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A critical review of fenestration/window system design methods for high performance buildings

期刊

ENERGY AND BUILDINGS
卷 248, 期 -, 页码 -

出版社

ELSEVIER SCIENCE SA
DOI: 10.1016/j.enbuild.2021.111184

关键词

Window technology; Fenestration system design optimization; Knowledge-based design; Simulation-based design

资金

  1. NSF [2011296, 2013093]
  2. Directorate For Engineering
  3. Div Of Civil, Mechanical, & Manufact Inn [2013093, 2011296] Funding Source: National Science Foundation

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This paper explores window design studies for high-performance buildings, emphasizing the importance of well-designed fenestration systems operated with proper control strategies in reducing energy usage while maintaining a comfortable environment for occupants.
ABSTR A C T Fenestrations allow for natural daylight and outdoor views, but also represent the least thermally effi-cient portion of the building envelope, and thus can be a source of unwanted direct sunlight and associ-ated discomfort glare. A well-designed fenestration system operated with proper control strategies is capable of reducing building energy usage significantly while maintaining a both thermally and visually comfortable environment for occupants. This paper reviews and analyzes window design studies for high-performance buildings, which could be interpreted as decision-making processes to achieve the window performance goals by controlling a series of design variables (e.g., location and dimensions of windows, glazing type, etc.). An overview of available design options for window systems to date is intro-duced first, and then the decision-making methodologies of window systems are categorized and ana-lyzed to present a comprehensive review, where we present a detailed analysis of sequential knowledge-based design methods and simulation-based optimization methods. Last, potential challenges and future research trends are identified and analyzed to help promote all automatic simulation-based optimization design methods for high performance fenestration systems. (c) 2021 Elsevier B.V. All rights reserved.

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