Okechi, Ikechukwu K.; Aguayo, Federico; Torres, Anthony. (2022). Coefficient of Thermal Expansion of Concrete Produced with Recycled Concrete Aggregates. Journal of Civil Engineering and Construction, 11(2), 65-74.
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Abstract
This study presents a comparison between the coefficient of thermal expansion (CTE) of concrete produced with natural aggregate and that of concrete produced with recycled concrete aggregate. In order to achieve this, natural aggregate concrete (NAC) specimens were produced, tested, then crushed and sieved in the laboratory to obtain recycled concrete aggregates, which was then used in the production of recycled aggregate concrete (RAC) specimens. The RAC samples were then tested and compared to the NAC samples. The CTE testing was carried out using a AFTC2 CTE measurement system produced by Pine Instrument Company. In addition to CTE testing, the water absorption, specific gravity, and unit weight of the aggregates was determined. A vacuum impregnation procedure was used for the water absorption test. The recycled aggregate properties showed a significantly higher absorption capacity than that of the natural aggregates, while the unit weight and specific gravity of the recycled aggregate were lower than that of the natural aggregates. The average CTE results showed that both the NAC and the RAC samples expanded similarly. The results show that the CTE of RAC depends on the natural aggregate used in the NAC, which was recycled to produce the RAC. Also, there was no significant difference between the average CTE values of the RAC and that of NAC that could discredit the use of recycled aggregate in concrete.
Keywords
Coefficient of thermal expansion; Recycled concrete aggregate; Natural concrete aggregate.
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
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)
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
Lee, Wonil; Lin, Ken-yu; Johnson, Peter W.; Seto, Edmund Y.w. (2022). Selection of Wearable Sensor Measurements for Monitoring and Managing Entry-level Construction Worker Fatigue: A Logistic Regression Approach. Engineering Construction & Architectural Management (09699988), 29(8), 2905-2923.
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Abstract
Purpose: The identification of fatigue status and early intervention to mitigate fatigue can reduce the risk of workplace injuries. Off-the-shelf wearable sensors capable of assessing multiple parameters are available. However, using numerous variables in the fatigue prediction model can elicit data issues. This study aimed at identifying the most relevant variables for measuring occupational fatigue among entry-level construction workers by using common wearable sensor technologies, such as electrocardiogram and actigraphy sensors. Design/methodology/approach: Twenty-two individuals were assigned different task workloads in repeated sessions. Stepwise logistic regression was used to identify the most parsimonious fatigue prediction model. Heart rate variability measurements, standard deviation of NN intervals and power in the low-frequency range (LF) were considered for fatigue prediction. Fast Fourier transform and autoregressive (AR) analysis were employed as frequency domain analysis methods. Findings: The log-transformed LF obtained using AR analysis is preferred for daily fatigue management, whereas the standard deviation of normal-to-normal NN is useful in weekly fatigue management. Research limitations/implications: This study was conducted with entry-level construction workers who are involved in manual material handling activities. The findings of this study are applicable to this group. Originality/value: This is the first study to investigate all major measures obtainable through electrocardiogram and actigraphy among current mainstream wearables for monitoring occupational fatigue in the construction industry. It contributes knowledge on the use of wearable technology for managing occupational fatigue among entry-level construction workers engaged in material handling activities. [ABSTRACT FROM AUTHOR]; Copyright of Engineering Construction & Architectural Management (09699988) is the property of Emerald Publishing Limited and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Keywords
Construction Workers; Wearable Technology; Logistic Regression Analysis; Fatigue (physiology); Frequency-domain Analysis; Heart Beat; Lifting & Carrying (human Mechanics); Construction Safety; Information And Communication Technology (ict) Applications; Management; Technology
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.
Kandil, Amr; El-Rayes, Khaled; El-Anwar, Omar. (2010). Optimization Research: Enhancing the Robustness of Large-Scale Multiobjective Optimization in Construction. Journal Of Construction Engineering And Management, 136(1), 17 – 25.
