Collaborative multidisciplinary learning : quantity surveying students’ perspectives

The construction industry is highly fragmented and is known for its adversarial culture, culminating in poor quality projects not completed on time or within budget. The aim of this study is thus to guide the design of QS programme curricula in order to help students develop the requisite knowledge and skills to work more collaboratively in their multi-disciplinary future workplaces. A qualitative approach was considered appropriate as the authors were concerned with gathering an initial understanding of what students think of multi-disciplinary learning. The data collection method used was a questionnaire which was developed by the Behaviours4Collaboration (B4C) team. Knowledge gaps were still found across all the key areas where a future QS practitioner needs to be collaborative (either as a project contributor or as a project leader) despite the need for change instigated by the multi-disciplinary (BIM) education revolution. The study concludes that universities will need to be selective in teaching, and innovative in reorienting, QS education so that a collaborative BIM education can be effected in stages, increasing in complexity as the students’ technical knowledge grows. This will help students to build the competencies needed to make them future leaders. It will also support programme currency and delivery

Occupant Satisfaction with Building Systems and Thermostat Usage in Energy-Efficient Affordable Housing in Southern California: Preliminary Findings

This preliminary study examines resident satisfaction with building systems in energy-efficient affordable housing, addressing a gap in understanding how these systems impact low-income households. As California pushes toward net-zero energy goals, insights into resident experiences are essential for achieving energy efficiency while ensuring occupant well-being and equitable access to sustainable living environments. Seven residents of a newly constructed energy-efficient affordable housing property were interviewed in a semi-structured format. Thematic analysis revealed varied satisfaction levels with systems such as heating, cooling, lighting, and water heating. While residents appreciated the building’s energy systems, they shared concerns regarding hot water delivery and usage of advanced thermostat features. Some expressed frustration with unclear instructions and limited perceived control, while others were satisfied with basic functionality. Although the studied property benefits from many energy efficiency features, findings of this research highlight the need for improvement areas through user-centric design and retrofit, better education, and support to enhance system usability and satisfaction. This preliminary study sets the ground for broader research while shedding light on potential action plans for policymakers, developers, and designers to improve energy-efficient affordable housing and promote equity through tailoring solutions to low-income residents\u27 needs, supporting the broader net-zero energy agenda while ensuring their well-being and satisfaction

Enhancing Building Safety Design for Active Shooter Incidents: Exploration of Building Exit Parameters using Reinforcement Learning-Based Simulations

With the alarming rise in active shooter incidents (ASIs) in the United States, enhancing public safety through building design has become a pressing need. This study proposes a reinforcement learning-based simulation approach addressing gaps in existing research that has neglected the dynamic behaviours of shooters. We developed an autonomous agent to simulate an active shooter within a realistic office environment, aiming to offer insights into the interactions between building design parameters and ASI outcomes. A case study is conducted to quantitatively investigate the impact of building exit numbers (total count of accessible exits) and configuration (arrangement of which exits are available or not) on evacuation and harm rates. Findings demonstrate that greater exit availability significantly improves evacuation outcomes and reduces harm. Exits nearer to the shooter's initial position hold greater importance for accessibility than those farther away. By encompassing dynamic shooter behaviours, this study offers preliminary insights into effective building safety design against evolving threats

A review of tertiary BIM education for advanced engineering communication with visualization

SPECT with Tc-99m-labeled agents is better able to detect viability after nitrate administration. Nitrates induce vasoclilation and may increase blood flow to severely hypoperfused but viable myocardium, thereby enhancing tracer delivery and improving the detection of viability. Quantitative data on the changes in blood flow are lacking in SPECT but can be provided by PET. The aim of the present study was to use PET to evaluate whether nitrate administration increases blood flow to chronically dysfunctional but viable myocardium. Methods: N-13-Ammonia PET was used to quantitatively assess blood flow, and F-18-FDG PET was used as the gold standard to detect viable myocardium. Twenty-five patients with chronic ischemic left ventricular dysfunction underwent N-13-ammonia PET at rest and after nitrate administration. Results: A significant increase in nitrate-enhanced blood flow was observed in viable segments (from 0.55 +/- 0.15 to 0.68 +/- 0.24 mL/min/g, P <0.05). No statistically significant change in blood flow was observed in nonviable segments (0.60 +/- 0.20 vs. 0.55 +/- 0.18 mL/min/g). A ratio of at least 1.1 for nitrate-enhanced flow to resting flow allowed optimal detection of viable myocardium, yielding a sensitivity of 82% with a specificity of 100%. Conclusion: N-13-Ammonia PET showed a significant increase in nitrate-enhanced blood flow in viable myocardium, whereas blood flow remained unchanged after nitrate administration in nonviable myocardium. Nitrate use during myocardial perfusion imaging will lead to improved assessment of myocardial viability

