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An improved window opening behavior model involving the division of the dummy variable’s interval level: Case study of an office building in Xi’an during summer

  • Research Article
  • Architecture and Human Behavior
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Abstract

Window opening behavior significantly impacts indoor air quality, thermal comfort, and energy consumption. A field measurement was carried out in three typical rooms (a standard office, a meeting room and a smoking office) within an office building. The window state and the physical environment were continuously recorded during the measured periods. Three typical window opening behaviors were found in the measured samples, namely, active, moderate, and passive. The common logistic regression coefficient indicated that solar radiation exhibited the greatest effect on window opening behavior in the smoking office and standard office. Typically, window opening behavior in the meeting room was the most strongly correlated with time of the day, mainly because of the meeting schedule for occupants in the meeting room. This study discussed the dividing principles involved in setting the dummy variable interval level (discretizing continuous variables and dividing them into different intervals), and proposed a method to determine the optimal interval level of each variable. The improved model led to the increase in the prediction accuracy rate of the window being opened by 2.0% and 3.3% according to the comparison with the original model based on dummy variables and the common model based on continuous variables, respectively. This study can provide a reference value for simulating energy consumption in office buildings in the future.

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References

  • Andersen R, Fabi V, Toftum J, et al. (2013). Window opening behaviour modelled from measurements in Danish dwellings. Building and Environment, 69: 101–113.

    Article  Google Scholar 

  • Barthelmes VM, Heo Y, Fabi V, et al. (2017). Exploration of the Bayesian Network framework for modelling window control behaviour. Building and Environment, 126: 318–330.

    Article  Google Scholar 

  • Beuzen T, Marshall L, Splinter KD (2018). A comparison of methods for discretizing continuous variables in Bayesian Networks. Environmental Modelling & Software, 108: 61–66.

    Article  Google Scholar 

  • Calì D, Andersen RK, Müller D, et al. (2016). Analysis of occupants’ behavior related to the use of windows in German households. Building and Environment, 103: 54–69.

    Article  Google Scholar 

  • Calì D, Wesseling MT, Müller D (2018). WinProGen: A Markov-Chain-based stochastic window status profile generator for the simulation of realistic energy performance in buildings. Building and Environment, 136: 240–258.

    Article  Google Scholar 

  • Cao Y, Pan S, Liu Y, et al. (2022). The window opening behavior of infant families: A case study during transition season in the cold region of China. Energy and Buildings, 254: 111588.

    Article  Google Scholar 

  • Chen SH, Pollino CA (2012). Good practice in Bayesian network modelling. Environmental Modelling & Software, 37: 134–145.

    Article  Google Scholar 

  • Cho H, Cabrera D, Sardy S, et al. (2021). Evaluation of performance of energy efficient hybrid ventilation system and analysis of occupants’ behavior to control windows. Building and Environment, 188: 107434.

    Article  Google Scholar 

  • D’Oca S, Hong T (2014). A data-mining approach to discover patterns of window opening and closing behavior in offices. Building and Environment, 82: 726–739.

    Article  Google Scholar 

  • Deme Belafi Z, Naspi F, Arnesano M, et al. (2018). Investigation on window opening and closing behavior in schools through measurements and surveys: a case study in Budapest. Building and Environment, 143: 523–531.

    Article  Google Scholar 

  • Deng T, Shen X, Cheng X, et al. (2021). Investigation of window-opening behaviour and indoor air quality in dwellings situated in the temperate zone in China. Indoor and Built Environment, 30: 938–956.

    Article  Google Scholar 

  • Du C, Yu W, Ma Y, et al. (2021). A holistic investigation into the seasonal and temporal variations of window opening behavior in residential buildings in Chongqing, China. Energy and Buildings, 231: 110522.

    Article  Google Scholar 

  • Fabi V, Andersen RV, Corgnati S, et al. (2012). Occupants’ window opening behaviour: A literature review of factors influencing occupant behaviour and models. Building and Environment, 58: 188–198.

    Article  Google Scholar 

  • Faheem M, Bhandari N, Tadepalli S, et al. (2022). Investigation on window opening behavior in naturally ventilated hostels of warm and humid climate. Energy and Buildings, 268: 112184.

    Article  Google Scholar 

  • Field A, Miles J, Field Z (2012). Discovering Statistics Using R. London: SAGE Publications.

