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.
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…
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
Gatti, U.; Migliaccio, G.; Bogus, S.M.; Priyadarshini, S.; Scharrer, A. (2013). Using Workforce’s Physiological Strain Monitoring to Enhance Social Sustainability of Construction. Journal Of Architectural Engineering, 19(3), 179 – 85.
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Abstract
Sustainability is often described in terms of the triple bottom line, which refers to its environmental, economic, and social dimensions. However, the economic and environmental impacts of decisions have been easier to determine than have been the social impacts. One area of social sustainability that is particularly applicable to construction projects is that of construction workforce safety and well-being. This is a critical part of sustainability, and a socially sustainable construction industry needs to consider the safety and well-being of construction workers. However, construction activities are generally physically demanding and performed in harsh environments. Monitoring workers' physical strain may be an important step toward enhancing the social sustainability of construction. Recently introduced physiological status monitors (PSMs) have overcome the past limitations, allowing physical strain to be monitored without hindering workers' activities. Three commercially available PSMs have been selected and tested to assess their reliability in monitoring a construction workforce during dynamic activities. The results show that two of the PSMs are suitable candidates for monitoring the physiological conditions of construction workers. A survey was also conducted among industry practitioners to gain insight into industry needs and challenges for physical strain monitoring.
Keywords
Construction Industry; Environmental Factors; Labour Resources; Occupational Safety; Socio-economic Effects; Sustainable Development; Workforce Physiological Strain Monitoring; Social Sustainability; Socioeconomic Impacts; Environmental Impacts; Social Impacts; Construction Projects; Construction Workforce Safety; Physical Strain
Kim, Sang-Chul; Kim, Yong-Woo. (2014). Computerized Integrated Project Management System for a Material Pull Strategy. Journal Of Civil Engineering And Management, 20(6), 849 – 863.
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Abstract
The purpose of this paper is to present a computerized integrated project management system and report results of a survey on the effectiveness of the system. The system consists of a scheduling system, material management system, labor/equipment system, and safety/quality control system. The backbone system is a scheduling system that adopts a production planning system and a project scheduling system. The lowest level in the scheduling system is a daily work management system, which is linked to each functional management system (i.e. material management system, labor/equipment system, and safety/quality control system). The paper focuses on the material management and scheduling systems to implement a material pull system to reduce material inventories on site. Details of material management and scheduling systems are discussed, and a sample application is presented to demonstrate the features of the proposed computer application system. The paper presents practitioners and researchers with a practical tool to integrate material management and scheduling systems for site personnel.
Keywords
Construction; Lean Construction; Material Management System; Integrated System; Daily Work Management
Sprague, Tyler S. (2015). Products of Place the Era of Reinforced-Concrete Skyscrapers in Seattle, 1921-1931. Pacific Northwest Quarterly, 106(3), 107 – 119.
Ochsner, Jeffrey Karl. (2016). Meditations on the Empty Chair: The Form of Mourning and Reverie. American Imago, 73(2), 131 – 163.
Keywords
Vietnam-veterans-memorial; Photography; Thoughts
Shakouri, Mahmoud; Lee, Hyun Woo; Kim, Yong-woo. (2017). A Probabilistic Portfolio-Based Model for Financial Valuation of Community Solar. Applied Energy, 191, 709 – 726.
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Abstract
Community solar has emerged in recent years as an alternative to overcome the limitations of individual rooftop photovoltaic (PV) systems. However, there is no existing model available to support probabilistic valuation and design of community solar based on the uncertain nature of system performance over time. In response, the present study applies the Mean-Variance Portfolio Theory to develop a probabilistic model that can be used to increase electricity generation or reduce volatility in community solar. The study objectives include identifying the sources of uncertainties in PV valuation, developing a probabilistic model that incorporates the identified uncertainties into portfolios, and providing potential investors in community solar with realistic financial indicators. This study focuses on physical, environmental, and financial uncertainties to construct a set of optimized portfolios. Monte Carlo simulation is then performed to calculate the return on investment (ROI) and the payback period of each portfolio. Lastly, inclusion vs. exclusion of generation and export tariffs are compared for each financial indicator. The results show that the portfolio with the maximum output offers the highest ROI and shortest payback period while the portfolio with the minimum risk indicates the lowest ROI and longest payback period. This study also reveals that inclusion of tariffs can significantly influence the financial indicators, even more than the other identified uncertainties. (C) 2017 Elsevier Ltd. All rights reserved.
