Zobrazeno 1 - 10
of 38
pro vyhledávání: '"Goopyo Hong"'
Autor:
Goopyo Hong, Namchul Seong
Publikováno v:
Buildings, Vol 13, Iss 10, p 2526 (2023)
With an increasing concern for global warming, there have been many attempts to reduce greenhouse gas emissions. About 30% of total energy has been consumed by buildings, and much attention has been paid to reducing building energy consumption. There
Externí odkaz:
https://doaj.org/article/2fcbc09e889f4cb8bb741748c0f07ab3
Autor:
Chanhyung Shim, Goopyo Hong
Publikováno v:
Energies, Vol 16, Iss 19, p 6845 (2023)
The thermal performance of building envelopes is significantly affected by building insulation and airtightness. However, most studies have focused on improving thermal performance in building envelopes, while few studies on improving airtightness in
Externí odkaz:
https://doaj.org/article/7c2418c17715465bbef889f6550a1e58
Publikováno v:
Buildings, Vol 12, Iss 10, p 1636 (2022)
With the development of metering technologies, data mining techniques such as machine learning have been increasingly used for the prediction of building energy consumption. Among various machine learning methods, the KNN algorithm was implemented to
Externí odkaz:
https://doaj.org/article/3a3178e2916944858606d9c5f2eed8e4
Publikováno v:
Energies, Vol 15, Iss 8, p 2854 (2022)
Thermal bridges in building envelopes can cause significant heat loss and heat gain. In this study, the developed thermal bridge breaker was applied to an interior insulation finishing system in residential buildings to minimize the thermal bridges i
Externí odkaz:
https://doaj.org/article/0ff0ab5feffb4e78877c97cb18852f6a
Publikováno v:
Energies, Vol 13, Iss 19, p 5038 (2020)
In commercial buildings, HVAC systems are becoming a primary driver of energy consumption, which already account for 45% of the total building energy consumption. In the previous literature, researchers have studied several energy conservation measur
Externí odkaz:
https://doaj.org/article/4c0e3cba8290430cab5b1cb1af7b4b23
Autor:
Goopyo Hong, Byungseon Sean Kim
Publikováno v:
Energies, Vol 11, Iss 6, p 1494 (2018)
We would like to thank Yaolin Lin and Wei Yang for their comments [...]
Externí odkaz:
https://doaj.org/article/15908215f0264ca1a42180bebe946b65
Autor:
Goopyo Hong, Byungseon Sean Kim
Publikováno v:
Energies, Vol 11, Iss 2, p 407 (2018)
The purpose of this study was to develop a data-driven predictive model that can predict the supply air temperature (SAT) in an air-handling unit (AHU) by using a neural network. A case study was selected, and AHU operational data from December 2015
Externí odkaz:
https://doaj.org/article/0833f8f36dee48c4b0a1b9ec9a06eed6
Publikováno v:
Energies, Vol 9, Iss 11, p 979 (2016)
The aim of the present study was to investigate the thermal performance of window systems using full-scale measurements and simulation tools. A chamber was installed on the balcony of an apartment to control the temperatures which can create condensa
Externí odkaz:
https://doaj.org/article/915ad8cf4cd74b9e95743f05b77284ce
Autor:
Namchul Seong1, Goopyo Hong2
Publikováno v:
ASHRAE Transactions. 2023, Vol. 129 Issue Part1, p809-816. 8p.
Publikováno v:
Journal of The Korean Society of Living Environmental System. 29:604-612
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c78aa329375eaf65310613817ba6d6ea
https://doi.org/10.21086/ksles.2022.12.29.6.604
https://doi.org/10.21086/ksles.2022.12.29.6.604