    Google Scholar 

  • Fritsch R, Kohler A, Nygård-Ferguson M, et al. (1990). A stochastic model of user behaviour regarding ventilation. Building and Environment, 25: 173–181.

    Article  Google Scholar 

  • Gu Y, Cui T, Liu K, et al. (2021). Study on influencing factors for occupant window-opening behavior: Case study of an office building in Xi’an during the transition season. Building and Environment, 200: 107977.

    Article  Google Scholar 

  • Gustin M, McLeod RS, Lomas KJ (2019). Can semi-parametric additive models outperform linear models, when forecasting indoor temperatures in free-running buildings? Energy and Buildings, 193: 250–266.

    Article  Google Scholar 

  • Haldi F, Robinson D (2009). Interactions with window openings by office occupants. Building and Environment, 44: 2378–2395.

    Article  Google Scholar 

  • Herkel S, Knapp U, Pfafferott J (2008). Towards a model of user behaviour regarding the manual control of windows in office buildings. Building and Environment, 43: 588–600.

    Article  Google Scholar 

  • Hou J, Zhang Y, Sun Y, et al. (2017). Occupants’ windows opening behaviour in residences during heating season in Tianjin, China. Procedia Engineering, 205: 2744–2748.

    Article  Google Scholar 

  • Hwang RL, Chen B, Chen W (2021a). Analysis of incorporating a phase change material in a roof for the thermal management of school buildings in hot-humid climates. Buildings, 11: 248.

    Article  Google Scholar 

  • Hwang RL, Huang A, Chen W (2021b). Considerations on envelope design criteria for hybrid ventilation thermal management of school buildings in hot-humid climates. Energy Reports, 7: 5834–5845.

    Article  Google Scholar 

  • Indraganti M, Ooka R, Rijal HB, et al. (2015). Drivers and barriers to occupant adaptation in offices in India. Architectural Science Review, 58: 77–86.

    Article  Google Scholar 

  • Jeong B, Jeong JW, Park JS (2016). Occupant behavior regarding the manual control of windows in residential buildings. Energy and Buildings, 127: 206–216.

    Article  Google Scholar 

  • Kameni Nematchoua M, Ricciardi P, Reiter S, et al. (2017). Thermal comfort and comparison of some parameters coming from hospitals and shopping centers under natural ventilation: The case of Madagascar Island. Journal of Building Engineering, 13: 196–206.

    Article  Google Scholar 

  • Kim H, Hong T, Kim J (2019a). Automatic ventilation control algorithm considering the indoor environmental quality factors and occupant ventilation behavior using a logistic regression model. Building and Environment, 153: 46–59.

    Article  Google Scholar 

  • Kim A, Wang S, Kim JE, et al. (2019b). Indoor/outdoor environmental parameters and window-opening behavior: a structural equation modeling analysis. Buildings, 9: 94.

    Article  Google Scholar 

  • Kim M, Jung H, Park E, et al. (2020). Performance of an air purifier using a MnOx/TiO2 catalyst-coated filter for the decomposition of aldehydes, VOCs and ozone: An experimental study in an actual smoking room. Building and Environment, 186: 107247.

    Article  Google Scholar 

  • Lai D, Jia S, Qi Y, et al. (2018). Window-opening behavior in Chinese residential buildings across different climate zones. Building and Environment, 142: 234–243.

    Article  Google Scholar 

  • Larson MG (2008). Analysis of variance. Circulation, 117: 115–121.

    Article  Google Scholar 

  • Li N, Li J, Fan R, et al. (2015). Probability of occupant operation of windows during transition seasons in office buildings. Renewable Energy, 73: 84–91.

    Article  Google Scholar 

  • Liao FT (2015). Interpreting Probability Models: Logit, Probit, and Other Linear Models. Translated by Zhou MZ. Shanghai: Gezhi Publishing. (in Chinese)

    Google Scholar 

  • Liu Y, Chong W, Cao Y, et al. (2022). Characteristics analysis and modeling of occupants’ window operation behavior in hot summer and cold winter region, China. Building and Environment, 216: 108998.

    Article  Google Scholar 

  • Markovic R, Frisch J, van Treeck C (2019). Learning short-term past as predictor of window opening-related human behavior in commercial buildings. Energy and Buildings, 185: 1–11.

    Article  Google Scholar 

  • Naspi F, Arnesano M, Zampetti L, et al. (2018). Experimental study on occupants’ interaction with windows and lights in Mediterranean offices during the non-heating season. Building and Environment, 127: 221–238.

