As one of the compulsory courses of oil and gas storage and transportation engineering,“Strength Design and Safety Management of Storage and Transportation Facilities”is a comprehensive course of both practicality a...As one of the compulsory courses of oil and gas storage and transportation engineering,“Strength Design and Safety Management of Storage and Transportation Facilities”is a comprehensive course of both practicality and theory.In order to solve the unbalanced distribution of theoretical and applied content in the teaching process,the teaching team reformed the teaching mode of the structure design of large storage tanks in the course of“Strength Design and Safety Management of Storage and Transportation Facilities”and introduced case-based teaching.On the basis of the original course,practical engineering case analysis such as wind-induced buckling of large storage tank and uneven settlement of tank foundation was added,which increased the proportion of application content.It is a new type of discussion teaching integrating case collection,group discussion and afterclass experience exchange.According to the recent three years of teaching practice,students’interest in this course has increased greatly and teaching quality has improved significantly,which fully verified the feasibility of engineering case-based teaching in teaching reform.The teaching team has gradually improved the teaching process according to the relevant experience and lessons in classroom practice and made a successful attempt in the teaching reform of storage and transportation structure safety courses,which is of positive significance for training application-oriented composite talents with the ability to solve practical problems in the new era.展开更多
To address the issues of short setting time and high bleeding rate of A component,which easily cause pipe plugging and poor grouting performance when a two-component grout is injected synchronously behind the Segmenta...To address the issues of short setting time and high bleeding rate of A component,which easily cause pipe plugging and poor grouting performance when a two-component grout is injected synchronously behind the Segmental Lining,the inorganic retarder sodium pyrophosphate(TSPP)and three organic retarders were added to the A component:sodium citrate(SC),sodium tartrate(ST)and glycerol(GLY).The effect law and microscopic mechanism of viscosity,bleeding rate,setting time,gelling time,compressive strength,and stone rate were investigated.The results revealed that the addition of retarders could enhance the stability and setting time of the A component and increase the gelling time,stone rate,and compressive strength of two-component grout.Among them,the performance of the grout with an SC dosage of 0.1% was superior.The bleeding rate of this grout was reduced to 3.5%,the stone rate of the two-component grout was more than 99%,and the early compressive strength and late compressive strength of this grout were increased by approximately 35% and 7%,respectively.The initial and final setting time of the A component with a TSPP dosage of 0.3% was the longest,which was prolonged to 17 and 26 h,respectively.Microscopic analysis revealed that the four retarders hindered the hydration process of cement through complexation and adsorption,and inhibited the hydration of C_(3)S and the crystallisation of CH.Moreover,they reduced the defects caused by the rapid reaction of water glass and CH on the solid phase structure,enabled the microstructure of the stone body to be denser,and subsequently,enhanced the compressive strength.展开更多
Construction engineering and management(CEM)has become increasingly complicated with the increasing size of engineering projects under different construction environments,motivating the digital transformation of CEM.T...Construction engineering and management(CEM)has become increasingly complicated with the increasing size of engineering projects under different construction environments,motivating the digital transformation of CEM.To contribute to a better understanding of the state of the art of smart techniques for engineering projects,this paper provides a comprehensive review of multi-criteria decision-making(MCDM)techniques,intelligent techniques,and their applications in CEM.First,a comprehensive framework detailing smart technologies for construction projects is developed.Next,the characteristics of CEM are summarized.A bibliometric review is then conducted to investigate the keywords,journals,and clusters related to the application of smart techniques in CEM during 2000-2022.Recent advancements in intelligent techniques are also discussed under the following six topics:①big data technology;②computer vision;③speech recognition;④natural language processing;⑤machine learning;and⑥knowledge representation,understanding,and reasoning.The applications of smart techniques are then illustrated via underground space exploitation.Finally,future research directions for the sustainable development of smart construction are highlighted.展开更多
