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2023 IEEE Conference on engineering Informatics, EI 2023

作者： Jayasooriya, Darshana Rajeev, Pathmanathan Sanjayan, Jay Swinburne University of Technology Hawthorn Centre for Smart Infrastructure and Digital Construction Department of Civil & Construction Engineering MelbourneVIC3122 Australia

ISBN: (纸本)9798350338522

Steel fiber reinforced concrete (SFRC) is increasingly employed in civil engineering projects, including the construction of buildings, bridges, and rigid pavements. This growing interest is attributed to the notable advantages SFRC offers in terms of strength and durability, compared to traditional concrete and asphalt pavements. Key factors like the rheological properties, exemplified by the concrete slump, and strength characteristics, such as compressive strength, are crucial in both the design and practical application phases of these projects. Rheological and strength properties of SFRC depend mainly upon the fiber type, fiber geometry while compressive strength of normal concrete basically governs by its water to cement ratio and aggregate characteristics. Having all these various parameters makes the design and planning of SFRC structures complicated for engineers due to the dependency of these aspects towards the final output. In this context, machine learning (ML) techniques have gain huge attention due to their capability in predicting and forecasting interdependency of different variables accurately. In this study, machine learning (ML) technique named artificial neural networks (ANN) is used to predict the rheological and strength properties of SFRC. It was evident that ANN when properly optimized is an effective and robust tool to predict rheological and strength properties of SFRC. These predictions allow planners and engineers to predict performance for civil designs and compromise cost substantially while saving a lot of time and effort. © 2023 IEEE.

关键词： Steel fibers

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Synthesis,Performance,and Mechanism of Polycarboxylate Superplasticizers Containing Adsorption Groups

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Journal of Wuhan University of technology(Materials Science) 2025年第3期40卷 780-791页

作者： GUO Haoping WANG Peng CHEN Jiang ZHU Yiping SHEN Xuetao LOU Rongrong ZHU Senjie XU Xingen LIU Yuan LIU Ke SONG Shaomin LI Fei GE Dongliang Zhejiang Communications Construction Group Co. Ltd.Major Bridge Branch CompanyHangzhou 310051China Jiangsu Bositong New Material Co. Ltd.Huaian 211715China Zhejiang Communications Technology Co. Ltd.Hangzhou 310051China School of Civil and Transportation Engineering Beijing University of Civil Engineering and ArchitectureBeijing 100044China Zhejiang Commu-nications Construction Group Co. Ltd.Hangzhou 310051China

This article presents a preparation method for a tailing sand-specific polycarboxylate superplasticizer(AT9)containing multifunctional adsorption *** designing multifunctional adsorption groups(-COOH)as side chains grafted onto the main chain of conventional polycarboxylate ether,the antiadsorption effect is ***9 was characterized by gel permeation chromatography,and its performance was systematically evaluated in various tailings sand-cement mortar systems.A comparison was made between AT9 and traditional PCE in terms of their effects on the workability of concrete,and the interaction mechanism between AT9 and clay in cementitious systems was *** results indicate that AT9 enhances the adsorption and dispersion effects of polycarboxylate superplasticizers on cement particles,and increases steric hindrance,thereby avoids intercalation adsorption of tailings sand,improves its water-reducing and slump-retaining performance,and also contributes to the strength enhancement of concrete in later stages.

关键词： polycarboxylate superplasticizer molecular design tailings sand highly adsorptive concrete

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construction and Environmental Preservation in the Arctic Zone Applying Modelling

Construction and Environmental Preservation in the Arctic Zo...

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International Scientific Conference Arctic Territorial Development: Challenges and Solutions, ARCTD 2021

作者： Egorov, A.N. Department of Construction Technology Saint Petersburg State University of Architecture and Civil Engineering Saint Petersburg Russia

ISBN: (纸本)9783030996253

The article discusses the impact of temperature rise caused by climate change on the planet to the melting of permafrost in the Arctic zone. Both the positive impact—an increase in areas for active life, and the negative aspects of permafrost thawing are considered: methane release and an increase in the greenhouse effect, soil subsidence, destruction of buildings and structures. It is concluded that it is necessary to develop a methodology for monitoring and engineering influence to the processes of permafrost thawing, in both separate residential areas and all territories of the Arctic zone. In large-scale construction related to the development of territories, it is proposed to actively use construction printers that implement environmentally friendly technologies with minimal impact to the environment and require minimal labor, since have a high level of process automation. The article presents a developed mathematical model according to the criterion of minimizing damage from the negative impact of construction to the environment. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Greenhouse effect

