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An alternative approach to improve the compatibility of PCE in cement paste blend with coal gangue powder

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Waste Disposal and Sustainable Energy 2024年第1期6卷 139-150页

作者： Zonglin Xie Yuxuan Li Dahui Sun Yi Tian Jinyuan Hu Qiang Yuan Zheng Chen School of Civil engineering Central South UniversityChangshaChina China railway NO.9 Group CO. LTDShenyangChina national engineering Research Center for high-speed railway construction technology ChangshaChina Guangxi Key laboratory of Disaster Prevention and engineering Safety Guangxi UniversityNanningChina

Coal gangue(CG)is an environmental waste that faces an urgent demand for disposal in *** utilization of CG in construction materials has broad application prospects and gained increasing ***,the poor compatibility of polycarboxylate superplasticizer(PCE)with CG powder hinders its efficiency in a wide range of ***,this paper attempts to improve the compatibility of PCE with CG powder in cement paste based on the regulation of aggregation and the adsorption behavior of *** light scattering(DLS)and fluorescence spectroscopy tests were carried out to understand the improved *** results indicated that the addition of CG powder increases the ionic strengths of the cement liquid phase,which makes PCE tend to aggregate at a lower concentration compared with no CG powder ***(CH_(3)COO)_(2)Cu is beneficial for enhancing the workability of cement paste by reducing PCE aggregation while maintaining the compressive strength of cement ***,(CH_(3)COO)_(2)Cu extra addition can be regarded as an effective and sustainable way to improve the workability of cement paste with CG powder.

关键词： Coal gangue powder Polycarboxylate superplasticizer Compatibility Aggregation

Automatic Road Tunnel Crack Inspection Based on Crack Area Sensing and Multiscale Semantic Segmentation

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Computers, Materials & Continua 2024年第4期79卷 1679-1703页

作者： Dingping Chen Zhiheng Zhu Jinyang Fu Jilin He College of Mechanical and Electrical engineering Central South UniversityChangsha410083China Department of Geotechnical Guangdong Hualu Transportation Technology Company LimitedGuangzhou510000China national engineering Research Center of high-speed railway construction technology Changsha410075China

The detection of crack defects on the walls of road tunnels is a crucial step in the process of ensuring travel safetyand performing routine tunnel maintenance. The automatic and accurate detection of cracks on the surface of roadtunnels is the key to improving the maintenance efficiency of road tunnels. Machine vision technology combinedwith a deep neural network model is an effective means to realize the localization and identification of crackdefects on the surface of road *** propose a complete set of automatic inspection methods for identifyingcracks on the walls of road tunnels as a solution to the problem of difficulty in identifying cracks during manualmaintenance. First, a set of equipment applied to the real-time acquisition of high-definition images of walls inroad tunnels is designed. Images of walls in road tunnels are acquired based on the designed equipment, whereimages containing crack defects are manually identified and selected. Subsequently, the training and validationsets used to construct the crack inspection model are obtained based on the acquired images, whereas the regionscontaining cracks and the pixels of the cracks are finely labeled. After that, a crack area sensing module is designedbased on the proposed you only look once version 7 model combined with coordinate attention mechanism (CAYOLOV7) network to locate the crack regions in the road tunnel surface images. Only subimages containingcracks are acquired and sent to the multiscale semantic segmentation module for extraction of the pixels to whichthe cracks belong based on the DeepLab V3+ network. The precision and recall of the crack region localizationon the surface of a road tunnel based on our proposed method are 82.4% and 93.8%, respectively. Moreover, themean intersection over union (MIoU) and pixel accuracy (PA) values for achieving pixel-level detection accuracyare 76.84% and 78.29%, respectively. The experimental results on the dataset show that our proposed two-staged

关键词： Road tunnel crack inspection crack area sensing multiscale semantic segmentation CA-YOLO V7 DeepLab V3+

Debris Flow Susceptibility Evaluation in Meizoseismal Region:A Case Study in Jiuzhaigou,China

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Journal of Earth Science 2024年第1期35卷 263-279页