To address the challenges of long commuting times,traffic congestion,high energy consumption,and emissions in inter-city travel,a new type of flying coach has been developed.This innovation aims to significantly short...To address the challenges of long commuting times,traffic congestion,high energy consumption,and emissions in inter-city travel,a new type of flying coach has been developed.This innovation aims to significantly shorten inter-city commuting times,enhance travel efficiency,and simultaneously reduce energy consumption and emissions.The flying coach integrates rail power supply technology,an intelligent operating system,and advanced new materials,comprising a catenary power supply guide rod and various sensor components.Based on analysis of traditional aircraft design principles,the research team simulated the design of the rail-powered flying coach using software such as AutoCAD and SolidWorks for three-dimensional modeling.The analysis results indicate that,compared to traditional aircraft and rail trains,the design of the new flying coach reduces its overall weight while maintaining carrying capacity,thereby improving commuting efficiency and environmental performance.This development lays a solid foundation for creating a greener,more efficient,and convenient inter-city transportation network.展开更多
Considering the development of urban freight transport,this paper presents an operational strategy for freight transport based on the urban metro system.To improve the alignment between service capacity and transport ...Considering the development of urban freight transport,this paper presents an operational strategy for freight transport based on the urban metro system.To improve the alignment between service capacity and transport demand under passenger and freight co-transportation(PFCT),a mixed-integer nonlinear programming model(MINLP)is developed to simultaneously optimize the train timetable(TT)and rolling stock circulation plan(RSCP),with particular consideration of flexible train composition mode and skip-stop strategies.Moreover,by introducing allocation rules for passengers and freight,the tripartite interests of operators,passengers,and freight agents are synergistically considered in the proposed model.To facilitate the model solution,a variable neighborhood search(VNS)algorithm is designed for the generation of high-quality solutions in a reasonable computational time.Finally,based on a simplified example and empirical data from the Beijing Metro Yizhuang Line,several sets of numerical examples are implemented to validate the applicability and effectiveness of the model and the approach.展开更多
The rise of deep learning has brought about transformative advancements in both scientific research and engineering applications.The 2024 Nobel Prizes,particularly in Physics and Chemistry,highlighted the revolutionar...The rise of deep learning has brought about transformative advancements in both scientific research and engineering applications.The 2024 Nobel Prizes,particularly in Physics and Chemistry,highlighted the revolutionary impact of deep learning,with AlphaFold’s breakthrough in protein structure prediction exemplifying its potential.This review explores the historical evolution of deep learning,from its foundational theories in neural networks and connectionism to its modern applications in various fields.Focus is given to its use in geotechnical engineering,particularly in geological disaster prediction,tunnel safety monitoring,and structural design optimization.The integration of deep learning models such as Convolutional Neural Networks(CNNs),Recurrent Neural Networks(RNNs),and Transformers has enabled significant progress in analyzing complex,unstructured data,offering innovative solutions to longstanding engineering challenges.The review also examines the opportunities and challenges faced by the field,advocating for interdisciplinary collaboration and open data sharing to further unlock deep learning’s potential in advancing both scientific and engineering disciplines.As deep learning continues to evolve,it promises to drive further innovation,shaping the future of engineering practices and scientific discovery.展开更多
Purpose-This paper provides a comprehensive analysis of the Brazilian freight railway system,examining the efficacy of the current concession renewal model in light of persistent structural problems such as market con...Purpose-This paper provides a comprehensive analysis of the Brazilian freight railway system,examining the efficacy of the current concession renewal model in light of persistent structural problems such as market concentration,cargo dependence on export commodities and underutilization of the network.Situating Brazil within the broader international debate on railway reforms,the paper evaluates whether the ongoing early renewal of concessions can deliver a more diversified and competitive freight system.Design/methodology/approach-The study adopts a sequential mixed-methods research design that integrates longitudinal quantitative analysis with qualitative institutional and policy evaluation.The quantitative component examines time-series indicators published by ANTT,DNIT and INFRA S.A.from 1999 to 2023 to identify structural patterns in traffic growth,investment,safety and market concentration.The qualitative component employs a process-tracing logic to reconstruct the evolution of concession renewals and the implementation of Railway Law 14.273/2021,drawing on concepts from regulatory economics,institutional theory and industrial organization.These empirical streams are synthesized through an analytical framework that connects three dimensions-regulatory design,market structure and system performance-allowing for a systematic assessment of how Brazil’s institutional configuration shapes incentives,competitive dynamics and network utilization.Findings-The analysis confirms that the early renewal of concessions has successfully secured substantial private investment for capacity expansion on existing trunk lines.However,it has perpetuated the vertically integrated model,reinforcing the market power of incumbent operators and failing to significantly promote intramodal competition or cargo diversification.The