    Article  Google Scholar 

  • Nicol JF (2001). Characterising occupant behavior in buildings: Towards a stochastic model of occupant use of windows, lights, blinds heaters and fans. In: Proceedings of the 7th International IBPSA Building Simulation Conference, Rio de Janeiro, Brazil.

  • Niu B, Li D, Yu H, et al. (2022). Investigation of occupant window opening behaviour during the summer period in a Beijing maternity hospital. Journal of Building Engineering, 45: 103441.

    Article  Google Scholar 

  • Pan S, Xiong Y, Han Y, et al. (2018). A study on influential factors of occupant window-opening behavior in an office building in China. Building and Environment, 133: 41–50.

    Article  Google Scholar 

  • Pan S, Han Y, Wei S, et al. (2019). A model based on Gauss Distribution for predicting window behavior in building. Building and Environment, 149: 210–219.

    Article  Google Scholar 

  • Park J, Jeong B, Chae YT, et al. (2021). Machine learning algorithms for predicting occupants’ behaviour in the manual control of windows for cross-ventilation in homes. Indoor and Built Environment, 30: 1106–1123.

    Article  Google Scholar 

  • Peng Y, Lei Y, Tekler ZD, et al. (2022). Hybrid system controls of natural ventilation and HVAC in mixed-mode buildings: A comprehensive review. Energy and Buildings, 276: 112509.

    Article  Google Scholar 

  • Ren J, Zhou X, An J, et al. (2021). Comparative analysis of window operating behavior in three different open-plan offices in Nanjing. Energy and Built Environment, 2: 175–187.

    Article  Google Scholar 

  • Rijal HB, Tuohy P, Humphreys MA, et al. (2007). Using results from field surveys to predict the effect of open windows on thermal comfort and energy use in buildings. Energy and Buildings, 39: 823–836.

    Article  Google Scholar 

  • Sansaniwal SK, Mathur J, Mathur S (2021). Quantifying occupant’s adaptive actions for controlling indoor environment in naturally ventilated buildings under composite climate of India. Journal of Building Engineering, 41: 102399.

    Article  Google Scholar 

  • Schakib-Ekbatan K, Çakιcι FZ, Schweiker M, et al. (2015). Does the occupant behavior match the energy concept of the building? - Analysis of a German naturally ventilated office building. Building and Environment, 84: 142–150.

    Article  Google Scholar 

  • Shi Z, Qian H, Zheng X, et al. (2018). Seasonal variation of window opening behaviors in two naturally ventilated hospital wards. Building and Environment, 130: 85–93.

    Article  Google Scholar 

  • Shi S, Li H, Ding X, et al. (2020). Effects of household features on residential window opening behaviors: a multilevel logistic regression study. Building and Environment, 170: 106610.

    Article  Google Scholar 

  • Sorgato MJ, Melo AP, Lamberts R (2016). The effect of window opening ventilation control on residential building energy consumption. Energy and Buildings, 133: 1–13.

    Article  Google Scholar 

  • Stazi F, Naspi F, D’Orazio M (2017a). Modelling window status in school classrooms. Results from a case study in Italy. Building and Environment, 111: 24–32.

    Article  Google Scholar 

  • Stazi F, Naspi F, D’Orazio M (2017b). A literature review on driving factors and contextual events influencing occupants’ behaviours in buildings. Building and Environment, 118: 40–66.

    Article  Google Scholar 

  • Sun C, Zhang R, Sharples S, et al. (2018). A longitudinal study of summertime occupant behaviour and thermal comfort in office buildings in Northern China. Building and Environment, 143: 404–420.

    Article  Google Scholar 

  • Wang T, Wang L (2014). A steady heat transfer model of hollow double glazing under entire wave length heat radiation. Energy and Buildings, 81: 72–83.

    Article  Google Scholar 

  • Weerasinghe AS, Onyeizu EO, Rotimi JOB (2022). Environmental and socio-psychological drivers of building users’ behaviours: a case study of tertiary institutional offices in Auckland. Journal of Facilities Management, https://doi.org/10.1108/JFM-01-2022-0011

  • Wei Y, Yu H, Pan S, et al. (2019). Comparison of different window behavior modeling approaches during transition season in Beijing, China. Building and Environment, 157: 1–15.

    Article  Google Scholar 

  • Yao M, Zhao B (2017). Window opening behavior of occupants in residential buildings in Beijing. Building and Environment, 124: 441–449.