作者： Yongwei Li Linrong Xu Yonghui Shang Shuyang Chen School of Civil engineering Central South UniversityChangsha 410075China national engineering Research Center of high-speed railway construction technology Central South UniversityChangsha 410075China School of Civil engineering Central South University of Forestry and TechnologyChangsha 410004China

Jiuzhaigou is situated on a mountain-canyon region and is famous for frequent tectonic *** abundance of loose co-seismic landslides and collapses were produced on gullies after the Jiuzhaigou Earthquake on August 8,2017,which was served as material source for debris flow in later *** flow appears frequently which are seriously endangering the safety of people's lives and *** the earliest debris flow appeared in areas where no case ever reported *** debris flow susceptibility evaluation(DFSE)is used for predicting the areas prone to debris flow,which is urgently required to avoid hazards and help to guide the strategy of preventive ***,this work employs debris flow in Jiuzhaigou to reveal the characteristics of disaster-pregnant environment and to explore the application of machine learning in *** new viewpoints are suggested:(i)Material density factor of debris flow is first adopted in this work,and it is proved to be a critical factor for triggering debris flows by sensitivity analysis method.(ii)Deep neural network and convolutional neural network(CNN)achieve relatively good area under the curve(AUC)values and are 0.021-0.024 higher than traditional machine learning methods.(iii)Watershed units combined with CNNbased model can achieve more accurate,reliable and practical susceptibility *** work provides an idea for prevention of debris flow in mountainous lands.

关键词： machine learning earthquakes debris flow susceptibility convolutional neural network deep neural network watershed unit

基于贝叶斯自优化Bi-LSTM组合网络的高速铁路轨道-桥梁系统震后响应预测方法

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Journal of Central South University 2024年第3期31卷 965-975页

作者：彭康蒋丽忠周旺保余建向平吴凌旭 national engineering Research Center of high-speed railway construction technology Central South UniversityChangsha 410075China

中国高速铁路(HSR)规划建设逐渐向地震易发地区延伸,亟需一种及时、准确的灾后地震响应快速预测方法,以实现高速铁路系统运输生命线安全的快速评估。本文提出了一种基于贝叶斯自优化双向长短期记忆(Bi-LSTM)网络的快速预测方法,以经过... 详细信息

中国高速铁路(HSR)规划建设逐渐向地震易发地区延伸,亟需一种及时、准确的灾后地震响应快速预测方法,以实现高速铁路系统运输生命线安全的快速评估。本文提出了一种基于贝叶斯自优化双向长短期记忆(Bi-LSTM)网络的快速预测方法,以经过实验验证的高速铁路轨道-桥梁系统有限元模型地震动响应计算数据为样本,将预测地震响应和有限元计算结果进行比较,验证所提方法的精度和鲁棒性,表明该方法在预测高速铁路桥梁结构的非线性地震反应方面是有效的,且高速铁路轨道-桥梁系统的不同预测位置对预测精度的影响不明显;此外,为了降低神经网络训练数据量需求,提出了一种基于离散小波分解的分层聚类算法,结果表明,基于小波分解的分层聚类方法在保证预测精度的同时,有效地减少了训练地震集的输入数量。

关键词：高速铁路轨道-桥梁系统贝叶斯优化 Bi-LSTM神经网络离散小波分解聚类分析

Damage Evolution of Ballastless Track Concrete Exposed to Flexural Fatigue Loads:The Application of Ultrasonic Pulse Velocity,Impact-echo and Surface Electrical Resistance Method

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Journal of Wuhan University of technology(Materials Science) 2024年第2期39卷 353-363页

作者：杨志强李化建 WEN Jiaxing DONG Haoliang HUANG Fali WANG Zhen YI Zhonglai railway engineering Research Institute China Academy of Railway Science Corporation LimitedBeijing 100081China State Key laboratory for Track System of high-speed railway Beijing 100081China School of Civil engineering Beijing Jiaotong UniversityBeijing 100044China