system remains dominated by iron ore and agricultural commodities,with general cargo representing a minuscule share.The new authorization regime and short-line railway policies present a viable pathway for market opening but face significant operational and institutional barriers to implementation.Originality/value-This research offers a timely and critical assessment of a pivotal moment in Brazilian railway policy.It moves beyond a simplistic evaluation of volume growth to a structural analysis of market failures and the interplay between concession renewal and regulatory innovation.The findings provide actionable insights for policymakers in Brazil and other emerging economies seeking to balance private investment with public interest goals in railway infrastructure,highlighting the necessity of complementary,pro-competitive measures alongside financial investment.展开更多
The stator of the maglev track plays a crucial role in the operation of the maglev system.Currently,the efficiency of maglev track inspection is limited by several factors,including the large span of elevated structur...The stator of the maglev track plays a crucial role in the operation of the maglev system.Currently,the efficiency of maglev track inspection is limited by several factors,including the large span of elevated structures,manual visual inspection,short inspection window times,and limited GPS positioning accuracy.To address these issues,this paper proposes a deep learning-based method for detecting and locating stator surface damage.This study establishes a maglev track stator surface image dataset,trains different object detection models,and compares their performance.Ultimately,YOLO and ByteTrack object tracking algorithms were chosen as the basic framework and enhanced to achieve automatic identification of high-speed maglev track stator surface damage images and track and count stator surface localization feature images.By matching the identified damaged images with their corresponding stator segment and beam segment sequence numbers,the location of the damage is pinpointed to the corresponding stator segment,enabling rapid and accurate identification and localization of complex damage to the maglev track stator surface.展开更多
Bio-carbonation of reactive MgO has been regarded as a promising and eco-friendly method for construction and demolition waste(CDW)cementation in various geotechnical engineering applications.However,the beneficial ef...Bio-carbonation of reactive MgO has been regarded as a promising and eco-friendly method for construction and demolition waste(CDW)cementation in various geotechnical engineering applications.However,the beneficial effect of bio-carbonation of reactive MgO cemented CDW(BCM-samples)can be altered when exposed to wetting-drying cycles induced by extreme climate changes or groundwater fluctuations.To better understand the durability of BCM-samples and their underlying deterioration mechanisms,a series of BCM-samples was prepared to investigate their physical-mechanical performance and microstructure evolution subjected to the wetting-drying cycles.The results indicated that the wetting-drying cycles can deteriorate the BCM-samples,and their physical-mechanical behaviors change quickly at the cycle beginning and then smoothly after 2 cycles.With the increase in cycling,the apparent deterioration with efflorescence and microcrack development can be observed.The mass loss and water absorption rates increased while the dry density,compressional wave velocity,and unconfined compression strength decreased.Urea pre-hydrolysis treatment can significantly improve the durability of BCM-samples,as the more hydrated magnesia carbonates(HMCs)enhance the cementing effects.After 10 cycles,the UCS of pre-hydrolyzed samples decreased 25.4%to 4.45 MPa,while that of ordinary samples decreased 50.7%to 1.20 MPa.The deterioration of BCM-samples caused by wetting-drying cycles can be attributed to two factors.One of the main factors is the structural integrity changes caused by the rapid loss of soluble material at the initial cycling stages.Another factor is the decrease in cementation induced by the loss of brucite and HMCs at the following cycle stages.展开更多
In this study,the effects of low-dose sodium hypochlorite disinfection on water quality and biofilm growth in drinking water distribution systems(DWDS)after ultrafiltration pretreatment was investigated.The influence ...In this study,the effects of low-dose sodium hypochlorite disinfection on water quality and biofilm growth in drinking water distribution systems(DWDS)after ultrafiltration pretreatment was investigated.The influence of pipeline hydraulic residence time(HRT)on disinfection efficiency,by-product formation,microbial activity,and biofilm growth were considered.The results show that both microbial activities and metabolite secretion were stimulated by increasing HRT,aggravating the potential risk of microbial pollution in DWDS.The enhanced microbial metabolism could further weaken disinfection efficiency by consuming extra residual Chlorine,after which the formation of disinfection by-products was facilitated.Residual Chlorine was found negatively correlated with HRT.With prolonging HRT from 5 to 40 h,the concentration of disinfection by-products(Chlorate,Chlorite,and Trichloromethane)was on a continuously increasing trend by 37%,140%,and 75%,respectively.But the water kept in pipeline still reliably satisfied the Standards for drinking water quality in China(GB5749–2022).Besides,more biofilm with denser morphologies developed on rubber pipeline gaskets rather than the iron/plastic ones.Rubber material was inappropriate for DWDS due to its potential risk of secondary biological pollution.Prolonging HRT also enhanced the accumulation of dominant bacteria(e.g.Bradyrhizobium and Obscuribacter)and decreased microbial diversity.展开更多