    Article  Google Scholar 

  • Yun GY, Steemers K (2008). Time-dependent occupant behaviour models of window control in summer. Building and Environment, 43: 1471–1482.

    Article  Google Scholar 

  • Yun GY, Tuohy P, Steemers K (2009). Thermal performance of a naturally ventilated building using a combined algorithm of probabilistic occupant behaviour and deterministic heat and mass balance models. Energy and Buildings, 41: 489–499.

    Article  Google Scholar 

  • Yun GY, Kim H, Kim JT (2012). Thermal and non-thermal stimuli for the use of windows in offices. Indoor and Built Environment, 21: 109–121.

    Article  Google Scholar 

  • Zhang Y, Barrett P (2012). Factors influencing the occupants’ window opening behaviour in a naturally ventilated office building. Building and Environment, 50: 125–134.

    Article  Google Scholar 

  • Zhang WT (2018). SPSS Statistical Analysis Higher Course. Beijing: Higher Education Press. (in Chinese)

    Google Scholar 

  • Zheng H, Li F, Cai H, et al. (2019). Non-intrusive measurement method for the window opening behavior. Energy and Buildings, 197: 171–176.

    Article  Google Scholar 

  • Zhou X, Liu T, Shi X, et al. (2018). Case study of window operating behavior patterns in an open-plan office in the summer. Energy and Buildings, 165: 15–24.

    Article  Google Scholar 

  • Zhou P, Wang H, Li F, et al. (2022). Development of window opening models for residential building in hot summer and cold winter climate zone of China. Energy and Built Environment, 3: 363–372.

    Article  Google Scholar 

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Acknowledgements

The work was supported by the Natural Science Basic Research Program of Shaanxi Province of China (2023-JC-YB-473), and the Opening Fund of State Key Laboratory of Green Building in Western China (LSKF202314). The authors would like to express their gratitude to MogoEdit (http://en.mogoedit.com/) for the professional linguistic services provided.

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Authors and Affiliations

  1. Department of Building Environment and Energy Engineering, School of Civil Engineering, Chang’an University, Xi’an, 710061, China

    Yaxiu Gu, Tingting Wang, Qingqing Dong, Zhuangzhuang Ma, Tong Cui & Minyan Xie

  2. State Key Laboratory of Green Building in Western China, Xi’an University of Architecture & Technology, Xi’an, 710055, China

    Yaxiu Gu

  3. Hunan Architectural Design Institute, Changsha, 410011, China

    Changgui Hu

  4. China United Engineering Corporation Limited, Hangzhou, 310052, China

    Kun Liu

  5. Beijing Key Laboratory of Green Built Environment and Energy Efficient Technology, Beijing University of Technology, Beijing, 100124, China

    Song Pan

  6. Shaanxi Environmental Investigation and Assessment Center, Xi’an, 710054, China

    Qian Qi

Authors
  1. Yaxiu Gu
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  2. Tingting Wang
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  3. Qingqing Dong
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  4. Zhuangzhuang Ma
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  5. Tong Cui
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  6. Changgui Hu
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  7. Kun Liu
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  8. Song Pan
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  9. Qian Qi
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  10. Minyan Xie
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Contributions

Conceptualization: Yaxiu Gu, Tong Cui; Methodology: Qingqing Dong, Tingting Wang; Formal analysis and investigation: Qingqing Dong, Tingting Wang, Changgui Hu, Song Pan; Writing—original draft preparation: Yaxiu Gu, Kun Liu; Writing—review and editing: Yaxiu Gu, Tong Cui; Funding acquisition: Yaxiu Gu; Resources: Qian Qi; Supervision: Tong Cui. Data curation: Zhuangzhuang Ma; Minyan Xie. All authors read and approved the final manuscript.

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Correspondence to Tong Cui.

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12273_2023_1047_MOESM1_ESM.pdf

Appendix: An improved window opening behavior model involving the division of the dummy variable’s interval level: Case study of an office building in Xi’an during summer

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Gu, Y., Wang, T., Dong, Q. et al. An improved window opening behavior model involving the division of the dummy variable’s interval level: Case study of an office building in Xi’an during summer. Build. Simul. 16, 2123–2144 (2023). https://doi.org/10.1007/s12273-023-1047-8

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  • DOI: https://doi.org/10.1007/s12273-023-1047-8

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