In order to clarify the fatigue damage evolution of concrete exposed to flexural fatigue loads,ultrasonic pulse velocity(UPV),impact-echo technology and surface electrical resistance(SR) method were *** variable based on the change of velocity of ultrasonic pulse(Du) and impact elastic wave(Di)were defined according to the classical damage *** influences of stress level,loading frequency and concrete strength on damage variable were *** experimental results show that Du and Di both present a three-stages trend for concrete exposed to fatigue *** impact elastic wave is more sensitive to the microstructure damage in stage Ⅲ,the critical damage variable,i e,the damage variable before the final fracture of concrete of Di is slightly higher than that of ***,the evolution of SR of concrete exposed to fatigue loads were analyzed and the relationship between SR and Du,SR and Di of concrete exposed to fatigue loads were *** is found that the SR of concrete was decreased with the increasing fatigue cycles,indicating that surface electrical resistance method can also be applied to describe the damage of ballastless track concrete exposed to fatigue loads.

关键词： ballastless track fatigue damage ultrasonic pulse velocity impact-echo surface electrical resistance

Prediction of high-embankment settlement combining joint denoising technique and enhanced GWO-v-SVR method

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Journal of Rock Mechanics and Geotechnical engineering 2024年第1期16卷 317-332页

作者： Qi Zhang Qian Su Zongyu Zhang Zhixing Deng De Chen School of Civil engineering Southwest Jiaotong UniversityChengduChina MOE Key laboratory of high speed railway engineering Southwest Jiaotong UniversityChengduChina

Reliable long-term settlement prediction of a high embankment relates to mountain infrastructure *** study developed a novel hybrid model(NHM)that combines a joint denoising technique with an enhanced gray wolf optimizer(EGWO)-n-support vector regression(n-SVR)***-embankment field measurements were preprocessed using the joint denoising technique,which in-cludes complete ensemble empirical mode decomposition,singular value decomposition,and wavelet packet ***,high-embankment settlements were predicted using the EGWO-n-SVR *** this method,the standard gray wolf optimizer(GWO)was improved to obtain the EGWO to better tune the n-SVR model *** proposed NHM was then tested in two case ***,the influences of the data division ratio and kernel function on the EGWO-n-SVR forecasting performance and prediction efficiency were *** results indicate that the NHM suppresses noise and restores details in high-embankment field ***,the NHM out-performs other alternative prediction methods in prediction accuracy and *** demonstrates that the proposed NHM is effective in predicting high-embankment settlements with noisy field ***,the appropriate data division ratio and kernel function for EGWO-n-SVR are 7:3 and radial basis function,respectively.

关键词： high embankment Settlement prediction Joint denoising technique Enhanced gray wolf optimizer Support vector regression

WT-FCTGN:A wavelet-enhanced fully connected time-gated neural network for complex noisy traffic flow modeling

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Chinese Physics B 2024年第7期33卷 652-664页

作者：廖志芳孙轲刘文龙余志武刘承光宋禹成 School of Computer Science and engineering Central South UniversityChangsha 410083China national engineering Research Center of high-speed railway construction technology Changsha 410075China School of Civil engineering Central South UniversityChangsha 410075China School of Traffic&Transportation engineering Central South UniversityChangsha 410083China

Accurate forecasting of traffic flow provides a powerful traffic decision-making basis for an intelligent transportation system. However, the traffic data's complexity and fluctuation, as well as the noise produced during collecting information and summarizing original data of traffic flow, cause large errors in the traffic flow forecasting results. This article suggests a solution to the above mentioned issues and proposes a fully connected time-gated neural network based on wavelet reconstruction(WT-FCTGN). To eliminate the potential noise and strengthen the potential traffic trend in the data, we adopt the methods of wavelet reconstruction and periodic data introduction to preprocess the data. The model introduces fully connected time-series blocks to model all the information including time sequence information and fluctuation information in the flow of traffic, and establishes the time gate block to comprehend the periodic characteristics of the flow of traffic and predict its flow. The performance of the WT-FCTGN model is validated on the public Pe MS data set. The experimental results show that the WT-FCTGN model has higher accuracy, and its mean absolute error(MAE), mean absolute percentage error(MAPE) and root mean square error(RMSE) are obviously lower than those of the other algorithms. The robust experimental results prove that the WT-FCTGN model has good anti-noise ability.

