About the project or challenge area

Buildings and construction are responsible for approximately 40% of all greenhouse gas emissions with operational-related CO2 emissions accounting for approximately 30% of total anthropogenic emissions. Current advances in the field of insulation materials, smart monitoring and renewable energy will shift the environmental burden in the construction sector towards the embodied carbon of the materials. Current practices in Life Cycle Assessments rely mostly on the embodied carbon lacking crucial data on the operational energy use. LCA analyses require detailed calculations of material volumes and building energy consumption and performance, and are tailored to specific designs.

Moreover, the interrelationships between material optioneering and building energy consumption are not clearly defined. For example, material substitution with timber can greatly reduce the embodied carbon of the building but there is a risk of summer overheating due to the lower thermal mass of wood. This project will develop a real-time decision-support tool that can reliably inform practitioners about the whole life carbon of buildings at the early stages of concept design. The tool will rely on developing a surrogate model based on current advances in machine learning and available datasets. Of key importance is the review of different Machine learning algorithms and different LCA databases to provide reliable predictions.

This project has been designed in collaboration with Hoare Lea. Students will work with operational data and have access to expertise from the Hoare Lea team, with the primary contact being Sam Wilkinson, Senior Associate.

Why choose this Project?

• Work closely with an industrial partner and academic experts in relevant fields
• Develop a thorough understanding in machine learning and LCA analysis
• Develop a systems thinking approach
• Produce high quality work and publish and present in international conferences

About you

Ideally applicants will have either engineering or computer sciences background. However, we welcome applicants with other qualifications who can demonstrate enthusiasm about climate change and sustainability and have experience with computer programming.

How to apply

All students can apply using the button below, following the Admissions Statement Admissions Statement (PDF, 220kB). Please note that this is an advertised project, which means you only have to complete Section A of the Research Statement.

Before applying, we recommend getting in touch with the project's supervisors. If you are interested in this project and would like to learn more about the research you will be undertaking, please use the contact details on this page.