Since the publication of UK government’s 2011 Construction Strategy document, there has been a flurry of activities in the construction sector around the adoption of various digitalisation approaches including BIM to enhance productivity and profitability. Seven years later several other initiatives have been started to push this agenda forward based on the successes (and indeed the challenges) of Level 2 BIM implementation in public sector projects since 2016. ICE’s 2017 State of the Nation report was entirely dedicated to Digital Transformation of the infrastructure sector. This has recently been followed up by the Data for the Public Good report by the National Infrastructure Commission (NIC). Centre for Digital Built Britain (CDBB) was set up to progress the digitalisation agenda beyond level 2 BIM and a number projects are afoot already in that regard.
The idea of Digital Twin has been mooted by the NIC and several others which is expected to enable the decision makers seek intelligent answers to various complex issues like whether a reduction in energy consumption per person can be achieved over a period of time or indeed assess the impact of closing a road in the event of an accident or natural disaster.
It is generally believed that secure sharing of infrastructure data will result in reduced impact on environment, lower costs to consumers of utilities and improved transport and enable development of smart cities among other things.
However, there are significant technical challenges to be overcome before such a vision can become a reality. For example, despite major advances in recent years, an accurate digital model of any facility is still not easily achievable. The ambitions of NIC and other public bodies will require developing retrofit models of existing assets with accuracy. Through the use of sensors and other technologies like 3D laser scanning it is now possible to capture some of the data needed to develop digital twins of assets. However, there are still a number of open research questions around the efficacy of these approaches. The captured data generally needs a lot of processing before it can be converted into useable virtual models.
This project will investigate the challenges surrounding the development of digital twins of existing facilities utilising cyber-physical systems (CPS) technologies. In particular, this project will follow on from another project on development of as-built models of buildings which utilised 3D laser scanning and Semantic web technologies to automate the process of converting the point cloud data into IFC compliant models for use in BIM tools. This project will extend the results of that project by developing simulation approaches utilising the models thus developed from the Point Cloud Data from the laser scan. The simulation approaches will implement two-way communication between the building and its virtual model by seamlessly utilising signals from heat and other sensors.
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.
Applicants cannot apply for this funding if currently engaged in Doctoral study at Northumbria or elsewhere.
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 note: Applications that do not include a research proposal of approximately 1,000 words (not a copy of the advert), or that do not include the advert reference (e.g. RDF19/EE/ABE/KUMAR) will not be considered.
Start Date: 1 October 2019
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