Migliaccio, G. C.; Bogus, Susan M.; Cordova-Alvidrez, A. A. (2014). Continuous Quality Improvement Techniques for Data Collection in Asset Management Systems. Journal Of Construction Engineering And Management, 140(4).
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Abstract
Transportation infrastructure assets are among the largest investments made by governmental agencies. These agencies use data on asset conditions to make decisions regarding the timing of maintenance activities, the type of treatment, and the resources to employ. To collect and record these data, agencies often utilize trained evaluators who assess the asset either on site or by analyzing photos and/or videos. These visual assessments are widely used to evaluate conditions of various assets, including pavement surface distresses. This paper describes a Data Quality Assessment & Improvement Framework (DQAIF) to measure and improve the performance of multiple evaluators of pavement distresses by controlling for subjective judgment by the individual evaluators. The DQAIF is based on a continuous quality improvement cyclic process that is based on the following main components: (1)assessment of the consistency over timeperformed using linear regression analysis; (2)assessment of the agreement between evaluatorsperformed using inter-rater agreement analysis; and (3)implementation of management practices to improve the results shown by the assessments. A large and comprehensive case study was employed to describe, refine, and validate the framework. When the DQAIF is applied to pavement distress data collected on site by different evaluators, the results show that it is an effective method for quickly identifying and solving data collection issues. The benefit of this framework is that the analyses employed produce performance measures during the data collection process, thus minimizing the risk of subjectivity and suggesting timely corrective actions. The DQAIF can be used as part of an asset management program, or in any engineering program in which the data collected are subjected to the judgment of the individuals performing the evaluation. The process could also be adapted for assessing performance of automated distress data acquisition systems.
Keywords
Asset Management; Civil Engineering Computing; Data Acquisition; Decision Making; Inspection; Maintenance Engineering; Quality Control; Regression Analysis; Roads; Transportation; Continuous Quality Improvement Techniques; Asset Management System; Governmental Agencies; Transportation Infrastructure Assets; Maintenance Activities; Visual Assessment; Pavement Surface Distresses; Data Quality Assessment & Improvement Framework; Dqaif; Linear Regression Analysis; Interrater Agreement Analysis; Data Collection Process; Automated Distress Data Acquisition System; Manual Pavement Distress; Pavement Management; Quantitative Analysis; Data Collection; Assets; Reliability; Case Studies
El-Anwar, Omar; Chen, Lei. (2016). Automated Community-Based Housing Response: Offering Temporary Housing Solutions Tailored to Displaced Populations Needs. Journal Of Computing In Civil Engineering, 30(6).
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Abstract
Following disasters, emergency management agencies are under immense pressure to make quick decisions regarding the provision of temporary housing, including their locations and types. Such decisions can significantly impact the socioeconomic recovery of displaced families and available budgets for other postdisaster activities. To address these challenges, a new holistic temporary housing planning framework is proposed to offer customized housing plans tailored to the specific social, economic, and psychological needs of displaced families while controlling expenditures. This paper presents the theoretical formulation and implementation details of the community-based housing response pool, which is a comprehensive framework that aims at (1)quantifying the specific needs and preferences of each displaced family, (2)evaluating the ability of housing alternatives to meet those needs, (3)computing temporary housing life cycle costs, and (4)optimizing housing decisions accordingly. The paper also presents an application example to demonstrate and evaluate the optimization model capabilities.
Keywords
Decision Making; Disasters; Emergency Management; Life Cycle Costing; Optimisation; Socio-economic Effects; Town And Country Planning; Automated Community-based Housing Response; Temporary Housing Solutions; Displaced Population Needs; Emergency Management Agencies; Temporary Housing Provision; Housing Locations; Housing Types; Socioeconomic Recovery; Displaced Families; Postdisaster Activity Budgets; Holistic Temporary Housing Planning Framework; Customized Housing Plans Tailored; Expenditure Control; Community-based Housing Response Pool; Housing Alternatives Ability Evaluation; Temporary Housing Life Cycle Cost Computing; Housing Decisions Optimization; Optimization Model Capabilities; Multiobjective Optimization; Maeviz-hazturk; Earthquake
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
Abdirad, Hamid; Dossick, Carrie S. (2019). Normative and Descriptive Models for COBie Implementation: Discrepancies and Limitations. Engineering, Construction And Architectural Management, 26(8), 1820 – 1836.
