Applications of Artificial Intelligence (AI) in Fire Safety Design

Summary

Accidental fires continue to pose significant threats to public safety and building resilience and have far-reaching consequences—physical, psychological, economic, social, and environmental.

In response to the tragical Grenfell Tower fire in June 2017, the UK Government enacted the Building Safety Act 2022, establishing the Building Safety Regulator (BSR) and introducing stringent safety checks for higher-risk buildings throughout their lifecycle.

Despite these efforts, there are still significant challenges to providing overall fire safety in buildings, especially in the early stages of building design and the incorporation of effective evacuation strategies.

Current regulations often fail to address emerging risks associated with innovative materials, advanced systems, and modern construction technologies.

Large full-scale compartment fire tests, while providing the best insight into fire development, are extremely expensive and often take months if not years to conduct.

Instead, computational fluid dynamics (CFD) models, are used to aid fire safety design, but they are often computationally intensive and time-consuming, hindering reliable fire safety assessments.

Artificial intelligence (AI) models offer innovative solutions to these challenges in fire safety design, as they can rapidly analyse complex systems, identify patterns, and predict fire behaviour with high accuracy, enhancing decision-making and resource allocation.

The integrate physical laws directly into AI models, enabling precise simulations of fire dynamics, heat transfer, fire toxicity and structural responses without relying on computationally expensive numerical methods.

Recent advancements in the application of AI in fire safety has shown its significant potential in improving decision-making, optimizing building designs, and enhancing operational safety.

This research project aims to address the critical knowledge gaps in fire safety design by integrating AI with advanced fire dynamics simulations and seeks to advance fire dynamics predictions, streamline fire safety analysis, and uncover new insights through real-world fire data analysis.

Historical fire incident reports and regulatory documents will be collected to understand the fundamental fire dynamics, fire toxicity and structural responses, base on which AI models will be developed and trained.

The developed model will be then used to simulate real fire scenarios in diverse environments, such as room fires, and large-scale building fires (e.g., multi-story buildings) in both controlled and real-world settings and validated against known benchmarks, such as experimental data, historical fire events, and simulation results using traditional CFD models.

The supervisors have all necessary and complementary expertise and have published widely in international journals and conferences in the areas of fire dynamics, material flammability, fire toxicity, structure response under fire conditions, numerical heat transfer, applications of AI in fires, as well as computer modelling of fire related phenomena.

The supervisors also collaborate widely with universities, research institutions and industry, both nationally and internationally.

The research will involve a wide range of disciplines including engineering, chemistry, mathematics, and computer engineering. The diversity of this research theme means that the student will potentially cross these disciplines

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)

Our fully funded PhD scholarships will cover tuition fees and provide a maintenance allowance of £21,000 (approximately) 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), 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.

*Part time PhD scholarships may be available to home candidates, based on 0.5 of the full time rate, and will require a six year registration period.

Due consideration should be given to financing your studies.