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Road sub-surface defect detection based on gprMax forward simulation-sample generation and Swin Transformer-YOLOX

Frontiers of Structural and Civil Engineering 2024年第3期18卷 334-349页

作者： Longjian LI Li YANG Zhongyu HAO Xiaoli SUN Gongfa CHEN School of Civil and Transportation Engineering Guangdong University of TechnologyGuangzhou 510006China JSTI Group Guizhou Engineering survey and design co. Ltd.Guangzhou 510800China Guangzhou Municipal Engineering Testing co. Ltd.Guangzhou 510520China

Training samples for deep learning networks are typically obtained through various field experiments,which require significant manpower,resource and time ***,it is possible to utilize simulated data to augment the training *** this paper,by co.paring the actual experimental model with the simulated model generated by the gprMax[1]forward simulation method,the feasibility of obtaining simulated samples through gprMax simulation is ***,the samples generated by gprMax forward simulation are used for training the network to detect objects in existing real *** the same time,aiming at the detection and intelligent reco.nition of road sub-surface defects,the Swin-YOLOX algorithm is introduced,and the excellence of the detection network,which is improved by augmenting the simulated samples with real samples,is further *** co.paring the prediction performance of the object detection models,it is observed that the model trained with mixed samples achieved a recall of 94.74%and a mean average precision(maP)of 97.71%,surpassing the model trained only on real samples by 12.95%and 15.64%,*** feasibility and excellence of training the model with mixed samples are *** potential of using a fusion of simulated and existing real samples instead of repeatedly acquiring new real samples by field experiment is demonstrated by this study,thereby improving detection efficiency,saving resources,and providing a new approach to the problem of multiple interpretations in ground penetrating radar(GPR)data.

关键词： ground penetrating radar gprMax forward modeling sample generation Swin-YOLOX object detection

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Carbon efficiency modeling and optimization of solar-powered cellular networks

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Science China(Information Sciences) 2024年第5期67卷 228-243页

作者： Yuxi ZHAO Xiaohu GE Wen YAN Tao HAN Yi ZHONG School of Electronic Information and communications Huazhong University of Science and Technology Huawei Technology co. Ltd.

As wireless co.munication traffic experiences rapid growth, the carbon emissions caused by the co.munication industry are also on the rise. To achieve “carbon neutrality”, researchers are co.sidering the use of renewable energy sources to power cellular networks, thereby reducing carbon emissions. However, a challenge arises when using renewable energy, specifically owing to the unpredictable nature of both the energy co.sumption of the cellular network and the power generation from renewable sources. This inco.sistency results in low renewable energy utilization and reduced carbon efficiency. Herein, we co.struct a carbon efficiency model of solar-powered cellular networks using practical data from solar radiation. We propose a mechanism that alternately optimizes the performance of the renewable energy network and the cellular network. This approach is based on co.vex optimization theory and the Dinkelback algorithm, and it leads to the design of a carbon efficiency optimization algorithm. This algorithm aims to improve the carbon efficiency of cellular networks and reduce their carbon emissions. Simulation results demonstrate that our optimization scheme yields a maximum improvement of 2.56 × 108bps/g in the carbon efficiency of the cellular network as co.pared to co.ventional power allocation schemes such as the traditional water filling method and heuristic energy sharing and charge/discharge algorithms.

关键词： cellular networks renewable energy carbon efficiency co.vex optimization theory dinkelbach

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Short-term prediction of on-street parking occupancy using multivariate variable based on deep learning

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Journal of Traffic and Transportation Engineering(English Edition) 2024年第1期11卷 28-40页

作者： Mengqi Lyu Yanjie Ji Chenchen Kuai Shuichao Zhang School of Transportation Southeast UniversityNanjing 211189China Shandong Provincial communications Planning and design Institute Group co. Ltd.Jinan 250101China School of Civil and Transportation Engineering Ningbo University of TechnologyNingbo 315211China

Short-term prediction of on-street parking occupancy is essential to the ITS system,which can guide drivers in finding vacant parking *** the spatial dependencies and exogenous dependencies need to be co.sidered simultaneously,which makes short-term prediction of on-street parking occupancy ***,this paper proposes a deep learning model for predicting block-level parking ***,the importance of multiple points of interest(POI)in different buffers is sorted by Boruta,used for feature *** results show that different types of POI data should co.sider different buffer *** based on the real on-street parking data,long short-term memory(LSTM)that can address the time dependencies is applied to predict the parking *** results demonstrate that LSTM co.sidering POI data after Boruta selection(LSTM(+BORUTA))outperforms other baseline methods,including LSTM,with an average testing MAPE of 11.78%.The selection process of POI data helps LSTM reduce training time and slightly improve the prediction performance,which indicates that co.plex co.relations among the same type of POI data in different buffer zones will also affect the prediction accuracy of *** there are more restaurants on both sides of the street,the prediction performance of LSTM(+BORUTA)is significantly better than that of LSTM.

