PhD project

Binks Institute for Sustainability: Use of Data Science for Reliable Metrics to Benchmark Environmental Impact and Decarbonisation of Transport Infrastructure Projects

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Application deadline

30 April 2024

Context

In 2017, the UK government launched its modern Industrial Strategy, followed by the announcement of the Construction Sector Deal in 2018. The Government’s Transforming Infrastructure Performance (TIP) programme and Transport Infrastructure Efficiency (TIES) programmes, referenced in the Sector Deal were tasked with benchmarking research and development as a key tool to drive increased productivity in construction projects, reduce the cost of construction and whole-life cost of built assets, reduce carbon impacts and enable faster delivery and greater certainty of construction projects, in light of recognising that encouraging the adoption of digital manufacturing approaches and active energy technologies within construction projects is central to delivering these outcomes. Since then, the University of Dundee has undertaken two projects funded by TCN+ and Innovate UK (TIES Living Lab) to examine metrics and benchmarks for construction projects however, it was clear that several challenges had to be addressed regarding the approach to the large data sets existing within industry, to fully develop appropriate reliable metrics that could be used to then benchmark improvement within the transport infrastructure section.  One such area is the decarbonisation of the transport infrastructure sector of which £600bn of work is expected over the next 5-10 years. The role of data, metrics, benchmarking and the use of digital twins to optimise will help the development of a more carbon and cost efficient transport infrastructure however the road map to this remains unclear. A newly funded KTP project (KTP13627) at Dundee working with Project EU Ltd is examining the underpinning computing science behind metrics however a deep dive into data mining and data science is required to provide a broader understanding.

Aims and Objectives

The overall aim of the project is to develop an approach to allow rapid reliable analysis of existing large data sets within complex construction projects to identify metrics which can be used to inform future design processes and whole life carbon policies.  

 The main objectives will include: 

Develop and utilising suitable data mining tools (including AI) to sort and analyse existing data sets for carbon, cost and time for ongoing or completed complex construction projects.

Determine the suitability of mined data and develop a set of consistent whole life metrics (focussing on carbon but with cost/schedule in mind).

Apply the developed metrics and benchmarks to a set of digital demonstrator projects (digital twin project) to determine the efficacy of the metrics to enhance the decarbonation of transportation infrastructure projects. 

The project will require significant interface with the national and devolved governments regarding transportation policy, as well as the public and private sector industry who are involved in construction of infrastructure projects (e.g. Network Rail, Transport Scotland). In addition the project will require interface with existing standardisation bodies (such as British Standards, CEN and ISO), policy makers such as the UK Government and devolved nations as well as computer and data science expertise (involving data mining/AI).

Impact

The project has potential to make significant impact to the way complex construction projects are delivered. This can have significant impact on carbon reduction (decarbonisation) over the whole life of project (just transition to net zero) as well as cost savings through more efficient use of materials. There is potential impact on policy development in how projects are delivered which can also have knock on impact on social justice. 

Diversity statement

Our research community thrives on the diversity of students and staff which helps to make the University of Dundee a UK university of choice for postgraduate research. We welcome applications from all talented individuals and are committed to widening access to those who have the ability and potential to benefit from higher education.

How to apply

  1. Email Dr Moray Newlands to
    • Send a copy of your CV
    • Discuss your potential application and any practicalities (e.g. suitable start date).
  2. After discussion with Dr Newlands, formal applications can be made via our direct application system.
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Supervisors

Principal supervisor

Second supervisor

Person

Senior Lecturer, Head of Computing (Discipline)

m.z.crabb@dundee.ac.uk +44 (0)1382 385491