Abstracts – Browse Results
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Abu Awwad, K (2020) The implementation of building information modelling Level 2 in the UK construction industry: the case of small and medium enterprises, Unpublished PhD Thesis, School of Energy, Construction and Environment, Coventry University.
Al-Saeed, Y W M (2018) Towards developing a sustainability assessment framework for residential buildings in Iraq, Unpublished PhD Thesis, , Coventry University.
Al-Werikat, G K E (2017) The impact of supply chain management on construction projects performance in Jordan, Unpublished PhD Thesis, School of Energy, Construction and Environment, Coventry University.
AlAbbadi, G (2020) Development of a framework towards enhancing workers productivity in the Jordanian construction industry, Unpublished PhD Thesis, , Coventry University.
Alhajeri, M (2011) Health and safety in the construction industry: challenges and solutions in the UAE, Unpublished PhD Thesis, Department of the Built Environment, Coventry University.
Banwo, O (2016) The development of a procurement decision support system to enhance construction claims management practice, Unpublished PhD Thesis, School of Energy, Construction and Environment, Coventry University.
Banwo, O O (2022) Development of a framework for building cost information management in Nigeria, Unpublished PhD Thesis, , Coventry University.
Briscoe, G (2008) Studies of the UK labour market with special reference to the construction sector, Unpublished PhD Thesis, Department of the Built Environment, Coventry University.
Charef, R (2019) A BIM-based framework to integrate a sustainable end-of-life into the asset lifecycle: towards the circular economy, Unpublished PhD Thesis, , Coventry University.
Dike, I (2017) A critical exploration of the impact of building information modelling on the culture and performance of UK construction supply chains, Unpublished PhD Thesis, , Coventry University.
Gherbal, N E M (2015) The influence and evaluation of the project manager's performance in the Libyan construction industry, Unpublished PhD Thesis, School of Engineering and Computing, Coventry University.
Ghostin, M (2020) Exploring an implementation framework for building information modelling to support sustainable development in the Lebanese construction industry: a qualitative approach, Unpublished PhD Thesis, , Coventry University.
Hendy, A O A (2007) An approach to sustainable construction in post-disaster contexts: with specific reference to the Marmara region of Turkey, Unpublished PhD Thesis, Department of the Built Environment, Coventry University.
Hermawan, F (2015) A strategic approach to enhancing sustainable practices in public building projects: a case study of Indonesian local authorities, Unpublished PhD Thesis, School of Energy, Construction and Environment, Coventry University.
Karami, S (2008) Using by-product industrial materials to replace all cement in construction products, Unpublished PhD Thesis, Department of Built Environment, Coventry University.
Lashford, C (2016) Modelling the role of SuDS management trains to minimise the flood risk of new-build housing developments in the UK, Unpublished PhD Thesis, School of Energy, Construction and Environment, Coventry University.
- Type: Thesis
- Keywords: accuracy; climate; decision support; drainage; efficiency; mining; pavement; regression analysis; UK; water
- ISBN/ISSN:
- URL: http://curve.coventry.ac.uk/open/items/474dda63-e82a-4c40-9833-b1891f351fac/1
- Abstract:
In a changing climate with an increasing risk of flooding, developing a sustainable approach to flood management is paramount. Sustainable Drainage Systems (SuDS) present a change in thinking with regards to drainage; storing water in the urban environment as opposed to rapidly removing it to outflows. The Non-Statutory Standards for SuDS (DEFRA 2015a) presented a requirement for all developments to integrate SuDS in their design to reduce runoff. This research models the impact on water quantity of combining different SuDS devices to demonstrate their success as a flood management system, as compared to conventional pipe based drainage. The research uses MicroDrainage®, the UK industry standard flood modelling tool which has an integrated SuDS function, to simulate the role of SuDS in a management train. As space is often cited as the primary reason for rejecting SuDS, determining the most effective technique at reducing runoff is critical. Detention basins were concluded as being highly effective at reducing peak flow (150 l/s when combined with swales), however Porous Pavement Systems (PPS) was nearly twice as effective per m3, reducing peak flow by up to 0.075 l/s/m3 compared to 0.025 l/s/m3. This therefore suggests that both detention basins and PPS should be high priority devices when developing new sites, but that no matter what combination of modelled SuDS are installed a reduction in runoff in comparison to conventional drainage can be achieved. A SuDS decision support tool was developed to assist design in MicroDrainage® by reducing the time spent determining the number of SuDS required for a site. The tool uses outputs from MicroDrainage® to rapidly predict the minimum and maximum peak flow for a site, in comparison to greenfield runoff, based on the site parameters of area, rainfall rate, infiltration, combined with the planned SuDS. The tool was underpinned by a model analysis for each site parameter and each SuDS device, which produced r2 values >0.8, with 70% above 0.9. This ensured a high level of confidence in the outputs, enabling a regression analysis between runoff and each site parameter and SuDS device at the 99% confidence level, with the outputs combined to create the tool. The final aspect of the research validated MicroDrainage® to analyse the accuracy of the software at predicting runoff. Using field data from Hamilton, Leicester, and laboratory data for PPS and filter drains, a comparison could be made with the output from MicroDrainage®. The field data created a Nash-Sutcliffe Efficiency (NSE) of 0.88, with filter drains and PPS providing an NSE of 0.98 and 0.94 respectively. This demonstrates the success with which MicroDrainage® predicts runoff and provides credibility to the outputs of the research. Furthermore, it offers SuDS specialists the confidence to use MicroDrainage® to predict runoff when using SuDS.
Li, P (2017) The international competitiveness of Chinese construction firms, Unpublished PhD Thesis, Royal Agricultural University, Coventry University.
Noruwa, B I (2020) Application and effects of emerging technologies on variation minimisation in the UK construction projects, Unpublished PhD Thesis, , Coventry University.
Nosheen, A (2022) Development of an effective claim management framework for the UK construction industry, Unpublished PhD Thesis, , Coventry University.
Swai, L (2022) Development of a conceptual framework for enhancing payment practices in the UK construction industry, Unpublished PhD Thesis, , Coventry University.
Tabatabaei Sameni, S (2019) Overheating investigation in UK social housing flats built to the Passivhaus standard, Unpublished PhD Thesis, School of Art and Design, Coventry University.