Wind load evaluation of modular housing structures for Canadian Indigenous regions

Abstract

Indigenous communities across Canada face a persistent housing crisis characterized by housing shortages, overcrowding, dwellings requiring major repairs, and housing costs that exceed 30% of household income. These challenges are exacerbated in remote and northern regions, where communities experience pronounced climate change impacts, including stronger wind events, colder temperatures, and increased environmental uncertainty. Geographic isolation, limited access to construction resources, and harsh climate conditions make it difficult to construct, maintain, and sustain conventional housing throughout its service life. Accordingly, resilient and cost-effective housing solutions suited to these environments are urgently required. This thesis investigates modularly constructed (MC) housing as a sustainable solution for Indigenous communities in northern Canada. MC structures offer advantages in constructability, transportation efficiency, and adaptability to remote conditions while providing opportunities to improve durability and reduce material waste. Although interest in modular systems is growing, previous research has focused primarily on mid- and high-rise structures, with comparatively little attention paid to low-rise MC configurations. Research addressing the combined challenges of extreme wind loading and limited climate data in northern regions is also scarce. To overcome these limitations, this research develops an integrated framework that combines climate data reliability assessment, advanced extreme wind prediction methodologies, and structural performance evaluation of the MC configurations. The first objective (Chapter 2) of this research is to review the ongoing challenges that Indigenous communities throughout Canada face in housing. It explores the structural and socio-environmental challenges affecting Indigenous housing, including climate impact, material deterioration, and constructability limitations. This study proposes modular housing as a sustainable and adaptable solution. Next (Chapter 3), the thesis examines the spatial relationship between Indigenous communities and nearby weather stations to assess data availability and reliability. The analysis identifies significant gaps in meteorological coverage and demonstrates that limited record lengths and spatial variability can substantially influence extreme wind predictions. Third, Chapter 4 applies the Up-Crossing Rate (UCR) analysis to estimate extreme wind velocities using limited wind datasets. Unlike traditional extreme value analysis methods, which require long-term records, the UCR approach utilizes the full wind speed time history to provide reliable predictions for shorter datasets. The method is validated against established statistical approaches, showing strong agreement for long-term return periods while maintaining applicability in data-scarce environments. The fourth objective (Chapter 5) introduces a record length coefficient to correct for the systematic bias associated with short-duration datasets. Using data from over 200 meteorological stations across Canada, the study quantifies the influence of record length on extreme wind predictions and develops a record length coefficient to account for limited datasets. This approach improves the reliability of predictions derived from limited data and supports their use in engineering designs. The final objective of this thesis (Chapter 6) is to investigate the aerodynamic performance of modular housing configurations evaluated using computational fluid dynamics (CFD). Experimentally validated simulations were used to analyze single- and multi-module low-rise structures subjected to wind loading. The results indicate that modular configurations, particularly those involving stacking and overhangs, can generate significantly higher localized pressure coefficients than those predicted by current design codes. Comparisons with the National Building Code of Canada reveal potential underestimation of critical wind loads.