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STRUCTURAL ASSESSMENT OF COMPOSITE HIGHWAY BRIDGES CONSIDERING VEHICLE-BRIDGE DYNAMIC INTERACTION

ce/papers 2024年第1-2期7卷 165-174页

作者： da Silva, Ana Célia Soares Alencar, Guilherme Santana da Silva, José Guilherme Santos Civil Engineering Post-graduate Program [PGECIV/UERJ Brazil Brazil Brazil

Over time, as the bridge deck pavement deterioration process increases, the calculated vertical translational displacements and stresses are higher. In this context, the chances of mechanical failure occurrence increase and may cause limitation in the service life of steel and composite (steel-concrete) bridges. Thus, the current work presents a methodology for fatigue analysis developed by the authors through the years. The methodology is devoted specifically for the assessment of composite bridges employing the hot-spot local S-N approach and a coupled vehicle-pavement-bridge system considering progressive pavement deterioration with stochastically generated roughness profiles. © 2024 Ernst & Sohn GmbH.

关键词： Deterioration

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Optimization of machine learning models for predicting the compressive strength of fiber-reinforced self-compacting concrete

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Frontiers of Structural and civil engineering 2023年第2期17卷 284-305页

作者： Hai-Van Thi MAI May Huu NGUYEN Son Hoang TRINH Hai-Bang LY Civil Engineering Department University of Transport TechnologyHanoi 100000Vietnam Civil and Environmental Engineering Program Graduate School of Advanced Science and EngineeringHiroshima UniversityHiroshima 739-8527Japan

Fiber-reinforced self-compacting concrete(FRSCC)is a typical construction material,and its compressive strength(CS)is a critical mechanical property that must be adequately *** the machine learning(ML)approach to estimating the CS of FRSCC,the current research gaps include the limitations of samples in databases,the applicability constraints of models owing to limited mixture components,and the possibility of applying recently proposed *** study developed different ML models for predicting the CS of FRSCC to address these *** neural network,random forest,and categorical gradient boosting(CatBoost)models were optimized to derive the best predictive model with the aid of a 10-fold cross-validation technique.A database of 381 samples was created,representing the most significant FRSCC dataset compared with previous studies,and it was used for model *** findings indicated that CatBoost outperformed the other two models with excellent predictive abilities(root mean square error of 2.639 MPa,mean absolute error of 1.669 MPa,and coefficient of determination of 0.986 for the test dataset).Finally,a sensitivity analysis using a partial dependence plot was conducted to obtain a thorough understanding of the effect of each input variable on the predicted CS of *** results showed that the cement content,testing age,and superplasticizer content are the most critical factors affecting the CS.

关键词： compressive strength self-compacting concrete artificial neural network decision tree CatBoost

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Rheological and stability analysis of cement pastes incorporating silica-based wastes

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Particuology 2024年第6期89卷 144-152页

作者： Julia da Rosa Martins Janaíde Cavalcante Rocha Dachamir Hotza Luciano Senff Graduate Program in Materials Science and Engineering(PPGMAT) Federal University of Santa Catarina(UFSC)Florianópolis88040-900SCBrazil Graduate Program in Civil Engineering(PPGEC) Federal University of Santa Catarina(UFSC)Florianópolis88040-900SCBrazil Graduate Program in Chemical Engineering(POSENQ) Federal University of Santa Catarina(UFSC)Florianópolis88040-900SCBrazil Department of Mobility Engineering Federal University of Santa Catarina(UFSC)Joinville89219-600SCBrazil

