCM than the pore density.
Journal ArticleDOI
A Critical Review on the Control Strategies Applied to PCM-Enhanced Buildings
TL;DR: An extensive review has been made with regard to various control strategies applied to PCM-enhanced buildings, such as ON/OFF control, conventional control methods (classical control, optimal, adaptive, and predictive control) and intelligent controls.
Journal ArticleDOI
Numerical investigation on heat transfer characteristics during melting of lauric acid in a slender rectangular cavity with flow boundary condition
TL;DR: In this paper, the melting mechanism and thermal behavior of phase change material (PCM) in a slender rectangular cavity with heat transfer fluid (HTF) flowing over one side and the other sides thermally insulated.
References
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Book
Neural network design
TL;DR: This book, by the authors of the Neural Network Toolbox for MATLAB, provides a clear and detailed coverage of fundamental neural network architectures and learning rules, as well as methods for training them and their applications to practical problems.
Journal ArticleDOI
Review on thermal energy storage with phase change: materials, heat transfer analysis and applications
TL;DR: In this paper, a review of the history of thermal energy storage with solid-liquid phase change has been carried out and three aspects have been the focus of this review: materials, heat transfer and applications.
Journal ArticleDOI
Artificial neural networks in renewable energy systems applications: a review
TL;DR: In this article, the authors present various applications of neural networks mainly in renewable energy problems in a thematic rather than a chronological or any other order, which clearly suggest that artificial neural networks can be used for modelling in other fields of renewable energy production and use.
Journal ArticleDOI
Applications of artificial neural networks in energy systems
TL;DR: In this paper, the authors present various applications of neural networks in energy problems in a thematic rather than a chronological or any other order, including modeling the heat-up response of a solar steam-generating plant, estimation of a parabolic trough collector intercept factor, and the estimation of the local concentration ratio.
Journal ArticleDOI
Applications of artificial neural networks for thermal analysis of heat exchangers – A review
TL;DR: In this paper, the authors reviewed the applications of ANN for thermal analysis of heat exchangers and highlighted the limitations of ANN in this field and its further research needs in the field.
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