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Developing an Artificial Neural Network Model for Life Cycle Carbon Estimating in Office Buildings (Advert Ref: EE16/ARCH/FERNANDO)


   Faculty of Engineering and Environment

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  Dr N Fernando  No more applications being accepted  Funded PhD Project (Students Worldwide)

About the Project

The building sector globally accounts for a large share of carbon emission (RICS,2012). Further, carbon emission of buildings during life cycle can be broadly divided in to three main stages (Peng, 2016).

• Construction stage (including processes such as the procurement of raw materials, building material production, transportation, and construction),
• Operational stage
• Demolition stage (including processes such as building demolition and waste material recycling and processing)

Operational carbon emissions accounts for approximately 85% of total emissions (Peng, 2016). Therefore, it is vital to consider operational carbon emissions during early stage design as it accounts most for most of carbon emission during life cycle of buildings. Regulatory move towards zero carbon buildings by 2019, which will make zero operational carbon, encourages a shift towards embodied carbon (Ashworth & Perera, 2015). Therefore, it is essential to design future building with zero operational carbon emissions. However, it is believed that the carbon emission reduction potential is high in the early stages of a project (RICS, 2012) driving the need of a rigorous early stage life cycle carbon estimating. While effort is made to estimate life cycle carbon emission in detailed design stages, there are limited approaches in estimating life cycle carbon emission during early stages of the design. Therefore, this research attempts to fill this knowledge gap by developing a ANN model to predict life cycle carbon at early stages of design.

This research is to develop an Artificial Neural Network (ANN) model for life cycle carbon estimating based on design parameters and occupancy density. This model will aid designers to optimise carbon efficiency with zero operational carbon designs from a very early stage of the design.

The research project will contribute to knowledge by capturing carbon intensive activities in life cycle of the buildings, and developing a computer aided model which will predict optimum life cycle carbon based early stage designs of buildings.

Eligibility and How to Apply:
Please note eligibility requirement:
- Academic excellence of the proposed student i.e. 2:1 (or equivalent GPA from non-UK universities [preference for 1st class honours]); or a Masters (preference for Merit or above); or APEL evidence of substantial practitioner achievement.
- Appropriate IELTS score, if required

For further details of how to apply, entry requirements and the application form, see
https://www.northumbria.ac.uk/research/postgraduate-research-degrees/how-to-apply/

Please ensure you quote the advert reference above on your application form.

Deadline for applications: 22 July 2016

Start date: 03 October 2016

Northumbria University is an equal opportunities provider and in welcoming applications for studentships from all sectors of the community we strongly encourage applications from women and under-represented groups.

Funding Notes

The studentship includes a full stipend, paid for three years at RCUK rates (in 2016/17 this is £14,296 pa) and fees (Home/EU £4,350 / International £13,000).

References

1. Wong I. L., Perera R. S., and Eames P. C., (2010), “Goal directed life cycle costing as a method to evaluate the economic feasibility of office buildings with conventional and TI-façades”, Journal of Construction Management and Economics, ISSN 0144-6193 print/ISSN 1466-433X online © 2010 Taylor & Francis http://www.informaworld.com DOI: 10.1080/01446191003753867.

2. Rahman S., Odeyinka, H., Perera S. and Bi Y., (2012) “Product-cost modelling approach for the development of a decision support system for optimal roofing material selection”, Expert Systems with Applications, 39 (8). pp. 6857-6871. ISSN 0957-4174, ELSEVIER, doi:10.1016/j.eswa.2012.01.010, http://dx.doi.org/10.1016/j.eswa.2012.01.010.

3. Victoria, M, Perera, S and Davies, A (2015) Developing an early design stage embodied carbon prediction model: A case study In: Raidén, A B and Aboagye-Nimo, E (Eds) Procs 31st Annual ARCOM Conference, 7-9 September 2015, Lincoln, UK, Association of Researchers in Construction Management, 267-276.

4. Ekundayo, D., Perera, S., Udeaja, C. and Zhou, L. (2011), “Achieving economic and environmental sustainability through optimum balance of costs”, Proceedings of the 10th International Postgraduate Research Conference in the Built Environment (IPGRC), University of Salford, UK, 14-15 September 2011, pp 673-684, ISBN: 978-1-907842-17-7.

5. Victoria, M. F., Perera, S., Zhou, L., & Davies, A. (2015, October). Estimating Embodied Carbon: A dual currency approach. In Sustainable Buildings and Structures: Proceedings of the 1st International Conference on Sustainable Buildings and Structures, 29 October-1 November 2015, Suzhou, PR China, CRC Press, 223-230.

6. Ashworth, A and Perera, S (2015), Cost Studies of Buildings, 6th Edition, chap 24, Routledge, in print http://www.routledge.com/books/details/9781138017351/.

7. Dissanayake D.M.S.M., Fernando N.G., Jayasinghe S.J.A.R.S. and Rathnaweera P.H.S.B.(2015), Preliminary project cost estimation model using artificial neural networks for public sector office buildings in Sri lanka. Proceeding of the 8th FARU International Research Conference, 11th & 12th December 2015, Colombo. Sri Lanka