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Abstract
Many construction planning problems require optimizing multiple and conflicting project objectives such as minimizing construction time and cost while maximizing safety, quality, and sustainability. To enable the optimization of these construction problems, a number of research studies focused on developing multiobjective optimization algorithms (MOAs). The robustness of these algorithms needs further research to ensure an efficient and effective optimization of large-scale real-life construction problems. This paper presents a review of current research efforts in the field of construction multiobjective optimization and two case studies that illustrate methods for enhancing the robustness of MOAs. The first case study utilizes a multiobjective genetic algorithm (MOGA) and an analytical optimization algorithm to optimize the planning of postdisaster temporary housing projects. The second case study utilizes a MOGA and parallel computing to optimize the planning of construction resource utilization in large-scale infrastructure projects. The paper also presents practical recommendations based on the main findings of the analyzed case studies to enhance the robustness of multiobjective optimization in construction engineering and management.
Keywords
Optimizing Resource Utilization; Trade-off; Highway Construction; Genetic Algorithms; Cost; Model; Network; Design; Colony; Optimization Models; Parallel Processing; Resource Management; Housing; Multiple Objective Analysis; Linear Analysis; Algorithms
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
Lee, Namhun; Schaufelberger, John E. (2014). Risk Management Strategies for Privatized Infrastructure Projects: Study of the Build-Operate-Transfer Approach in East Asia and the Pacific. Journal Of Management In Engineering, 30(3).
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Abstract
Private-public partnerships have been adopted for the development of public infrastructure to meet the growing demand for public services. Many Asian countries have used the build-operate-transfer (BOT) approach to develop public infrastructure projects. However, the potential benefits of undertaking a BOT project are accompanied by corresponding risks from the private sector's perspective. The objectives of this study are (1)to identify and discuss major risks inherent in the East Asia and Pacific regions, and (2)to propose risk management strategies for future BOT projects to be successful. This paper reports the results of five case study analyses undertaken to review their primary risks and mitigated methods. In addition, this paper proposes some strategies for future BOT projects. Two main categories of risks were analyzed: general risks and project-specific risks. Risk management strategies were suggested for each category of risk. The main finding of this study indicates that the private sector cannot be the only participant in risk management. The host government's active support is the most essential factor for the profitability and economic viability of a BOT project in the East Asia and Pacific regions.
Keywords
Organisational Aspects; Project Management; Public Administration; Public Utilities; Risk Management; Structural Engineering; Risk Management Strategies; Privatized Infrastructure Projects; Build-operate-transfer Approach; East Asia; Private-public Partnerships; Public Services; Asian Countries; Public Infrastructure Projects; Pacific Regions; Future Bot Projects; Project-specific Risks; General Risks; Build-operate-transfer; Privatized Infrastructure
Choi, Kunhee; Lee, Hyun Woo; Bae, Junseo; Bilbo, David. (2016). Time-Cost Performance Effect of Change Orders from Accelerated Contract Provisions. Journal Of Construction Engineering And Management, 142(3).
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Abstract
Accelerated contract provisions (ACPs) such as cost-plus-time (A+B) and incentives/disincentives (I/D) are increasingly common, yet very little is known about their pure time-cost performance effects on change orders. To fill this large knowledge gap, a two-stage research methodology drawing on 1,372 highway improvement projects completed in California was adopted for this study. The Stage I study investigated the marginal change-order impacts of two ACPs, pure A+B and I/D combined with A+B. How ACP change orders affect projects' time-cost performance was numerically modeled and successfully validated over the Stage II study. The results clearly showed that both ACPs led to more schedule-change and cost-change orders than conventionally contracted projects, whereas I/D combined with A+B performed significantly better than pure A+B in terms of the magnitude of schedule-change orders. This conveys an important recommendation to state transportation agencies (STAs) that A+B be used with an I/D provision. The results and numerical models of this study would help STAs better assess and justify the impact of change orders on the duration and cost of projects, enabling them to more effectively use contingency amounts. Use of the models can also benefit contractors requesting a change order because the models can provide them with advanced knowledge of the probable time-cost growth rates specifically for the pursued ACP. (C) 2015 American Society of Civil Engineers.
Keywords
Construction Industry; Contracts; Costing; Incentive Schemes; Numerical Analysis; Order Processing; Performance Evaluation; Roads; Scheduling; Time Management; Transportation; Projects Time-cost Performance Effect; Cost-change Order; Accelerated Contract Provision; Knowledge Gap; California; Acp; Schedule-change Order; State Transportation Agency; Numerical Model; Sta; Incentive; Highway Improvement Project; Labor Productivity; Construction; Impact; Model; Projects; Change Order; Highway Rehabilitation; Decision Modeling; Regression; Validation; Contracting