With the rapid development of transportation infrastructure,ensuring road safety through timely and accurate highway inspection has become increasingly critical.Traditional manual inspection methods are not only time-...With the rapid development of transportation infrastructure,ensuring road safety through timely and accurate highway inspection has become increasingly critical.Traditional manual inspection methods are not only time-consuming and labor-intensive,but they also struggle to provide consistent,high-precision detection and realtime monitoring of pavement surface defects.To overcome these limitations,we propose an Automatic Recognition of PavementDefect(ARPD)algorithm,which leverages unmanned aerial vehicle(UAV)-based aerial imagery to automate the inspection process.The ARPD framework incorporates a backbone network based on the Selective State Space Model(S3M),which is designed to capture long-range temporal dependencies.This enables effective modeling of dynamic correlations among redundant and often repetitive structures commonly found in road imagery.Furthermore,a neck structure based on Semantics and Detail Infusion(SDI)is introduced to guide cross-scale feature fusion.The SDI module enhances the integration of low-level spatial details with high-level semantic cues,thereby improving feature expressiveness and defect localization accuracy.Experimental evaluations demonstrate that theARPDalgorithm achieves a mean average precision(mAP)of 86.1%on a custom-labeled pavement defect dataset,outperforming the state-of-the-art YOLOv11 segmentation model.The algorithm also maintains strong generalization ability on public datasets.These results confirm that ARPD is well-suited for diverse real-world applications in intelligent,large-scale highway defect monitoring and maintenance planning.展开更多
To enhance the deformation capacity of vertical support columns of underground structures and improve their overall seismic performance,a new truncated column connected by unbonded prestressed tendons is proposed,insp...To enhance the deformation capacity of vertical support columns of underground structures and improve their overall seismic performance,a new truncated column connected by unbonded prestressed tendons is proposed,inspired by the concepts of the toughness seismic resistance and rocking design.Although many experimental and numerical studies have focused on underground structures,research on the behavior of truncated columns remains limited.This paper develops threedimensional(3D)finite element(FE)models for various columns,including cast-in-place column(CIPC)and prestressed tendon truncated column(PTTC),to evaluate the effects of three parameters,including axial compression ratio(ACR),initial tendon stress,and the effect of hole diameter on mechanical performance—specifically deformation capacity,strength,residual deformation and gap width.The results indicate that the deformability and self-centering ability of the prestressed tendon truncated column is obviously superior to the cast-in-place column,but its strength was comparatively lower.The axial compression ratio has obvious effects on seismic performance,especially deformation and residual deformation,while initial tendon stress and hole diameter influence performance only in the case of a small axial compression ratio.This study systematically identifies the influence of various factors on seismic performance.Additionally,this study proposes a method to evaluate the self-centering capability of structures and establishes an empirical relationship between maximum recoverable deformation and the axial compression ratio.The developed numerical model can serve as a tool for future studies to predict the seismic responses of overall subway stations that feature truncated columns.展开更多
The use of Unmanned Aerial Vehicles(UAVs)for defect detection on railway slopes is becoming increasingly widespread due to their ability to capture high-resolution images over large,inaccessible,and topographically co...The use of Unmanned Aerial Vehicles(UAVs)for defect detection on railway slopes is becoming increasingly widespread due to their ability to capture high-resolution images over large,inaccessible,and topographically complex areas.However,current UAV-based detection methods face several critical limitations,including constrained deployment frequency,limited availability of annotated defect data,and the lack of mature risk assessment frameworks.To address these challenges,this study introduces a novel approach that integrates diffusion models with Large Language Models(LLMs)to generate highquality synthetic defect images tailored to railway slope scenarios.Furthermore,an improved transformerbased architecture is proposed,incorporating attention mechanisms and LLM-guided diffusion-generated imagery to enhance defect recognition performance under complex environmental conditions.Experimental evaluations conducted on a dataset of 300 field-collected images from high-risk railway slopes demonstrate that the proposed method significantly outperforms existing baselines in terms of precision,recall,and robustness,indicating strong applicability for real-world railway infrastructure monitoring and disaster prevention.展开更多