This study investigates the influence of waste characteristics,especially zeta potential,on the properties of cement pastes and *** focus is to evaluate the impact of the zeta potential of cement particles and waste materials on the sedimentation speed,rheology,and hardening time of stabilized cement *** Cement II F 40,retarder additive,silica,and fly ash were used in the *** pastes were prepared,and during the stabilization period,their rheological properties and pH were *** zeta potential and sedimentation speed of the cement and waste particles were measured at the pH that the pastes presented during the entire stabilization *** the stabilization period,the pastes were subjected to the hardening time *** zeta potential analyses revealed diverse values for the different powder types,with the cement particles exhibiting a zeta potential of−3.0 mV,the silica particles exhibiting−10.5 mV,and the fly ash particles exhibiting−20.3 *** influence of the high zeta potential modulus was observed on the sedimentation speed,with the solution containing fly ash exhibiting a speed of 40.01μm/s,whereas the solution containing only cement exhibited a speed of 99.38μm/*** the pastes,the results indicate that the presence of fly ash particles with a significantly negative zeta potential led to a 16%reduction in hardening time compared to particles with a lower modulus of zeta *** tests showed that the inclusion of fly ash particles prevented the formation of *** the zeta potential influenced agglomerate formation and hardening time,it was found to have no effect on yield stress or viscosity.

关键词： Wastes Zeta potential Setting time Rheometry

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Digital Twin in Prefabricated Construction – Approaches, Challenges and Requirements 41

Digital Twin in Prefabricated Construction – Approaches, Ch...

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41st International Symposium on Automation and Robotics in Construction, ISARC 2024

作者： Rangasamy, Veerakumar Yang, Jyh-Bin Graduate Institute Program of Construction Engineering and Management Department of Civil Engineering National Central University Taiwan

ISBN: (纸本)9780645832211

Digital Twin (DT) is a virtual replica that mirrors physical objects, systems, or entities. In the construction sector, DTs play a crucial role in building management, optimizing energy usage, predicting maintenance, and enhancing building lifecycle management. Although effectively integrated into traditional construction practices, its application in the prefabricated construction (PC) field remains relatively limited. Despite its potential to transform the PC, a significant research gap exists in comprehensive literature addressing the approaches, challenges, and requirements specific to this field. This study aims to bridge this gap through a mixed-method research approach that includes bibliometric analysis and systematic review. Publications related to PC and DT are collected from the Scopus database, followed by bibliometric analysis to offer a quantitative insight into the current research trends, prolific authors, and geographical distribution. Furthermore, this study conducts a systematic review that qualitatively analyzes the objectives of DT applications in PC, explores its methodological approaches, identifies challenges and recommendations for practitioners and researchers, and suggests future needs. The findings highlight the pressing need for standardization, robust data management, and scalable solutions to navigate the complexities. Conclusively, this paper presents a comprehensive conceptual framework to facilitate the application of DT in various phases of PC. The critical limitation is the reliance on the publications on the Scopus database and its potential biases. Excluding the need to expand on more emergent publications, discussing empirical DT studies in PC to highlight interoperability and standardization needs is also required for future research. © 2024 ISARC. All Rights Reserved.

关键词： Cyber Physical System

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Low-cost real-time environmental noise monitoring system design and implementation

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International Journal of Environmental Studies 2024年第3期81卷 1045-1057页

作者： Hamamcı, Samet Feyyaz Doğru, Ahmet Özgür Graduate School Geographical Information Technologies PhD Program Istanbul Technical University Istanbul Turkey Faculty of Civil Engineering Department of Geomatics Engineering Istanbul Technical University Istanbul Turkey

Environmental noise has a negative impact on human health and well-being. Real-time noise monitoring for effective noise control and management helps to identify noise sources and areas with high noise pollution, and potential mitigation strategies in urban planning. This paper reports work with a pilot scale system that can continuously collect noise data to assess noise levels accurately for real-time monitoring of environmental noise, focusing on hardware and software aspects and potential applications. The system permits the transfer of measurement data to the central server computer, with storage and display there, with the code written using Python. This system includes Web integration, with open source technologies to provide data access, and is based on Wi-Fi communication and a Control Card with Wi-Fi technology. © 2023 Informa UK Limited, trading as Taylor & Francis Group.

