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Integrating Flood-Resistant Design and Construction Strategies in Sustainable Homes in the Central Valley: Effective Approaches for New and Existing Structures
Get PDFAs climate change intensifies, California’s Central Valley faces unprecedented weather events, including increased flood risks, leaving homeowners vulnerable, especially those in disadvantaged communities. This paper, based on a master’s thesis, examines effective strategies for integrating flood-resistant design and construction practices into new homes and retrofit solutions for existing homes by assessing local flood vulnerabilities. Employing a mixed-methods approach grounded in an extensive literature review, this study combines a homeowner survey with qualitative interviews with local design, construction, and development professionals in the residential sector. Insights from the survey informed the interview design, enabling a deeper exploration of challenges specific to the region. Survey results revealed homeowners\u27 past experiences and future concerns, while interviews with industry professionals identified practical and cost-effective flood mitigation strategies and retrofitting measures for existing homes. By bridging the gap between technical industry practices and accessible guidance, this research supports evidence-based policies and guidelines, and aligns with the UN’s Sustainable Development Goal 11, to foster safe, resilient, and sustainable communities in flood-prone areas of the Central Valley
GenAI for Building Energy Efficiency
Get PDFThe 17 United Nations Sustainable Development Goals (SDGs) are an urgent call for action by nearly every industry. The buildings sector has made significant efforts toward the SDGs by enhancing energy efficiency. The emergence of generative artificial intelligence (GenAI) technologies, such as advanced algorithms and models, has brought new possibilities for further enhancing energy efficiency in buildings. However, the potential of GenAI in this domain has not yet been fully explored. This study provides a comprehensive overview of the current applications of GenAI in enhancing building energy efficiency. A total of 34 studies were identified from the Scopus and arXiv databases and analyzed using content and thematic analysis. Results show that GenAI provides significant advantages in building energy data processing, energy prediction, as well as energy modeling and management. This research enriches the existing knowledge body by summarizing the applications of GenAI in enhancing building energy efficiency. Furthermore, it highlights future trends of this emerging AI technology, paving the way toward a more sustainable built environment
Location-Based Work Sampling: Application and Evaluation for Workflow Issue Identification
Get PDFThis study explores the application of Location-Based Work Sampling (LBWS) to enhance construction site management, focusing on workflow issue identification. For that, a Case Study was conducted on a new construction project in Herning, Denmark. The authors applied the LBWS tool to identify the distribution of working time of seven trades. The Case Study presented a structured five-step methodology: (1) understanding, (2) adaptation, (3) application, (4) analysis, and (5) evaluation. During the adoption step, the “Ajour system” app was selected as the optimal software based on the technique “Chosen By Advantages”. At the application step, the authors registered 2,800 random observations of worker activities classified into production, preparation, transportation, walking, talking and waiting. The analysis step aimed to understand the utility of the tool for three kinds of uses: (1) spatial-time distribution, (2) heat maps, and (3) congestion and interferences. Finally, the utility of the LBWS was evaluated through a focus group with seven construction industry-related professionals and academia. Key findings of spatial-time analysis highlighted workflow inefficiencies, such as increased waiting and preparation times of some trades. Heat maps aided in visualizing workers’ time spent at different locations, while congestion analysis revealed the negative impact of overlapping trades in the same workspace. The results of the focus group highlighted the tool’s potential for site management improvements and data-driven layout optimization. Overall, the LBWS tool received a positive response, especially for its simplicity and accessibility
The Best Value Approach 4.0 - Advanced Air Mobility Case Study
Get PDFThe Best Value Approach (BVA) has been researched and developed for 25 years in the procurement and project management sectors. It has documented test projects showing a high level of performance for organizations. Although the approach has been successful, changes in technology continue to alter the landscape of the procurement industry. BVA 4.0 was created to adapt the approach to meet current industry demands. In this paper, the researcher wanted to better understand the impact of the changes of BVA 4.0 and better understand its implications. BVA 4.0 was tested ith an organization to determine whether it is an improvement to BVA. The test project was a high profile air mobility project for a government organization. The organization found great results from test project and procured the service 4-6 months faster than with their own process. During the process, the organization reverted to their traditional process and only used a portion of the BVA 4.0. This initial test showed that the BVA 4.0 was an improvement to BVA with no negative sideaffects from the changes. The BVA 4.0 was able to eliminate time, and effort in the procurement process. More research needs to be conducted to determine the performance of BVA 4.0 and verify the results of the case study