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Abstract
Purpose The purpose of this paper is to inquire into the reasons why Construction Operation Building Information Exchange (COBie) has not become mainstream across the construction industry despite the significant attempts to promote it. Design/methodology/approach This paper framed and compared the normative model of COBie to a descriptive model of COBie. The normative model was based on the assumptions and planned procedures outlined in the COBie documentation. The descriptive model was developed through a case study of COBie implementation, with ethnographic observations, interviews and artifact analysis as the data collection methods and thematic analysis as the data analysis method. Findings The comparative analysis of the normative and descriptive models showed that the underlying normative assumptions of COBie can be challenged in its implementation. In the case study, implementing COBie disrupted the conventional practice of few participating firms as the data requirements and the expected sequences and timelines of tasks were not aligned with the industry norms for exchanging data. Furthermore, the normative model of COBie could not account for the unanticipated variability in the internal routines of firms for submittal production. Practical implications - COBie, as an instruction-based model, may not provide enough flexibility for some firms to adapt to its requirements such that COBie tasks become integrated with their existing workflows. COBie tasks may become additional efforts, and at times, conflict with the industry norms and firms' routines, and therefore, disrupt the efficiency goals. Originality/value This paper provides empirical evidence to clarify why implementing COBie has not been as efficient for all industry players as expected.
Keywords
Construction Industry; Information Dissemination; Information Systems; Cobie; Hand Over; Information And Communication Technologies; Information Exchanges; Operations; Facilities Management; Bim; Construction; Case Study; Information Exchange; Information And Communication Technology (ict) Applications; Project Hand Over
Rodriguez, Barbara X.; Huang, Monica; Lee, Hyun Woo; Simonen, Kathrina; Ditto, Jim. (2020). Mechanical, Electrical, Plumbing and Tenant Improvements over the Building Lifetime: Estimating Material Quantities and Embodied Carbon for Climate Change Mitigation. Energy And Buildings, 226.
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Abstract
The building industry is expanding its ability to mitigate the environmental impacts of buildings through the application of life cycle assessment (LCA). Most building LCA studies focus on core and shell (C&S) and rarely assess mechanical, electrical, and plumbing (MEP) and tenant improvements (TI). However, C&S typologies in the commercial sector pose particular challenges to achieving net zero carbon due to the numerous renovations these building undergo through during their service life. MEP and TI are installed multiple times over the lifetime of commercial buildings leading to cumulative environmental impact caused by increasing material quantities and embodied carbon (EC). This study aimed to establish a preliminary range of material quantities and embodied carbon impacts for MEP and TI components, focusing on commercial office buildings in the Pacific Northwest. The first research stage involved quantifying material quantities while a second stage aimed to calculate Embodied Carbon Coefficients (ECC) and LCA impacts using different data sources. The embodied carbon estimates ranged from 40 to 75 kg CO(2)e/m(2) for MEP and 45-135 kg CO(2)e/m(2) for TI. However, with recurring instalments during a life span of 60 years the impacts become comparable to known impacts of core and shell systems. (C) 2020 Elsevier B.V. All rights reserved.
Keywords
Embodied Carbon; Life Cycle Assessment; Tenant Improvement; Mechanical; Electrical And Plumbing
Zuidema, Christopher; Austin, Elena; Cohen, Martin A.; Kasner, Edward; Liu, Lilian; Isaksen, Tania Busch; Lin, Ken-Yu; Spector, June; Seto, Edmund. (2022). Potential Impacts Of Washington State’s Wildfire Worker Protection Rule On Construction Workers. Annals Of Work Exposures & Health, 66(4), 419 – 432.
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Abstract
Driven by climate change, wildfires are increasing in frequency, duration, and intensity across the Western United States. Outdoor workers are being exposed to increasing wildfire-related particulate matter and smoke. Recognizing this emerging risk, Washington adopted an emergency rule and is presently engaged in creating a permanent rule to protect outdoor workers from wildfire smoke exposure. While there are growing bodies of literature on the exposure to and health effects of wildfire smoke in the general public and wildland firefighters, there is a gap in knowledge about wildfire smoke exposure among outdoor workers generally and construction workers specifically-a large category of outdoor workers in Washington totaling 200,000 people. Several data sources were linked in this study-including state-collected employment data and national ambient air quality data-to gain insight into the risk of PM2.5 exposure among construction workers and evaluate the impacts of different air quality thresholds that would have triggered a new Washington emergency wildfire smoke rule aimed at protecting workers from high PM2.5 exposure. Results indicate the number of poor air quality days has increased in August and September in recent years. Over the last decade, these months with the greatest potential for particulate matter exposure coincided with an annual peak in construction employment that was typically 9.4-42.7% larger across Washington counties (one county was 75.8%). Lastly, the 'encouraged' threshold of the Washington emergency rule (20.5 mu g m(-3)) would have resulted in 5.5 times more days subject to the wildfire rule on average across all Washington counties compared to its 'required' threshold (55.5 mu g m(-3)), and in 2020, the rule could have created demand for 1.35 million N-95 filtering facepiece respirators among construction workers. These results have important implications for both employers and policy makers as rules are developed. The potential policy implications of wildfire smoke exposure, exposure control strategies, and data gaps that would improve understanding of construction worker exposure to wildfire smoke are also discussed.
