Adaptive Smart Retrofitting for Historical Buildings: Innovative Integration of Sustainable Wall Technologies with Energy AI-based feedback system

Summary

Historical buildings are the essence of a community, embodying visual, cultural, and social elements that shape a unique identity and sense of place. They bridge the past and present, contributing to the environmental and cultural richness of a community. Preserving built heritage aligns with sustainability goals and addresses climate change impacts, yet challenges arise in retrofitting these structures due to their vulnerability to climate change and complex technical considerations.

Retrofitting historical buildings presents multifaceted challenges. Misguided efforts risk compromising heritage values, creating cultural disconnection. Technical challenges arise from unique construction, with traditional materials posing compatibility issues. Moisture management and the ‘rebound effect’ add complexity, exacerbated by a limited understanding of traditional wall structures.

The application of Artificial Intelligence in heritage building retrofit is an emerging research field in response to these unique challenges. This research aims to develop sensor-equipped wall technologies supported by an integrated adaptive AI-based feedback system. This dynamic approach fosters tailoring solutions that take into consideration the unique constructional characteristics of heritage buildings, optimising energy consumption and occupant thermal comfort and well-being while preserving the building fabric and the intrinsic values embedded in building heritage.

The project extends beyond theory, involving laboratory practical development and testing of wall systems performance compatible with heritage techniques. The integrated AI-based feedback system is a focal point, employing machine learning and sensor fusion to process diverse data. The goal is to design a system that dynamically responds to data inputs, allowing real-time adjustments for optimised energy consumption and thermal comfort. The potential evaluation under real environmental conditions serves as a real-case application, demonstrating the feasibility of the proposed AI-enhanced retrofit strategies. In this way, the project seeks to harmonise heritage preservation with sustainability goals, creating a resilient and eco-friendly future for historical buildings and their communities.

Essential criteria

Applicants should hold, or expect to obtain, a First or Upper Second Class Honours Degree in a subject relevant to the proposed area of study.

We may also consider applications from those who hold equivalent qualifications, for example, a Lower Second Class Honours Degree plus a Master’s Degree with Distinction.

In exceptional circumstances, the University may consider a portfolio of evidence from applicants who have appropriate professional experience which is equivalent to the learning outcomes of an Honours degree in lieu of academic qualifications.

• Research proposal of 2000 words detailing aims, objectives, milestones and methodology of the project

Equal Opportunities

The University is an equal opportunities employer and welcomes applicants from all sections of the community, particularly from those with disabilities.

Appointment will be made on merit.

Funding and eligibility

This project is funded by:

• Department for the Economy (DfE)
• Vice Chancellor's Research Scholarship (VCRS)

Our fully funded PhD scholarships will cover tuition fees and provide a maintenance allowance of £19,237 (tbc) per annum for three years (subject to satisfactory academic performance).  A Research Training Support Grant (RTSG) of £900 per annum is also available.

These scholarships, funded via the Department for the Economy (DfE) and the Vice Chancellor’s Research Scholarships (VCRS), are open to applicants worldwide, regardless of residency or domicile.

Applicants who already hold a doctoral degree or who have been registered on a programme of research leading to the award of a doctoral degree on a full-time basis for more than one year (or part-time equivalent) are NOT eligible to apply for an award.

Due consideration should be given to financing your studies.