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Field-Based Assessment of Joint Motions in Construction Tasks with and without Exoskeletons in Support of Worker-Exoskeleton Partnership Modeling and Simulation 22

Field-Based Assessment of Joint Motions in Construction Task...

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Proceedings of the Winter Simulation Conference

作者： Sean Tyler Bennett Peter Gabriel Adamczyk Fei Dai Michael Wehner Dharmaraj Veeramani Zhenhua Zhu Department of Mechanical Engineering University of Wisconsin-Madison Madison WI USA Department of Civil & Environmental Engineering West Virginia University Morgantown WV USA Department of Industrial & Systems Engineering University of Wisconsin-Madison Madison WI USA Department of Civil & Environmental Engineering University of Wisconsin-Madison Madison WI USA

Construction workers are required to perform repetitive, physically demanding manual handling work which may pose severe risks for work-related musculoskeletal disorders and injuries. Exoskeletons have substantial potential to protect worker safety and well-being and increase construction productivity by augmenting and complementing workers' physical abilities. However, a key barrier for their adoption in construction is the lack of rigorous research-based real-world evaluation of the beneficial impact of exoskeleton use in practice. As the foundational step to address this issue, this paper presents a field-based assessment to reconstruct and analyze worker joint motions with and without back- and shoulder-assisted exoskeletons in two construction tasks: pushing/emptying gondolas and installing/removing wooden blocks between steel studs. The findings from this research will inform future investigations on worker-exoskeleton partnership to model and simulate the impact on worker and work performance from various perspectives including biomechanics, ergonomics, productivity, and profitability.

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Reliability of electric vehicle charging infrastructure:A cross-lingual deep learning approach

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Communications in Transportation Research 2023年第1期3卷 81-91页

作者： Yifan Liu Azell Francis Catharina Hollauer M.Cade Lawson Omar Shaikh Ashley Cotsman Khushi Bhardwaj Aline Banboukian Mimi Li Anne Web Omar Isaac Asensio School of Public Policy Georgia Institute of TechnologyAtlanta30332USA Sam Nunn School of International Affairs Georgia Institute of TechnologyAtlanta30332USA School of Civil&Environmental Engineering Georgia Institute of TechnologyAtlanta30332USA H.Milton Stewart School of Industrial and Systems Engineering Georgia Institute of TechnologyAtlanta30332USA School of Computer Science Georgia Institute of TechnologyAtlanta30332USA School of Computer Science Stanford UniversityPalo Alto94305USA School of Economics Georgia Institute of TechnologyAtlanta30332USA Institute for Data Engineering&Science(IDEaS) Georgia Institute of TechnologyAtlanta30332USA

Vehicle electrification has emerged as a global strategy to address climate change and emissions externalities from the transportation *** of charging infrastructure is needed to accelerate technology adoption;however,managers and policymakers have had limited evidence on the use of public charging stations due to poor data sharing and decentralized ownership across *** this article,we use machine learning based classifiers to reveal insights about consumer charging behavior in 72 detected languages including *** investigate 10 years of consumer reviews in East and Southeast Asia from 2011 to 2021 to enable infrastructure evaluation at a larger geographic scale than previously *** find evidence that charging stations at government locations result in higher failure rates with consumers compared to charging stations at private points of *** evidence contrasts with predictions in the *** European markets,where the performance is closer to *** also find that networked stations with communication protocols provide a relatively higher quality of charging services,which favors policy support for connectivity,particularly for underserved or remote areas.

关键词： Electric vehicles Consumer behavior Charging infrastructure Public policy Machine learning Natural language processing Transformer algorithms

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Risk management for bridges: A case study of unforeseen failure mode

Risk management for bridges: A case study of unforeseen fail...

