Fully Funded PhD Studentship in Digital Characterisation of the Building Stock

This is project one of two

Bentley Systems is the leading global provider of software solutions to engineers, architects, geospatial professionals, constructors, and owner-operators for the design, construction, and operations of infrastructure. Bentley Institute advances the infrastructure professions by encouraging and supporting Bentley users’ ambitions in going digital. Its initiatives attract and advance infrastructure professionals, and future professionals, through continuous learning about technology solutions and support for research, as well as project delivery and asset performance best practices.

Context
A team at UCL-Energy has been developing a new kind of 3D model of the UK building stock. The model’s purpose is to assess energy use in buildings, and study the potential for energy and carbon mitigation measures. The techniques have been trialled successfully in London and several other cities. This ‘3DStock’ model is built by bringing together a number of publicly available datasets to produce a full spatial model which contains 3D representations of all domestic and non-domestic buildings with associated floor space, use type and other attributes. 3DStock has been used for statistical analysis of building energy use, assessment of renewable energy potentials and analysis of district energy systems. A version of 3DStock is being developed to create the London Building Stock Model (LBSM) for the Greater London Authority to be used in climate change mitigation planning in Greater London.

Data from 3DStock is passed to the SimStock modelling platform which automatically generates dynamic simulation models to predict the energy and environmental performance of the building stock and comparisons are made to actual energy meter data.

Further development of key aspects of these building stock models is planned in association with Bentley Systems, the leading global provider of software solutions for the design, construction, and operations of buildings and infrastructure. This project is one of two:

Digital Characterisation of the Building Stock
Digital models of the building stock require increasing levels of detail to generate more accurate representations and produce performance predictions with higher levels of validity and utility. This PhD will focus on the application of a variety of techniques to process visual, LiDAR and other data sources to derive detailed building and built environment characteristics, materials and components to improve the veracity of current models.

Person specification
Both topics require candidates with advanced computer skills. Experience in one or more of the following would be an advantage: image processing, machine learning, dynamic energy simulation, visualisation and statistics.

Candidates should have a Master’s degree and / or a first or upper-second class Bachelor’s degree.

How to apply
Please submit a pre-application by email to the UCL ERBE Centre Manager ([Email Address Removed]).

The application should include the following:
• A covering letter clearly stating which project you wish to apply for, your motivation, and your understanding of eligibility according to these guidelines: https://www.epsrc.ac.uk/skills/students/help/eligibility/
• CV
• Names and addresses of two academic referees
• A copy of your degree certificate(s) and transcript(s) of degree(s),

Pre-application deadline: 3rd June 12:00 noon (UK time)
Interview date: tbc

ERBE CDT
You will be undertaking this project in UCL at the main (Bloomsbury) campus as part of the new EPSRC-SFI Centre for Doctoral Training in Energy Resilience and the Built Environment (ERBE CDT). This is a collaboration between UCL, Loughborough University and Marine and Renewable Energy Ireland (MaREI). For more information please see http://erbecdt.ac.uk/#about.