It has been challenging for designers to identify the appropriate design parameters that would reduce building energy consumption while achieving thermal comfort for building occupants. This study aims to determine the most important architectural building design parameters (ABDPs) that can increase thermal comfort and reduce energy use in educational buildings. The effect of 15 ABDPs in an Australian educational lecture theatre and their variabilities on energy consumption and students’ thermal comfort for each parameter were analysed using Monte Carlo (MC) techniques. Two thousand simulations for every input parameter were performed based on the selected distribution using the Latin hypercube sampling (LHS) technique. Sensitivity analyses (SA) and uncertainty analyses (UA) were used to assess the most important ABDPs in terms of thermal discomfort hours and energy consumption. The study found that the ABDPs, such as cooling set-point temperatures and roof construction, significantly reduce the operative temperature by up to 14.2% and 20.0%, respectively. Consequently, these reductions could significantly shorten the thermal discomfort hours, thereby reducing energy consumption by 43.7% and 41.0%, respectively. The findings of this study enable building designers to identify which ABDPs have a substantial impact on thermal comfort and energy consumption.

Big data application is a significant transformative driver of change in the retail, health, engineering, and advanced manufacturing sectors. Big data studies in construction are still somewhat limited, although there is increasing interest in what big data application could achieve. Through interviews with construction professionals, this paper identifies the capabilities needed in construction firms to enable the accrual of the potentially transformative benefits of big data application in construction. Based on previous studies, big data application capabilities, needed to transform construction processes, focussed on data, people, technology, and organisation. However, the findings of this research suggest a critical modification to that focus to include knowledge and the organisational environment along with people, data, and technology. The research findings show that construction firms use big data with a combination strategy to enable transformation by (a) driving an in-house data management policy to rolling-out the big data capabilities; (b) fostering collaborative capabilities with external firms for resource development, and (c) outsourcing big data services to address the capabilities deficits impacting digital transformation.

This study experimentally investigated water penetration through semi-interlocking masonry (SIM) walls using a standard test methodology. The main objective of this study was to investigate the water-penetration performance of dry-stacked SIM walls and the effects of using gap-fillers on the testing walls. The performance of a traditional unreinforced masonry wall was used as the benchmark against which the results for SIM walls were compared. This paper reports the water-penetration performance results of several types of SIM walls investigated in this study.

An auto-ethnography and then analyses of narratives and ethnographies of other construction professionals are used to argue that reproduction of knowledge and expertise development is constrained by both normative professional thinking and a discourse of economic constraint generated by a highly competitive marketplace with a focus on time, cost, and quality trade-offs. The analysis of construction professionals’ narratives suggests that expertise development in construction is essentially an incremental process built on scenarios and influenced mostly by context and people, discourses of practices, legalities and professional expectations. Sometimes that incrementalism is distorted through radical innovation, but that is rare. Construction expertise in these stories is reproduced from base level learning and grows through practice. Practitioners, it is argued, accumulate knowledge and expertise, but the practice that emanates remains bounded within prevailing discourse which itself changes incrementally.

The Attitudes of Demolition Contractors to Reusing Building Components: A Study in New South Wales, Australia

Big data applications consist of (a) data collection using big data sources, (b) storing and processing data and (c) analysing data to gain insights for creating organisational benefit. The influx of digital technologies and digitisation in the construction process includes big data as one newly emerging digital technology adopted in the construction industry. Big data application is in a nascent stage in construction, and there is a need to understand the tangible benefit(s) that big data can offer the construction industry. This study explores the benefits of big data in the construction industry. Using a qualitative case study design, construction professionals in an Australian construction firm were interviewed. The research highlights that the benefits of big data include reduction of litigation among project stakeholders, enablement of near-to-real-time communication and facilitation of effective subcontractor selection. By implication, on a broader scale, these benefits can improve contract management, procurement and management of construction projects. This study contributes to an ongoing discourse on big data application and, more generally, digitisation in the construction industry.