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Coefficient of Thermal Expansion of Concrete Produced with Recycled Concrete Aggregates

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.

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

Selection of Wearable Sensor Measurements for Monitoring and Managing Entry-level Construction Worker Fatigue: A Logistic Regression Approach

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

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.

Research Validation: Challenges and Opportunities in the Construction Domain

Lucko, Gunnar; Rojas, Eddy M. (2010). Research Validation: Challenges and Opportunities in the Construction Domain. Journal Of Construction Engineering And Management, 136(1), 127 – 135.

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Abstract

Validation of the research methodology and its results is a fundamental element of the process of scholarly endeavor. Approaches used for construction engineering and management research have included experiments, surveys and observational studies, modeling and simulation, theory building, case studies, and various subtypes thereof. Some studies use more than one approach. A particular contribution of this paper is that it reviews different types of validation using examples of studies, analyzes the specific challenges that were found to be significant, and presents how they were successfully overcome in each case. Another contribution is that it describes new opportunities for research validation that are emerging at the horizon as well as ongoing collaborative efforts to enhance the access of construction researchers to validation tools. This paper increases the awareness of the paramount role that validation techniques play in scholarly work by providing readers with recommendations to properly validate their own research efforts.

Keywords

Labor Productivity; Regression-models; Delivery-systems; Performance; Cost; Methodology; Management; Framework; Control Methods; Delphi Method; Models; Research Needs; Sampling Design; Statistical Analysis; Surveys; Validation; Verification

Guideline for Building Information Modeling in Construction Engineering and Management Education

Lee, Namhun; Dossick, Carrie S.; Foley, Sean P. (2013). Guideline for Building Information Modeling in Construction Engineering and Management Education. Journal Of Professional Issues In Engineering Education And Practice, 139(4), 266 – 274.

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Keywords

Buildings (structures); Computer Aided Instruction; Construction Industry; Educational Courses; Management Education; Structural Engineering Computing; Building Information Modeling; Construction Engineering And Management Education; Cem Education; Bim; Cem Curriculum

Continuous Quality Improvement Techniques for Data Collection in Asset Management Systems

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

Automated Community-Based Housing Response: Offering Temporary Housing Solutions Tailored to Displaced Populations Needs

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