检索结果-南通市图书馆

Non-destructive Testing and Intelligent Evaluation of Road Structural Conditions using GPR and FWD

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Journal of Traffic and transportation engineering(English Edition) 2024年

作者： Zhen Liu Siqi Wang Xingyu Gu Qiao Dong National Demonstration Center for Experimental Road and Traffic engineering Education (Southeast University) Department of Roadway engineering， School of transportation， Southeast University

Aiming at the assessment of road structural conditions， a method of combining ground penetrating radar (GPR) and falling weight deflectometer (FWD) for assessing the pavement structural integrity and strength was proposed in this study. First， 3D GPR was performed to detect the thickness and internal distress of pavement structural layers using the canny edge detection and you only look once version eight (YOLOv8) detection algorithms. Results showed that the error of thickness extraction was approximately 3%， and the distress detection achieved a mean average precision (mAP) of 0.859 and an inference time of 11.43 ms with a GTX 1070 GPU. Then， the extracted thickness was used for the modulus (E) inversion of pavement structure layers based on FWD test data and regression analysis. Finally， the distress ratio inside pavement structures (DRIPS) was proposed as a structural integrity index. The relationship between E and DRIPS was revealed and showed a good correlation. The greater the DRIPS value， the worse the pavement structural integrity and strength. It provides a reference for the evaluation of road structural conditions. This strategy proved to be reliable for nondestructive testing and evaluation of road structures， which could improve the comprehensiveness and effectiveness for evaluating road structural conditions.

关键词：

Laboratory Evaluation of Performance Recovery of Aged SBS-modified Asphalt Using Regenerants with Different Base Oil Components

在线全文

同方期刊数据库

学校读者我要写书评

暂无评论

China Petroleum Processing & Petrochemical Technology 2024年第2期26卷 98-107页

作者： Li Hongzhen Li Shengbin Feng Zhuangzhuang Jiang Mengmeng Li Ning Dong Fuqiang Shandong Yimeng Traffic Development Group Co. Ltd.Zibo 276004China College of Civil and transportation engineering Hohai UniversityNanjing 210098China

In this study,the regenerative effects of different regenerants on aged SBS-modified asphalt from different perspectives were investigated,including their conventional properties,viscoelastic behavior,creep-related properties,and *** oils composed of different proportions of aromatic and saturated hydrocarbons as well as the styrene-butadiene-styrene(SBS)restorer were used to prepare the *** results showed that the components of the base oil of the regenerant played a crucial role in determining the characteristics and performance of the recycled SBSmodified *** containing a high proportion of aromatics dissolved the hard segment in the SBS restorer,thereby delaying the effect of a reduction in the regenerants on the performance of the aged asphalts at a high *** containing a high proportion of saturates dissolved the soft segment in the SBS restorer to enhance the lowtemperature performance of the recycled *** addition,the stress sensitivity of the recycled asphalts increased with the fraction of aromatics in the *** the aromatic content of the base oil components of the regenerants increased and their saturate content decreased,the state of dispersion of the SBS phase in the recycled SBS-modified asphalts *** optimal content of aromatics in the base oil of the regenerants should be set in the range of 33%to 47%to ensure the adequate performance of the recycled asphalts and a high efficiency of the SBS restorer.

关键词： aged SBS-modified asphalt regeneration mechanisms base oil rheological properties morphology

维普期刊数据库

Machine learning of element geochemical anomalies for adverse geology identification in tunnels

在线全文

学校读者我要写书评

暂无评论

Journal of Earth Science 2024年

作者： Ruiqi Shao Peng Lin Zhenhao Xu Fumin Liu Yilong Liu School of Qilu transportation， Shandong University State Key Laboratory for Tunnel engineering Jinan Institute of Geotechnical and Underground engineering， Shandong University

Geological analysis， despite being a long-term method for identifying adverse geology in tunnels， has significant limitations due to its reliance on empirical analysis. The quantitative aspects of geochemical anomalies associated with adverse geology provide a novel strategy for addressing these limitations. However， statistical methods for identifying geochemical anomalies are insufficient for tunnel engineering. In contrast， data mining techniques such as machine learning have demonstrated greater efficacy when applied to geological data. Herein， a method for identifying adverse geology using machine learning of geochemical anomalies is proposed. The method was identified geochemical anomalies in tunnel that were not identified by statistical methods. We by employing robust factor analysis and self-organizing maps to reduce the dimensionality of geochemical data and extract the anomaly elements combination (AEC). Using the AEC sample data， we trained an isolation forest model to identify the multi-element anomalies， successfully. We analyzed the adverse geological features based the multi-element anomalies. This study， therefore， extends the traditional approach of geological analysis in tunnels and demonstrates that machine learning is an effective tool for intelligent geological analysis. Correspondingly， the research offers new insights regarding the adverse geology and the prevention of hazards during the construction of tunnels and underground engineering projects.

