AHP Based Thermal Comfort Assessment through Passive Design Allocation in Tropical School Offices

Since global environmental issues are widely discussed nowadays, a number of studies are being carried out to resolve the challenges of reducing energy usage in buildings, especially related to energy use to sustain the indoor thermal comfort level. Among the methodologies used, Analytical Hierarchy Process (AHP) is commonly used to study the problems with multiple influencing factors which consist of different degree of implications. In this study, this model is used to investigate the effectiveness and consistency of respondents’ feedback onto the utility of passive design features in office buildings in order to sustain the indoor thermal comfort levels besides depending on artificial cooling equipment. A number of 122 academic staff from 5 units of primary schools within urban areas in Seremban District was involved in the study. All the schools were equipped with passive design elements, but different types of mechanical ventilation systems were installed in particular schools. Questionnaires with Likert scales were distributed to assist the respondents rank their subjective opinions with objective numerical values. The outputs of rankings generated through AHP by the respondents in different schools were studied, and their validities were further analyzed with ANOVA tests to justify the consistency of the findings. The results showed that there is not much significant difference among the evaluated batches, and thus, model is potential to be further developed into a more comprehensive evaluation tool to link with unidentified environmental and physical factors which generate important design data for future building designers.

References

[1] Peter S.P. Wong, Jason Zapantis, Driving carbon reduction strategies adoption in the Australian construction sector – The moderating role of organizational culture, Building and Environment. 66 (2013) 120-130.

DOI: https://doi.org/10.1016/j.buildenv.2013.04.022

[2] Aslihan Karatas, Khaled El-Rayes, Evaluating the performance of sustainable development in urban neighborhoods based on the feedback of multiple stakeholders, Sustainable Cities and Society, 14 (2015) 374-382.

DOI: https://doi.org/10.1016/j.scs.2014.05.011

[3] Carol C. Menassa, Brad Baer, A framework to assess the role of stakeholders in sustainable building retrofit decisions, Sustainable Cities and Society, 10 (2014) 207-221.

DOI: https://doi.org/10.1016/j.scs.2013.09.002

[4] Mojtaba Valinejad Shoubi, Masoud Valinejad Shoubi, Ashutosh Bagchi, Azin Shakiba Barough, Reducing the operational energy demand in buildings using building information modeling tools and sustainability approaches, Ain Shams Engineering Journal, 6 (2015).

DOI: https://doi.org/10.1016/j.asej.2014.09.006

[5] Adrian Pitts, Future proof construction – Future building and systems design for energy and fuel flexibility, Energy Policy, 36 (2008) 4539-4543.

DOI: https://doi.org/10.1016/j.enpol.2008.09.015

[6] Paul A. Mathew, Laurel N. Dunn, Michael D. Sohn, Andrea Mercado, Claudine Custudio, Travis Walter, Big-data for building energy performance: Lessons from assembling a very large national database of building energy use, Applied Energy, 140 (2015).

DOI: https://doi.org/10.1016/j.apenergy.2014.11.042

[7] Johnny K.W. Wong, Heng Li, Application of the analytic hierarchy process (AHP) in multi-criteria analysis of the selection of intelligent building systems, Building and Environment, 43 (2008) 108-125.

DOI: https://doi.org/10.1016/j.buildenv.2006.11.019

[8] E. Pikas, J. Kurnitski, R. Liias, M. Thalfeldt, Quantification of economic benefits of renovation of apartment buildings as a basis for cost optimal 2030 energy efficiency strategies, Energy and Buildings, 86 (2015) 151-160.

DOI: https://doi.org/10.1016/j.enbuild.2014.10.004

[9] Sarah V. Russell-Smith, Michael D. Lepech, Renate Fruchter, Yves B. Meyer, Sustainable target value design: integrating life cycle assessment and target value design to improve building energy and environmental performance, Journal of Cleaner Production, 88 (2015).

DOI: https://doi.org/10.1016/j.jclepro.2014.03.025

[10] Verbeeck G., Hens H, Life cycle inventory of buildings: A contribution analysis, Building and Environment, 45(2010) 964-967.

DOI: https://doi.org/10.1016/j.buildenv.2009.10.003

[11] Nor Ashikin Mohamed Yusof, Siti Hasliah Salleh, Analytical Hierarchy Process in Multiple Decisions Making for Higher Education in Malaysia, Procedia - Social and Behavioral Sciences, 81 (2013) 389-394.

DOI: https://doi.org/10.1016/j.sbspro.2013.06.448

[12] Thomas L. Saaty, Decision making with the analytic hierarchy process, Int. J. Services Sciences, 1(2008) 83-98.

[13] Qingyan Chen, Ventilation performance prediction for buildings: A method overview and recent applications, Building and Environment, 44 (2009) 848-858.

DOI: https://doi.org/10.1016/j.buildenv.2008.05.025