Colburn, Gregg, and Clayton Page Aldern. Homelessness Is a Housing Problem: How Structural Factors Explain U.S. Patterns. Oakland: University of California Press, 2022.
Year: 2024
Automating building environmental assessment: A systematic review and future research directions
T.A.D.K. Jayasanka, Amos Darko, D.J. Edwards, Albert P.C. Chan, Farzad Jalaei, Automating building environmental assessment: A systematic review and future research directions, Environmental Impact Assessment Review, Volume 106, 2024, 107465, ISSN 0195-9255, https://doi.org/10.1016/j.eiar.2024.107465.
Abstract
Building environmental assessment (BEA) is critical to improving sustainability. However, the BEA process is inefficient, costly, and often inaccurate. Because automation has the potential to enhance the efficiency and accuracy of the BEA process, studies have focused on automating BEA (ABEA). Updated until now, a comprehensive analysis of prevailing literature on ABEA remains absent. This study conducts the first comprehensive systematic analysis appraising the state-of-the-art of research on ABEA. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guided to systematically analyse 91 relevant studies. Results uncover that only 29.7% of BEA systems worldwide have automated their processes, with the US LEED residing at the vanguard of automation efforts. The New Buildings scheme was mostly focused on, while largely ignoring other schemes, e.g., Existing Buildings. Five key digital approaches to ABEA were revealed, namely building information modelling (BIM) and plug-in software, BIM-ontology, data mining and machine learning, cloud-BIM, and digital twin-based approaches. Based on identified gaps, future research directions are proposed, specifically: using data mining and machine learning models for ABEA; development of a holistic cloud-based approach for real-time BEA; and digital twin for dynamic BEA. This study generates a deeper understanding of ABEA and its theoretical implications, such as major constructs and emerging perspectives, constitute a basis for holistic, and innovation in, BEA.
Artificial Intelligence in Performance-Driven Design: Theories, Methods, and Tools
Abstract
Artificial Intelligence in Performance-Driven Design: Theories, Methods, and Tools explores the application of artificial intelligence (AI), specifically machine learning (ML), for performance modeling within the built environment. This work establishes the theoretical foundations and methodological frameworks for utilizing AI/ML, with an emphasis on multi-scale modeling encompassing energy flows, environmental quality, and human systems.
The book examines relevant practices, case studies, and computational tools that harness AI's capabilities in modeling frameworks, enhancing the efficiency, accuracy, and integration of physics-based simulation, optimization, and automation processes. Furthermore, it highlights the integration of intelligent systems and digital twins throughout the lifecycle of the built environment, to enhance our understanding and management of these complex environments.
This book also:
• Incorporates emerging technologies into practical ideas to improve performance analysis and sustainable design
• Presents data-driven methodologies and technologies that seamlessly integrate into modeling and design platforms
• Shares valuable insights for developing decarbonization pathways in urban buildings
• Includes contributions from expert researchers and educators across a range of related fields
Artificial Intelligence in Performance-Driven Design is ideal for architects, engineers, planners, and researchers involved in sustainable design and the built environment. It’s also of interest to students of architecture, building science and technology, urban design and planning, environmental engineering, and computer science and engineering.
Unraveling energy justice in NYC urban buildings through social media sentiment analysis and transformer deep learning
Ashayeri, M., & Abbasabadi, N. (2024). Unraveling energy justice in NYC urban buildings through social media sentiment analysis and transformer deep learning. Energy and Buildings, 306, 113914-. https://doi.org/10.1016/j.enbuild.2024.113914
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Abstract
This study explores the intricate relationship between human sentiment on social media data, herein tweet posts on X platform, urban building characteristics, and the socio-spatial dynamics of New York City (NYC) boroughs. Leveraging Natural Language Processing (NLP) techniques, particularly sentiment analysis, augmented by the capabilities of transformer deep learning models, RoBERTa, the study places particular emphasis on the term ‘Stay-at-Home’ to encapsulate the pronounced shift in building occupancy during the pandemic's inaugural year. This focus intertwines with pivotal terms like ‘Energy Bill’ and ‘HVAC’, shedding light on their interconnected implications. The sentiment analysis leverages data from New York City's PLUTO and the Department of Energy's LEAD databases to emotional disparities connected to urban building characteristics as well as demographic and socioeconomic factors. This analytical approach unravels prevailing public emotions and extends the discussion to include energy justice concerns, viewing them through the lens of the city's built infrastructure. The research uncovers profound disparities in the built environment and the allocation of resources in NYC, highlighting the critical need to embrace a spatial justice framework for a sustainable future. This research can aid designers, planners, and policymakers in their efforts to promote equitable and inclusive urban development.