Keywords
Particulate Matter; Industrial Safety; Occupational Exposure; Rules; Smoke; Construction Industry; Employment; Occupational Hazards; Descriptive Statistics; Industrial Hygiene; Wildfires; N95 Respirators; Washington (state); Forest Fires; Pm 2.5; Respirator; Wildfire Smoke Protection Rule; Wildland Fire; Pm2 5; Health Impacts; Climate-change; Forest-fire; Exposure; Firefighters; Infiltration
Neff, Gina; Fiore-Silfvast, Brittany; Dossick, Carrie Sturts. (2010). A Case Study of the Failure of Digital Communication to Cross Knowledge Boundaries in Virtual Construction. Information Communication & Society, 13(4), 556 – 573.
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Abstract
When can digital artefacts serve to bridge knowledge barriers across epistemic communities? There have been many studies of the roles new information and communication technologies play within organizations. In our study, we compare digital and non-digital methods of inter-organizational collaboration. Based on ethnographic fieldwork on three construction projects and interviews with 65 architects, engineers, and builders across the USA, we find that IT tools designed to increase collaboration in this setting instead solidify and make explicit organizational and cultural differences between project participants. Our study suggests that deeply embedded disciplinary thinking is not easily overcome by digital representations of knowledge and that collaboration may be hindered through the exposure of previously implicit distinctions among the team members' skills and organizational status. The tool that we study, building information modelling, reflects and amplifies disciplinary representations of the building by architects, engineers, and builders instead of supporting increased collaboration among them. We argue that people sometimes have a difficult time overcoming the lack of interpretive flexibility in digital coordinating tools, even when those tools are built to encourage interdisciplinary collaboration.
Keywords
Digital Communications; Data Transmission Systems; Communication & Technology; Digital Electronics; System Analysis; Building Information Modelling; Collaboration; Qualitative Methods; Teams; Civil Engineering Computing; Digital Communication; Groupware; Knowledge Representation; Organisational Aspects; Virtual Reality; Case Study; Virtual Construction; Knowledge Barriers; Epistemic Community; Interorganizational Collaboration; Ethnographic Fieldwork; Interpretive Flexibility; Digital Coordinating Tool; Digital Collaboration; Technology; Objects; Design; Representations; Organizations
Migliaccio, Giovanni C.; Guindani, Michele; D’Incognito, Maria; Zhang, Linlin. (2013). Empirical Assessment of Spatial Prediction Methods for Location Cost-Adjustment Factors. Journal Of Construction Engineering & Management, 139(7), 858 – 869.
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Abstract
In the feasibility stage of a project, location cost-adjustment factors (LCAFs) are commonly used to perform quick order-of-magnitude estimates. Nowadays, numerous LCAF data sets are available in North America, but they do not include all locations. Hence, LCAFs for unsampled locations need to be inferred through spatial interpolation or prediction methods. Using a commonly used set of LCAFs, this paper aims to test the accuracy of various spatial prediction methods and spatial interpolation methods in estimating LCAF values for unsampled locations. Between the two regression-based prediction models selected for the study, geographically weighted regression analysis (GWR) resulted the most appropriate way to model the city cost index as a function of multiple covariates. As a direct consequence of its spatial nonstationarity, the influence of each single covariate differed from state to state. In addition, this paper includes a first attempt to determine if the observed variability in cost index values could be at least partially explained by independent socioeconomic variables. (C) 2013 American Society of Civil Engineers.
Keywords
Construction Industry; Interpolation; Regression Analysis; Socio-economic Effects; Spatial Prediction Methods; Location Cost-adjustment Factors; Empirical Assessment; Lcaf; Order-of-magnitude Estimates; North America; Unsampled Locations; Spatial Interpolation Methods; Geographically Weighted Regression Analysis; Gwr; Independent Socioeconomic Variables; Inflation; Indexes; Estimation; Geostatistics; Construction Costs; Planning; Budgeting
Migliaccio, G. C.; Bogus, Susan M.; Cordova-Alvidrez, A. A. (2014). Techniques for Continuous Improvement of Quality of Data Collection in Systems of Capital Infrastructure Management. Journal Of Construction Engineering And Management, 140(4).