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Investigation of FRP and SFRC Technologies for Efficient Tunnel Reinforcement Using the Cohesive Zone Model

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Structural Durability & Health Monitoring 2024年第2期18卷 161-179页

作者： Gang Niu Zhaoyang Jin Wei Zhang Yiqun Huang China Communications Construction Investment Development Co. Ltd.Fuzhou350000China Rail Transit Branch of China Communications Construction Co. Ltd.Beijing101317China School of Civil Engineering Fujian University of TechnologyFuzhou350118China

Amid urbanization and the continuous expansion of transportation networks,the necessity for tunnel construction and maintenance has become *** this need requires the investigation of efficient,economical,and robust tunnel reinforcement *** paper explores fiber reinforced polymer(FRP)and steel fiber reinforced concrete(SFRC)technologies,which have emerged as viable solutions for enhancing tunnel *** is celebrated for its lightweight and high-strength attributes,effectively augmenting load-bearing capacity and seismic resistance,while SFRC’s notable crack resistance and longevity potentially enhance the performance of tunnel ***,current research predominantly focuses on experimental analysis,lacking comprehensive theoretical *** bridge this gap,the cohesive zone model(CZM),which utilizes cohesive elements to characterize the potential fracture surfaces of concrete/SFRC,the rebar-concrete interface,and the FRP-concrete interface,was employed.A modeling approach was subsequently proposed to construct a tunnel segment model reinforced with either SFRC or ***,the corresponding mixed-mode constitutive models,considering interfacial friction,were integrated into the proposed *** validation and numerical simulations corroborated the accuracy of the proposed ***,this study examined the reinforcement design of tunnel *** a numerical evaluation,the effectiveness of innovative reinforcement schemes,such as substituting concrete with SFRC and externally bonding FRP sheets,was assessed utilizing a case study from the Fuzhou Metro Shield Tunnel construction Project.

关键词： Tunnel segment FRP SFRC cohesive zone model constitutive model fracture process

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Deep convolutional generative adversarial networks for traffic data imputation encoding time series as images

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International Journal of Transportation Science and technology 2023年第1期12卷 1-18页

作者： Tongge Huang Pranamesh Chakraborty Anuj Sharma Civil Constructionand Environmental Engineering DepartmentIowa State UniversityAmesIowa 50011USA Department of Civil Engineering Indian Institute of Technology KanpurKanpurU.P208016India

Sufficient high-quality traffic data are a crucial component of various Intelligent Transportation System (ITS) applications and research related to congestion prediction, speed prediction, incident detection, and other traffic operation tasks. Nonetheless, missing traffic data are a common issue in sensor data which is inevitable due to several reasons, such as malfunctioning, poor maintenance or calibration, and intermittent communications. Such missing data issues often make data analysis and decision-making complicated and challenging. In this study, we have developed a generative adversarial network (GAN) based traffic sensor data imputation framework (TSDIGAN) to efficiently reconstruct the missing data by generating realistic synthetic data. In recent years, GANs have shown impressive success in image data generation. However, generating traffic data by taking advantage of GAN based modeling is a challenging task, since traffic data have strong time dependency. To address this problem, we propose a novel time-dependent encoding method called the Gramian Angular Summation Field (GASF) that converts the problem of traffic time-series data generation into that of image generation. We have evaluated and tested our proposed model using the benchmark dataset provided by Caltrans Performance Management Systems (PeMS). This study shows that the proposed model can significantly improve the traffic data imputation accuracy in terms of Mean Absolute Error (MAE) and Root Mean Squared Error (RMSE) compared to state-of-the-art models on the benchmark dataset. Further, the model achieves reasonably high accuracy in imputation tasks even under a very high missing data rate (>50%), which shows the robustness and efficiency of the proposed model.

