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Aerogel: Numerical Study on the Thermal and Optical Performances of an Aerogel Glazing System with the Multivariable Optimization Using an Advanced Machine Learning Algorithm (Adv. Theory Simul. 9/2019)
Author(s) -
Zheng Siqian,
Zhou Yuekuan
Publication year - 2019
Publication title -
advanced theory and simulations
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.068
H-Index - 17
ISSN - 2513-0390
DOI - 10.1002/adts.201970032
Subject(s) - aerogel , multivariable calculus , particle swarm optimization , robustness (evolution) , thermal , computer science , glazing , materials science , mathematical optimization , algorithm , engineering , control engineering , mathematics , composite material , physics , chemistry , biochemistry , meteorology , gene
A numerical model is developed to characterize the sophisticated thermal and optical performances of a novel aerogel granule translucent window. An advanced optimization engine is proposed for the optimal design and robust operation by implementing the supervised machine learning and advanced optimization algorithms. The teaching‐learning‐based optimization shows more robustness than the particle swarm optimization, for the enhancement of thermal performance. More details can be found in article number 1900092 by Siqian Zheng and Yuekuan Zhou.