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Abstract
oLa infraestructura del transporte es una de las mas grandes inversiones que realizan los gobiernos. Las agencias gubernamentales de transporte administran este capital y utilizan la informacion de las condiciones de este para decidir la programacion y tipo de mantenimiento y recursos a ejercer. Para recolectar la informacion pertinente, las agencias emplean evaluadores adiestrados para evaluar la infraestructura, ya sea en sitio o analizando fotografias y/o videos. Las evaluaciones visuales son empleadas para inspeccionar las condiciones de la infraestructura, incluyendo el desgaste de la superficie de los caminos y carreteras. Este articulo describe un Data Quality Assessment & Improvement Framework (DQAIF) (Sistema de Evaluacion y Mejora de la Calidad de la Informacion) para medir y controlar los datos de los evaluadores del deterioro de carreteras, al controlar el criterio de estos. El DQAIF es en un proceso ciclico de Mejora Continua de Calidad compuesto por: a)la evaluacion del nivel de acuerdo entre evaluadores -por medio del analisis estadistico (inter-rater agreement analysis), b)la evaluacion de la consistencia a traves del tiempo -mediante analisis de regresion lineal, y c)la implementacion de practicas gerenciales para mejorar los resultados mostrados en las evaluaciones anteriores. Se llevo a cabo un estudio de caso para validar el sistema propuesto. Los resultados mostraron que el DQAIF es efectivo para identificar y resolver problemas de la calidad de los datos obtenidos en las inspecciones de infraestructura. Con este sistema se garantiza la reduccion del riesgo de la subjetividad y asi aplicar acciones de mantenimiento mas oportunas. El DQAIF puede ser empleado en un programa de gerencia de infraestructura o en cualquier programa de ingenieria en donde la informacion esta sujeta al juicio o criterio personal de los individuos que realizan la evaluacion. Este proceso puede ser adaptado, incluso, para evaluar el desempeno de sistemas automatizados de evaluacion de pavimentos.
Keywords
Manual Pavement Distress; Quality Control; Pavement Management; Inspection; Quantitative Analysis; Data Collection; Assets; Reliability; Construction Materials And Methods
El-Anwar, Omar; Ye, Jin; Orabi, Wallied. (2016). Efficient Optimization of Post-Disaster Reconstruction of Transportation Networks. Journal Of Computing In Civil Engineering, 30(3).
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Abstract
Catastrophes, such as hurricanes, earthquakes, and tsunamis often cause large-scale damage to transportation systems. In the aftermath of these disasters, there is a present challenge to quickly analyze various reconstruction plans and assess their impacts on restoring transportation services. This paper presents a new methodology for optimizing post-disaster reconstruction plans for transportation networks with superior computational efficiency employing mixed-integer linear programming (MILP). The model is capable of optimizing transportation recovery projects prioritization and contractors assignment in order to simultaneously: (1)accelerate networks recovery; and (2)minimize public expenditures. The full methodology is presented in two companion publications, where the focus of this paper is to propose new methods for (1)decomposing traffic analysis; (2)assessing the traffic and cost performance of reconstruction plans; (3)reducing the massive solution search space; and (4)phasing the use of mixed-integer linear programming to optimize the problem. An illustrative example is presented throughout the paper to demonstrate the implementation phases. (C) 2015 American Society of Civil Engineers.
Keywords
Cost Reduction; Disasters; Emergency Management; Integer Programming; Linear Programming; Project Management; Public Finance; Search Problems; Town And Country Planning; Transportation; Solution Search Space Reduction; Cost Performance Assessment; Traffic Performance Assessment; Traffic Analysis; Public Expenditure Minimization; Network Recovery Acceleration; Contractor Assignment; Transportation Recovery Project Prioritization; Milp; Mixed-integer Linear Programming; Post-disaster Reconstruction Plan Optimization; Transportation Service Restoration; Reconstruction Plans; Transportation System Large-scale Damage; Tsunami; Earthquake; Hurricane; Catastrophe; Transportation Network; Post-disaster Reconstruction Optimization; Optimizing Resource Utilization; Natural Disasters; Housing Projects; Construction; Performance; Robustness; Recovery; Plans; Transportation Network Reconstruction; Post-disaster Recovery; Multi-objective Optimization; Computational Cost; Contractors Assignment; Search Space