Niloufar Fadaei; Wei‐Mon Yan; Mohammad Mahdi Tafarroj; Alibakhsh Kasaeian · 10.1016/j.enconman.2018.06.055 https://doi.org/10.1016/j.enconman.2018.06.055
Energy Conversion and Management
Experimental
Machine learning / AI
Solar chimney power plant
Thermal storage / PCM
2018
Energy Conversion and Management
no
2018-06-23 12:00:00 00002904
the application of artificial neural networks to predict the performance of solar chimney filled with phase change materials
2018
Energy Conversion and Management
Niloufar Fadaei; Wei‐Mon Yan; Mohammad Mahdi Tafarroj; Alibakhsh Kasaeian
10.1016/j.enconman.2018.06.055
Summary
Paraffin wax was placed as a latent heat store inside a small experimental solar chimney built on a Tehran university campus, and its behaviour was examined through measurements and modelling. A multilayer neural network trained in MATLAB predicted the air temperatures with agreement above 99% against the test data and average relative deviations below 3%.
Description written by Solar Tower. The original abstract is available from the publisher via the link below.
Open source