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IABSE Conference Seoul 2020: Risk Intelligence of Infrastructures

作者： Pucci, Alessandro Sousa, Hélder S. Matos, José C. Puppio, Mario Lucio Giresini, Linda Sassu, Mauro Department of Civil Engineering University of Minho Guimarães Portugal Department of Energy Systems Territory and Constructions Engineering University of Pisa Pisa Italy Department of Civil and Environmental Engineering and Architecture University of Cagliari Cagliari Italy

ISBN: (纸本)9783857481758

Risk management plays a crucial role in the stakeholders' decision making because it is directly related to safety, serviceability and economy. There is now a growing concern about how to relocate known risks into an acceptance threshold: this implies the evaluation of several options obtained from hazard scenarios considering the related consequences. In parallel, practitioners usually rely on standard tools for risk assessment, and on structural codes to compute performances. Although this approach is currently widely implemented, this research shows that hazardous situations can arise in properly designed infrastructures, due to errors in management. This paper deals with such issue, also highlighting a gap in current codes that could contribute to losses caused by unforeseen failure modes. In this study, a preliminary FMEA assessment was performed to identify the failure modes that required a deeper quantitative analysis. In a second step, a quantitative analysis was implemented, using a modular methodology that combines reliability theory with a risk-based approach. The results evidenced that a wider analysis focused on the identification of vulnerable areas shall be considered in every stage of the asset management. Furthermore, the dynamic of this process is regulated by the established safety level concerning possible damages to people, production sites and commercial activities. © 2021 IABSE Conference, Seoul 2020: Risk Intelligence of Infrastructures - Report. All rights reserved.

关键词： Risk analysis

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Heterogeneous traffic information provision on road networks with competitive or cooperative information providers

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Transportation Research Part C: Emerging Technologies 2022年 142卷

作者： Xie, Tingting Liu, Yang Department of Industrial Systems Engineering and Management National University of Singapore Singapore Department of Civil and Environmental Engineering National University of Singapore Singapore

This paper studies the long-term effects of heterogeneous information provision on road networks with multiple information providers (IPs). To capture the information heterogeneity resulting from various IPs, we consider that users subscribing to different IPs receive non-identical information sets about the available routes and make route choices within their information sets. We investigate both IPs’ strategic interactions and users’ route choices in a bi-level "leader–follower" game. At the upper level, IPs act as leaders who compete or cooperate to determine the optimal information sets provided for their users to maximize their objectives. Three models are developed to investigate IPs’ strategic interactions, i.e., Nash game, Stackelberg game, and cooperation, in which IPs are non-cooperative, leader and followers, and cooperative, respectively. At the lower level, users act as followers to choose their user-optimal routes based on their received information sets. Wardrop Equilibrium with Multiple Information Classes (WEMIC) is defined to capture users’ route choices. The WEMIC problem is formulated as an equivalent variational inequality (VI) problem. The existence and uniqueness of the VI solution are proved. When IPs play the Nash game, the problem is formulated as an Equilibrium Problem with Equilibrium Constraints (EPEC) with discrete variables and non-continuous payoff functions. To solve the EPEC efficiently, we propose a Binary Coded Nash Dominance based Evolutionary (BCNDE) algorithm embedded with a heuristic method for action space reduction. Finally, numerical experiments with two IPs (a big IP and a small IP) are conducted to analyze the effects of unit information cost in the Nash game and the impact of the leader's strategy in the Stackelberg game, respectively. We find that the small IP may benefit from higher information costs in the Nash game. Moreover, the effects of IPs’ competition and cooperation are compared from both the perspectives of I

关键词： Heuristic methods

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Enhancing landslide susceptibility mapping incorporating landslide typology via stacking ensemble machine learning in Three Gorges Reservoir,China

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Geoscience Frontiers 2024年第4期15卷 78-96页