Understanding the microscopic time-dependent mechanical behavior of shale is critical for assessing macroscopic creep and engineering applications.Grid nanoindentation experiments and nanoindentation creep tests were ...Understanding the microscopic time-dependent mechanical behavior of shale is critical for assessing macroscopic creep and engineering applications.Grid nanoindentation experiments and nanoindentation creep tests were systematically conducted to investigate microscopic creep behaviors in shale.The indentation creep displacements and creep rates of the shale's soft,intermediate,and hard phases showed the same evolution patterns.The creep deformation was much higher in the soft phase than in the other two phases.However,the difference in the steady-state creep rates between the three mechanical phases was negligible.A linear relationship was observed between the microscopic contact creep modulus and the microscopic Young's modulus,hardness,creep displacement,and creep rate.The primary mechanism of microscopic creep in shale revealed by the creep strain rate sensitivity parameter was the extension and closure of microcracks.The differences in the microscopic creep parameters derived from the experimental data using the deconvolution methods and representative point methods were evaluated,and the applicability of the two methods was described.The performances of commonly used creep models to predict the microscopic creep behaviors were evaluated.The Burgers model provided the best performance in predicting the steady-state creep deformation and creep rate.The ability of the Mori-Tanaka and Voigt-Reuss-Hill models to derive macroscopic parameters from microscopic mechanical parameters was compared.Both methods provided macroscopic Young's modulus values close to the experimental values;however,neither could predict macroscopic creep parameters based on microscopic creep parameters.展开更多
Reliable traffic flow prediction is crucial for mitigating urban congestion.This paper proposes Attentionbased spatiotemporal Interactive Dynamic Graph Convolutional Network(AIDGCN),a novel architecture integrating In...Reliable traffic flow prediction is crucial for mitigating urban congestion.This paper proposes Attentionbased spatiotemporal Interactive Dynamic Graph Convolutional Network(AIDGCN),a novel architecture integrating Interactive Dynamic Graph Convolution Network(IDGCN)with Temporal Multi-Head Trend-Aware Attention.Its core innovation lies in IDGCN,which uniquely splits sequences into symmetric intervals for interactive feature sharing via dynamic graphs,and a novel attention mechanism incorporating convolutional operations to capture essential local traffic trends—addressing a critical gap in standard attention for continuous data.For 15-and 60-min forecasting on METR-LA,AIDGCN achieves MAEs of 0.75%and 0.39%,and RMSEs of 1.32%and 0.14%,respectively.In the 60-min long-term forecasting of the PEMS-BAY dataset,the AIDGCN out-performs the MRA-BGCN method by 6.28%,4.93%,and 7.17%in terms of MAE,RMSE,and MAPE,respectively.Experimental results demonstrate the superiority of our pro-posed model over state-of-the-art methods.展开更多
Accurate prediction of rockburst intensity levels is crucial for ensuring the safety of deep hard rock engineering construction.This paper introduced an expert system for rockburst intensity level prediction that empl...Accurate prediction of rockburst intensity levels is crucial for ensuring the safety of deep hard rock engineering construction.This paper introduced an expert system for rockburst intensity level prediction that employs machine learning algorithms as the basis for its inference rules.The system comprises four modules:a database,a repository,an inference engine,and an interpreter.A database containing 1114 rockburst cases was used to construct 357 datasets that serve as the repository for the expert system.Additionally,19 types of machine learning algorithms were used to establish 6783 micro-models to construct cognitive rules within the inference engine.By integrating probability theory and marginal analysis,a fuzzy scoring method based on the SoftMax function was developed and applied to the interpreter for rockburst intensity level prediction,effectively restoring the continuity of rockburst characteristics.The research results indicate that ensemble algorithms based on decision trees are more effective in capturing the characteristics of rockburst.Key factors for accurate prediction of rockburst intensity include uniaxial compressive strength,elastic energy index,the maximum principal stress,tangential stress,and their composite indicators.The accuracy of the proposed rockburst intensity level prediction expert system was verified using 20 engineering rockburst cases,with predictions aligning closely with the actual rockburst intensity levels.展开更多
Stony debris flows,characterized by coarse boulders embedded in a sediment-laden matrix,greatly amplify destructive potential by altering flow dynamics and impact forces.Conventional single-phase particle-fluidmixture...Stony debris flows,characterized by coarse boulders embedded in a sediment-laden matrix,greatly amplify destructive potential by altering flow dynamics and impact forces.Conventional single-phase particle-fluidmixture models often struggle to capture the complexities introduced by coarse boulders and multi-phase interactions,while strong-coupling methods can be computationally prohibitive for practical hazard assessments.In this study,we propose a semi-hybrid,fully resolved coupling numerical framework for modeling boulder-laden debris flows.This framework conceptualizes debris flows as a composite system comprising a continuous viscous fluidphase(including finesediments)and a discrete phase of arbitrarily shaped coarse particles.The continuous phase