Abstract Noncompliance with regulatory requirements during residential construction remains a persistent issue in Australia, often leading to costly defects, compromised safety, and reduced building performance. This study identifies the most common compliance risks in low-rise residential buildings and develops two practical tools to support proactive defect mitigation: (1) a regulatory-aligned framework that maps frequent noncompliant building works to relevant provisions of the National Construction Code, Australian Standards, and Australian Building Codes Board Housing Provisions; and (2) a Bayesian beta-regression forecasting model for predicting future noncompliance rates. Using 15 quarters (2020–2024) of compliance data from the Victorian Building and Plumbing Commission and 3,743 private inspection records, a thematic analysis was conducted, which revealed that timber framing, footings and slab construction, weatherproofing of brickwork, and waterproofing works exhibit the highest rates of noncompliance. The proposed framework demonstrates clear linkages between recurring compliance risks and their underlying regulatory obligations, providing a practical reference for builders and supervisors. The Bayesian beta-regression model, validated through posterior diagnostics and out-of-sample testing, showed strong predictive capability for forecasting timber-framing noncompliance, with the results indicating a gradual upward trend across future quarters. Collectively, the regulatory-aligned framework and the predictive model offer construction practitioners and regulators structured, evidence-based tools to enhance compliance oversight, improve training, and reduce rework, thereby supporting safer and higher-quality residential construction.
Abstract Curved glued-laminated (glulam) timber beams have been used in practice as structural components in roof systems and bridges, capitalizing on the architectural freedom of using wood as a building material. Despite their use in practice, there is limited experimental data on the structural behavior of curved glulam beams, both during fabrication and at their ultimate limit state. To address this gap, this study examines the structural behavior of curved glulam beams both during fabrication and under mechanical loading to failure through a series of experimental tests. A total of 13 beam tests are described, which varied in their radius to better understand the influence of beam curvature on the residual strain distribution and the beam stiffness, strength, and failure mode at ultimate limit states. The beams were instrumented with distributed fiber-optic sensors to generate high-resolution strain measurements along the length and over the depth of the beams for the first time. Results of the study demonstrate that a complex state of strain, and thus stress, exists in a curved glulam beam after fabrication through mechanical bending of the laminations. Under structural loading, the studied beams exhibited a range of failure modes, which depended on the beam radius, including flexural failure in tension, shear failure, and radial tension failure. The experimental results are also compared with North American wood design standards, and the results suggest that these standards can predict the strength of the curved glulam beams tested in this study to within 5% of their ultimate load-carrying capacity.
Abstract Accurately characterizing existing building envelope materials is critical for retrofit prioritization, yet current nondestructive testing methods remain expensive, equipment-intensive, and inaccessible for routine use. This study explored whether low-cost WiFi signal attenuation could serve as a practical screening indicator for identifying building wall assemblies. A Raspberry Pi-based sensing system measured the received signal strength indicator at 2.4 and 5 GHz across 10 distinct wall assemblies (8 campus buildings plus a controlled test box and an open-air baseline). Because each assembly was characterized by a single 3-min measurement run at one location, assembly identity is fully confounded with measurement location, and the analysis is therefore reported as exploratory and descriptive. On that basis, the grouping of measurement cases was associated with 92.5%–94.9% of the observed signal variance across both frequency bands, and 84.4% of case pairs were separated beyond a conservative Bonferroni-corrected threshold. Every wall case was separated from the open-air baseline by at least 18.7 dB. These results do not establish a validated method for identifying wall assemblies; rather, they present an initial low-cost measurement and analysis framework and quantify the magnitudes of separation. By requiring only a sub-$100 Raspberry Pi and a smartphone, this approach lowers the barrier for nonspecialist building assessment, contributing to the emerging paradigm of citizen building science in which ordinary occupants participate meaningfully in retrofit decision-making.
