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Abstract

Urban regeneration projects in constrained town-centre sites present complex challenges where health and safety (H&S), buildability, cost, and programme must be balanced alongside planning and housing delivery objectives. This paper examines the regeneration of a former night club site in Northampton, UK, which has secured planning permission for a new three-storey residential development comprising 19 flats to address identified local housing needs. The study uses an exploratory case study approach based on planning documents, design review evidence, indicative cost/ programme comparison and H&S criteria. This aided the selection of the adopted structural solution—namely a steel frame with precast concrete floors and a reinforced concrete basement—over alternative structural form and construction method combinations. The paper presents an appraisal of site-specific hazards, including restricted access, proximity to existing buildings and public highways, ground conditions, and the need to minimise temporary works risks. These factors were evaluated alongside comparative assessments of alternative structural systems, such as reinforced concrete frames, load-bearing masonry, and hybrid solutions. The findings show that the chosen steel–precast–concrete basement solution offered clear H&S advantages, including reduced on-site labour, shorter working-at-height durations, improved construction sequencing, and enhanced predictability of temporary and permanent works behaviour. Cost and programme analyses are integrated to show how the selected structural form not only mitigated key safety risks but also achieved favourable outcomes in terms of construction duration, preliminaries, and whole-life value. The paper further explores the potential of emerging developments in AI – enabled decision support for H&S-led design decision-making, particularly in risk identification, option appraisal, and scenario analysis. Thus, future research directions are proposed to enhance AI-enabled frameworks for safer, more efficient regeneration projects within dense urban environments.

Keywords

Urban regeneration; health and safety; structural form selection; steel frame construction; precast concrete; AI-enabled decision support

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