作者： Lanbing Yu Yang Wang Biswajeet Pradhan Faculty of Engineering China University of GeosciencesWuhan 430074China Research Center of Geohazard Monitoring and Warning in the Three Gorges Reservoir Chongqing 404199China Centre for Advanced Modelling and Geospatial Information Systems(CAMGIS) School of Civil and Environmental EngineeringFaculty of Engineering and ITUniversity of Technology SydneyUltimoNSW 2007Australia Earth Observation Centre Institute of Climate ChangeUniversiti Kebangsaan Malaysia43600 UKMBangiSelangorMalaysia

Different types of landslides exhibit distinct relationships with environmental conditioning ***,in regions where multiple types of landslides coexist,it is required to separate landslide types for landslide susceptibility mapping(LSM).In this paper,a landslideprone area located in Chongqing Province within the middle and upper reaches of the Three Gorges Reservoir area(TGRA),China,was selected as the study area.733 landslides were classified into three types:reservoir-affected landslides,non-reservoir-affected landslides,and *** landslide inventory datasets and 15 landslide conditional factors were trained by three Machine Learning models(logistic regression,random forest,support vector machine),and a Deep Learning(DL)*** comparing the models using receiver operating characteristics(ROC),the landslide susceptibility indexes of three types landslides were acquired by the best performing *** indexes were then used as input to generate the final map based on the Stacking *** results revealed that DL model showed the best performance in LSM without considering landslide types,achieving an area under the curve(AUC)of 0.854 for testing and 0.922 for ***,when we separated the landslide types for LSM,the AUC improved by 0.026 for testing and 0.044 for ***,this paper demonstrates that considering different landslide types in LSM can significantly improve the quality of landslide susceptibility *** maps in turn,can be valuable tools for evaluating and mitigating landslide hazards.

关键词： Landslide susceptibility mapping Deep learning model Landslide types Stacking method

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Composting of recovered rock wool from hydroponics for the production of soil amendment

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environmental Science and Pollution Research 2024年第20期31卷 29280-29293页

作者： Istenič, Darja Prosenc, Franja Zupanc, Neva Turel, Matejka Holobar, Andrej Milačič, Radmila Marković, Stefan Mihelič, Rok Faculty of Health Sciences University of Ljubljana Zdravstvena pot 5 Ljubljana Slovenia Faculty of Civil and Geodetic Engineering University of Ljubljana Jamova cesta 2 Ljubljana Slovenia BioResource Systems Research Group School of Civil Engineering University of Leeds LeedsLS2 9JT United Kingdom Knauf Insulation d.o.o Trata 32 Škofja Loka Slovenia ECHO Instruments d.o.o Zeče 25 Slovenske Konjice Slovenia Department of Environmental Sciences Jožef Stefan Institute Jamova cesta 39 Ljubljana Slovenia Department of Agronomy Biotechnical Faculty University of Ljubljana Jamnikarjeva 101 Ljubljana Slovenia

Due to its fibrous structure and high water holding capacity, rock mineral wool (RMW) has boosted the development of hydroponics. Consequently, the amount of waste RMW has also increased tremendously, which has stimulated the research and development of RMW reuse options. In this study, composting and degradability of RMW from hydroponics (gRMW) were tested in combination with different ratios of biowaste compost, including physical and chemical properties of the starting and final materials, and potential ecological hazards of the final product. gRMW had high water holding capacity and low organic matter content, which was easily degradable. Limits of toxic elements according to EU regulation were not exceeded. Degraded gRMW mixtures with compost did not exhibit toxicity to plants or aquatic bacteria and showed intermediate or limited habitat function for earthworms, which preferred the sole gRMW not mixed with compost. Overall, degraded gRMW exhibited parameters of safe soil amendment. © The Author(s) 2024.