关键词： Smart parking Parking occupancy Short-term prediction Long short-term memory Boruta

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Local failure mechanism of sand-blocking fence in latticed dune along desert roads

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Journal of Mountain Science 2024年第2期21卷 526-537页

作者： LI Liangying LV Lele LI Qi WANG Zhenqiang YANG Youhai YIN Wenhua School of Civil Engineering Lanzhou Jiaotong UniversityLanzhou 730070China Ningxia Highway survey and design Institute co.Ltd Yinchuan 750001China

The latticed dunes in the Tengger Desert are widely distributed,and the sand-blocking fence placed here are highly susceptible to local failure due to co.plex wind-sand activities,posing a serious threat to the safe operation of the *** explore the local failure mechanism of sand-blocking fence in the latticed dune area,the local failure of sand-blocking fence in the latticed dune areas along the Wuhai-Maqin Highway in China was *** the first main ridge of the latticed dune as the placement location,the structure of the wind-sand flow field of sand-blocking fence placed at top,the bottom and the middle of windward slope was analyzed by co.putational Fluid Dynamics(CFD).The results show that when placed at top of the first main ridge,the wind speed near the sand-blocking fence is the highest,up to 15.23 m/***,the wind load strength on the sand barrier is co.respondingly larger,up to 232.61 N∙*** the strength of material co.tinues to decrease,the nylon net is prone to *** roots of the angle steel posts are susceptible to hollowing by vortex action,which can cause sand-blocking fence to fall over in strong wind *** placed at the bottom of windward slope,wind speed drop near sand-blocking fence is greatest,with the decrease of 12.48-14.32 m/s co.pared to the original wind *** is highly likely to lead to large-scale deposition of sand particles and burial of the sand-blocking *** placed in the middle of windward slope,sand-blocking fence is subjected to less wind load strength(168.61N∙m-2)and sand particles are mostly deposited at the bottom of windward slope,with only a small amount of sand accumulating at the root of sand-blocking *** on field observations and numerical modelling results,when the sand-blocking fence is placed in latticed dune area,it should be placed in the middle of the windward slope of the first main ridge as a matter of *** the sand-blocking fence should be placed

关键词： Latticed dune Sand-blocking fence Local failure Numerical simulation Desert roads

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Investigation of FRP and SFRC Technologies for Efficient Tunnel Reinforcement Using the co.esive 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 co.struction Investment Development co. Ltd.Fuzhou350000China Rail Transit Branch of China communications co.struction co. Ltd.Beijing101317China School of Civil Engineering Fujian University of TechnologyFuzhou350118China

Amid urbanization and the co.tinuous expansion of transportation networks,the necessity for tunnel co.struction and maintenance has beco.e *** this need requires the investigation of efficient,eco.omical,and robust tunnel reinforcement *** paper explores fiber reinforced polymer(FRP)and steel fiber reinforced co.crete(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 co.prehensive theoretical *** bridge this gap,the co.esive zone model(CZM),which utilizes co.esive elements to characterize the potential fracture surfaces of co.crete/SFRC,the rebar-co.crete interface,and the FRP-co.crete interface,was employed.A modeling approach was subsequently proposed to co.struct a tunnel segment model reinforced with either SFRC or ***,the co.responding mixed-mode co.stitutive models,co.sidering interfacial friction,were integrated into the proposed *** validation and numerical simulations co.roborated 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 co.crete with SFRC and externally bonding FRP sheets,was assessed utilizing a case study from the Fuzhou Metro Shield Tunnel co.struction Project.

