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.
Bogus, Susan M.; Migliaccio, Giovanni C.; Jin, Ruoyu. (2013). Study of the Relationship between Procurement Duration and Project Performance in Design-Build Projects: Comparison between Water/Wastewater and Transportation Sectors. Journal Of Management In Engineering, 29(4), 382 – 391.
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Abstract
Previous studies on building, industrial, and transportation projects found that projects delivered using design-build tend to perform better than projects delivered with the traditional design-bid-build method. However, performance of design-build projects is affected by various factors, with procurement-related factors being among the most influential. Whereas other aspects of procurement have been largely investigated, the effect of procurement duration on project performance has been studied only for design-build transportation projects. In addition, few studies have focused specifically on the delivery of water/wastewater projects. This paper includes the results of a study on the relationship between procurement duration and performance of water/wastewater design-build projects. The study methodology was based on regression analysis of data from a sample of water/wastewater design-build projects. The results show that unlike the transportation sector, procurement duration has little effect on either schedule or cost performance in the water/wastewater sector. Likely reasons for this difference were then explored through a content analysis of procurement documents. (C) 2013 American Society of Civil Engineers.
Keywords
Design Engineering; Procurement; Project Management; Regression Analysis; Transportation; Waste Management; Procurement Documents; Schedule Performance; Cost Performance; Design-build Transportation Projects; Procurement-related Factors; Design-bid-build Method; Water-wastewater Sectors; Transportation Sectors; Project Performance; Procurement Duration; Design/build; Project Delivery; Water; Wastewater
El-Anwar, Omar; Chen, Lei. (2014). Maximizing the Computational Efficiency of Temporary Housing Decision Support Following Disasters. Journal Of Computing In Civil Engineering, 28(1), 113 – 123.
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Abstract
Postdisaster temporary housing has long been a challenging problem because of its interlinked socioeconomic, political, and financial dimensions. A significant need for automated decision support was obvious to address this problem. Previous research achieved considerable advancements in developing optimization models that can quantify and optimize the impacts of temporary housing decisions on the socioeconomic welfare of displaced families and total public expenditures on temporary housing as well as other objectives. However, the computational complexity of these models hindered its practical use and adoption by emergency planners. This article analyzes the computational efficiency of the current implementation of the most advanced socioeconomic formulation of the temporary housing problem, which uses integer programming. Moreover, it presents the development of a customized variant of the Hungarian algorithm that has a superior computational performance while maintaining the highest quality of solutions. An application example is presented to demonstrate the unique capabilities of the new algorithm in solving large-scale problems.
Keywords
Decision Support Systems; Emergency Management; Integer Programming; Computational Efficiency; Temporary Housing Decision Support Following Disasters; Financial Dimensions; Political Dimensions; Socioeconomic Dimensions; Socioeconomic Welfare; Emergency Planners; Socioeconomic Formulation; Hungarian Algorithm; Multiobjective Optimization; Maeviz-hazturk; Housing; Computation; Disasters; Temporary Structures; Temporary Housing; Optimization; Disaster Management
Migliaccio, G. C.; Zandbergen, Paul; Martinez, A. A. (2015). Empirical Comparison of Methods for Estimating Location Cost Adjustments Factors. Journal Of Management In Engineering, 31(2).
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Abstract
Location factors are used to adjust conceptual cost estimates by project location. Presently, the construction industry has adopted a simple, proximity-based interpolation method to estimate location factors for missing locations. Although this approach is widely accepted, its validity has not been statistically substantiated. This study assessed the current method of adjusting conceptual cost estimates by project location and compared its performance against two alternative spatial interpolation methods. A Moran's I test was used to confirm the presence of strong spatial autocorrelation, which supports the use of proximity-based methods. Additional statistical evaluations of current and alternative methods were also conducted. Results provided statistical justification for the current method. However, an alternative method was proven to outperform the current method. Moreover, several opportunities for future research were identified as a result of this exploratory study. (C) 2014 American Society of Civil Engineers.
