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Structural performance of cold-formed steel wall systems incorporating sustainable composite sheathing
(The University of Waikato, 2026) Huang, Kang; Hudd, Ray; Roy, Krishanu
Cold-formed steel (CFS) wall systems are widely adopted in low- and mid-rise buildings due to their high strength-to-weight ratio and construction efficiency. The structural behaviour of these systems is governed by the interaction between thin-walled steel framing, sheathing materials and mechanical fasteners. In recent years, sustainable composite boards manufactured from recycled packaging and plastics—commercially available in New Zealand under the name SaveBOARD—have been proposed as alternative sheathing materials; however, their structural performance in load-bearing CFS walls has not been systematically investigated in peer-reviewed research. This thesis presents a multi-scale experimental investigation into the structural performance of CFS wall systems incorporating sustainable composite sheathing (SaveBOARD). The research integrates material characterisation, connection-level testing, full-height single-stud wall subassembly tests under axial compression, and full-scale wall tests under quasi-static cyclic lateral loading. Key parameters include sheathing type, stud thickness, screw spacing configuration and axial load interaction. The results demonstrate that sustainable composite boards can provide effective restraint against local and distortional buckling within the tested configurations. In the axial subassembly tests, the gypsum-sheathed specimen increased ultimate axial resistance by 36.8% relative to the bare frame, while the PIL- and EPL-sheathed specimens achieved increases of 36.5% and 27.0%, respectively. Under cyclic loading, the tested composite-sheathed walls exhibited reduced pinching and more stable hysteretic behaviour than the gypsum reference specimens, primarily because the response was governed by progressive bearing deformation at screw connections rather than abrupt brittle panel fracture. Screw spacing is identified as a primary structural parameter, with diminishing returns observed under excessive densification. A stability–connection coupling interpretation is developed to explain the interaction between connection degradation and global wall response. Overall, the findings support the structural feasibility of using sustainable composite sheathing in CFS wall systems within the tested configurations and provide a mechanistic basis for performance-informed design considerations and future analytical modelling.
Epiphyte ecology in urban forests: Community assembly, traits, ecophysiology and the role of tree ferns
(The University of Waikato, 2026-11-06) Rogers, Hannah; Clarkson, Bruce D.; Burdon, Francis J.; Clearwater, Michael J.
Vascular epiphytes are a conspicuous feature of New Zealand’s temperate rainforests. Epiphytes contribute to ecosystem functioning by increasing species diversity, enhancing habitat heterogeneity, and influencing ecosystem processes such as primary production and the cycling of water and nutrients. However, research on epiphytes in temperate regions remains limited compared to tropical regions, especially in urban environments. This thesis addresses key research gaps in our understanding of urban epiphyte communities by reporting results from four interconnected studies. Collectively, these advance our knowledge of the biology and ecology of indigenous epiphytes in two warm temperate cities on North Island, New Zealand. In the first study, tree ferns were shown to augment native species richness in urban plant communities. Ground ferns and vascular epiphyte diversity were significantly higher in plots with tree ferns, illustrating strong facilitative effects. In contrast, light-demanding seedlings, saplings and trees were less frequent in plots with tree ferns, suggesting competitive interactions between these plant groups. Nonetheless, tree ferns can accelerate ecological restoration by increasing native plant diversity and providing an established canopy that helps suppress light-demanding invasive plant species. Community structure also differed significantly among site types in Hamilton: tree ferns increased total basal area, whereas restored sites supported more diverse tree and shrub communities. Associated shade-tolerant species, such as Schefflera digitata, suggest that enrichment planting of extant tree fern stands with such species may encourage a successional pathway towards conifer-broadleaved forest. The second study investigated trait matching between epiphytes and host species. Root and rhizome characteristics among 10 epiphyte species showed varying associations with specific host preferences—either favouring tree ferns, woody trees, or exhibiting generalist tendencies. Species mainly associated with tree ferns had longer, more abundant rhizome hairs, while generalist epiphytes had wider rhizomes, longer roots, and longer, more abundant rhizome scales. Links revealed between epiphyte traits and host preferences suggest that biotic filters (e.g., host availability) may exert a greater effect on epiphyte assemblages than stochastic processes (e.g., dispersal limitation). To better understand epiphyte tolerance to water and light availability, the third study involved an ex-situ greenhouse experiment. This revealed distinct physiological responses of four epiphytic ferns to water and light availability, which were associated with epiphyte microhabitat preferences. During a 12-week simulated drought, the species most closely associated with tree ferns (Asplenium polyodon) exhibited a rapid decline in photosynthetic capacity (Amax). The generalist Pyrrosia elaeagnifolia was drought-resistant, maintaining Amax and stomatal conductance (gs). Unexpectedly, the generalist Lecanopteris pustulata was not drought-resistant, exhibiting significant declines