关键词： Noise pollution

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Application of machine learning technique for predicting and evaluating chloride ingress in concrete

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Frontiers of Structural and civil engineering 2022年第9期16卷 1153-1169页

作者： Van Quan TRAN Van Loi GIAP Dinh Phien VU Riya Catherine GEORGE Lanh Si HO Department of Civil Engineering University of Transport TechnologyHanoi 100000Vietnam Civil and Environmental Engineering Program Graduate School of Advanced Science and EngineeringHiroshima UniversityHiroshima 739-8527Japan

The degradation of concrete structure in the marine environment is often related to chloride-induced corrosion of reinforcement ***,the chloride concentration in concrete is a vital parameter for estimating the corrosion level of reinforcement *** research aims at predicting the chloride content in concrete using three hybrid models of gradient boosting(GB),artificial neural network(ANN),and random forest(RF)in combination with particle swarm optimization(PSO).The input variables for modeling include exposure condition,water/binder ratio(W/B),cement content,silica fume,time exposure,and depth of *** results indicate that three models performed well with high accuracy of prediction(R2⩾0.90).Among three hybrid models,the model using GB_PSO achieved the highest prediction accuracy(R2=0.9551,RMSE=0.0327,and MAE=0.0181).Based on the results of sensitivity analysis using SHapley Additive exPlanation(SHAP)and partial dependence plots 1D(PDP-1D),it was found that the exposure condition and depth of measurement were the two most vital variables affecting the prediction of chloride *** the number of different exposure conditions is larger than two,the exposure significantly impacted the chloride content of concrete because the chloride ion ingress is affected by both chemical and physical *** study provides an insight into the evaluation and prediction of the chloride content of concrete in the marine environment.

关键词： gradient boosting random forest chloride content concrete sensitivity analysis

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A hybrid machine learning model to estimate self-compacting concrete compressive strength

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Frontiers of Structural and civil engineering 2022年第8期16卷 990-1002页

作者： Hai-Bang LY Thuy-Anh NGUYEN Binh Thai PHAM May Huu NGUYEN Civil Engineering Department University of Transport TechnologyHanoi 100000Vietnam Civil and Environmental Engineering Program Graduate School of Advanced Science and EngineeringHiroshima UniversityHiroshima 739-8527Japan

This study examined the feasibility of using the grey wolf optimizer(GWO)and artificial neural network(ANN)to predict the compressive strength(CS)of self-compacting concrete(SCC).The ANN-GWO model was created using 115 samples from different sources,taking into account nine key SCC *** validation of the proposed model was evaluated via six indices,including correlation coefficient(R),mean squared error,mean absolute error(MAE),IA,Slope,and mean absolute percentage *** addition,the importance of the parameters affecting the CS of SCC was investigated utilizing partial dependence *** results proved that the proposed ANN-GWO algorithm is a reliable predictor for SCC’s *** that,an examination of the parameters impacting the CS of SCC was provided.

关键词： artificial neural network grey wolf optimize algorithm compressive strength self-compacting concrete

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Long-term performance: strength and metal encapsulation in alkali-activated iron ore tailings

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Environmental Science and Pollution Research 2024年第34期31卷 47071-47083页

作者： Levandoski, William Mateus Kubiaki Ferrazzo, Suéllen Tonatto Piovesan, Maria Alice Bruschi, Giovani Jordi Consoli, Nilo Cesar Korf, Eduardo Pavan Graduate Program in Environmental Science and Technology Universidade Federal da Fronteira Sul RS Erechim99700-970 Brazil Graduate Program in Civil Engineering Universidade Federal Do Rio Grande Do Sul RS Porto Alegre90035-190 Brazil Undergraduate Program in Environmental and Sanitary Engineering Universidade Federal da Fronteira Sul RS Erechim99700-970 Brazil

