Explaining Effective Parameters on the Employees' Priorities in the Daylighting Condition in Office Environments by Fuzzy Analysis Method

Message:
Article Type:
Research/Original Article (دارای رتبه معتبر)
Abstract:
Background and Objective

 A good lighting condition in an office building, in terms of energy efficiency,  is achievable through better use of natural light, but this requires consideration of all effective parameters. Therefore, providing the desirable daylighting in office environments that are based on the priorities of employees, is a necessity in terms of design and construction. Despite much research in this area, there is no comprehensive theoretical framework. The aim of this study is to achieve a comprehensive model in this regard.

Method

 At first, an analytical review of research related to the use of natural light in office buildings has been done. In this section, the meta-analysis method and comparison of the results of previous researches and the development of a theoretical model have been used. Then, by using the opinions of 15 experts - with experience in office space design - and fuzzy network analysis, the proposed variables and parameters in this theoretical model are tried to be prioritized. 

Findings

 According to which, people's preferences in the three structures of employees' mental priorities over natural light and their priorities in relation to the required lighting efficiency and in relation to lighting control equipment can be summarized. In addition, the most important components affecting the determination and limitation of these priorities are stated.

Discussion and Conclusion

 The results of fuzzy analysis of the components obtained from the mentioned studies and the proposed framework showed that the variables of optimal levels of light and visual comfort and glare and parameters of distance from the window and landscape can have a greater impact on creating optimal lighting conditions.

Language:
Persian
Published:
Journal of Environmental Sciences and Technology, Volume:24 Issue: 7, 2023
Pages:
51 to 68
https://www.magiran.com/p2554381