Imposed floor loads directly influence the embodied carbon of new building structures, and often determine the reuse potential of existing ones, with important sustainability impacts. Despite this, engineering design codes and practices predominantly adopt loads based on historical precedents, rather than empirical evidence or statistical analysis. Existing physical survey data for office loadings is scarce, outdated, and fails to capture extreme scenarios. This paper introduces a novel stochastic methodology based on realistic modern office layouts (from 29 industry fit-out drawings), probabilistic models of furniture and partition weights (derived from approximately 500 individual product specifications) and occupancy scenarios (informed by surveys and interviews). The resulting dataset contains over 55 million load samples, capturing spatial, temporal and specification variations across variety of office uses. A mean loading of 0.35–0.38 kN/m 2 was determined, with increasing variance over smaller areas. Annual maximum loads were analysed, revealing that extreme loads are influenced by tall, heavily loaded items of storage furniture, particularly at smaller sampled areas, with high occupancy events increasingly important over larger areas. A standard minimum UK office imposed load of 2.5 kN/m 2 was found to have a return period of 11 years for serviceability, or 397 years if factored for ultimate limit state design; however these return periods increase significantly if the maximum storage furniture pressure is limited. Partitions added a mean load of 0.25–0.26 kN/m 2 , increasing to approximately 0.5 kN/m 2 for extreme loads with a 50-year return period, with little influence from area size. There is potential for this new approach to be applied to new building uses and across multiple storeys, with the study also revealing the need for additional extreme loading data regarding storage furniture and high occupancy events. The novel stochastic framework, and the resulting outputs, enable informed serviceability loading decision-making based on return-periods and show how offices can be designed and managed to minimise extreme loads. Moreover, they allow realistic load specification in buildings, guidance documents and design codes, avoiding over-design and unnecessary demolition and consumption of emissions-intensive structural materials.
Hawkins et al. (Thu,) studied this question.