关键词： traffic flow modeling time-series wavelet reconstruction

A method for support stiffness failure identification in a steel spring floating slab track of urban railway: a case study in China

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Journal of Zhejiang University-Science A(Applied Physics & engineering) 2024年第3期25卷 206-222页

作者： Junyuan ZHENG Caiyou ZHAO Duojia SHI Ping WANG Jian WANG Bolong JIANG Xi SHENG Key laboratoryof high-speed railway engineering Ministry of EducationSouthwest Jiaotong UniversityChengdu 60031China School of Civil engineering Southwest Jiaotong UniversityChengdu 610031China 01 DYNA(Qingdao)Test&Data Co. Ltd.Qingdao 266000China Rail Transit Digital construction and Measurement technology national engineering Research Center China Railway Design CorporationTianjin300308China Institute of Urban Smart Transportation&Safety Maintenance Shenzhen UniversityShenzhen 518060China

The extensive use of steel spring floating slab tracks has effectively addressed the challenge of alleviating the environmental vibrations induced by urban rail transit ***,under the combined action of train dynamic loads and complex environmental factors,problems,such as the fracture of steel spring vibration isolators and suspension vibrations induced by the uneven settlement of the base,often *** failure of isolator support stiffness is often hidden in its early stages and is challenging to identify by conventional detection *** the same time,it will aggravate the wheel-rail interaction,accelerate the deterioration of track structure,and even affect the driving *** study first establishes a detailed coupled train-floating slab track-foundation analytical *** the influence of the vibration isolator support stiffness failure on the dynamic indices of the floating slab track system response is analyzed.A set of defect identification methods that can detect the number of failed steel springs,severity of damage,and their location is ***,an intelligent monitoring system for support stiffness of floating slab track is built by combining the density-based spatial clustering of applications with noise algorithm and statistical data analysis and is applied to a rail line in southern *** a three-year monitoring campaign,a suspension failure and a fracture of a steel spring were each successfully detected and detailed failure information was *** investigation results were consistent with the damage identification *** repair,the track structure dynamic response returned to the average pre-damage level and further deterioration had been *** proposed damage identification methods and monitoring system provide an approach for intelligent identification of track structure support stiffness failures.

关键词： Floating slab track Support stiffness Detailed analytical model Failure identification Monitoring system

Dynamic response and failure process of horizontal-layered fractured structure rock slope under strong earthquake

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Journal of Mountain Science 2024年第3期21卷 882-900页

作者： WANG Tong LIU Xianfeng HOU Zhaoxu XU Jiahang ZHANG Jun YUAN Shengyang JIANG Guanlu HU Jinshan School of Civil engineering Southwest Jiaotong UniversityChengdu 610031China Key laboratory of high-speed railway engineering of Ministry of Education Southwest Jiaotong UniversityChengdu 610031China School of Civil engineering Xinjiang Institute of EngineeringUrumqi 830023China China railway First Survey and Design Institute Group Co.LTD Xi'an 710043China

Rock slope with horizontal-layered fractured structure(HLFS)has high stability in its natural ***,a strong earthquake can induce rock fissure expansion,ultimately leading to slope *** this study,the dynamic response,failure mode,and spectral characteristics of rock slope with HLFS under strong earthquake conditions were investigated based on the large-scale shaking table model *** this basis,multiple sets of numerical calculation models were further established by UDEC discrete element *** influencing factors were considered in the parametric study of numerical simulations,including slope height,slope angle,bedding-plane spacing and secondary joint spacing as well as bedrock dip *** results showed that the failure process of rock slope with HLFS under earthquake action is mainly divided into four phases,i.e.,the tensile crack of the slope shoulder joints and shear dislocation at the top bedding plane,the extension of vertical joint cracks and increase of shear displacement,the formation of step-through sliding surfaces and the instability,and finally collapse of fractured rock *** acceleration response of slopes exhibits elevation amplification effect and surface *** simulations indicate that the seismic stability of slopes with HLFS exhibits a negative correlation with slope height and angle,but a positive correlation with bedding-plane spacing,joint spacing,and bedrock dip *** results of this study can provide a reference for seismic stability evaluation of weathered rock slopes.

关键词： Seismic behavior Horizontal layered Weathered rock slope Shaking table test Failure mode