EDP Sciences logo
Web of Conferences logo
Search
Menu
All issues Volume 396 (2023) E3S Web of Conf., 396 (2023) 01050 References
Open Access
Issue
E3S Web of Conf.
Volume 396, 2023
The 11th International Conference on Indoor Air Quality, Ventilation & Energy Conservation in Buildings (IAQVEC2023)
Article Number 01050
Number of page(s) 8
Section Indoor Environmental Quality (IEQ), Human Health, Comfort and Productivity
DOI https://doi.org/10.1051/e3sconf/202339601050
Published online 16 June 2023
  1. Yang, J., Fu, H., & Qin, M. (2015). Evaluation of different thermal models in EnergyPlus for calculating moisture effects on building energy consumption in different climate conditions. Procedia Engineering, 121, 1635-1641. [CrossRef] [Google Scholar]
  2. Qin, M., & Yang, J. (2016, February). Evaluation of different thermal models in EnergyPlus for calculating moisture effects on building energy consumption in different climate conditions. In Building Simulation (Vol. 9, No. 1, pp. 15-25). Springer Berlin Heidelberg. [CrossRef] [Google Scholar]
  3. Lam, K. P., Zhao, J., Ydstie, E. B., Wirick, J., Qi, M., & Park, J. H. (2014). An EnergyPlus whole building energy model calibration method for office buildings using occupant behavior data mining and empirical data. ASHRAE Journal, 160-167. [Google Scholar]
  4. Chenari, B., Lamas, F. B., Gaspar, A. R., & da Silva, M. G. (2017). Simulation of occupancy and CO2-based demand-controlled mechanical ventilation strategies in an office room using EnergyPlus. Energy Procedia, 113, 51-57. [CrossRef] [Google Scholar]
  5. Esteves, D., Silva, J., Rodrigues, N., Martins, L., Teixeira, J., & Teixeira, S. (2019, July). Simulation of PMV and PPD thermal comfort using energyplus. In International Conference on Computational Science and Its Applications (pp. 52-65). Springer, Cham. [Google Scholar]
  6. Buratti, C., Moretti, E., Belloni, E., & Cotana, F. (2013). Unsteady simulation of energy performance and thermal comfort in non-residential buildings. Building and Environment, 59, 482-491. [CrossRef] [Google Scholar]
  7. Hong, S. H., Lee, J. M., Moon, J. W., & Lee, K. H. (2018). Thermal comfort, energy and cost impacts of PMV control considering individual metabolic rate variations in residential building. Energies, 11(7), 1767. [CrossRef] [Google Scholar]
  8. Zhao, J., Lam, K. P., Ydstie, B. E., & Loftness, V. (2016). Occupant-oriented mixed-mode EnergyPlus predictive control simulation. Energy and Buildings, 117, 362-371. [CrossRef] [Google Scholar]
  9. Lee, S., Bilionis, I., Karava, P., & Tzempelikos, A. (2017). A Bayesian approach for probabilistic classification and inference of occupant thermal preferences in office buildings. Building and Environment, 118, 323-343. [CrossRef] [Google Scholar]
  10. Lee, S., Karava, P., Tzempelikos, A., & Bilionis, I. (2019). Inference of thermal preference profiles for personalized thermal environments with actual building occupants. Building and Environment, 148, 714-729. [CrossRef] [Google Scholar]
  11. Wang, Z., de Dear, R., Luo, M., Lin, B., He, Y., Ghahramani, A., & Zhu, Y. (2018). Individual difference in thermal comfort: A literature review. Building and Environment, 138, 181-193. [CrossRef] [Google Scholar]
  12. Jung, W., & Jazizadeh, F. (2019). Comparative assessment of HVAC control strategies using personal thermal comfort and sensitivity models. Building and Environment, 158, 104-119. [CrossRef] [Google Scholar]
  13. Zhang, H., & Tzempelikos, A. (2021). Thermal preference-based control studies: review and detailed classification. Science and Technology for the Built Environment, 27(8), 1031-1039. [CrossRef] [Google Scholar]
  14. Ličina, V. F., Cheung, T., Zhang, H., De Dear, R., Parkinson, T., Arens, E., ... & Zhou, X. (2018). Development of the ASHRAE global thermal comfort database II. Building and Environment, 142, 502-512. [CrossRef] [Google Scholar]
  15. Fard, Z. Q., Zomorodian, Z. S., & Korsavi, S. S. (2021). Application of machine learning in thermal comfort studies: A review of methods, performance and challenges. Energy and Buildings, 111771. [Google Scholar]
  16. Chen, C. F., De Simone, M., Yilmaz, S., Xu, X., Wang, Z., Hong, T., & Pan, Y. (2021). Intersecting heuristic adaptive strategies, building design and energy saving intentions when facing discomfort environment: A cross-country analysis. Building and Environment, 204, 108129. [CrossRef] [Google Scholar]
  17. Langevin, J., Gurian, P. L., & Wen, J. (2015). Tracking the human-building interaction: A longitudinal field study of occupant behavior in air-conditioned offices. Journal of Environmental Psychology, 42, 94-115. [CrossRef] [Google Scholar]
  18. Langevin, J. (2019). Longitudinal dataset of human-building interactions in US offices. Scientific data, 6(1), 1-10. [CrossRef] [PubMed] [Google Scholar]
  19. ASHRAE Standard 55. Thermal environmental conditions for human occupancy. ASHRAE Inc., Atlanta, GA. [Google Scholar]

Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.

Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.

Initial download of the metrics may take a while.