Life Cycle Energy Saving Strategies and Evaluation Framework for Pre-1919 Constructions Kingston University in United Kingdom

Buildings are responsible for a significant portion of energy consumption and carbon emissions in the UK, with pre-1919 constructions presenting unique challenges for energy efficiency retrofitting. These older buildings often feature solid walls, single-glazed windows, and lack modern insulation and ventilation systems, making conventional energy-saving measures difficult to implement without compromising their structural and historical integrity.

This PhD project at Kingston University, within the Faculty of Engineering, Computing and the Environment, aims to develop a scientifically grounded retrofitting strategy specifically tailored for pre-1919 buildings. The research will analyze existing building databases and conduct physical simulations to identify typical features and retrofitting challenges. Life Cycle Assessment (LCA) will be performed for various retrofitting measures to evaluate both operational and life cycle energy performance.

A key outcome will be the development of a comprehensive evaluation framework that scores retrofitting options based on quantifiable criteria, including operational energy consumption, life cycle energy consumption, and impacts on the building's structural integrity and surrounding community. The project will also integrate machine learning techniques to automate the optimization of retrofitting designs and enhance predictive accuracy.

By utilizing this framework, practitioners will be able to design retrofitting solutions that minimize operational energy, reduce life cycle carbon emissions, and preserve the historical and structural integrity of pre-1919 buildings. The research outcomes are expected to improve the scientific rigor, predictability, and efficiency of energy-saving retrofitting practices, contributing to the decarbonization of the UK’s building stock.

Funding for this position is available through the Graduate School studentships competition for October 2026 entry, potentially covering tuition and stipend. Applicants should have a strong background in civil engineering, architecture, environmental science, or a related discipline, with skills or interest in building simulation, LCA, or machine learning. The application deadline is March 4, 2026.

For application details, visit the Kingston University PhD Studentships page and the Faculty of Engineering, Computing and the Environment research webpage. This opportunity is ideal for candidates passionate about sustainable building practices, energy technologies, and heritage conservation.