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Associations between Neighborhood Built Environment, Residential Property Values, and Adult BMI Change: The Seattle Obesity Study III

Buszkiewicz, James H.; Rose, Chelsea M.; Ko, Linda K.; Mou, Jin; Moudon, Anne Vernez; Hurvitz, Philip M.; Cook, Andrea J.; Drewnowski, Adam. (2022). Associations between Neighborhood Built Environment, Residential Property Values, and Adult BMI Change: The Seattle Obesity Study III. SSM-Population Health, 19.

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Abstract

Objective: To examine associations between neighborhood built environment (BE) variables, residential property values, and longitudinal 1-and 2-year changes in body mass index (BMI). Methods: The Seattle Obesity Study III was a prospective cohort study of adults with geocoded residential addresses, conducted in King, Pierce, and Yakima Counties in Washington State. Measured heights and weights were obtained at baseline (n = 879), year 1 (n = 727), and year 2 (n = 679). Tax parcel residential property values served as proxies for individual socioeconomic status. Residential unit and road intersection density were captured using Euclidean-based SmartMaps at 800 m buffers. Counts of supermarket (0 versus. 1+) and fast-food restaurant availability (0, 1-3, 4+) were measured using network based SmartMaps at 1600 m buffers. Density measures and residential property values were categorized into tertiles. Linear mixed-effects models tested whether baseline BE variables and property values were associated with differential changes in BMI at year 1 or year 2, adjusting for age, gender, race/ethnicity, education, home ownership, and county of residence. These associations were then tested for potential disparities by age group, gender, race/ethnicity, and education. Results: Road intersection density, access to food sources, and residential property values were inversely associated with BMI at baseline. At year 1, participants in the 3rd tertile of density metrics and with 4+ fast-food restaurants nearby showed less BMI gain compared to those in the 1st tertile or with 0 restaurants. At year 2, higher residential property values were predictive of lower BMI gain. There was evidence of differential associations by age group, gender, and education but not race/ethnicity. Conclusion: Inverse associations between BE metrics and residential property values at baseline demonstrated mixed associations with 1-and 2-year BMI change. More work is needed to understand how individual-level sociodemographic factors moderate associations between the BE, property values, and BMI change.

Keywords

Body-mass Index; Physical-activity; Food Environment; Socioeconomic-status; Weight-gain; Health; Quality

Automated Extraction of Geometric Primitives with Solid Lines from Unstructured Point Clouds for Creating Digital Buildings Models

Kim, Minju; Lee, Dongmin; Kim, Taehoon; Oh, Sangmin; Cho, Hunhee. (2023). Automated Extraction of Geometric Primitives with Solid Lines from Unstructured Point Clouds for Creating Digital Buildings Models. Automation In Construction, 145.

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Abstract

Point clouds produced by laser scanners are an invaluable source of data for reconstructing multi-dimensional digital models that reflect the as-is conditions of built facilities. However, previous studies aimed to reconstruct models by overlaying the dataset on top of ground-truth reference models to manually adjust the accuracy of the output. Therefore, this paper describes the extraction of geometric primitives with solid lines—the simplest form of objectified data that computer-aided design systems can handle—from unorganized data points and creation of digital models of built facilities in a form of floor plan. The geometric primitives are extracted from 3D points by hybridizing machine learning algorithms, which are mean-shift clustering, non-convex hull, and random sample and consensus (RANSAC). This paper provides a solution for creating a new form of as-built model with high accuracy and robustness from scratch without the involvement of ground-truth solutions or manual adjustments. © 2022 Elsevier B.V.

Keywords

Computer Aided Design; Geometry; Laser Applications; Learning Algorithms; Machine Learning; Scanning; As-build Model Creation; Build Facility; From-point-to-line; Geometric Primitives; Laserscanners; Model Creation; Outline Extractions; Point-clouds; Point-to-line; Solid Lines

Formal Prevention through Design Process and Implementation for Mechanical, Electrical, and Plumbing Worker Safety

Osburn, Laura; Lee, Hyun Woo; Gambatese, John A. (2022). Formal Prevention through Design Process and Implementation for Mechanical, Electrical, and Plumbing Worker Safety. Journal Of Management In Engineering, 38(5).

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Abstract

There are many studies that focus on Prevention through Design (PtD) for construction workers and developing formalized PtD processes for construction projects. However, few studies have aimed at developing a formalized PtD process for mechanical/electrical/plumbing (MEP) worker safety. A formal process for implementing PtD for MEP worker safety is badly needed because MEP work onsite and during operation and maintenance (O&M) can lead to injury and death. To address this knowledge gap, our research team aimed to create a formalized PtD process for MEP safety and developed case studies that detail how the process can be implemented in the field. The formalized process and case studies would then be used in an implementation guide created specifically for the industry. This project was completed through expert interviews, six case studies, and ongoing discussion and review by an Industry Advisory Council. Using these methods, the team identified factors for implementation success and developed a formalized PtD process specific to the MEP worker context. The process consists of five phases: (1) hazard identification, (2) risk assessment, (3) design review, (4) implementation, and (5) learning. We anticipate that this study will contribute to the field of PtD research through creating one of the first formalized PtD processes for MEP construction and O&M worker safety, and through a cross-case analysis of the six PtD cases that indicated not only the importance of stakeholder engagement and cross-disciplinary dialogue, but that effective PtD implementation can occur even outside of a collaborative project delivery context at any point during design and construction.