Developing a Circular Economy Checklist for Designing Modular Buildings: A Case Study in Sri Lanka
Get PDFClimatic change and its impact on humankind is increasingly evident. Being the species that brought about this devastation, our interventions are now needed to proactively and paradigmatically change production and consumption patterns. Circular Economy (CE) is one such sustainability-friendly goal that is gaining traction in the Building Construction Industry (BCI). Given the massive negative impact that BCI has on the environment in terms of resource consumption, carbon emissions and waste generation, design practices must be shifted from object-centric thinking to a systemic & systematic endeavour. Even though Off-Site Construction (OSC) and Design for Manufacturing and Assembly (DfMA) have circular potential given their inherent features of resource efficiency, the question remains as to whether the Whole Life Cycle of a modular building is factored in, in incorporating CE principles in the modular building design. Hence, this study proposes a circular planning and designing checklist for a modular building to be characterised as a Circular Modular Building. For this purpose, a literature review was conducted to identify the Design for Circular Manufacturing and Assembly (DfCMA) checklist items and to consolidate the different terms associated with the DfCMA concept. Following the literature review, empirical data was collected from a case study of a Sri Lankan modular construction project. Given the rapid growth of OSC and its continuing demand, it is timely that more such mechanisms are injected towards incorporating CE principles in modular building design to decouple economic development from environmental sustainability
Measuring Innovation in New Zealand Construction Organisations: Developing a Measurement Tool for New Zealand’s Medium and Large Companies
Get PDFNew Zealand’s construction industry is the cornerstone of economic development and the labour force but is slow in innovation when compared to other sectors. To minimise this problem, this research developed a comprehensive, multidimensional tool which measures and improves innovation inside medium and large construction companies of New Zealand. The developed tool measures innovation through two main dimensions: Innovation Potential - consisting of categories such as Workforce Skills, Organisational Structure, Business Strategy, Technology, and External Influences - and Business Innovation Score, which measures the actual innovation outputs of the company. A mixed-methods research approach was used for the development, testing, and validation of the tool, and includes case studies and expert feedback. results reflect the tool\u27s ability to identify innovation barriers and drivers, and later demonstrates practical advice for industry users. The study demonstrates a new framework especially tailored for the New Zealand construction industry’s environment. The tool allows innovation adoption while it improves the performance of the organisations. This research also demonstrates the adaptability of the tool for application in international construction environments. These characteristics make the tool it a significant contribution toward addressing innovation challenges in the today’s construction industry
Self-Supervised Learning Framework for Automated Material Grouping of Demolition Waste: Advancing Sustainable Waste Management
Get PDFThe construction and demolition (C&D) sector generates significant waste, necessitating efficient sorting and recycling to promote sustainable waste management. Traditional sorting methods in C&D waste management often depend on manual processes, which are labor-intensive and prone to errors, thus limiting recycling efficiency. While automated sorting systems have been introduced, they face challenges with the complex, heterogeneous nature of C&D debris and require large datasets that are manually labeled—meaning every image must be tagged with material types by experts—for training. This study addresses this gap by developing a self-supervised learning framework that reduces reliance on labeled data for effective feature extraction and material grouping. We implemented contrastive learning and autoencoder models, enhancing model performance through a dual approach of fine-tuning and parameter optimization, including edge detection, temperature, and batch size adjustments. The contrastive learning model, when optimized with lower temperatures and smaller batch sizes, exhibited superior feature differentiation and minimized loss. Clustering results highlighted that agglomerative hierarchical clustering provided the most coherent material groupings, outperforming other methods in adaptability to diverse debris characteristics. This framework provides a scalable, autonomous method for material grouping, which can streamline the sorting process by categorizing materials based on shared characteristics. By facilitating the initial grouping of materials, it reduces the manual effort required for detailed sorting and enhances recycling efficiency. Our findings demonstrate the effectiveness of self-supervised learning models in identifying distinct material features and clustering similar materials, contributing to sustainable waste management by enabling more efficient material recovery and recycling processes
