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An intuitive daylighting performance analysis and optimization approach

Author(s)
Andersen, Marilyne; Kleindienst, Sian A.; Yi, Lu; Lee, Jaime; Bodart, Magali; Cutler, Barbara; ... Show more Show less
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Article is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use.
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Abstract
The effective integration of daylighting considerations into the design process requires many issues to be considered simultaneously, such as daily and seasonal variations, illumination, and thermal comfort. To address the need for early integration into the design process, a new approach called Lightsolve has been developed. Its key objectives are to support the design process using a goal-oriented approach based on iterative design improvement suggestions; to provide climate-based annual metrics in a visual and synthesized format; and to relate quantitative and qualitative performance criteria using daylighting analysis data in various forms. This methodology includes the development of a time-segmentation process to represent weather and time in a condensed form, the adaptation of daylight metrics that encompass temporal and spatial considerations, and the creation of an interactive analysis interface to explore design options and design iterations. This system relies on optimization techniques to generate these suggestions. Lightsolve allows the designer to explore other design alternatives that may better fulfil the objectives and to learn about appropriate strategies to resolve daylight or sunlight penetration issues. It offers architects and building engineers support for daylighting design that can be employed interactively within the existing design process.
Date issued
2008-10
URI
http://hdl.handle.net/1721.1/67501
Department
Massachusetts Institute of Technology. Building Technology Group
Journal
Building Research and Information
Publisher
Taylor & Francis Group
Citation
Andersen, Marilyne et al. “An intuitive daylighting performance analysis and optimization approach.” Building Research & Information 36.6 (2008): 593-607. ©2008 Taylor & Francis.
Version: Final published version
ISSN
1466-4321
0961-3218

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