Legacies of redlining lead to unequal cooling effects of urban tree canopy
Jung, M. C., Yost, M. G., Dannenberg, A. L., Dyson, K., & Alberti, M. (2024). Legacies of redlining lead to unequal cooling effects of urban tree canopy. Landscape and Urban Planning, 246. https://doi.org/10.1016/j.landurbplan.2024.105028
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Abstract
Redlining—a racially discriminatory policy of systematic disinvestment established by the Home Owners’ Loan Corporation (HOLC) in the 1930s and continued until the late 1960s—still influences the contemporary landscape of cities in the US. While the heterogeneous distribution of land surface temperature and tree canopy cover between neighborhoods with different HOLC grades have been recently examined, the development of long-term and city-specific heat management strategies is still limited. Here, we explored the effect of redlining in Portland, Oregon, and Philadelphia, Pennsylvania, to assess its contemporary impact on climate equity. We performed a change analysis of land surface temperature and tree canopy area over the past and introduced mixed-effects models to test the intra- and inter-city differences in canopy cooling effects between the different HOLC grades. We found that (1) persistent temporal patterns of lower land surface temperatures and larger tree canopy areas are observed in higher HOLC grades, (2) greater green equity was achieved through contrasting temporal changes in tree canopy areas across HOLC grades in Portland and Philadelphia, and (3) opposite patterns exist between these cities, with stronger canopy cooling effects in neighborhoods with a Low HOLC grade in Portland and those with a High HOLC grade in Philadelphia. Differences in tree canopy change between the two cities over the past decade highlight potential influences of city-specific tree planting practices. Local planners should back tree planting initiatives to equitably mitigate urban heat exposure, considering historical redlining contexts and contemporary landscape features.
Keywords
Redlining; HOLC grade; Tree canopy; Land surface temperature; Tree equity
An Ontological Analysis for Comparison of the Concepts of Sustainable Building and Intelligent Building
Borhani, A., Borhani, A., Dossick, C. S., & Jupp, J. (2024). An Ontological Analysis for Comparison of the Concepts of Sustainable Building and Intelligent Building. Journal of Construction Engineering and Management, 150(4). https://doi.org/10.1061/JCEMD4.COENG-13711
Abstract
The concept of intelligent building is emerging in the contemporary built environment. Intelligent buildings aim to leverage digital technologies and information throughout the building’s life cycle (design, construction, and operation phases) to improve the building’s performance and value. In recent years, academic scholars and industry practitioners have made efforts to articulate the intelligent building concept and identify its components. However, there is still no commonly accepted definition for the term intelligent (or smart) building. Furthermore, the term is used interchangeably with similar terms such as sustainable building and high-performance building. The primary gaps in research are the lack of a holistic and clearly defined list of intelligent building components. This gap limits building stakeholders’ abilities to decide which technologies to implement in their buildings, prove its capabilities and advantages, and improve its performance. In response to the identified gaps, this research conceptualizes intelligent building in comparison with the concept of sustainable building. We identified the key components that each concept entails and conducted a comparative analysis of the identified components. The findings of this research include a categorization of intelligent building’s definitions which helps to conceptualize intelligent building and distinguish it from other similar concepts. In addition, the research team used the developed ontologies for intelligent and sustainable buildings to provide a fundamental overview of the structure of building evaluation systems and their different approaches for determining evaluation criteria. Overall, this study contributes to the body of knowledge by identifying and classifying components of intelligent buildings, which is a prerequisite for intelligent buildings’ evaluation. It also makes a distinction between the concepts of intelligent building and sustainable building in order to determine their context and applications.
Incentive-based coordination for scheduled delivery in prefab construction
Kim, Y.-W., & Rhee, B.-D. (2024). Incentive-based coordination for scheduled delivery in prefab construction. Construction Management and Economics, 1–16. https://doi.org/10.1080/01446193.2024.2305763.
Abstract
An increasing number of projects are adopting prefabrication to economize on time, labor, and materials in fixed-position layout operations, such as construction, ship building, and aircraft manufacturing. In such contexts, independent contractor and fabricator make interdependent decisions, which calls for prudent supply chain management because performance relies on coordination between their decisions. Many studies have developed integrated systems and propose various algorithms for scheduling efficiency and reliability. Nevertheless, they pay scant attention to conflicting interests amongst independent partners, which may result in subpar performance not only for the supplier but for the contractor as well. Coordination of conflicting interests has been extensively studied in economics and supply chain management; yet, those studies focus on order-quantity decisions under demand uncertainty for profit maximization, while managers in fixed-position operations are more concerned about delivery decisions under scheduling uncertainty for cost minimization. We consider the case of construction and explore a contractual scheme that aligns the agents' decisions for coordination in a construction supply chain. Specifically, we propose a supplier rebate for coordination: the supplier grants a rebate if the contractor accepts the shipment in accordance with the delivery schedule that the contractor initially chose. We show that the optimal rebate fully coordinates the supply chain to minimize the joint supply chain costs. Thus, both the contractor and supplier benefit from the coordination by negotiating a mutually acceptable way to allocate the savings in joint costs between them. We further show that the rebate motivates the contractor to enhance its work scheduling.