Keywords

Construction Safety; Health; Attitude; Prevention Through Design (ptd); Construction Worker Safety; Mechanical; Electrical; Plumbing (mep)

Immersive VR Versus BIM for AEC Team Collaboration in Remote 3D Coordination Processes

Asl, Bita Astaneh; Dossick, Carrie Sturts. (2022). Immersive VR Versus BIM for AEC Team Collaboration in Remote 3D Coordination Processes. Buildings, 12(10).

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Abstract

Building Information Modeling (BIM) and Virtual Reality (VR) are both tools for collaboration and communication, yet questions still exist as to how and in what ways these tools support technical communication and team decision-making. This paper presents the results of an experimental research study that examined multidisciplinary Architecture, Engineering, and Construction (AEC) team collaboration efficiency in remote asynchronous and synchronous communication methods for 3D coordination processes by comparing BIM and immersive VR both with markup tools. Team collaboration efficiency was measured by Shared Understanding, a psychological method based on Mental Models. The findings revealed that the immersive experience in VR and its markup tool capabilities, which enabled users to draw in a 360-degree environment, supported team communication more than the BIM markup tool features, which allowed only one user to draw on a shared 2D screenshot of the model. However, efficient team collaboration in VR required the members to properly guide each other in the 360-degree environment; otherwise, some members were not able to follow the conversations.

Keywords

Mental Models; Virtual-reality; Performance; Virtual Reality (vr); Building Information Modeling (bim); 3d Coordination; Clash Resolution; Remote Collaboration; Multidisciplinary Aec Team

On the Tradeoffs between Embodied and Operational Carbon in Building Envelope Design: The Impact of Local Climates and Energy Grids

Echenagucia, Tomas Mendez; Moroseos, Teresa; Meek, Christopher. (2023). On the Tradeoffs between Embodied and Operational Carbon in Building Envelope Design: The Impact of Local Climates and Energy Grids. Energy & Buildings, 278.

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Abstract

The building envelope has a substantial influence on a building's life cycle operational and embodied car-bon emissions. Window-to-wall ratios, wall assemblies, shading and glazing types, have been shown to have a significant impact on total emissions. This paper provides building designers, owners, and policy makers with actionable guidance and a prioritization framework for establishing co-optimized lifecycle carbon performance of facade assembly components in a broad spectrum of climate contexts and energy carbon intensities. A large parametric study of building envelopes is conducted using building perfor-mance simulation and cradle-to-gate embodied carbon calculations in 6 US cities. The authors derive the total carbon emissions optimization for commercial office and residential space types using standard code-reference models and open-source lifecycle data. Comparisons between optimal total carbon solu-tions and (i) optimal operational carbon and (ii) minimum required assemblies, show the impact of under and over investing in envelope-related efficiency measures for each climate. Results show how the rela-tionship between embodied and operational carbon is highly localized, that optimal design variables can vary significantly. In low carbon intensity energy grids, over investment in envelope embodied carbon can exceed as 10 kgCO2e/m2, while under investment in high carbon intensity grids can be higher than 150 kgCO2e/m2.Published by Elsevier B.V.

Keywords

Facades; Building-integrated Photovoltaic Systems; Carbon Emissions; Carbon; Building Performance; Building Designers; Building Envelopes; Refuse Containers; Building Performance Simulation; Embodied Carbon; Operational Carbon; Parametric Modeling; Environmental-impact; Search

Lingzi Wu

Lingzi Wu is an Assistant Professor with the Department of Construction Management (CM) at the University of Washington (UW). Prior to joining UW in September 2022, Dr. Wu served as a postdoctoral fellow in the Department of Civil and Environmental Engineering at University of Alberta, where she received her MSc and PhD in Construction Engineering and Management in 2013 and 2020 respectively. Prior to her PhD, Dr. Wu worked in the industrial construction sector as a project coordinator with PCL Industrial Management from 2013 to 2017.

An interdisciplinary scholar focused on advancing digital transformation in construction, Dr. Wu’s current research interests include (1) integration of advanced data analytics and complex system modeling to enhance construction practices and (2) development of human-in-the-loop decision support systems to improve construction performance (e.g., sustainability and safety). Dr. Wu has published 10 papers in top journals and conference proceedings, including the Journal of Construction Engineering and Management, Journal of Computing in Civil Engineering, and Automation in Construction. Her research and academic excellence has received notable recognition, including a “Best Paper Award” at the 17th International Conference on Modeling and Applied Simulation, and the outstanding reviewer award from the Journal of Construction Engineering and Management.