in Amax and gs. Asplenium flaccidum (associated with tree ferns in urban settings) was drought-avoidant, with low but constant Amax and gs. Light environments mimicking two distinct host microhabitats (tree ferns and woody trees) revealed greater shade tolerance in A. polyodon than P. elaeagnifolia, as indicated by predawn Fv/Fm. High light conditions exacerbated plant drought stress, as shown by reduced recovery compared with plants under low light. Finally, epiphyte community data were revisited to explicitly test the influence of environmental predictors on obligate epiphyte diversity in constrained (i.e., urban forests) and unconstrained (i.e., non-urban forests) host communities. Obligate epiphyte communities in urban forests were more homogeneous than in non-urban forests, supporting fewer epiphytic shrubs, lycophytes and orchids. SEMs showed that urban epiphyte richness was indirectly influenced by forest age and tree fern basal area, and directly positively influenced by relative humidity stability and Dicksonia squarrosa basal area. In non-urban forests, epiphyte richness was positively associated with tree fern and woody tree basal areas. Epiphyte richness increased with host species richness and was influenced by host assemblage composition. Tree fern basal area positively influenced epiphyte richness in urban forests, although woody tree basal area had a negative relationship, which may reflect a lack of high-quality host species. This research has expanded our understanding of epiphyte communities in temperate cities and how host assemblages, morphological and physiological traits, and environmental conditions influence them. It also provides a basis for implementing ecological restoration of diverse host assemblages that provide sheltered, damp habitat suitable for epiphytes. Future long-term studies on a wider range of species will be needed to build upon this research.
Energy system modelling for the decarbonisation of industrial process heat
(The University of Waikato, 2026) Chong, Daniel Jia Sheng; Walmsley, Michael R. W.; Atkins, Martin John
Industrial process heat is a major source of fossil fuel use and carbon emissions, yet it is often represented only coarsely in large-scale energy system models. This limits the ability of existing models to assess site-level fuel-switching opportunities, spatial resource allocation, and the wider electricity system implications of industrial decarbonisation. In particular, modelling industrial process heat requires approaches that can capture the diversity of industrial demand sites, the location of fuel and electricity supply options, and the infrastructure needed to connect them. This thesis develops a spatially explicit energy modelling framework to evaluate nationwide fuel-switching pathways for site-level industrial process heat up to approximately 500°C, corresponding to temperatures that can be supplied by high-pressure steam. The framework combines P-graph superstructure generation with an automated translation tool that converts the structural representation into a Pyomo-based generalised disjunctive programming model. This enables large-scale structural optimisation using reusable modular components and multiple simulation modes. A modular architecture is developed to represent model components in a scalable and reusable manner. The framework is further supported by geospatial preprocessing, standardised input-processing tools, and output reporting modules, which help facilitate the integration of high-spatial-resolution data within a unified P-graph and algebraic modelling workflow. The methodology is demonstrated through a New Zealand case study that compiles data with high spatial granularity on industrial process heat demand, electricity generation assets, biomass resources, grid infrastructure, and geospatial linkages between supply and demand nodes. The energy systems model is evaluated using three simulation modes: deterministic multiperiod optimisation, sequential deterministic optimisation, and Monte Carlo uncertainty analysis. Together, these modes allow the framework to evaluate systems-level least-cost decarbonisation pathways, grid reinforcement upgrade requirements, and the robustness of system configurations under uncertain input conditions. The deterministic multiperiod factory model captures temporal variation in demand and supply conditions. Building on the multiperiod model, the sequential framework represents staged investment and includes grid reinforcement assessment, while the Monte Carlo analysis evaluates uncertainty in key modelling parameters. The results indicate that biomass resources play a dominant role in the system-level least-cost industrial process heat decarbonisation in the New Zealand case study. Electrification increases industrial electricity demand by approximately 3.5–9.2 TWh, depending on scenario assumptions, creating additional pressure on generation and grid infrastructure. Sequential analysis shows that grid reinforcement costs can be represented through an adjusted electricity price coefficient, while Monte Carlo analysis provides a distributional view of electrification uptake, biomass utilisation, and spatial outcomes under uncertainty. These findings show that both biomass and electrification should be viewed as complementary decarbonisation pathways in the industrial process heat space, with their relative roles shaped by local resource availability, electricity costs, and infrastructure constraints. The central contribution of the thesis is a spatially explicit energy modelling framework that combines P-graph superstructure generation with a translation tool converting the structural representation into a Pyomo-based generalised disjunctive programming model. At the same time, the framework demonstrates how P-graph can be extended to support large-scale, spatially explicit, and uncertainty-aware energy system analysis.