关键词：

A Comparative Study of Machine Learning Models for Traffic Accident Severity Prediction on Rural highways

在线全文

同方期刊数据库

学校读者我要写书评

暂无评论

Journal of Traffic and transportation engineering(English Edition) 2024年

作者： Fengxiang Guo Jingyang Li Feng Zhu Bijiang Tian Wenchen Yang School of transportation Science and engineering， Harbin Institute of Technology Yunnan Key Laboratory of Digital Communications National engineering Research Center for Efficient Maintenance， Safety and Durability of Roads and Bridges，Broadvision engineering Consultants Co.， Ltd Kunming Faculty of transportation engineering， Kunming University of Science and Technology School of Civil and Environmental engineering， Nanyang Technological University

The use of machine learning models for analyzing Traffic Accident Severity (TAS) is increasingly common in safety assessment and traffic accident prevention. However， many existing studies have not fully considered the importance of feature engineering， model hyperparameter optimization， and training set proportions， all of which significantly affect the performance of these models. This study addresses the research gap by developing a TAS model using the Light Gradient Boosting Machine (LightGBM) and integrating two feature engineering methods (Random Forest (RF) and Principal Component Analysis (PCA)). Additionally， we compared the LightGBM with three other machine learning models: Support Vector Machine (SVM)， Binary Logistic Regression (BL)， and Deep Neural Network (DNN). This comparison evaluates the effectiveness of different machine learning approaches in classifying TAS， taking into account variations in feature engineering techniques and training set proportions. The case study examines rural highway accidents in Yunnan Province， China， focusing on three categories of factors influencing TAS: accident characteristics， traffic flow， and highway conditions. Moreover， the SHAP (SHapley Additive exPlanations) values were employed to identify the primary factors contributing to the accident severity. The results show that with the training set size of 80%， all four models achieve the highest predictive accuracy for severe accidents. Notably， the PCA+lightGBM combination model outperforms others in overall accident prediction accuracy and has the highest recall rate and F1 score for severe accidents. Comparing the four models under different feature inputs， the impact of feature selection on model performance is less significant than reducing the data heterogeneity. LightGBM and DNN are more susceptible to data heterogeneity， and improving data homogeneity markedly boosts the model’s performance. Through SHAP analysis， it is evident that the modes of transportati

关键词：

Fault Identification for Shear-Type Structures Using Low-Frequency Vibration Modes

在线全文

同方期刊数据库

学校读者我要写书评

暂无评论

Computer Modeling in engineering & Sciences 2024年第3期138卷 2769-2791页

作者： Cuihong Li Qiuwei Yang Xi Peng School of Civil engineering Shaoxing UniversityShaoxing312000China School of Civil and transportation engineering Ningbo University of TechnologyNingbo315211China engineering Research Center of Industrial Construction in Civil engineering of Zhejiang Ningbo University of TechnologyNingbo315211China

Shear-type structures are common structural forms in industrial and civil buildings,such as concrete and steel frame *** diagnosis of shear-type structures is an important topic to ensure the normal use of *** main drawback of existing damage assessment methods is that they require accurate structural finite element models for damage ***,for many shear-type structures,it is difficult to obtain accurate *** order to avoid finite elementmodeling,amodel-freemethod for diagnosing shear structure defects is developed in this *** method only needs to measure a few low-order vibration modes of the *** proposed defect diagnosis method is divided into two *** the first stage,the location of defects in the structure is determined based on the difference between the virtual displacements derived from the dynamic flexibility matrices before and after *** the second stage,damage severity is evaluated based on an improved frequency sensitivity *** innovations of this method lie in two *** first innovation is the development of a virtual displacement difference method for determining the location of damage in the shear *** second is to improve the existing frequency sensitivity equation to calculate the damage degree without constructing the finite *** has been verified on a numerical example of a 22-story shear frame structure and an experimental example of a three-story steel shear *** on numerical analysis and experimental data validation,it is shown that this method only needs to use the low-order modes of structural vibration to diagnose the defect location and damage degree,and does not require finite element *** proposed method should be a very simple and practical defect diagnosis technique in engineering practice.

