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Analysis of Personal Factors in Determination of Thermal Comfort Zone at University

Naderzadeh, Sajjad | 2021

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  1. Type of Document: M.Sc. Thesis
  2. Language: Farsi
  3. Document No: 54082 (46)
  4. University: Sharif University of Technology
  5. Department: Energy Engineering
  6. Advisor(s): Rajabi Ghahnavieh, Abbas
  7. Abstract:
  8. Due to the energy crisis in recent years, much of which is due to excessive energy consumption in the air conditioning of buildings, many studies have been conducted from the perspective of engineering sciences on the subject of insulation and optimization of buildings. This study aims to investigate the conditions of thermal comfort from the mental and psychological perspective of human beings, which is the basis of the individual's decision to accept thermal adaptation behavior in the standard temperature range. In this study, the thermal adaptation model was designed on the theory of programmed behavior, which can explain the adaptation of individuals to the comfort temperature region. This study was conducted based on data collected by a questionnaire from 70 students of Sharif University of Technology who live in Tarasht dormitory 3. In the proposed model, the factors that directly affect people's intention to adapt to ambient temperatures, such as attitude, mental norm, and behavioral control, are understood, and their interactions are examined.Through structural equation modeling and keyword analysis, this study shows that all three factors, as well as the interaction of perceived behavior control and mental norms, significantly affect individuals' intentions to adapt. Using this result, by directly intervening on these factors and spending a small amount of money through education and information in a period of time, residents can be mentally and without prejudice, ready to accept the minimum standard temperature range and reduce the heating load of the building up to 30%
  9. Keywords:
  10. Energy Consumption Reduction ; Planned Behavior ; Thermal Comfort ; Predicted Mean Vote Model ; Energy and Buildings ; Thermal Comfort Zone ; Behavior Identification ; Energy Consumption Optimization

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