4.7 Article

Optimal design of classroom spaces in naturally-ventilated buildings to maximize occupant satisfaction with human bioeffluents/body odor levels

期刊

BUILDING AND ENVIRONMENT
卷 169, 期 -, 页码 -

出版社

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.buildenv.2019.106543

关键词

Natural ventilation; Indoor air quality; Human bioeffluents; Human body odor; Education buildings; Multi-objective genetic algorithm

资金

  1. Universidad Panamericana
  2. Consejo Nacional de Ciencia y Tecnologia (CONACYT)
  3. ZJU-UIUC Institute Research Program

向作者/读者索取更多资源

Inadequate indoor air quality in education buildings has been reported to cause health problems, contagion, poor academic performance and absenteeism of occupants. To minimize these adverse effects, the use of natural ventilation systems and hybrid ventilation systems in buildings have increased in recent years. This paper presents the development of a novel optimization model that provides the capability of optimizing education building design in order to maximize occupant satisfaction in the classrooms space in terms of perception of human bioeffluents/body odor while minimizing the construction cost. The multi-objective optimization model is developed in three main stages: (1) model formulation stage that identifies relevant design variables, objective functions and constraints; (2) model implementation stage that executes the optimization computations; and (3) model evaluation stage that analyses the performance of the developed model using an application example. The findings of this performance analysis illustrates the capability of the developed optimization model to generate a wide range of optimal trade-offs solutions, where each provides a unique and optimal trade-off between occupant satisfaction with human bioeffluents/body odor levels and its construction cost. This enables designers to generate and analyze these optimal trade-offs and accordingly identify an optimal set of design decisions that maximize satisfaction with human bioeffluents/body odor levels of occupants while complying with specified budget constraint.

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