关键词： Traffic data imputation Generative adversarial networks Realistic data generation Time-dependent encoding Deep convolutional neural networks

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Eco-Labelling in construction Sector 4

Eco-Labelling in Construction Sector

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4th International Conference on Digital Age and Technological Advances for Sustainable Development, ICDATA 2023

作者： Estokova, Adriana Ondo-Estok, Peter Institute for Sustainable and Circular Construction Technical University of Kosice Faculty of Civil Engineering Košice Slovakia Institute of Technology Economics and Management in Construction Technical University of Kosice Faculty of Civil Engineering Košice Slovakia

ISBN: (纸本)9798350311112

The paper is focused on the analysis of selected eco-labelling programs in the field of construction in various countries. It focuses on the analysis of the number of product and construction groups and the number of construction products' licenses in order to compare individual programs from the point of view of assessing the environmental suitability of construction products. Based on the analysis, it can be concluded that construction product groups in individual countries represent a 14-56% share on the total number of product groups for which environmental requirements are set in the environmental assessment of type I, so called eco-labelling process. The highest percentage of construction groups was identified in the Hong Kong eco-labelling program, on the contrary, the lowest in the Dutch program 'Milieukeur'. Regarding the total number of licenses granted to construction products, the leader is the 'Blue Angel' program in Germany. For a more comprehensive evaluation of eco-labelling programs in the construction sector in particular countries, the eco-labelling coefficient of construction products (ELCCP) was proposed. © 2023 IEEE.

关键词： Building materials

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Research on the Synchronization Theory of the Vibration System of Four Circularly Symmetrical Vibrator 10

Research on the Synchronization Theory of the Vibration Syst...

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2023 10th International Conference on Advanced Manufacturing technology and Materials engineering, AMTME 2023

作者： Zhang, Nan Zhang, Sheng Jia, Yijun Beijing Construction Safety Monitoring Engineering Technology Research Center School of Electromechanical and Vehicle Engineering Beijing University of Civil Engineering and Architecture Beijing102616 China

This dissertation aims to study the synchronization properties of a vibrating system consisting of four oscillators, with three located equidistantly on the same circular trajectory and the fourth exciter situated at the center. This study is divided into three stages. Firstly, by utilizing the Lagrange equation, the dynamic model is developed for the research object, and the differential equation is derived when the body runs stable. Secondly, the differential equation obtained in the previous step is solved using Hamiltonian theory, and the solution of the equation is obtained. The necessary conditions required for the vibration system to achieve stable synchronization are also deduced. Finally, the accuracy of the synchronization characteristics is verified by using simulation techniques. The findings indicate that with specific prerequisites met, four motors can achieve synchronicity while the vibration system maintains stability and elliptical motion of the system centroid. These research outcomes establish a theoretical basis for the development of similar vibrational equipment. © Published under licence by IOP Publishing Ltd.

关键词： Synchronization

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Bearing Analysis of Screw Pile Based on ABAQUS 10

Bearing Analysis of Screw Pile Based on ABAQUS

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10th International Conference on Advances in Machinery, Material Science and engineering Application, MMSE 2024

作者： Liu, Yang Ding, Peng Meng, Fanguang Li, Wei Wu, Bing Chang, Xu Shi, Cheng Deng, Zhiyun Tian, Daopo China Construction First Bureau Group South China Construction Co Ltd Shenzhen518000 China China Construction Science & Technology Group Co. Ltd Beijing100195 China School of Civil Engineering Huaqiao University Xiamen361021 China Department of Hydraulic Engineering Tsinghua University Beijing100084 China School of Civil Engineering Beijing Jiaotong University Beijing100044 China College of Civil Engineering Henan Polytechnic University Jiaozuo454003 China

ISBN: (纸本)9781643685465

A 3D FEM of 'SSP-stratum' was established by ABAQUS. Multi working condition numerical simulation analysis was carried out, compared and analyzed the on-site bearing test data of screw pile to determine the true friction coefficient between pile and soil, and studied the influence of geological conditions and structural types on the bearing performance of pile. Research had shown the pile-soil friction coefficient was about 0.6. Increasing the Young's modulus of the stratum helped to improve the bearing performance of the screw pile. The compressive bearing capacity of circular steel pipe + screw pile (CSSP) was about 2 times higher than that of circular steel pipe (CSP), and the compressive bearing capacity of circular steel pipe + large blade + screw pile (CSBSP) was about 2.4 times higher than that of CSP. The tension bearing capacity of SSP was about 3.4 times higher than that of SP, and the tensile bearing capacity of CSBSP was about 4.9 times higher than that of CSP. The large blades enhanced the load-bearing capacity of the screw section and optimized the stress distribution of the structure. © 2024 The Authors.