is treated as a generalized nonlinear Coulomb-viscoplastic fluidusing the smoothed particle hydrodynamics(SPH)method,while coarse particles are modeled via the distributed contact discrete element method(DCDEM).These two phases are coupled through an efficienttwo-way resolved scheme,ensuring accurate simulation of flow-boulder interactions within a unifiedtimeframe.We validate the proposed method against two physical experiments:(1)gravity-driven concrete flows and(2)debris flowinteracting with slit-type barriers.Results confirmthe method's robustness in accurately capturing fluid-solid-structureinteractions and deposition processes.Its capabilities are further showcased through the simulation of a stony debris-flowevent inWenchuan County,China,highlighting its promise for real-world engineering applications and validating the effectiveness of the existing cascade dam system in mitigating debrisflowimpact and energy dissipation.展开更多
Shield tunneling in saturated ground poses challenges due to the potential risk of ground collapse resulting from seepage force and inadequate support pressure.This study employed a laboratory model test and a theoret...Shield tunneling in saturated ground poses challenges due to the potential risk of ground collapse resulting from seepage force and inadequate support pressure.This study employed a laboratory model test and a theoretical validation to elucidate the mechanisms of face failure and subsequent ground collapse in saturated ground during slurry pressure-balanced shield(SPBS)tunneling operations.A slurry circulation system was developed to ensure steady shield tunneling and to replicate the phenomena of ground collapse.Investigations into shield tunneling parameters and ground responses,including soil pressure,pore water pressure,and surface subsidence,were conducted to understand the mechanisms of face failure and subsequent ground collapse.The theoretical solution for the critical collapse pressure of the tunnel face,based on the rotational failure mechanism,was validated through the comparison with the experimentally determined critical collapse pressure.The results indicate that:(1)appropriate adjustments of tunneling parameters are crucial for promoting filtercake formation,maintaining chamber pressure,and minimizing ground subsidence;(2)chamber pressure,soil pressure,pore water pressure,and ground subsidence are closely correlated with shield tunneling parameters and the formation of filter cake;(3)ground collapse follows a continuous failure mode due to the destruction of filtercake and the decrease in chamber pressure;(4)the soil pressure at the cutterhead is more sensitive to disturbances from shield tunneling than chamber pressure;and(5)experimentally determined critical collapse pressures is consistent with the theoretical solution of limit analysis.展开更多
Time-delayed blasting is widely utilized in engineering to mitigate induced vibration hazards and enhance fragmentation.The underlying vibration reduction principle is the decrease of the charge weight per delay,while...Time-delayed blasting is widely utilized in engineering to mitigate induced vibration hazards and enhance fragmentation.The underlying vibration reduction principle is the decrease of the charge weight per delay,while the potential for further vibration reduction remains debated,largely due to unclear underlying mechanisms.In light of the popularization of electronic detonators and the representativeness of double-hole configurationsfor multiple blastholes,it is essential to investigate the vibration characteristics induced by time-delayed double blastholes.Therefore,a series of doubleborehole experimental blasts was conducted in an underground roadway to clarify the variation in vibration from single-hole to dual-hole conditions.Based on the experimental data and inherent limitations,an exact full-fieldtheoretical model was further employed to systematically analyze the effects of delay time,charge length,and borehole inclination angle on vibrations induced by various doublehole configurations.The experimental data and theoretical analysis reveal that the general scaled distance effectively predicts vibrations in delayed blasting but does not reflectvibration reduction.Increasing delay time causes fluctuatingPPVs,which stabilize slightly above single-hole PPVs as delay times exceed a certain value.The delayed blasting primarily reduces near-fieldfrequencies.Longer charge lengths in double boreholes increase PPV levels and attenuation rates within a certain length,and the vibration behavior of combined long and short charge lengths is governed by the long blasthole.Larger blasthole inclination angles enhance vibration amplitude and reduce PPV attenuation rates.Optimizing inclination angles is more critical than adjusting delay times,and parallel boreholes offer the best vibration control.展开更多
