Assessing the applicability of the European standard EN 17037:2018 for office spaces in a cold climate

Sepúlveda, Abel; Luca, Francesco De; Varjas, Toivo; Kurnitski, Jarek

doi:10.1016/j.buildenv.2022.109602

Cited by 9 publications

(1 citation statement)

References 36 publications

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“…According to the European standard EN 17037, "Daylight in Buildings," the level of visual comfort is de ned by the amount of direct sun exposure, the view out of the structure, glare prevention, and daylight provision in internal spaces. In fact, daylight is the most favored source of light for building users, and it has even enhanced the value of real estate (Sepúlveda et al, 2022).…”

Section: Introductionmentioning

confidence: 99%

Impact of external obstructions and dirt accumulation on sustainable daylight performance through intelligent parametric optimization for open-plan offices.

Thakur,

Sharma

2024

Preprint

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Daylight is frequently viewed as a valuable resource for increasing energy efficiency and improving indoor visual comfort. The quality and quantity of natural light entering a building depends on both internal and external factors. People require adequate daylight at their workstations, particularly in open-plan settings, in order to function well. The development of dirt or particles on the windows, such as moss, dust, water, and sand, and shading effects due to nearby obstructions prevents light energy from accessing the created envelope. The open-plan office in Hamirpur district of Himachal Pradesh, India was chosen for this study to undertake an experiment with varied amounts of dirt accumulation and nearby shading effect. A thorough survey of the literature is also performed in order to uncover research methodologies applied to optimization of daylight. This research shows how parametric modeling may be used to increase the daylight performance of an open-plan office in a humid subtropical environment (Cwa). The foundation model of an open-plan office was used to optimize daylight. To conduct the study, a grasshopper script is created using the primary plug-ins Honeybee, Ladybug, Octopus, and TT Toolbox. The statistical mean bias error (MBE) is used to validate the base model. Using sensitivity analysis, the results are further evaluated to discover interrelationships.

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Section: Introductionmentioning

confidence: 99%