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Put out fires in Facility Management through the Digital Twin adoption: outcomes from Italy
No full textThe Architecture, Construction, Engeneering and Operation (AECO) industry is benefitting from the digitalisation spread. Several digital technologies, including Artificial Intelligence (AI) and Digital Twin (DT) are revolutioning the industry’s operations. Especially, the technological innovation of the Operation and Maintenance (O&M) phase of building life cycle has the potential to optimise the managing of buildings through more efficient, transparent, and sustainable practices. The academic literature, that focuses on the O&M digital innovation, identifies the DT as the main technology to support the digitalisation of facility management (FM) practices in buildings. These potentials, described in terms of improvements in operational time and costs, are not embraced by the market, which seems unready to introduce this innovation. Issues increase in those markets that are not identified as innovator leaders, such as Italy, which is considered a moderate innovator in the European panorame, presenting a very fragmented AECO industry of small-medium enterprises and a scarse innovation boost. With the objective to highlight the market’s willingness to embrace digital innovation, the present study discusses the degree to which digital technologies, and especially DT, are adopted in the Italian market. Thus, after identifing the potential benefits in the academic literature, and report the results of a previous studies on the Italian market perspective in digital innovation, this study discusses digital technologies’ adoption with FM operators. Assessing the real application of digital technologies and DT, the paper reasons about improvements in building performance and operational efficiency introduced by real-time monitoring and predicting building behaviour. The research shows that operators encounter difficulties with data handling and practical application of these technologies. This is also caused by a knowledge gap of the Italian market, which sees few companies that support the adoption of DT
Continuous Building Energy Modeling Concept in a Building’s Lifecycle with a Case Study
Full text linkBuilding Energy Modeling (BEM) is crucial for improving energy efficiency, minimizing energy consumption, and ensuring occupant comfort. Accurate BEM offers many benefits and insights for sustainable practices throughout a building\u27s lifecycle. However, continuous BEM is often underutilized for improving energy efficiency and decarbonization of the grid, particularly when combining multiple tools that accurately estimate energy consumption, detect abnormality, and offer sustainable recommendations. This study addresses the gap in continuous BEM throughout a building\u27s lifecycle, emphasizing the role of dynamic schedule adjustments for the HVAC system to optimize energy consumption. The project team conducted a case study of an institutional building in the Pacific Northwest. BEM was completed using Sefaira, assuming the same efforts were made during the design phase, and then an OpenStudio model was created to re-evaluate the energy simulation in comparison to the real energy consumption data during the operational phase. This research examines the benefits of using Sefaira during the design phase and OpenStudio during the operational phase for continuous BEM and simulation in its specific climate and building system schedule. The findings suggest that optimizing the schedule by implementing an optimum morning warm-up can enhance energy consumption, especially through the customization of the schedule in Openstudio. As a result, energy consumption can be reduced over the building’s lifecycle. This study underscores the necessity of integrating continuous energy modeling practices throughout a building\u27s lifecycle to achieve better energy management and sustainability
Occupant Satisfaction with Building Systems and Thermostat Usage in Energy-Efficient Affordable Housing in Southern California: Preliminary Findings
Full text linkThis 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
Value Engineering and Decision-Making Process in Façade Project Development: A Real Estate Case Study
No full textThis study explores the application of Value Engineering (VE) and Life Cycle Costing (LCC) in the development of a LEED Gold-certified office building in São Paulo, Brazil. The project, characterized by high-end real estate design and sustainability objectives, involved a thorough examination of façade material options, particularly precast concrete panels. The methodology integrates SWARA and WASPAS frameworks for evaluating façade materials, leveraging Building Information Modeling (BIM) technologies for 4D and 5D modeling to enhance decision-making. Key findings highlight significant cost savings through VE, achieving a 27% reduction in initial costs by optimizing façade panel design and crane operations. LCC analysis revealed a comprehensive understanding of the financial implications over a 60-year lifespan, contrasting precast concrete with thermal insulating coatings. This study underscores the importance of concurrent design processes in real estate projects, emphasizing the need for early contractor involvement and transparent cost management strategies. The findings contribute to improved decision-making frameworks in sustainable real estate development
Machine Learning Techniques to Forecast Fatal Accidents on Construction Sites in Brazil
