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Impact of Building Design Parameters on Daylighting Metrics Using an Analysis, Prediction, and Optimization Approach Based on Statistical Learning Technique

Author

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  • Jaewook Lee

    (Illinois School of Architecture, University of Illinois at Urbana-Champaign, Champaign, IL 61820, USA)

  • Mohamed Boubekri

    (Illinois School of Architecture, University of Illinois at Urbana-Champaign, Champaign, IL 61820, USA)

  • Feng Liang

    (Department of Statistics, University of Illinois at Urbana-Champaign, Champaign, IL 61820, USA)

Abstract

Daylighting metrics are used to predict the daylight availability within a building and assess the performance of a fenestration solution. In this process, building design parameters are inseparable from these metrics; therefore, we need to know which parameters are truly important and how they impact performance. The purpose of this study is to explore the relationship between building design attributes and existing daylighting metrics based on a new methodology we are proposing. This methodology involves statistical learning. It is an emerging methodology that helps us to analyze a large quantity of output data and the impact of a large number of design variables. In particular, we can use these statistical methodologies to analyze which features are important, which ones are not, and the type of relationships they have. Using these techniques, statistical models may be created to predict daylighting metric values for different building types and design solutions. In this article we will outline how this methodology works, and analyze the building design features that have the strongest impact on daylighting performance.

Suggested Citation

  • Jaewook Lee & Mohamed Boubekri & Feng Liang, 2019. "Impact of Building Design Parameters on Daylighting Metrics Using an Analysis, Prediction, and Optimization Approach Based on Statistical Learning Technique," Sustainability, MDPI, vol. 11(5), pages 1-21, March.
    • Handle: RePEc:gam:jsusta:v:11:y:2019:i:5:p:1474-:d:212598
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    References listed on IDEAS

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    Cited by:

    1. Fabrizio M. Amoruso & Udo Dietrich & Thorsten Schuetze, 2019. "Integrated BIM-Parametric Workflow-Based Analysis of Daylight Improvement for Sustainable Renovation of an Exemplary Apartment in Seoul, Korea," Sustainability, MDPI, vol. 11(9), pages 1-29, May.
    2. Tony-Andreas Arntsen & Bozena Dorota Hrynyszyn, 2021. "Optimization of Window Design for Daylight and Thermal Comfort in Cold Climate Conditions," Energies, MDPI, vol. 14(23), pages 1-17, November.
    3. Ali Mohammed AL-Dossary & Daeung Danny Kim, 2020. "A Study of Design Variables in Daylight and Energy Performance in Residential Buildings under Hot Climates," Energies, MDPI, vol. 13(21), pages 1-16, November.
    4. Nataša Šprah & Mitja Košir, 2019. "Daylight Provision Requirements According to EN 17037 as a Restriction for Sustainable Urban Planning of Residential Developments," Sustainability, MDPI, vol. 12(1), pages 1-22, December.
    5. Erika Dolníková & Dušan Katunský & Zuzana Miňová & Bystrík Dolník, 2021. "Influence of the Adaptation of Balconies to Loggias on the Lighting Climate inside an Apartment Building under Cloudy Sky," Sustainability, MDPI, vol. 13(6), pages 1-24, March.

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