关键词： Horticulture

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Characterization of Ralstonia Insidiosa C1 Isolated from Alpine Regions: Capability in Pha Degradation and Production

SSRN

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SSRN 2024年

作者： Chang, Young-Cheol Suzuki, Hinako Terayama, Takumi Reddy, M. Venkateswar Mawatari, Yasuteru Seki, Chigusa Sarkar, Omprakash Course of Chemical and Biological Engineering Division of Sustainable and Environmental Engineering Muroran Institute of Technology Hokkaido050-8585 Japan Department of Civil and Environmental Engineering Colorado State University Fort CollinsCO80523 United States Department of Sciences and Informatics Course of Chemical and Biological Systems Muroran Institute of Technology 27-1 Mizumoto Muroran050-8585 Japan Biochemical Process Engineering Division of Chemical Engineering Department of Civil Environmental and Natural Resources Engineering Luleå University of Technology Luleå971 87 Sweden

This study diverges by investigating the potential degradation of poly-3-hydroxybutyrate (PHB), a biodegradable plastic, in upstream locales such as alpine regions. PHB-degrading bacteria were identified in both campus soil, representing a residential area, and Kurodake soil, an alpine expanse in Hokkaido, Japan. Notably, campus soil exhibited greater microbial diversity. Conversely, Ralstonia insidiosa C1, isolated from Kurodake soil, demonstrated the highest PHB degradation proficiency. R. insidiosa C1 efficiently degraded up to 3% (w/v) of PHB and various films, including PBAT, P(3HB-co-3HV), and PHBH, at 14 ºC. This bacterium synthesized PHB using substrates such as 3-hydroxybutyric acid (3-HB), sugars, and acetic acid. Additionally, it produced P(3HB-co-3HV) using a mixture of fatty acids. Analysis verified that the biopolymer synthesized by strain C1 using glucose was PHB. The distinctive capability of R. insidiosa C1, encompassing both the production and degradation of bioplastics, underscores its potential to establish a novel material circulation model. © 2024, The Authors. All rights reserved.

关键词： Soils

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A Macroscopic Fundamental Function Aided Neural Networks For Traffic Flows Prediction From Mobile Signaling Data

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IEEE Internet of Things Journal 2024年

作者： Fang, Jie Wu, Xiongwei Xu, Mengyun Li, Chunping Wu, Xuesong Li, Li Fujian Expressway Science and Technology Innovation Research Institute Co. Ltd Fujian Fuzhou350001 China Fuzhou University College of Civil Engineering Fujian Fuzhou350108 China National University of Singapore Civil and Environmental Engineering Singapore Singapore Shenzhen Campus of Sun Yat-sen University School of Intelligent Systems Engineering Guangdong Shenzhen518107 China

The widespread deployment of the Internet of Things (IoT) allows for the utilization of mobile signaling data (MSD) in cellular networks to perceive the underlying traffic states on road networks. Nevertheless, the application of MSD for traffic flow prediction can be impeded by the limited positioning accuracy of MSD and stringent privacy policies. To surmount these obstacles, we propose a traffic flow prediction method that integrates an estimation process using a macroscopic fundamental function (M) with a positional factor (P), combined with the sequence-to-sequence (S2S) neural networks model (MPS2S). First, we estimate traffic flow using a macroscopic fundamental function (M). In this approach, we introduce a positional factor (P) that fuses road inflows and outflows to capture the relationship between cellular network and road network. Next, we employ a S2S neural network model, which considers the spatial and temporal aggregation information to infer future traffic flows. Specifically, an encoder estimates traffic parameters from MSD, a decoder infers multi-step traffic flows, and a coefficients estimation method introduces the macroscopic fundamental function into the neural network. To validate the prediction performance of our proposed model, we collect video data from roadside cameras to measure ground truth values. In addition, we analyze the impact of the positional factor on our estimation method and the impact of spatial and temporal aggregation on our prediction model in real-world freeway scenarios. The results indicate that MSD can link the potential traffic information, and our method contributes to better traffic flow prediction. © 2014 IEEE.

