Journal Home > Volume 11 , Issue 2
Building Simulation 2018, 11(2): 389-403 https://doi.org/10.1007/s12273-017-0395-7
Research Article | Issue | Published: 23 August 2017

Building performance assessment of user behaviour as a post occupancy evaluation indicator: Case study on youth housing in Egypt

Show Author's Information Wael Seddik Moustafa1,  Mahmoud Mohamed Abdelrahman2,  Ibrahim Rizk Hegazy1( )
Department of Architecture, Faculty of Engineering, Mansoura University, Mansoura, Egypt
Department of Architecture, Faculty of Engineering, Kafr Elsheikh University, Kafr Elsheikh, Egypt
Keywords:
building performance, natural ventilation, CFD, daylighting, residential prototype, user behaviour, POE, post occupancy evaluation
Cite this article:
Moustafa WS, Abdelrahman MM, Hegazy IR. Building performance assessment of user behaviour as a post occupancy evaluation indicator: Case study on youth housing in Egypt. Building Simulation, 2018, 11(2): 389-403. https://doi.org/10.1007/s12273-017-0395-7
Download citation
EndNote(RIS)
BibTeX

509

Views

16

Downloads

Citations

2

Crossref

N/A

WoS

4

Scopus

0

CSCD

Abstract Full text About this article

Youth housing prototypes are widely spread all over Egypt as a cheap economic housing for youth which are designed in a number of different shapes. A post occupancy evaluation (POE) has been conducted to one of these prototypes to assess some modifications spontaneously done by users to the original design for the sake of enhancing building performance, e.g., creating new openings to improve lighting and natural ventilation thermal comfort, and making sunshades to control direct sunlight and thermal radiation. These assessments have been validated using simulation techniques i.e. CFD, thermal and daylight simulations, to compare natural ventilation, thermal comfort, and daylight energy efficiency in the original designs to that in the user modified. A wind tunnel test has been conducted to validate the standard k–epsilon turbulence CFD simulation in addition to daylighting in-situ measurements to validate natural lighting. The outcome of this research could be widely used as an important feedback tool in the future designs of the same prototype to evaluate user behaviour role in building performance efficiency. The research showed that some of these behaviours has improved thermal comfort by 60% to 87% from the original design while daylight efficiency has been improved by 31.8% to 41.4% while sensible cooling loads’ improvement ranges from 27.4% to 77.2% for the northern zone and 29.9% to 91.6% for the southern one, and thus, it could be used as a reliable POE feedback tool.


menu
Abstract
Full text
Outline
About this article

Building performance assessment of user behaviour as a post occupancy evaluation indicator: Case study on youth housing in Egypt

Show Author's information Wael Seddik Moustafa1, Mahmoud Mohamed Abdelrahman2, Ibrahim Rizk Hegazy1( )
Department of Architecture, Faculty of Engineering, Mansoura University, Mansoura, Egypt
Department of Architecture, Faculty of Engineering, Kafr Elsheikh University, Kafr Elsheikh, Egypt

Abstract

Youth housing prototypes are widely spread all over Egypt as a cheap economic housing for youth which are designed in a number of different shapes. A post occupancy evaluation (POE) has been conducted to one of these prototypes to assess some modifications spontaneously done by users to the original design for the sake of enhancing building performance, e.g., creating new openings to improve lighting and natural ventilation thermal comfort, and making sunshades to control direct sunlight and thermal radiation. These assessments have been validated using simulation techniques i.e. CFD, thermal and daylight simulations, to compare natural ventilation, thermal comfort, and daylight energy efficiency in the original designs to that in the user modified. A wind tunnel test has been conducted to validate the standard k–epsilon turbulence CFD simulation in addition to daylighting in-situ measurements to validate natural lighting. The outcome of this research could be widely used as an important feedback tool in the future designs of the same prototype to evaluate user behaviour role in building performance efficiency. The research showed that some of these behaviours has improved thermal comfort by 60% to 87% from the original design while daylight efficiency has been improved by 31.8% to 41.4% while sensible cooling loads’ improvement ranges from 27.4% to 77.2% for the northern zone and 29.9% to 91.6% for the southern one, and thus, it could be used as a reliable POE feedback tool.