As an educator and mentor, Dr. Wu aims to create an inclusive, innovative, and interactive learning environment where students develop personal, technical, and transferable skills to grow today, tomorrow, and into the future.

Narjes Abbasabadi

Narjes Abbasabadi, Ph.D., is an Assistant Professor in the Department of Architecture at the University of Washington. Dr. Abbasabadi also leads the Sustainable Intelligence Lab. Abbasabadi’s research centers on sustainability and computation in the built environment. Much of her work focuses on advancing design research efforts through developing data-driven methods, workflows, and tools that leverage the advances in digital technologies to enable augmented intelligence in performance-based and human-centered design. With an emphasis on multi-scale exploration, her research investigates urban building energy flows, human systems, and environmental and health impacts across scales—from the scale of building to the scale of neighborhood and city.

Abbasabadi’s research has been published in premier journals, including Applied Energy, Building and Environment, Energy and Buildings, Environmental Research, and Sustainable Cities and Society. She received honors and awards, including “ARCC Dissertation Award Honorable Mention” (Architectural Research Centers Consortium (ARCC), 2020), “Best Ph.D. Program Dissertation Award” (IIT CoA, 2019), and 2nd place in the U.S. Department of Energy (DOE)’s Race to Zero Design Competition (DOE, 2018). In 2018, she organized the 3rd IIT International Symposium on Buildings, Cities, and Performance. She served as editor of the third issue of Prometheus Journal, which received the 2020 Haskell Award from AIA New York, Center for Architecture.

Prior to joining the University of Washington, she taught at the University of Texas at Arlington and the Illinois Institute of Technology. She also has practiced with several firms and institutions and led design research projects such as developing design codes and prototypes for low-carbon buildings. Most recently, she practiced as an architect with Adrian Smith + Gordon Gill Architecture (AS+GG), where she has been involved in major projects, including the 2020 World Expo. Abbasabadi holds a Ph.D. in Architecture from the Illinois Institute of Technology and Master’s and Bachelor’s degrees in Architecture from Tehran Azad University.

College of Built Environments’ Research Restart Fund Awards Four Grants in First of Two Cycles

The College of Built Environments launched a funding opportunity for those whose research has been affected by the ongoing pandemic. The Research Restart Fund, with awards up to $5,000, has awarded 4 grants in its first of two cycles. A grant was awarded to Real Estate faculty member Arthur Acolin, who is partnering with the City of Seattle’s Office of Planning and Community Development to understand barriers that homeowners, particularly those with lower incomes, face to building Accessory Dwelling Units…

The Effect of Luminance Distribution Patterns on Occupant Preference in a Daylit Office Environment

Van Den Wymelenberg, Kevin; Inanici, Mehlika; Johnson, Peter. (2010). The Effect of Luminance Distribution Patterns on Occupant Preference in a Daylit Office Environment. Leukos, 7(2), 103 – 122.

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Abstract

New research in daylighting metrics and developments in validated digital High Dynamic Range (HDR) photography techniques suggest that luminance based lighting controls have the potential to provide occupant satisfaction and energy saving improvements over traditional illuminance based lighting controls. This paper studies occupant preference and acceptance of patterns of luminance using HDR imaging and a repeated measures design methodology in a daylit office environment. Three existing luminance threshold analysis methods [method1: predetermined absolute luminance threshold (for example, 2000 cd/m(2)), method2: scene based mean luminance threshold, and method3: task based mean luminance threshold] were studied along with additional candidate metrics for their ability to explain luminance variability of 18 participant assessments of 'preferred' and 'just disturbing' scenes under daylighting conditions. Per-pixel luminance data from each scene were used to calculate Daylighting Glare Probability (DGP), Daylight Glare Index (DGI), and other candidate metrics using these three luminance threshold analysis methods. Of the established methods, the most consistent and effective metrics to explain variability in subjective responses were found to be; mean luminance of the task (using method3; (adj)r(2) = 0.59), mean luminance of the entire scene (using method2; (adj)r(2) = 0.44), and DGP using 2000 cd/m(2) as a glare source identifier (using method1; (adj)r(2) = 0.41). Of the 150 candidate metrics tested, the most effective was the 'mean luminance of the glare sources', where the glare sources were identified as 7* the mean luminance of the task position ((adj)r(2) = 0.64). Furthermore, DGP consistently performed better than DGI, confirming previous findings. 'Preferred' scenes never had more than similar to 10 percent of the field of view (FOV) that exceeded 2000 cd/m(2). Standard deviation of the entire scene luminance also proved to be a good predictor of satisfaction with general visual appearance.

Keywords

Glare; Daylight Metrics; Luminance Based Lighting Controls; Discomfort Glare; Occupant Preference; High Dynamic Range