Understanding the shakedown behavior of fill material is paramount to estimate the deformation stability of railway subgrade.Especially for red mudstone fill material(RMF),the noticeable overestimation of bearing capa...Understanding the shakedown behavior of fill material is paramount to estimate the deformation stability of railway subgrade.Especially for red mudstone fill material(RMF),the noticeable overestimation of bearing capacity would be encountered if the conventional strength method is used.This paper presents the shakedown analysis on RMF,with a specific emphasis on the effect of water content.A series of cyclic triaxial tests with 50,000 loading cycles was conducted.Two-stage behavior of permanent deformation and dissipated energy responses was clearly characterized,from which an energy-based criterion was proposed to determine the shakedown limits.The proposed energy-based criterion was validated by examining its performance to various geomaterials including cohesive soils and unbound granular materials(UGMs).By applying the proposed method to RMF,the S-shape evolution curve was obtained in terms of shakedown limits with initial suction.Microfabric difference was believed as the main consequence of the S-shape mode.Demonstration was confirmed by the mercury intrusion porosimetry(MIP)and scanning electron microscope(SEM)analyses.By applying the proposed method to different geomaterials,an extensive comparison was made between the shakedown limits and the static shear strength.The ratio of shakedown limits to the static shear strength for saturated RMF specimen fell within the range of soft clays,while that of unsaturated specimen lies within the range of UGMs.展开更多
文摘As one of the compulsory courses of oil and gas storage and transportation engineering,“Strength Design and Safety Management of Storage and Transportation Facilities”is a comprehensive course of both practicality and theory.In order to solve the unbalanced distribution of theoretical and applied content in the teaching process,the teaching team reformed the teaching mode of the structure design of large storage tanks in the course of“Strength Design and Safety Management of Storage and Transportation Facilities”and introduced case-based teaching.On the basis of the original course,practical engineering case analysis such as wind-induced buckling of large storage tank and uneven settlement of tank foundation was added,which increased the proportion of application content.It is a new type of discussion teaching integrating case collection,group discussion and afterclass experience exchange.According to the recent three years of teaching practice,students’interest in this course has increased greatly and teaching quality has improved significantly,which fully verified the feasibility of engineering case-based teaching in teaching reform.The teaching team has gradually improved the teaching process according to the relevant experience and lessons in classroom practice and made a successful attempt in the teaching reform of storage and transportation structure safety courses,which is of positive significance for training application-oriented composite talents with the ability to solve practical problems in the new era.
基金Funded by the National Natural Science Foundation of China(No.52378394)the Fundamental Research Funds for the Central Universities(No.B230201037)。
文摘To address the issues of short setting time and high bleeding rate of A component,which easily cause pipe plugging and poor grouting performance when a two-component grout is injected synchronously behind the Segmental Lining,the inorganic retarder sodium pyrophosphate(TSPP)and three organic retarders were added to the A component:sodium citrate(SC),sodium tartrate(ST)and glycerol(GLY).The effect law and microscopic mechanism of viscosity,bleeding rate,setting time,gelling time,compressive strength,and stone rate were investigated.The results revealed that the addition of retarders could enhance the stability and setting time of the A component and increase the gelling time,stone rate,and compressive strength of two-component grout.Among them,the performance of the grout with an SC dosage of 0.1% was superior.The bleeding rate of this grout was reduced to 3.5%,the stone rate of the two-component grout was more than 99%,and the early compressive strength and late compressive strength of this grout were increased by approximately 35% and 7%,respectively.The initial and final setting time of the A component with a TSPP dosage of 0.3% was the longest,which was prolonged to 17 and 26 h,respectively.Microscopic analysis revealed that the four retarders hindered the hydration process of cement through complexation and adsorption,and inhibited the hydration of C_(3)S and the crystallisation of CH.Moreover,they reduced the defects caused by the rapid reaction of water glass and CH on the solid phase structure,enabled the microstructure of the stone body to be denser,and subsequently,enhanced the compressive strength.
基金funded by the project of Guangdong Provincial Basic and Applied Basic Research Fund Committee(2022A1515240073)the Pearl River Talent Recruitment Program(2019CX01G338),Guangdong Province.
文摘Construction engineering and management(CEM)has become increasingly complicated with the increasing size of engineering projects under different construction environments,motivating the digital transformation of CEM.To contribute to a better understanding of the state of the art of smart techniques for engineering projects,this paper provides a comprehensive review of multi-criteria decision-making(MCDM)techniques,intelligent techniques,and their applications in CEM.First,a comprehensive framework detailing smart technologies for construction projects is developed.Next,the characteristics of CEM are summarized.A bibliometric review is then conducted to investigate the keywords,journals,and clusters related to the application of smart techniques in CEM during 2000-2022.Recent advancements in intelligent techniques are also discussed under the following six topics:①big data technology;②computer vision;③speech recognition;④natural language processing;⑤machine learning;and⑥knowledge representation,understanding,and reasoning.The applications of smart techniques are then illustrated via underground space exploitation.Finally,future research directions for the sustainable development of smart construction are highlighted.