Full text linkGlobal estimates indicate that the construction industry has one of the highest rates of occupational accidents. Given this scenario, the sector has adopted emergent technologies to improve safety conditions and decision-making. Thus, machine learning (ML) emerges as a promising tool to streamline data analysis besides being used to predict events based on datasets. In construction, the use of the ML model to predict site accidents remains emerging without studies using historical data from emerging South and Latin American countries. Therefore, this paper aims to develop a prediction model using machine learning for fatal accidents using historical data from construction. The dataset contains 2,305 accidents, including fatal and non-fatal, from 2018 to 2023, distributed in 17 binary and categorical variables. After the pre-processing, seven predictive models were generated with different classifiers to determine which models fit the dataset better. Among the classifiers, the gradient-boosting model exhibited the best performance, achieving an accuracy of 0.885, 0.88 precision, 0.833 recall, and 0.881 F1-Score. As a contribution, this study brings insights regarding the use of predictive models in construction safety management, calling attention to the attributes that have the most influence on a fatal accident. In addition, the model can assist managers in identifying scenarios that are more prone to accidents and propose effective preventive measures
A Transformer-based Semi-Supervised Learning for Occupant Feedback Evaluation
No full textIndoor Environmental Quality (IEQ) focuses on ensuring that occupants experience comfortable and healthy indoor settings, covering factors such as temperature, humidity, air quality, acoustics, and lighting. Assessing IEQ from occupants’ perspectives is challenging due to the subjective natures of comfort and health perceptions. Existing methods for collecting direct occupant feedback, including surveys, questionnaires, observations, and interviews, frequently result in insufficient data, limiting the comprehensive and holistic understanding of occupant satisfaction in indoor environments. In response to these challenges, this paper proposes a semi-supervised learning-based framework aimed at deriving a metric of comfort and health satisfaction from sparse occupant feedback. Semi-supervised models leverage both labeled examples and the underlying structure of unlabeled data, enhancing their ability to generalize. The proposed framework leverages a Transformer-based model to extrapolate and analyze limited occupant feedback (labeled data) through leveraging multidimensional indoor environmental data (unlabeled data), offering a robust approach to assess subjective IEQ satisfaction. The formulation of the proposed framework involves three key steps: (1) collection of IEQ data, (2) collecting occupants’ direct feedback feedback, and (3) iterative model training and data annotation. Experimental evaluation conducted at the Virginia Tech Blacksburg campus yielded promising results, showing the effectiveness of the proposed approach in supporting IEQ management and occupant feedback analysis. This study contributes to the field of adaptive environmental controls, aimed at creating more tailored indoor environments that meet the specific comfort and health needs of occupants
Exploring the Definition of Capacity in Sustainable Construction: A Knowledge Mapping Approach
No full textThe global environmental crisis is becoming increasingly severe, and sustainable construction is widely regarded as a key solution for mitigating climate change. Improving sustainable construction capacity is significant and challenging for advancing the development of the sustainable construction industry. Defining capacity is the first step in addressing this challenge. However, capacity possesses multidimensional attributes, and current research does not clearly identify its meaning within the sustainable construction domain. This paper aims to provide insights into the definition of capacity in sustainable construction. Specifically, this research aims to identify the core concept, sub-areas, and emerging trends related to capacity within the sustainable construction field. Using Scopus as the database, this study analysed 1,721 global research papers related to the capacity of sustainable construction from the past decade. CiteSpace was employed to generate knowledge maps. Keyword frequencies, bursts, centrality, and clusters were used to identify research hotspots, classifications, and emerging trends. The definition of capacity in sustainable construction focuses on two core aspects: construction performance and construction materials. Key sub-areas of capacity research in this field include green buildings, energy-efficient buildings, and zero-energy buildings. Emerging trends in capacity research within sustainable construction involve energy system optimisation and carbon reduction. This exploration is crucial for understanding capacity in sustainable construction and makes a positive contribution to the sustainability of future construction practices
Review On Strength Properties of Graphene Incorporated Sustainable Concrete By Reducing Cement Quantity
No full textAbstract
