Model-based design, synthesis and use of thermally insulating mortar formulations for energy conservation in buildings

Sarilak, Dusitporn; Kerdlap, Wanwisa; Embley, Ben; Chisti, Yusuf; Hansupalak, Nanthiya

doi:10.1016/j.jclepro.2020.124287

Cited by 3 publications

(1 citation statement)

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“…Data storage refers to the storage and management of energy consumption big data [31]. Energy consumption big data storage includes hardwareandsoftware.Dataanalysisreferstotheuseofanalytical methods or tools to examine, transform, and model energy consumption big data based on the energy consumption data warehouse and explore the relationship between energy consumption changes and internal and external factors such as the environment, building, operating equipment, and personnel activities.Theanalysisresultsproposerelevantenergyconservationmeasuresandformulaterelevantenergyconservationpolicies [32]. The data application is based on the energy conservation platform of the large public buildings and realizes the evaluation of energy efficiency, prediction of energy consumption,diagnosisofenergysaving,quotaofenergyconsumption,etc.…”

Section: Energy Saving Of Large Publicmentioning

confidence: 99%

Analysis of Energy Conservation Big Data of Embedded Large Public Buildings and Construction of the Information Model by 5G

Zhao

Yan

2022

Wireless Communications and Mobile Computing

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The problem of energy shortage has become one of the most serious problems in the process of economic development. The research is aimed at studying the energy conservation data and information model of large public buildings. Based on the theories of 5G technology, embedded system, and energy conservation of large public buildings, firstly, 5G technology is used to collect research data. Secondly, some large public buildings in Northwest China are analyzed for energy conservation by using ZigBee and other related technologies and algorithms. Finally, the office buildings in large public buildings are used as samples for the construction of the information model to be analyzed. The research results denote that large public buildings are mainly concentrated in hospitals, hotels, shopping malls, and so on. The south-facing window to wall ratio is higher than that of the north-facing window to wall ratio, and the east-west-facing window to wall ratio has the lowest probability of appearing. In addition, the thermal conductivity of the roof of most of the large buildings is less than 1.0 W, while the thermal conductivity of the outer wall of the roof is distributed around 2.5 W, and the thermal conductivity of the outer wall is around 0.6 W. Finally, commercial buildings have higher heating and cooling loads than residential buildings. In the construction of the information model for energy conservation of large public buildings, the neural networks (NNs) and clustering analysis algorithm are introduced into the prediction model of energy consumption data, and it is found that compared with the actual observed value, the overall trend shows consistency, both of which are periodic fluctuations. However, there are still some errors in some data. Therefore, an analysis of energy conservation data of embedded large public buildings and the construction of information models based on 5G has important guiding significance for the construction industry to improve business performance and market competitiveness.

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Section: Energy Saving Of Large Publicmentioning

confidence: 99%