Emami, Anahita; Sah, Hos Narayan; Aguayo, Federico; Khaleghian, Seyedmeysam. (2022). Experimental Investigations and Empirical Modeling of Rubber Wear on Concrete Pavement. Journal of Engineering Tribology.
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Abstract
Material loss due to wear plays a key role in the service life of rubber components in various tribological applications, such as tires, shoe soles, wiper blades, to name a few. It also adversely affects energy consumption, economy, and CO2 emissions around the globe. Therefore, understanding and modeling the wear behavior of rubbers are important in the design of economic and environment-friendly rubber compounds. In this study, we investigated the effect of normal load and sliding velocity on the wear rate of rubber compounds widely used in the tire treads and evaluated the wear models previously proposed for rubbers to determine the best model to predict the rubber wear rate. The sliding wear rates of different types of Styrene-Butadiene Rubber (SBR) and Isoprene Rubber (IR) compounds on a broom finish concrete slab were measured for different sliding velocities and normal loads. The experimental results were used to evaluate and discuss different wear models proposed in the literature. A new empirical model was proposed to predict the wear rate by considering mechanical properties associated with rubber wear. The experimental results revealed that the wear rate of rubber compounds non-linearly depends on the normal load or friction force, while the effect of sliding velocity on the wear rate is not significant in the 20–100 mm/s range. Moreover, traces of both mechanical (abrasion) and chemical (smearing) wear were observed on all rubber compounds.
Keywords
Tire tread compounds, rubber wear, rubber-concrete interaction, smearing wear and abrasion, wear model
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.
Shang, Luming; Lee, Hyun Woo; Dermisi, Sofia; Choe, Youngjun. (2020). Impact of Energy Benchmarking and Disclosure Policy on Office Buildings. Journal Of Cleaner Production, 250.
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Abstract
Building energy benchmarking policies require owners to publicly disclose their building's energy performance. In the US, the adoption of such policies is contributing to an increased awareness among tenants and buyers and is expected to motivate the owners of less efficient buildings to invest in energy efficiency improvements. However, there is a lack of studies specifically aimed at investigating the impact of such policies on office buildings among major cities through quantitative analyses. In response, this study evaluated the effectiveness of the benchmarking policy on energy efficiency improvements decision-making and on real estate performances, by applying two interrupted time series analyses to office buildings in downtown Chicago. The initial results indicate a lack of statistically strong evidence that the policy affected the annual vacancy trend of the energy efficient buildings (represented by ENERGY STAR labeled buildings). However, the use of interrupted time series in a more in-depth analysis shows that the policy is associated with a 6.7% decrease in vacancy among energy efficient buildings. The study proposed a method to quantitatively evaluate the impact of energy policies on the real estate performance of office buildings, and the result confirms the positive impact of energy-efficient retrofits on the real estate performance. The study findings support the reasoning behind the owners' decision in implementing energy efficiency improvements in their office buildings to remain competitive in the market. (C) 2019 Elsevier Ltd. All rights reserved.
Keywords
Office Buildings; Building Failures; Time Series Analysis; Real Property; Energy Consumption; Metropolis; Building Performance; Chicago (ill.); Building Energy Benchmarking And Disclosure Policies; Building Energy Efficiency; Time Series Modeling; Energy Star (program); Building Management Systems; Buildings (structures); Decision Making; Energy Conservation; Maintenance Engineering; Time Series; Disclosure Policy; Energy Benchmarking Policies; Building; Benchmarking Policy; Energy Efficiency Improvements Decision-making; Estate Performance; Energy Efficient Buildings; Energy Star; Energy Policies; Energy-efficient Retrofits; Interrupted Time-series; Regression; Behavior; Designs; Building Energy Benchmarking And; Disclosure Policies; Buildings; Cities; Energy Efficiency; Energy Policy; Markets; Quantitative Analysis; United States
Kim, Taehoon; Kim, Yong-woo; Lee, Dongmin; Kim, Minju. (2022). Reinforcement Learning Approach To Scheduling Of Precast Concrete Production. Journal Of Cleaner Production, 336.
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Abstract
The production scheduling of precast concrete (PC) is essential for successfully completing PC construction projects. The dispatching rules, widely used in practice, have the limitation that the best rule differs according to the shop conditions. In addition, mathematical programming and the metaheuristic approach, which would improve performance, entail more computational time with increasing problem size, let alone its models being revised as the problem size changes. This study proposes a PC production scheduling model based on a reinforcement learning approach, which has the advantages of a general capacity to solve various problem conditions with fast computation time and good performance in real-time. The experimental study shows that the proposed model outperformed other methods by 4-12% of the total tardiness and showed an average winning rate of 77.0%. The proposed model could contribute to the successful completion of off-site construction projects by supporting the stable progress of PC construction.
Keywords
Precast Concrete; Reinforcement Learning; Deep Q -network; Production Scheduling; Minimize; Model
Hsieh, Shang-hsien; Lin, Hsien-tang; Chi, Nai-wen; Chou, Kuang-wu; Lin, Ken-yu. (2011). Enabling The Development Of Base Domain Ontology Through Extraction Of Knowledge From Engineering Domain Handbooks. Advanced Engineering Informatics, 25(2), 288 – 296.
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Abstract
Domain ontology, encompassing both concepts and instances, along with their relations and properties, is a new medium for the storage and propagation of domain specific knowledge. A significant problem remains the effort which must be expended during ontology construction. This involves collecting the domain-related vocabularies, developing the domain concept hierarchy, and defining the properties of each concept and the relationships between concepts. Recently several engineering handbooks have described detailed domain knowledge by organizing the knowledge into categories, sections, and chapters with indices in the appendix. This paper proposes the extraction of concepts, instances, and relationships from a handbook of a specific domain to quickly construct base domain ontology as a good starting point for expediting the development process of more comprehensive domain ontology. The extracted information can also be reorganized and converted into web ontology language format to represent the base domain ontology. The generation of a base domain ontology from an Earthquake Engineering Handbook is used to illustrate the proposed approach. In addition, quality evaluation of the extracted base ontology is performed and discussed. (C) 2010 Elsevier Ltd. All rights reserved.
Keywords
Ontology; Earthquake Engineering; World Wide Web; Theory Of Knowledge; Vocabulary; Programming Languages; Domain Handbook; Domain Ontology; Owl; Web Ontology Language; Knowledge Representation Languages; Ontologies (artificial Intelligence); Base Domain Ontology; Knowledge Extraction; Engineering Domain Handbooks; Domain Specific Knowledge Storage; Domain Specific Knowledge Propagation; Domain-related Vocabularies; Domain Concept Hierarchy; Development Process; Web Ontology Language Format; Earthquake Engineering Handbook; Semantic Web; Management; Design