Keywords
Solar Energy; Photovoltaic Power Systems; Monte Carlo Method; Market Volatility; Energy Economics; Community Solar; Monte Carlo Simulation; Photovoltaic Systems; Portfolio Theory; Uncertainty; Environmental Uncertainties; Financial Indicator; Financial Uncertainties; Physical Uncertainties; Identified Uncertainties; Probabilistic Model; Mean-variance Portfolio Theory; Probabilistic Valuation; Individual Rooftop Photovoltaic Systems; Financial Valuation; Probabilistic Portfolio-based Model; Investment; Monte Carlo Methods; Photovoltaic Cells; Risk Analysis; Tariffs; Resolution Lidar Data; Electricity Consumption; Pv Systems; Autoregressive Models; Potential Assessment; Generation Systems; Neural-networks; Energy; Buildings; Economic Theory; Electricity; Exports; Probabilistic Models; Risk
Nnaji, Chukwuma; Lee, Hyun Woo; Karakhan, Ali; Gambatese, John. (2018). Developing a Decision-Making Framework to Select Safety Technologies for Highway Construction. Journal Of Construction Engineering And Management, 144(4).
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Abstract
Highway construction has consistently reported relatively high fatality rates largely because of the considerable exposure of workers to live traffic. To address this anomaly, traffic control planners are tasked with making decisions geared toward reducing hazardous situations caused by transiting vehicles and construction equipment. The growing application of technologies to enhance worker safety should be considered during the traffic control planning process. In certain cases, decisions such as choosing among technology options are made using experiential individual knowledge without the application of scientific and systematic decision-making methods. Use of experience-based decision making in this context is largely the result of sparse literature on scientific methods of selecting between alternatives in highway construction work zones. By applying the Choosing by Advantages (CBA) decision-making method, a process that achieves sound and effective decisions, the current study aims to fill the gap in practice by proposing a decision-making framework that could enhance the value-cost selection process of safety technologies in highway construction work zones. A situation that applied work zone intrusion alert technologies (WZIATs) was selected as a case study. Using a focus group session and case projects as an evaluation study process, the proposed framework based on the CBA decision-making process was applied to evaluate three WZIATs. Findings from the current study will benefit safety professionals and practitioners by providing a step-by-step approach to make sound decisions that can enhance the level of safety in highway construction work zones.
Keywords
Construction Equipment; Decision Making; Occupational Safety; Project Management; Road Building; Effective Decisions; Decision-making Framework; Value-cost Selection Process; Highway Construction Work Zones; Work Zone Intrusion Alert Technologies; Cba Decision-making Process; Sound Decisions; Traffic Control Planners; Worker Safety; Traffic Control Planning Process; Technology Options; Scientific Decision-making Methods; Systematic Decision-making Methods; Experience-based Decision Making; Advantages Decision-making Method; Safety Technologies; Knowledge; Signs
Kim, Jonghyeob; Han, Sangwon; Hyun, Chang-taek. (2019). Identification and Reduction of Synchronous Replacements in Life-Cycle Cost Analysis of Equipment. Journal Of Management In Engineering, 35(1).
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Abstract
Life-cycle cost analysis (LCCA) is a methodology used to calculate the total cost of a project from initial planning to final disposal. In conventional approaches, LCCA assumes that regular and preventive maintenance will be performed according to each replacement cycle for individual components, and replacement for each component is considered independently. However, because the components of equipment used in buildings are installed systemically, replacements of major components may cause unexpected replacements of dependent minor components. Therefore, it is necessary to identify additional replacements based on the associations among these related replacement components to achieve a more reliable LCCA. In response, this study proposes an LCCA model that comprehensively considers the relationships among the maintenance components. The development of the model involves identifying relationships among components using social network analysis (SNA), arranging individual replacement timings of the components that reflect these relationships, and analyzing the life-cycle cost (LCC) based on the arranged timing. To validate the model, its applicability and effectiveness was illustrated and tested using 19 components of a rainwater reuse system. This study makes a theoretical contribution to the body of knowledge by suggesting concepts of synchronous relationships and replacements based on SNA. In addition, the use of the model proposed in this study enables practitioners to analyze LCCs that reflect synchronous replacements, which allows more reasonable decision-making considering hidden costs in conventional LCC. (C) 2018 American Society of Civil Engineers.
Keywords
Decision Making; Life Cycle Costing; Preventive Maintenance; Synchronous Replacements; Life-cycle Cost Analysis; Lcca Model; Maintenance Components; Social Network Analysis; Painted Surfaces; Decision-making; Prediction; Model; Risk; Maintenance; Replacement; Synchronous Replacement; Synchronous Relationship; Life-cycle Cost Analysis (lcca); Social Network Analysis (sna)