Keywords: building performance, natural ventilation, CFD, daylighting, residential prototype, user behaviour, POE, post occupancy evaluation

References(48)

M Abdelrahman, O Farag, W Moustafa (2016). The role of CFD simulation software in improving residential buildings’ efficiency: Case study on youth housing in New Damietta. Journal of Al-Azhar University Engineering Sector, 13(4): 22–34.
Google Scholar
K-U Ahn, CS Park (2016). Different Occupant Modeling Approaches for Building Energy Prediction. Energy Procedia, 88: 721–724.
Google Scholar
ASHRAE (2004). Energy Standard for Buildings Except Low-Rise Residential Buildings. ANSI/ASHRAE Standard 90.1-2004. Atlanta, GA, USA: American Society of Heating, Refrigerating and Air- Conditioning Engineers.
ASHRAE (2009). ASHRAE Handbook: Fundamentals. Atlanta, GA, USA: American Society of Heating, Refrigerating and Air- Conditioning Engineers.
V Betta, F Cascetta, P Labruna, A Palombo (2004). A numerical approach for air velocity predictions in front of exhaust flanged slot openings. Building and Environment, 39: 9–18.
Google Scholar
JK Calautit, BR Hughes (2014). Wind tunnel and CFD study of the natural ventilation performance of a commercial multi-directional wind tower. Building and Environment, 80: 71–83.
Google Scholar
Q Chen (2009). Ventilation performance prediction for buildings: A method overview and recent applications. Building and Environment, 44: 848–858.
Google Scholar
Y Chen, X Luo, T Hong (2016). An agent-based occupancy simulator for building performance simulation. In: Proceedings of ASHRAE Annual Conference, St. Louis, MO, USA.
S D’Oca, T Hong, S Corgnati (2014). Occupant behavior of window opening and closing in office buildings: data mining approaches. In: Proceedings of the 2014 Behavior, Energy, and Climate Change Conference, Washington DC, USA.
S D’Oca, T Hong (2015). Occupancy schedules learning process through a data mining framework. Energy and Buildings, 88: 395–408.
Google Scholar
S D’Oca, S Corgnati, T Hong (2015). Data mining of occupant behavior in office buildings. Energy Procedia, 78: 585–590.
Google Scholar
X Feng, D Yan, T Hong (2015). Simulation of occupancy in buildings. Energy and Buildings, 87: 348–359.
Google Scholar
J Franke, A Hellsten, H Schlünzen, B Carissimo (2007). Best practice guideline for the CFD simulation of flows in the urban environment. Meteorological Institute, Centre for Marine and Atmospheric Sciences, University of Hamburg.
HS Gabr (2009). Post occupancy evaluation of buildings as a necessary tool in sustainable building performance. Available at http://faculty.ksu.edu.sa/hs/ArchCairo%202004%20Conference/HishamGabr%20paper.doc. Access 1 Mar 2016.
F Ghiaus C Allard (2005). Natural Ventilation in the Urban Environment: Assessment and Design. Abingdon, UK: Routledge.
Ö Göçer, Y Hua, K Göçer (2015). Completing the missing link in building design process: Enhancing post-occupancy evaluation method for effective feedback for building performance. Building and Environment, 89: 14–27.
Google Scholar
F Haldi, D Robinson (2011). The impact of occupants’ behaviour on building energy demand. Journal of Building Performance Simulation, 4: 323–338.
Google Scholar
T Hong, S D’Oca, W Turner, SC Taylor-Lange (2015). An ontology to represent energy-related occupant behavior in buildings. Part I: Introduction to the DNAs framework. Building and Environment, 92: 764–777.
Google Scholar
T Hong, H Sun, Y Chen, S Taylor-Lange, D Yan (2016). An occupant behavior modeling tool for co-simulation. Energy and Buildings, 117: 272–281.
Google Scholar
T Hong, D Yan, S D’Oca, C Chen (2017). Ten questions concerning occupant behavior in buildings: The big picture. Building and Environment, 114: 518–530.
Google Scholar
JCR Hunt, EC Poulton, JC Mumford (1976). The effects of wind on people; New criteria based on wind tunnel experiments. Building and Environment, 11: 15–28.
Google Scholar
WD Janssen, B Blocken, T van Hooff (2013). Pedestrian wind comfort around buildings: Comparison of wind comfort criteria based on whole-flow field data for a complex case study. Building and Environment, 59: 547–562.
Google Scholar
T Kubota, M Miura, Y Tominaga, A Mochida (2008). Wind tunnel tests on the relationship between building density and pedestrian- level wind velocity: Development of guidelines for realizing acceptable wind environment in residential neighborhoods. Building and Environment,43: 1699–1708.
Google Scholar
S Lee, I Bilionis, P Karava, A Tzempelikos (2017). A Bayesian approach for probabilistic classification and inference of occupant thermal preferences in office buildings. Building and Environment, 118: 323–343.