关键词： Tunnel segment FRP SFRC co.esive zone model co.stitutive model fracture process

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Characteristics and Influencing Factors of Microplastics in Snow in the Inner Mongolia Plateau, China

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Engineering 2024年第6期37卷 69-77页

作者： Hongwei Yu Junrong Shao Huawei Jia Diga Gang Baiwen Ma Chengzhi Hu State Key Laboratory of Environmental Aquatic Chemistry Research Center for Eco-Environmental SciencesChinese Academy of SciencesBeijing 100085China University of Chinese Academy of Sciences Beijing 100049China Changjiang survey PlanningDesign and Research Co.Ltd.Wuhan 430010China

Microplastics(MPs;<5 mm)have beco.e one of the most prominent global environmental pollution *** can spread to high altitudes through atmospheric transport and can be deposited by rainfall or snowfall,potentially thre... 详细信息

Microplastics(MPs;co.e one of the most prominent global environmental pollution *** can spread to high altitudes through atmospheric transport and can be deposited by rainfall or snowfall,potentially threatening the structure and function of natural *** in terrestrial and aquatic eco.ystems alter the growth and functional characteristics of ***,little attention has been given to the possible harm associated with MPs deposited in snow,particularly in the co.text of global climate *** co.lected from surface snow in the Inner Mongolia Plateau,China,were used for quantitative analysis and *** results showed that MPs were easily detected,and the related co.centration was approximately(68±10)–(199±22)MPsL1 in snow *** were the most co.mon morphology,the polymer co.position was largely varied,and the abundance and co.position of MPs were linked to human activity to a great ***-throughput sequencing results showed that the co.position and abundance of microorganisms also differed in snow samples from areas with different MP pollution characteristics,indicating a co.siderable difference in microbial functional *** may have an interference effect on the individual growth and functional expression of microorganisms in *** addition,the results showed that functional living areas(e.g.,landfills and suburban areas)in cities play an important role in the properties of *** instance,the highest abundance of MPs was found in thermal power plants,whereas the abundance of polymers per sample was significantly lower in the suburban *** MP co.taminants hidden in snow can alter microbial structure and function and are therefore a potential threat to eco.ystem health.

关键词： Human activities Snow Microplastics Microbial co.munity Urban function Environmental effect

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co.parative study of different machine learning models in landslide susceptibility assessment: A case study of co.ghua District, Guangzhou, China

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China Geology 2024年第1期7卷 104-115页

作者： Ao Zhang Xin-wen Zhao Xing-yuezi Zhao Xiao-zhan Zheng Min Zeng Xuan Huang Pan Wu Tuo Jiang Shi-chang Wang Jun He Yi-yong Li Wuhan Center China Geological SurveyMinistry of Natural Resources(Geosciences Innovation Center of Central South China)Wuhan 430205China Guangzhou Institute of Geological survey Guangzhou 510080China Hubei Transportation Planning design Institute co. LtdWuhan 430050China

Machine learning is currently one of the research hotspots in the field of landslide *** clarify and evaluate the differences in characteristics and prediction effects of different machine learning models,co.ghua District,which is the most prone to landslide disasters in Guangzhou,was selected for landslide susceptibility *** evaluation factors were selected by using co.relation analysis and variance expansion factor *** four machine learning methods namely Logistic Regression(LR),Random Forest(RF),Support Vector Machines(SVM),and Extreme Gradient Boosting(XGB),landslide models were *** analysis and evaluation of the model were co.ducted through statistical indices and receiver operating characteristic(ROC)*** results showed that LR,RF,SVM,and XGB models have good predictive performance for landslide susceptibility,with the area under curve(AUC)values of 0.752,0.965,0.996,and 0.998,*** model had the highest predictive ability,followed by RF model,SVM model,and LR *** frequency ratio(FR)accuracy of LR,RF,SVM,and XGB models was 0.775,0.842,0.759,and 0.822,*** and XGB models were superior to LR and SVM models,indicating that the integrated algorithm has better predictive ability than a single classification algorithm in regional landslide classification problems.

关键词： Landslides susceptibility assessment Machine learning Logistic Regression Random Forest Support Vector Machines XGBoost Assessment model Geological disaster investigation and prevention engineering

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Geochemical Anomalies Identified by Multifractal Modeling: Implications for Mineral Exploration in the Ziyoutun Cu-Au District, Jilin Province, China

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Acta Geologica Sinica(English Edition) 2024年第4期98卷 1111-1124页

作者： MA Huchao WANG Da BAI Feng LIU Meng GONG Anzhou HU Haiyan State Key Laboratory of Geological Processes and Mineral Resources School of Earth Sciences and ResourcesChina University of GeosciencesBeijing 100083China School of Gemmology China University of GeosciencesBeijing 100083China Guizhou Nengda Electric Power design co. Ltd.Guiyang 550002China Chongqing Chuandongnan survey&design Institute co. Ltd.Chongqing 400038China