Graphene, an allotrope of carbon with outstanding mechanical, physical, and thermal properties, is increasingly gaining recognition in scientific research. Its unique nanostructure has revolutionized cement composites by enhancing their mechanical strength, durability, and overall performance. The construction industry is actively exploring new, sustainable materials that improve the mechanical properties of concrete. Graphene-based nanomaterials like Graphene oxide (GO), Graphene Nanoplates, and Carbon Nanotubes (CNTs) have gained significant attention due to their superior reinforcement capabilities. This study examines the impact of GO in cement composites incorporating supplementary cementitious materials (SCMs) such as fly ash, silica fume, rice husk ash, and geopolymer concrete. Adding GO significantly improved early-age strength due to its nucleation effect, with optimal performance at 0.05% GO. Beyond this dosage, agglomeration reduced strength enhances dispersion. GO demonstrated reduced carbon emissions and improved workability and long-term durability while refining the microstructure through enhanced hydration reactions, proving the most sustainable and cost-efficient. Moreover, Graphene’s interaction with various mineral additives further strengthens cementitious composites, reducing permeability and increasing resistance to environmental degradation. The review highlights advancements in GO applications and their synergy with different materials, offering valuable insights for future research. Despite extensive studies on GO’s capabilities, continuous research is necessary to harness its potential fully in concrete technology. The findings of this review not only provide a comprehensive understanding of GO’s influence on cement-based composites and pave the way for further innovations in sustainable and high-performance construction materials
Exploring the Performance Trends in LEED-Certified Schools in Massachusetts: Analyzing Scorecards for Sustainability Insights
Full text linkSchools are essential environments for student development, with the quality of these buildings playing a significant role in shaping students’ learning experiences. Several factors, including indoor air quality, thermal comfort, acoustics, and daylight access, can impact both student well-being and academic performance. Therefore, evolving government regulations and updates to sustainable building standards, such as Leadership in Energy and Environmental Design (LEED) certifications, have prioritized enhancing the quality of school buildings. This study aims to identify the trends within LEED for school certifications between 2019 and 2024 by examining each rating system category to determine whether these trends vary across categories and investigating the influence of sustainability policies. For this purpose, LEED v4 scorecards for all LEED-certified school buildings in Massachusetts were collected and analyzed to investigate the correlation between various LEED criteria and certification levels. The findings of this study show that the overall certification points do not strongly correlate with any single category, indicating that multiple categories collectively influence the final certification score. However, the Energy and Atmosphere category has emerged as a critical differentiator in LEED certification, particularly with the recent adoption of the International Energy Conservation Code in Massachusetts. Temporal analyses also highlighted growing trends in the Indoor Environmental Quality category, reflecting post-pandemic priorities and updated Green Schools policies in Massachusetts. This study provides actionable insights for stakeholders to optimize sustainability efforts, particularly by targeting the most impactful categories to enhance certification outcomes and foster healthier, more sustainable learning environments
Energy Consumption Intensity Indicators and Sustainability Benchmarking in the Hotel Industry: Perceptions of Stakeholders in the DACH Region
No full textCurrent legislation mandates that some parts of the European hotel industry implement intensity metrics and benchmarking systems to monitor its environmental impact for non-financial reporting purposes. Comprehending and optimizing resource consumption is crucial for enhancing sustainability and boosting operational efficiency. This research aims to develop intensity indicators to measure energy consumption relevant to the hotel industry and create a framework for efficient benchmarking clusters. Using a qualitative research approach, 16 semi-structured interviews with four stakeholder groups from Germany, Austria, and Switzerland (DACH) are conducted to gain in-depth insights from different perspectives. Grounded Theory and content analysis serve as a methodology for data analysis. The results show that (i) hospitality stakeholders in the DACH region have limited knowledge about sustainability reporting, (ii) generating intensity indicators are suitable to quantify and compare energy consumption, (iii) the primary energy consumption in kWh must be measured, (iv) collecting per floor area as well as an occupant-related variable is necessary when performing energy consumption audits. Consequently, the intensity metrics Energy Use Intensity (EUI), Energy Use per Guest Night (EUPGN), and Energy Use per Net Revenue (EUPR) are formulated. Furthermore, (v) operational and physical determinants significantly influence energy consumption and must be differentiated for efficient benchmarking. Further scientific research is required to develop a regulatory-compliant reporting framework that defines and audits supplementary input factors related to energy use. Moreover, conducting quantitative benchmarking audits in less-studied areas, such as Central Europe, may enhance global comparability and identify new opportunities for energy savings