Keywords
Construction supply chain; coordination; delivery schedule reliability; prefabrication; rebate for scheduled delivery
Guest editorial: Public private partnerships: past, present and future
Laishram, B., Devkar, G., Ke, Y., & Aziz, A. A. (2024). Guest editorial: Public private partnerships: past, present and future. Built Environment Project and Asset Management, 14(1), 1–3. https://doi.org/10.1108/BEPAM-02-2024-207.
Suitability of the height above nearest drainage (HAND) model for flood inundation mapping in data-scarce regions: a comparative analysis with hydrodynamic models
Thalakkottukara, N. T., Thomas, J., Watkins, M. K., Holland, B. C., Oommen, T., & Grover, H. (2024). Suitability of the height above nearest drainage (HAND) model for flood inundation mapping in data-scarce regions: a comparative analysis with hydrodynamic models. Earth Science Informatics. https://doi.org/10.1007/s12145-023-01218-x.
Abstract
Unprecedented floods from extreme rainfall events worldwide emphasize the need for flood inundation mapping for floodplain management and risk reduction. Access to flood inundation maps and risk evaluation tools remains challenging in most parts of the world, particularly in rural regions, leading to decreased flood resilience. The use of hydraulic and hydrodynamic models in rural areas has been hindered by excessive data and computational requirements. In this study, we mapped the flood inundation in Huron Creek watershed, Michigan, USA for an extreme rainfall event (1000-year return period) that occurred in 2018 (Father's Day Flood) using the Height Above Nearest Drainage (HAND) model and a synthetic rating curve developed from LIDAR DEM. We compared the flood inundation extent and depth modeled by the HAND with flood inundation characteristics predicted by two hydrodynamic models, viz., HEC-RAS 2D and SMS-SRH 2D. The flood discharge of the event was simulated using the HEC-HMS hydrologic model. Results suggest that, in different channel segments, the HAND model produces different degrees of concurrence in both flood inundation extent and depth when compared to the hydrodynamic models. The differences in flood inundation characteristics produced by the HAND model are primarily due to the uncertainties associated with optimal parameter estimation of the synthetic rating curve. Analyzing the differences between the HAND and hydrodynamic models also highlights the significance of terrain characteristics in model predictions. Based on the comparable predictive capability of the HAND model to map flood inundation areas during extreme rainfall events, we demonstrate the suitability of the HAND-based approach for mitigating flood risk in data-scarce, rural regions.
Keywords
Flood inundation mapping; Father's Day Flood; Data-scarce regions; HAND; HEC-RAS 2D; SMS-SRH 2D
Association between property investments and crime on commercial and residential streets: Implications for maximizing public safety benefits
Walter, R. J., Acolin, A., & Tillyer, M. S. (2024). Association between property investments and crime on commercial and residential streets: Implications for maximizing public safety benefits. SSM – Population Health, 25, 101537–101537. https://doi.org/10.1016/j.ssmph.2023.101537.
Abstract
Physical property investments enhance public safety in communities while alleviating the need for criminal justice system responses. Policy makers and local government officials must allocate scare resources for community and economic development activities. Understanding where physical property investments have the greatest crime reducing benefits can inform decision making to maximize economic, safety, and health outcomes. This study uses Spatial Durbin models with street segment and census tract by year fixed effects to examine the impact of physical property investments on changes in property and violent crime over an 11-year period (2008-2018) in six large U.S. cities. The units of analysis are commercial and residential street segments. Street segments are classified into low, medium, and high crime terciles defined by initial crime levels (2008-2010). Difference of coefficients tests identify significant differences in building permit effects across crime terciles. The findings reveal there is a significant negative relationship between physical property investments and changes in property and violent crime on commercial and residential street segments in all cities. Investments have the greatest public safety benefit where initial crime levels are the highest. The decrease in violent crime is larger on commercial street segments, while the decrease in property crime is larger on residential street segments. Targeting the highest crime street segments (i.e., 90th percentile) for property improvements will maximize public safety benefits.
Keywords
Violent and property crime; Public safety; Physical property investments