Gender inequality in FIFA-governed football: A sociocultural and institutional analysis
(The University of Waikato, 2026-11) Sehrawat, Kunal; Roberts, William M.
This thesis investigates the systematic reproduction and contestation of gender inequality in the global football ecosystem across three interconnected domains: institutional governance, traditional media representation, and digital social media discourse. Formal structural barriers to women’s participation have been removed, yet profound disparities in resource allocation, structural visibility, and institutional recognition remain. Drawing on Pierre Bourdieu’s sociological framework of field, habitus, and capital, this study aims to uncover how the global football field remains organized by patriarchal logics that systematically devalue female athletic legitimacy. Methodologically, this study used qualitative methods and a multi-source approach, drawing on a total of 1,680 public documents. The data consisted of 1,200 social media posts from Twitter/X, Instagram, TikTok, Facebook, YouTube, and 480 institutional and mainstream media documents, such as FIFA annual reports, governance documents, benchmarking documents, and news articles. Thematic coding, qualitative content analysis, document analysis, and critical discourse analysis were used for all data analysis with NVivo. Empirical results show how market-oriented football decision actors use rationales to create a deficit of economic capital for young women, and how the feminine relation to sport, typically taken for granted in traditional sports media production, does not grant symbolic capital to young women. At the same time, the digital space becomes a space of intense contestation, as the female athlete and the organic fan use cultural capital to make themselves known as alternative counternarratives to the conventional one, to push for institutional responsibility, and as actors of digital violence and performance-based deprecation, to enforce the conventional boundaries between the two genders. Ultimately, this thesis posits that policy changes alone are insufficient to attain gender justice in sport. Rather, achieving sustainable equity requires a holistic reconfiguration of capital distribution and institutional control.
Architecting a co-designed clinical decision support system for diabetes management
(ACM, 2026) Wang, William Yu Chung; Jiang, Philip Hong Wei; Shafiu, Ibrahim; Paul, Ryan; Keenan, Rawiri; Madurapperumage, Anuradha; Liu, Chen
Diabetes mellitus, particularly Type 2 diabetes (T2D), imposes a substantial and inequitable burden on New Zealand, with domestic communities disproportionately affected. Early prediction of diabetes complications using machine learning (ML) has shown strong potential, yet most models remain disconnected from real-world clinical workflows and health information systems. This study outlines a co-design and design science research (DSR) programme to develop a machine learning–enabled clinical decision support (CDS) framework for predictive diabetes management in the Waikato region. Working with Health New Zealand (HNZ) Waikato, clinicians, and health informaticians, the research proceeds through three stages: situation awareness of current diabetes management processes, co-design of a data-driven CDS architecture, and evaluation via predictive performance metrics and process simulation. Expected contributions include an empirically grounded CDS framework tailored to local clinical and cultural contexts, improved predictive capabilities for T2D complications and resource planning, and a scalable pathway toward AI-enabled diabetes services that support health advancement and health equity.