How Work From Home Has Affected the Occupant’s Well-Being in the Residential Built Environment: An International Survey Amid the Covid-19 Pandemic

This paper presents the results from an international survey that investigated the impacts of the built environment on occupant well-being during the corona virus disease 2019 (COVID-19) pandemic when most professionals were forced to work from home (WFH). The survey was comprised of 81 questions focusing on the respondent’s profiles, residences, home indoor environmental quality, health, and home working experiences. A total of 1460 responses were collected from 35 countries, and 1137 of them were considered complete for the analysis. The results suggest that home spatial layout has a significant impact on occupant well-being during WFH since home-life distractions and noises due to the lack of a personal workspace are likely to prevent productive work. Lack of scenic views, inadequate daylighting, and poor acoustics were also reported to be detrimental to occupant productivity and the general WFH experience. It is also revealed from this survey that temperature, relative humidity, and indoor air quality generally have higher satisfaction ratios compared with the indoor lighting and acoustic conditions, and the home layout. Hence, home design for lighting, acoustics, and layout should also receive greater attention in the future

PREDICTING HVAC ENERGY CONSUMPTION IN COMMERCIAL BUILDINGS USING MULTIAGENT SYSTEMS

ABSTRACT Energy consumption in commercial buildings has been increasing rapidly in the past decade. The knowledge of future energy consumption can bring significant value to commercial building energy management. For example, prediction of energy consumption decomposition helps analyze the energy consumption patterns and efficiencies as well as waste, and identify the prime targets for energy conservation. Moreover, prediction of temporal energy consumption enables building managers to plan out the energy usage over time, shift energy usage to off-peak periods, and make more effective energy purchase plans. This paper proposes a novel model for predicting heating, ventilation and air conditioning (HVAC) energy consumption in commercial buildings. The model simulates energy behaviors of HVAC systems in commercial buildings, and interacts with a multiagent systems (MAS) based framework for energy consumption prediction. Prediction is done on a daily, weekly and monthly basis. Ground truth energy consumption data is collected from a test bed office building over 267 consecutive days, and is compared to predicted energy consumption for the same period. Results show that the prediction can match 92.6 to 98.2% of total HVAC energy consumption with coefficient of variation of the root mean square error (CV-RMSE) values of 7.8 to 22.2%. Ventilation energy consumption can be predicted at high accuracies (over 99%) and low variations (CV-RMSE values of 3.1 to 16.3%), while cooling energy consumption accounts for majority of inaccuracies and variations in total energy consumption prediction

Digital Modeling, Integrated Project Delivery and Industry Transformation: An Australian Case Study

This research is focused on realizing productivity benefits for the delivery of transport infrastructure in the Australian construction industry through the use of building information modeling (BIM), virtual design and construction (VDC) and integrated project delivery (IPD). Specific objectives include: (I) building an understanding of the institutional environment, business systems and support mechanisms (e.g., training and skilling) which impact on the uptake of BIM/VDC; (II) gathering data to undertake a cross-country analysis of these environments; and (III) providing strategic and practical outcomes to guide the uptake of such processes in Australia. Activities which will inform this research include a review of academic literature and industry documentation, semi-formal interviews in Australia and Sweden, and a cross-country comparative analysis to determine factors affecting uptake and associated productivity improvements. These activities will seek to highlight the gaps between current-practice and best-practice which are impacting on widespread adoption of BIM/VDC and IPD. Early findings will be discussed with intended outcomes of this research being used to: inform a national public procurement strategy; provide guidelines for new contractual frameworks; and contribute to closing skill gaps

Interoperability for the design and construction industry through semantic web technology

The domain of architecture, engineering and construction (AEC) has experienced significant improvements with the advent of building information modelling (BIM) applications, which allow AEC specialists to model all information concerning a building design into one three-dimensional building model. Much of these improvements are however generated by the mere availability of such an environment, whereas many more improvements were expected by achieving an appropriate interoperability of information. We are investigating why such an interoperability is not reached fully and consider the semantic web as an alternative approach to reach the targeted interoperability. In this paper, an AEC description framework based on semantic web technology is presented and compared to the BIM approach, after which we indicate how it might solve the issue of interoperability more appropriately. Our evaluation of this investigation indicates the semantic web approach as a valid alternative approach, although considerably more research is needed to show it capable of providing the targeted interoperability of information in the AEC domain