Google Scholar
X Liang, T Hong, GQ Shen (2016). Occupancy data analytics and prediction: A case study. Building and Environment, 102: 179–192.
Google Scholar
C Liao, Y Lin, P Barooah (2012). Agent-based and graphical modelling of building occupancy. Journal of Building Performance Simulation, 5: 5–25.
Google Scholar
X Luo, KP Lam, Y Chen, T Hong (2017). Performance evaluation of an agent-based occupancy simulation model. Building and Environment, 115: 42–53.
Google Scholar
AHA Mahmoud (2011). An analysis of bioclimatic zones and implications for design of outdoor built environments in Egypt. Building and Environment, 46: 605–620.
Google Scholar
AC Menezes, A Cripps, D Bouchlaghem, R Buswell (2012). Predicted vs. actual energy performance of non-domestic buildings: Using post-occupancy evaluation data to reduce the performance gap. Applied Energy, 97: 355–364.
Google Scholar
PA Mirzaei, F Haghighat (2010). Approaches to study urban heat island—abilities and limitations. Building and Environment, 45: 2192–2201.
Google Scholar
A Nabil, J Mardaljevic (2005). Useful daylight illuminance: A new paradigm for assessing daylight in buildings. Lighting Research & Technology, 37: 41–57.
Google Scholar
K Nassar, M Elnahas (2007). Occupant dynamics: Towards a new design performance measure. Architectural Science Review, 50: 100–105.
Google Scholar
CE Ochoa, MB Aries, JL Hensen (2012). State of the art in lighting simulation for building science: A literature review. Journal of Building Performance Simulation, 5: 209–233.
Google Scholar
W Parys, D Saelens, H Hens (2011). Coupling of dynamic building simulation with stochastic modelling of occupant behaviour in offices—A review-based integrated methodology. Journal of Building Performance Simulation, 4: 339–358.
Google Scholar
WFE Preiser, HZ Rabinowitz, ET White (2015). Post Occupancy Evaluation. Abingdon, UK: Routledge.
R Ramponi, B Blocken (2012). CFD simulation of cross-ventilation for a generic isolated building: impact of computational parameters. Building and Environment, 53: 34–48.
Google Scholar
CF Reinhart, DA Weissman (2012). The daylit area—Correlating architectural student assessments with current and emerging daylight availability metrics. Building and Environment, 50: 155–164.
Google Scholar
J Remund, SC Müller (2011). Solar radiation and uncertainty information of Meteonorm 7. In: Proceedings of 26th European Photovoltaic Solar Energy Conference and Exhibition, Hamburg, Germany.
M Santamouris (2001). Energy and Climate in the Urban Built Environment. Abingdon, UK: Routledge.
M Santamouris (2005). Energy in the urban built environment: The role of natural ventilation. In: C Ghiaus, F Allard (eds), Natural Ventilation in the Urban Environment: Assessment And Design. Abingdon, UK: Routledge.
F Stazi, F Naspi, M D’Orazio (2017). A literature review on driving factors and contextual events influencing occupants’ behaviours in buildings. Building and Environment, 118: 40–66.
Google Scholar
K Sun, T Hong (2017). A framework for quantifying the impact of occupant behavior on energy savings of energy conservation measures. Energy and Buildings, 146: 383–396.
Google Scholar
UN (2015). World Urbanization Prospects: The 2014 Revision. New York: United Nations Department of Economics and Social Affairs, Population Division.
T van Hooff, B Blocken (2010). Coupled urban wind flow and indoor natural ventilation modelling on a high-resolution grid: A case study for the Amsterdam ArenA stadium. Environmental Modelling & Software, 25: 51–65.
Google Scholar
T van Hooff, B Blocken (2013). CFD evaluation of natural ventilation of indoor environments by the concentration decay method: CO2 gas dispersion from a semi-enclosed stadium. Building and Environment, 61: 1–17.
Google Scholar
C Wang, D Yan, Y Jiang (2011). A novel approach for building occupancy simulation. Building Simulation, 4: 149–167.
Google Scholar
GJ Ward (1994). The RADIANCE lighting simulation and rendering system. In: Proceedings of the 21st Annual Conference on Computer Graphics and Interactive Techniques, Orlando, FL, USA.
R Yao, Q Luo, B Li (2011). A simplified mathematical model for urban microclimate simulation. Building and Environment, 46: 253–265.
Google Scholar
Publication history
Copyright

Publication history

Received: 15 March 2017
Revised: 27 June 2017
Accepted: 29 June 2017
Published: 23 August 2017
Issue date: April 2018

Copyright

© Tsinghua University Press and Springer-Verlag GmbH Germany 2017
Return