The Ziyoutun Cu-Au district is located in the Jizhong–Yanbian Metallogenic Belt and possesses excellent prospects. However, the thick regolith and co.plex tectonic settings present challenges in terms of detecting and deco.position of weak geochemical anomalies. To address this challenge, we initially co.ducted a co.prehensive analysis of 1:10,000-scale soil geochemical data. This analysis included multivariate statistical techniques, such as co.relation analysis, R-mode cluster analysis, Q–Q plots and factor analysis. Subsequently, we deco.posed the geochemical anomalies, identifying weak anomalies using spectrum-area modeling and local singularity analysis. The results indicate that the assemblage of Au-Cu-Bi-As-Sb represents the mineralization at Ziyoutun. In co.parison to co.ventional methods, spectrumarea modeling and local singularity analysis outperform in terms of identification of anomalies. Ultimately, we co.sidered four specific target areas(AP01, AP02, AP03 and AP04) for future exploration, based on geochemical anomalies and favorable geological factors. Within AP01 and AP02, the geochemical anomalies suggest potential mineralization at depth, whereas in AP03 and AP04 the surface anomalies require additional geological investigation. co.sequently, we reco.mend co.ducting drilling, following more extensive surface fieldwork, at the first two targets and verifying surface anomalies in the last two targets. We anticipate these findings will significantly enhance future exploration in Ziyoutun.

关键词： geochemical anomalies multivariate statistical analysis spectrum-area model local singularity analysis mineral prospecting Jilin Province

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Restoring force model of assembled piers co.nected with grouting sleeves and a mortise hybrid joint

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Journal of Traffic and Transportation Engineering(English Edition) 2024年

作者： Shangshun Lin Jianshuai Zhang Zhiqing Qin Shiji Ye Jinbing Zhao Fujian Provincial Key Laboratory of Advanced Technology and Information in Civil Engineering Fujian University of Technology Fujian communications Planning & design Institute co. Ltd. 3. Haoyao Times (Fujian) Group co. Ltd.

In order to investigate the simplified calculation method of the rebound model of the grouted sleeve and mortise-and-tenon hybrid-co.nected assembled reinforced co.crete piers， quasi-static tests were co.ducted on three types of piers: cast-in-place piers (SZT-1)， single-span assembled piers (SG-1)， and double-span assembled piers (SGT-1). It was found that the damage modes and seismic performance of the SGT-1 specimens were similar to those of SG-1， while the seismic performance of the hybrid-co.nected assembled piers was better than that of SZT-1. Parametric analyses were carried out using experimentally-validated finite-element models to investigate the effects of parameters such as axial co.pression ratio， slenderness ratio， longitudinal reinforcement ratio， co.crete strength， and the dimensions and materials of the protruding tenon and steel pipe on the seismic performance of the piers. In addition， the skeleton curve eigenvalue formula and rebound model are proposed， which can be used for elastic-plastic analysis and calculation of hybrid co.nection assembled piers.

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Delineating homogeneous domains of fractured rocks using topological manifolds and deep learning

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Journal of Rock Mechanics and Geotechnical Engineering 2024年第8期16卷 2996-3013页

作者： Yongqiang Liu Jianping Chen Fujun Zhou Jiewei Zhan Wanglai Xu Jianhua Yan co.lege of co.struction Engineering Jilin UniversityChangchun130026China China Railway First survey and design Institute Group co. Ltd.Xi’an710043China co.lege of Geological Engineering and Geomatics Chang’an UniversityXi’an710054China

Determining homogeneous domains statistically is helpful for engineering geological modeling and rock mass stability *** this text,a technique that can integrate lithology,geotechnical and structural information is proposed to delineate homogeneous *** technique is then applied to a high and steep slope along a ***,geological and geotechnical domains were described based on lithology,faults,and shear ***,topological manifolds were used to eliminate the inco.patibility between orientations and other parameters(*** length and roughness)so that the data co.cerning various properties of each disco.tinuity can be matched and characterized in the same Euclidean ***,the influence of implicit co.bined effect in between parameter sequences on the homogeneous domains co.ld be *** learning technique was employed to quantify abstract features of the characterization images of disco.tinuity properties,and to assess the similarity of rock mass *** results show that the technique can effectively distinguish structural variations and outperform co.ventional *** can handle multisource engineering geological information and multiple disco.tinuity *** technique can also minimize the interference of human factors and delineate homogeneous domains based on orientations or multi-parameter with arbitrary distributions to satisfy different engineering requirements.

关键词： Homogeneous domain Geological domain Geotechnical domain Structural domain Topological manifold Deep learning

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