关键词： Steel pipe

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Enhancing Flooding Depth Forecasting Accuracy in an Urban Area Using a Novel Trend Forecasting Method

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Water Resources Management 2024年第4期38卷 1359-1380页

作者： Yang, Song-Yue Jhong, You-Da Jhong, Bing-Chen Lin, Yun-Yang Department of Urban Planning and Spatial Information Feng Chia University Taichung407102 Taiwan Department of Water Resources Engineering and Conservation Feng Chia University Taichung407102 Taiwan Department of Civil and Construction Engineering National Taiwan University of Science and Technology Taipei106335 Taiwan

Accurate flood runoff and water level predictions are crucial research topics due to their significance for early warning systems, particularly in improving peak flood level forecasts and reducing time lags. This study proposes a novel method, Trend Forecasting Method (TFM), to improve model accuracy and overcome the time lag problem due to data scarcity. The proposed method includes the following steps: (1) select appropriate input factors causing flood events, (2) determine the most suitable AI method as the basis for forecasting models, (3) a forecasting model using a multi-step-ahead approach and a forecasting model with variation in flood depth as input are developed as compared to the selected model in Step 2, and (4) according to the rising limb and falling limb of a flood hydrograph, the maximum and minimum values predicted by the models above are respectively selected as the final outputs. The application to demonstrate the advantages of the proposed method was conducted in the Annan District of Tainan City, Taiwan. Of all the models tested, the Gated Recurrent Unit (GRU) demonstrated superior accuracy in forecasting flood depths, followed by Long Short-Term Memory (LSTM) and Bidirectional LSTM, with the Back Propagation Neural Network falling behind. With a Nash–Sutcliffe efficiency coefficient (NSE) of 0.56 for the next hour’s forecast, the GRU model’s structure appears particularly fitting for flood depth forecast. However, all four models showed time lag issues. TFM substantially enhanced the GRU model’s forecast accuracy, mitigating the time lag. TFM achieved an NSE of 0.82 for forecasting 10-, 20-, 30-, 40-, 50-, and 60-min lead time. The observed flood depths had a 68% probability of consistent rise or fall, validating TFM’s underlying hypothesis. Furthermore, including an autoregressive model in TFM reduced the time lag problem. © The Author(s), under exclusive licence to Springer Nature B.V. 2024.

关键词： Floods

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construction control of rigid frame-continuous girder bridge based on grey theory

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Journal of engineering and Applied Science 2024年第1期71卷 171页

作者： Wan, Lijun Qiao, Jiaqi Sun, Quansheng Liu, Jingyang School of Civil Engineering and Transportation Northeast Forestry University Harbin150050 China Institute of Cold Regions Science and Engineering Northeast Forestry University Harbin150050 China Heilongjiang Provincial Key Laboratory of Bridge Construction Control Inspection and Reinforcement Technology Harbin150050 China

To address the issue of excessive mid-span deflection in rigid frame-continuous girder bridges during the later stages of normal use and to provide a basis for setting the pre-camber of this bridge type. This study focused on a specific rigid frame-continuous girder bridge. Based on the outcomes of finite element analysis, a GM(1,1) model developed using grey theory was utilized to forecast the vertical deflection of the primary girder in the construction phase of a rigid frame-continuous girder bridge, resulting in notable outcomes. The results suggest that the GM(1,1) model grounded in grey theory offers precise estimations of the vertical deflection of the primary girder during the prestressing tendon tensioning stage, displaying a minimal deviation of merely 1.73 mm compared to actual measurements. Consequently, applying the GM(1,1) model based on grey theory for projecting the vertical deflection of the primary girder in the construction process of rigid frame-continuous girder bridges can advance the accuracy of construction management. Through comparative analysis of measured values estimated values and theoretical values at the construction site, it is evident that the predictive model effectively controls the displacement, thus serving as a reference for construction control in similar projects. © The Author(s) 2024.

关键词： Deflection (structures)

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