关键词： Fault diagnosis shear steel structure vibration mode dynamic flexibility frequency sensitivity

Vibration response and safety control for blasting vibration of the existing tunnel with defects

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Underground Space 2024年第2期15卷 76-89页

作者： Junying Xia Bo Wang Xinxin Guo Zhuoxiong Xie Key Laboratory of transportation Tunnel engineering Ministry of EducationSouthwest Jiaotong UniversityChengdu 610031China College of Environment and Civil engineering Chengdu University of TechnologyChengdu 610059China Guangdong Communication Planning&Design Institute Group Co. LtdGuangzhou 510507China

Current studies on blasting construction of small clear-distance tunnels have not considered the impact of existing tunnel lining defects when establishing safety *** paper offers a series of study results based on the blasting project of a new tunnel adjacent to the existing defect Xinling tunnel to thoroughly examine the dynamic response,safety control standards,and measures of the existing defect ***,structural models were developed to investigate the influence of the presence or absence of specific defects(like lining cracks and cavities behind the lining)on the dynamic response of the current tunnel lining to identify the most unfavorable defect ***,establish safety control standards for intact linings and those with the most unfavorable ***,two types of control measures,single safe charge and reasonable delay time,were studied based on the established safety control *** particular,the most adverse position of cracks was the wall facing the explosion,the rise in depth was more unfavorable for vibration response,and the impact of the longitudinal crack was restricted to the vicinity of the *** the vault was the most adverse cavity position,the rise in cavity area was more damaging,and the influence range varied with longitudinal cavity ***,the impact of cracks was mainly evident in the amplification effect of stress at the crack *** contrast,cavities had varied degrees of amplification effects on the vibration velocity and stress response and a relatively extensive influence *** control research was conducted,when the tunnel was intact,with a right wall crack,a vault cavity,and both vault cavity and crack for this project,the peak particle velocity(PPV)of the safety control standard for vibration velocity was 13,10,13,and 8 cm/s,respectively,and the respective single safe charge could be adjusted at 64,53,37,and 25 ***,the presence of different defects had a relati

关键词： Existing tunnel Defect Blasting construction Vibration response Control standards and measures

Progression of e-ticketing implementation for state transportation agencies for asphalt materials

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Journal of Road engineering 2024年第1期4卷 80-92页

作者： Joshua Withrow Gabriel B.Dadi Hala Nassereddine Department of Civil engineering University of KentuckyLexingtonKY 40506USA Kentucky transportation Cabinet FrankfortKY 40622USA

E-ticketing,which has been promoted by the Federal Highway Administration(FHWA)“every day counts”(EDC)initiative,utilizes software applications to digitally track and store information regarding highway construction materials paid by state transportation agencies(STAs)by weight in unit bid contract *** often face implementation barriers such as institutional inertia,or the resistance by stakeholders to adopt changes from the status quo,including new *** purpose of this paper is to determine the progression of STA e-ticketing policy adoption,specifically with a focus on asphalt paving operations,due to the COVID-19 *** accomplish this research effort,previous FHWA data,National Cooperative Highway Research Program(NCHRP)data,and other literatures are reviewed to determine an implementation *** data is collected from the American Association of State Highway and transportation Officials Committee on Con-struction to gain current feedback from STAs and their highway contractor partners after the COVID-19 ***,a case study featuring the Kentucky transportation Cabinet(KYTC),the Kentucky Association of Highway Contractors(KAHC),and the Plantmix Asphalt Industry of Kentucky(PAIKY)is performed to provide more in-depth *** major finding includes a statistically significant result indicating increased imple-mentation of e-ticketing for asphalt operations within the last two years,along with noting benefits including employee safety,task loading,and project documentation along with concerns regarding cellular connectivity and procurement *** findings indicate the importance of STAs investing in partnership with con-tractors to improve stakeholder buy-in before proceeding towards e-ticketing adoption.

关键词： Asphalt paving Construction inspection E-ticketing COVID-19

维普期刊数据库

Prediction of damage potential in mainshock–aftershock sequences using machine learning algorithms

在线全文

学校读者我要写书评

暂无评论

Earthquake engineering and engineering Vibration 2024年第4期23卷 919-938页

作者： Zhou Zhou Wang Meng Han Miao Yu Xiaohui Lu Dagang School of Civil and transportation engineering Beijing University of Civil Engineering and ArchitectureBeijing 100044China Multi-Functional Shaking Tables Laboratory Beijing University of Civil Engineering and ArchitectureBeijing 100044China College of Civil engineering Tongji UniversityShanghai 200092China College of Civil engineering and Architecture Guilin University of TechnologyGuilin 541004China School of Civil engineering Harbin Institute of TechnologyHarbin 150090China

