However, in the daylight system design of buildings especially offices, where occupants typically cannot change their positions and have restricted visual comfort choices, problems regularly occur in achieving the harmony between sufficiently well-lit spaces from the window and its undesired illuminance (under-lit and over-lit). Thus, in the design process of a well-lit workspace environment, both the quantitative and the qualitative criteria must be met. The typology of the building and its possible impact on optimum daylight rates in its internal areas is one of these criteria. Designing for the optimal level of natural light that gets inside a building is complicated by many factors that may affect the distribution of light. Bringing natural light to buildings is, therefore, one of the most important aspects of design. īringing natural light to buildings is, therefore, one of the most important aspects of design. The main purpose of such designs is to control the amount of inbound daylight.
A suitable design is expected to allow the right quantity of natural light into space and guide the entering light such that it creates a balance in daylight.
Natural light has assumed a pivotal function in the design of interior work environments, even more than in the design of any other building type. Nevertheless, the investigation of daylighting in workplaces has been a subject of interest for a long time. Due to the special needs for daylighting in interior work environments, it has become imperative to state that, the entrance of sunlight is valuable in creating a healthy, comfortable, and productive work-place. Daylighting is one of the most significant components of the environment that needs to be considered in order to provide an appropriate interior environment, as well as achieve energy efficiency and other sustainability outcomes. Sustainable architecture design is a complex combination process that requires the reconciliation of buildings, occupant requests, and ecological boundary conditions. RGB Reflectance value of (red, green, blue) Keywordsĭaylight performance, Parametric simulation tools, Genetic algorithms, Light-shelf Nomenclature Statistical analysis is achieved to investigate the relationship between the performance metric of the optimal design options and the other cases, the outcomes showed that the regression analysis indicated a high level of reliability as well as different levels of variation coefficients. After the optimization, the daylighting performance of useful daylight illuminance compared to reference models is increased respectively with an average value of 15.6% and 4.7% on the 21st of June, and by 17.5% and 5.8% on 21st of March, and by 5.8% and 11.3% on 21st of December. The optimization results indicate that the optimal design options of light-shelf parameters have great potential for illuminance improvement. Five parameters of light shelf design are optimized in two solar solstices (June and December) and one equinox in March under the Malaysian sky conditions. A case study of a typical office is carried out to test and verify the effectiveness of the optimization procedure for a light shelf system.
The approach uses parametric design, simulation modelling, and genetic algorithms. This study aims to achieve a balance of daylight availability in the work-plane environments of a fully glazed facade integrated with a light shelf system using an optimization procedure that can assist architects with assessing the daylighting performance of numerous design alternatives, and build-up the optimized design.
#Honeybee daylight software license#
This is an open access article under the CC BY license ( ).Ĭitation: Ali Ahmed Salem Bahdad, Sharifah Fairuz Syed Fadzil, Nooriati Taib, Optimization of Daylight Performance Based on Controllable Light-shelf Parameters using Genetic Algorithms in the Tropical Climate of Malaysia, Journal of Daylighting 7 (2020) 122-136. History: Received 30 April 2020 | Revised 5 June 2020 | Accepted 15 June 2020 | Published online 20 June 2020Ĭopyright: © 2020 The Author(s). School of Housing, Building, and Planning, Universiti Sains Malaysia (USM), Penang, Malaysia
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