Keywords
Construction Industry; Interpolation; Statistical Analysis; Location Cost Adjustment Factor; Proximity-based Interpolation Method; Project Location; Spatial Interpolation Method; Moran I Test; Spatial Autocorrelation; Statistical Evaluation; Geographical Information-systems; Construction; Layout; Gis; Conceptual Estimating; Geographic Information Systems; Construction Costs; Planning; Location Adjustments
Lee, Wonil; Migliaccio, Giovanni Ciro. (2016). Physiological Cost Of Concrete Construction Activities. Construction Innovation, 16(3), 281 – 306.
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Abstract
Purpose - The purpose of this paper was to investigate the physiological cost of concrete construction activities. Design/methodology/approach - Five concrete construction workers were recruited. The workers' three-week heart rate (HR) data were collected in summer and autumn. In this paper, several HR indexes were used to investigate the physiological cost of work in concrete construction trades, including average working HR, relative HR and ratio of working HR to resting HR. Findings - This paper measures how absolute and relative HRs vary throughout a workday and how working HR compares to resting HR for individual workers. Research limitations/implications - Field observations are usually extremely difficult as researchers need to overcome a number of barriers, including employers' resistance to perceived additional liabilities, employees' fear that their level of activity will be reported to managers and many other practical and technical difficulties. As these challenges increase exponentially with the number of employers, subjects and sites, this study was limited to a small number of subjects all working for the same employer on the same jobsite. Still, challenges are often unpredictable and lessons learned from this study are expected to guide both our and other researchers' continuation of this work. Originality/value - The time effect on the physiological cost of work has not been considered in previous studies. Thus, this study is noteworthy owing to the depth of the data collected rather than the breadth of the data.
Keywords
Concrete; Construction Industry; Costing; Human Resource Management; Occupational Health; Personnel; Physiology; Physiological Cost; Concrete Construction Activity; Construction Workers; Summer; Autumn; Construction Trade; Working Heart Rate; Relative Heart Rate; Resting Heart Rate; Employee Fear; Jobsite; Heart-rate Strain; Stress; Work; Risk; Management; Fusion; Model; Index; Biosensing And Environmental Sensing; Occupational Safety And Health; Threshold Limit Value; Work Physiology
Kim, Jonghyeob; Lee, Hyun Woo; Bender, William; Hyun, Chang-taek. (2018). Model for Collecting Replacement Cycles of Building Components: Hybrid Approach of Indirect and Direct Estimations. Journal Of Computing In Civil Engineering, 32(6).
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Abstract
Building maintenance, repair, and replacement (MR&R) costs are estimated to be two to three times larger than initial construction costs. Thus, it is important to accurately estimate and manage MR&R costs in the planning phase and/or design phase of a construction project based on life cycle cost analysis (LCCA). However, the nature of LCCA requires making necessary assumptions for the prediction and analysis of MR&R costs, and the reliability of the assumptions greatly impacts LCCA results. In particular, determining reasonable replacement cycles is especially important given that each replacement typically involves a significant amount of capital. However, conventional approaches largely focus on either collecting component-specific replacement cases or surveying expert opinions, both of which reduce the usability and reliability of replacement cycle data at an early stage. To overcome these limitations, this study aims to develop a replacement cycle collection model that can expedite the data collection by combining indirect estimations with direct estimations. The development of the model involves collecting replacement cases, developing replacement cycle and index estimation methods, and developing an algorithm to implement the suggested model. As a validation, the applicability and effectiveness of the model were illustrated and tested by using simulated cases based on 21 real-world facilities. This study makes a theoretical contribution to the body of knowledge by developing a replacement cycle data collection model based on long-term and macro perspectives. The developed model will also be of value to practitioners when they try to improve the reliability of their LCCA.
Keywords
Buildings (structures); Life Cycle Costing; Maintenance Engineering; Structural Engineering; Building Components; Building Maintenance; Planning Phase; Design Phase; Construction Project; Life Cycle Cost Analysis; Replacement Cycle Data Collection Model; Construction Costs; Lcca; Maintenance Repair And Replacement Cost; Service Life Prediction; Repair; Replacement; Replacement Cycles; Replacement Index; Database; Indirect Estimations