Understanding Potential Challenges in Demolition Robot Teleoperation to Inform Interface Design: Insights from Industry Professionals
Get PDFTeleoperation is receiving intense attention due to its potential to address health and safety concerns for construction workers caused by on-site hazards. It allows operators to control robots from a distance outside their field of view using wireless communication technologies. Currently one of the most frequently deployed robotic technologies in construction is the remotely operated demolition robot within the field of view. While distance teleoperation offers great potential for enhancing worker safety and addressing labor shortages, the complex and dynamic demolition sites present unique challenges. This paper introduces the preliminary results of a study that explored potential challenges in demolition robot teleoperation, informed by the challenges identified in traditional demolition machine operations and the key concerns raised by industry professionals. A user-centered approach was employed through narrative interviews and focus groups with demolition professionals. The findings indicate that the challenges faced in traditional demolition machine operations may persist in teleoperation and could be further exacerbated by the sensory degradation inherent in teleoperation. Besides, the interactions among challenges increase the complexity of their overall impact. Moreover, enhancing operators’ situational awareness without inducing cognitive overload or distraction is critical for effectively addressing these challenges. Additionally, the results suggest the need for context-aware, multimodal teleoperation interfaces to assist operators in managing operational challenges. This study contributes to understanding challenges that operators may face during teleoperation, offering valuable insights for developing teleoperation interfaces adaptable to diverse demolition contexts
Determinants of work location choice in academia
Get PDFThe COVID-19 pandemic has forced most workers to work from home (WFH). At first glance, this seems not to be a significant change for academics, who, even in regular times, are used to performing their research activities autonomously and balancing on-campus and off-campus locations. Instead, precisely because of their flexible habits, it is interesting to study where academics worked during the COVID-19 pandemic and which factors relate to their location choices. This paper addresses these issues using survey data from 7,865 Italian-tenured academics. First, cluster analysis unveils four main location choices of Italian academics during the COVID-19 pandemic depending on the frequency of access to home, university, or other spaces, namely Home-centric, University-centric, Between home and university, and Multi-located. Second, multinomial probit models reveal a nuanced picture of the factors associated with belonging to each cluster. Decisions over location choice depend mainly on work-related factors (i.e., discipline), then on space-related factors (i.e., satisfaction towards campus workspace characteristics and the need for a laboratory), finally, on, life-related factors (i.e., living with school children or a partner) and other factors (i.e., commuting times and gender). However, each of the four location patterns depends on different determinants. The results offer university and practice-wide implications anticipating future changes in how work in academia is spatially organized
Assessing the evolution of building whole life carbon across two socio-economically similar districts
No full textPopulation growth, rising housing costs, and regional disparities are driving a growing demand for new housing. However, buildings contribute approximately 40% of global carbon emissions, necessitating sustainable approaches in construction to mitigate climate impacts. This study evaluates whole life carbon (WLC) emissions in two Helsinki districts, Malminkartano and Kannelmäki as a control area, analyzing 187 buildings constructed between 2001 and 2020. Buildings are grouped by district and construction period into four Housing Portfolios (HPs) to examine trends in embodied and operational carbon emissions over time. Findings reveal a significant reduction of 45–50 % in WLC in newer HPs. The reductions are primarily due to advancements in energy efficiency and the decarbonization of Helsinki’s energy mix, which have lowered operational carbon emissions (~80 %). Embodied carbon (EC) remains relatively stable across HPs, except in Malminkartano’s recent timber-based developments, where EC has decreased by approximately 14 %. However, this emphasis on timber construction has slightly limited benefits stemming from operational carbon, resulting in less than 8 % reductions in WLC compared to the control district. The study highlights the importance of both material selection and operational efficiency in minimizing carbon impacts over a building’s life cycle, supporting climate-aligned urban development. Finally, the study emphasizes the time-value of carbon when assessing the WLC of buildings relative to climate change mitigation