Understanding the strength behavior and leaching characteristics of mining tailings stabilized with alkali-activated cements in the short, medium, and long term is crucial for the feasibility of material applications. In this context, this study assessed the stabilization/solidification of iron ore tailings (IOT) using alkali-activated binder (AAB) composed of sugarcane bagasse ash and eggshell lime at curing times of 7, 28, 60, 90, 180, and 365 days. Additionally, leaching tests were conducted, along with the examination of possible changes in the chemical and mineralogical composition resulting from exposure to acidic environments. Tests included unconfined compression strength (UCS), leaching, X-ray diffraction, and Fourier-transform infrared spectroscopy for the IOT-AAB mixtures. The highest increase in UCS was observed between 7 and 60 days, reaching 6.47 MPa, with minimal variation thereafter. The AAB-bonded IOT exhibited no metal toxicity over time. Elements Ba, Mn, Pb, and Zn present in IOT and ash were encapsulated in the cemented matrix, with complete encapsulation of all metals observed from 90 days of curing time. The mineralogy of the stabilized/solidified tailings showed no changes resulting from leaching tests. Characteristic bands associated with the presence of N-A-S–H gel were identified in both pre-leaching and post-leaching samples for all curing times analyzed. Exposure to acidic environments altered bands related to carbonate bonds formed in the IOT-AAB mixture. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2024.

关键词： Lime

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A strategy for out-of-roundness damage wheels identification in railway vehicles based on sparse autoencoders

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Railway engineering Science 2024年第4期32卷 421-443页

作者： Jorge Magalhães Tomás Jorge Rúben Silva António Guedes Diogo Ribeiro Andreia Meixedo Araliya Mosleh Cecília Vale Pedro Montenegro Alexandre Cury CONSTRUCT-LESE School of EngineeringPolytechnic of PortoPortoPortugal CONSTRUCT-LESE Faculty of EngineeringUniversity of PortoPortoPortugal Graduate Program in Civil Engineering Federal University of Juiz de ForaJuiz de ForaBrazil

Wayside monitoring is a promising cost-effective alternative to predict damage in the rolling stock. The main goal of this work is to present an unsupervised methodology to identify out-of-roundness(OOR) damage wheels, such as wheel flats and polygonal wheels. This automatic damage identification algorithm is based on the vertical acceleration evaluated on the rails using a virtual wayside monitoring system and involves the application of a two-step procedure. The first step aims to define a confidence boundary by using(healthy) measurements evaluated on the rail constituting a baseline. The second step of the procedure involves classifying damage of predefined scenarios with different levels of severities. The proposed procedure is based on a machine learning methodology and includes the following stages:(1) data collection,(2) damage-sensitive feature extraction from the acquired responses using a neural network model, i.e., the sparse autoencoder(SAE),(3) data fusion based on the Mahalanobis distance, and(4) unsupervised feature classification by implementing outlier and cluster analysis. This procedure considers baseline responses at different speeds and rail irregularities to train the SAE model. Then, the trained SAE is capable to reconstruct test responses(not trained) allowing to compute the accumulative difference between original and reconstructed signals. The results prove the efficiency of the proposed approach in identifying the two most common types of OOR in railway wheels.

关键词： OOR wheel damage Damage identification Sparse autoencoder Passenger trains Wayside condition monitoring

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INVESTIGATION OF FLEXURAL BEHAVIOUR OF STAINLESS STEEL CHANNEL SECTIONS

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ce/papers 2024年第1-2期7卷 240-249页

作者： de Lima, Cláucio Gonçalves Rodrigues, Monique Cordeiro Pereira, e Fernanda Lins Gonçalves PGECIV – Civil Engineering Post-Graduate Program UERJ – State University of Rio de Janeiro Brazil Structural Engineering Department UERJ – State University of Rio de Janeiro Brazil

In this paper, the design of austenitic stainless steel channel sections subjected to minor axis bending, specifically with tension in the web ("u" orientation) is analyzed. The values of moment resistance are predicted using Eurocode 3 criteria and the Continuous Strength Method (CSM), which are then compared with numerical models to assess effectiveness. The modeling is performed through ANSYS and calibrated with literature tests. It was found that Eurocode presents a considerable disparity in results, as well as an overly cautious response (on average, half the numerical load). The CSM reflects the performance more accurately but still with a certain level of conservatism (on average, around 35% lower). © 2024 Ernst & Sohn GmbH.

关键词： Codes (standards)

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