关键词： Cellular neural networks

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Rapid onset hazards,fault-controlled landslides and multi-method emergency decision-making

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Journal of Mountain Science 2022年第5期19卷 1357-1369页

作者： GUO Fu-yun MENG Xing-min QI Tian-jun DIJKSTRA Tom THORKILDSEN Jarsve Kristine YUE Dong-xia CHEN Guan ZHANG Yi DOU Xiao-dong SHI Peng-qing College of Earth and Environmental Sciences MOE Key Laboratory of Western China's Environmental SystemsLanzhou UniversityLanzhou 730000China Geological Environment Monitoring Lnstitute of Gansu Province Lanzhou 730050China School of Earth Sciences Lanzhou UniversityLanzhou 730000China Technology&Innovation Centre for Environmental Geology and Geohazards Prevention Lanzhou 730000China School of Architecture Building and Civil EngineeringLoughborough UniversityLoughboroughLE113TUUK

Numerous large-scale fragmented bedrock landslides developed along major fault system is a world-wide phenomenon,which are often characterized with repeated reactivation throughout *** to the large-scale and deep-seated features,it is normally difficult to control such landslides,which in turn pose great threat to local residents and ***,monitoring and forecasting these gigantic landslides has become a key protocol for risk *** paper introduces such a typical massive landslide,named Yahuokou landslide,besides Min River in Zhouqu County,Gansu Province,*** on July 16,2019 with a volume of approximately 4×106 m3,moving slowly and transitionally starting from top part,its toe had partially blocked the Min River and destroyed roads and houses eventually by August 11,*** to emergency response for such huge slowmoving landslide,there is no standard national ***,how to make effective emergency decision has become a *** on previous experiences,integrated multi-methods,including UAV imagery interpretation,we applied GNSS monitoring and field investigations in the early stages of landsliding,in order to assist the *** results show that the movement path of the current displacement is consistent with that of the 1989 reactivation event,and the slide body was separated into three relatively independent blocks with different sliding velocities and responses to *** upper and lower blocks appeared less affected by rainfall,while the middle block responded more to the changes in *** proves that the combined approaches using a variety of monitoring techniques can play an effective role in the monitoring of rapidly deformed transitional largescale landslides,and can also provide a set of reference methods for the emergency disposal of similar landslide hazards.

关键词： Yahuokou landslide Rapid detection Disaster pattern Movement process

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Design and Evaluation of Modular Gas and Wind Sensing Nodes for Static and Mobile Deployments

Design and Evaluation of Modular Gas and Wind Sensing Nodes ...

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IEEE/ASME (AIM) International Conference on Advanced Intelligent Mechatronics

作者： Wanting Jin Emmanuel Droz Alcherio Martinoli Distributed Intelligent Systems and Algorithms Laboratory School of Architecture Civil and Environmental Engineering École Polytechnique Fédérale de Lausanne (EPFL) Lausanne Switzerland

ISBN: (数字)9798350355369

ISBN: (纸本)9798350355376

Static and mobile sensor nodes can be employed in gas monitoring tasks to detect gas leaks in an early stage and localize gas sources. Due to the intermittent nature of gas plumes and the slow dynamics of commonly used gas sensors, measuring gas concentrations accurately and timely poses significant challenges. These challenges are exacerbated when measurements are gathered while moving. Actively sniffing in the airflow, facilitated by actuators, holds the potential to improve the quality of measurements obtained by the sensor nodes. In this paper, we present the design of a small-scale, modular sensor node endowed with gas and wind sensing modalities. To assess the benefits of active sampling and the rationale behind this enhancement, comparisons among three different air sampling modes in both static and mobile settings are conducted. Our findings suggest that passive sampling can adequately capture the primary features of gas plumes given sufficient exposure and measuring time at each position. However, active sampling enhances the responsiveness of sensor nodes, enabling the detection of more detailed fluctuations in the gas concentration and thus alleviating spatial shifts in the sensor response induced by mobility effects.

关键词： Actuators Mechatronics Fluctuations Position measurement Time measurement Sensors Task analysis

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