Assessing the potential damage caused by earthquakes is crucial for a community’s emergency *** this study,four machine learning(ML)methods—random forest,extremely randomized trees,AdaBoost(AB),and gradient boosting(GB)—were employed to develop prediction models for the damage potential of the mainshock(DIMS)and mainshock–aftershock sequences(DIMA).Building structures were modeled using eight single-degree-of-freedom(SDOF)systems with different hysteretic rules.A set of 662 recorded mainshock–aftershock(MS-AS)ground motions was selected from the PEER *** intensity measures(IMs)were chosen to represent the characteristics of the mainshock and *** results revealed that the selected ML methods can well predict the structural damage potential of the SDOF systems,except for the AB *** GB model exhibited the best performance,making it the recommended choice for predicting DIMS and DIMA among the four ML ***,the impact of input variables in the prediction was investigated using the shapley additive explanations(SHAP)*** high-correlation variables were sensitive to the structural period(T).At T=1.0 s,the mainshock peak ground velocity(PGVM)and aftershock peak ground displacement(PGDA)significantly influenced the prediction of *** T increased to 5.0 s,the primary high-correlation factor of the mainshock IMs changed from PGVM to the mainshock peak ground displacement(PGDM);however,the highcorrelation variable of the aftershock IMs remained *** high-correlation factors for DIMS showed trends similar to those of ***,a table summarizing the first and second high-correlation variables for predicting DIMS and DIMA were provided,offering a valuable reference for parameter selection in seismic damage prediction for mainshock–aftershock sequences.

关键词： machine learning mainshock-aftershock damage potential prediction the high-correlation variables SDOF systems

维普期刊数据库

Research on thermal insulation materials properties under HTHP conditions for deep oil and gas reservoir rock ITP-Coring

在线全文

学校读者我要写书评

暂无评论

Petroleum Science 2024年第4期21卷 2625-2637页

作者： Zhi-Qiang He He-Ping Xie Ling Chen Jian-Ping Yang Bo Yu Zi-Jie Wei Ming-Zhong Gao State Key Laboratory of Intelligent Construction and Healthy Operation and Maintenance of Deep Underground engineering College of Water Resource and Hydropower Sichuan University Guangdong Provincial Key Laboratory of Deep Earth Sciences and Geothermal Energy Exploitation and Utilization Institute of Deep Earth Sciences and Green Energy College of Civil and Transportation Engineering Shenzhen University School of Mechanical engineering Sichuan University College of Polymer Science and engineering Sichuan University

Deep oil and gas reservoirs are under high-temperature conditions, but traditional coring methods do not consider temperature-preserved measures and ignore the influence of temperature on rock porosity and permeability, resulting in distorted resource assessments. The development of in situ temperaturepreserved coring(ITP-Coring) technology for deep reservoir rock is urgent, and thermal insulation materials are key. Therefore, hollow glass microsphere/epoxy resin thermal insulation materials(HGM/EP materials) were proposed as thermal insulation materials. The materials properties under coupled hightemperature and high-pressure(HTHP) conditions were tested. The results indicated that high pressures led to HGM destruction and that the materials water absorption significantly increased; additionally,increasing temperature accelerated the process. High temperatures directly caused the thermal conductivity of the materials to increase; additionally, the thermal conduction and convection of water caused by high pressures led to an exponential increase in the thermal conductivity. High temperatures weakened the matrix, and high pressures destroyed the HGM, which resulted in a decrease in the tensile mechanical properties of the materials. The materials entered the high elastic state at 150.C, and the mechanical properties were weakened more obviously, while the pressure led to a significant effect when the water absorption was above 10%. Meanwhile, the tensile strength/strain were 13.62 MPa/1.3%and 6.09 MPa/0.86% at 100.C and 100 MPa, respectively, which meet the application requirements of the self-designed coring device. Finally, K46-f40 and K46-f50 HGM/EP materials were proven to be suitable for ITP-Coring under coupled conditions below 100.C and 100 MPa. To further improve the materials properties, the interface layer and EP matrix should be optimized. The results can provide references for the optimization and engineering application of materials and thus technical su

关键词： Deep oil and gas reservoir rock In situ temperature-preserved coring (ITP-Coring) Hollow glass microsphere/epoxy resin thermal insulation materials (HGM/EP materials) High-temperature and high-pressure (HTHP) Physical and mechanical properties ITP-Coring In situ temperature-preserved coring HGM/EP Hollow glass microsphere/epoxy resin HTHP High-temperature and high-pressure