基金College Student Innovation Training Program Project(S202410225147)。
文摘To address the challenges of long commuting times,traffic congestion,high energy consumption,and emissions in inter-city travel,a new type of flying coach has been developed.This innovation aims to significantly shorten inter-city commuting times,enhance travel efficiency,and simultaneously reduce energy consumption and emissions.The flying coach integrates rail power supply technology,an intelligent operating system,and advanced new materials,comprising a catenary power supply guide rod and various sensor components.Based on analysis of traditional aircraft design principles,the research team simulated the design of the rail-powered flying coach using software such as AutoCAD and SolidWorks for three-dimensional modeling.The analysis results indicate that,compared to traditional aircraft and rail trains,the design of the new flying coach reduces its overall weight while maintaining carrying capacity,thereby improving commuting efficiency and environmental performance.This development lays a solid foundation for creating a greener,more efficient,and convenient inter-city transportation network.
基金supported by the Beijing Natural Science Foundation(9252012)the National Natural Science Foundation of China(72371015,72288101,72431002,and 72161010)Key Laboratory of Railway Industry on Plateau Railway Transportation Intelligent Management and Control(GYYSHZ2301)。
文摘Considering the development of urban freight transport,this paper presents an operational strategy for freight transport based on the urban metro system.To improve the alignment between service capacity and transport demand under passenger and freight co-transportation(PFCT),a mixed-integer nonlinear programming model(MINLP)is developed to simultaneously optimize the train timetable(TT)and rolling stock circulation plan(RSCP),with particular consideration of flexible train composition mode and skip-stop strategies.Moreover,by introducing allocation rules for passengers and freight,the tripartite interests of operators,passengers,and freight agents are synergistically considered in the proposed model.To facilitate the model solution,a variable neighborhood search(VNS)algorithm is designed for the generation of high-quality solutions in a reasonable computational time.Finally,based on a simplified example and empirical data from the Beijing Metro Yizhuang Line,several sets of numerical examples are implemented to validate the applicability and effectiveness of the model and the approach.
基金support provided by the Hebei Province Full-Time Recruitment of National High-Level Innovative Talents Research Project(Grant No.2023HBQZYCSB004).
文摘The rise of deep learning has brought about transformative advancements in both scientific research and engineering applications.The 2024 Nobel Prizes,particularly in Physics and Chemistry,highlighted the revolutionary impact of deep learning,with AlphaFold’s breakthrough in protein structure prediction exemplifying its potential.This review explores the historical evolution of deep learning,from its foundational theories in neural networks and connectionism to its modern applications in various fields.Focus is given to its use in geotechnical engineering,particularly in geological disaster prediction,tunnel safety monitoring,and structural design optimization.The integration of deep learning models such as Convolutional Neural Networks(CNNs),Recurrent Neural Networks(RNNs),and Transformers has enabled significant progress in analyzing complex,unstructured data,offering innovative solutions to longstanding engineering challenges.The review also examines the opportunities and challenges faced by the field,advocating for interdisciplinary collaboration and open data sharing to further unlock deep learning’s potential in advancing both scientific and engineering disciplines.As deep learning continues to evolve,it promises to drive further innovation,shaping the future of engineering practices and scientific discovery.
文摘Purpose-This paper provides a comprehensive analysis of the Brazilian freight railway system,examining the efficacy of the current concession renewal model in light of persistent structural problems such as market concentration,cargo dependence on export commodities and underutilization of the network.Situating Brazil within the broader international debate on railway reforms,the paper evaluates whether the ongoing early renewal of concessions can deliver a more diversified and competitive freight system.Design/methodology/approach-The study adopts a sequential mixed-methods research design that integrates longitudinal quantitative analysis with qualitative institutional and policy evaluation.The quantitative component examines time-series indicators published by ANTT,DNIT and INFRA S.A.from 1999 to 2023 to identify structural patterns in traffic growth,investment,safety and market concentration.The qualitative component employs a process-tracing logic to reconstruct the evolution of concession renewals and the implementation of Railway Law 14.273/2021,drawing on concepts from regulatory economics,institutional theory and industrial organization.These empirical streams are synthesized through an analytical framework that connects three dimensions-regulatory design,market structure and system performance-allowing for a systematic assessment of how Brazil’s institutional configuration shapes incentives,competitive dynamics and network utilization.Findings-The analysis confirms that the early renewal of concessions has successfully secured substantial private investment for capacity expansion on existing trunk lines.However,it has perpetuated the vertically integrated model,reinforcing the market power of incumbent operators and failing to significantly promote intramodal competition or cargo diversification.The system remains dominated by iron ore and agricultural commodities,with general cargo representing a minuscule share.The new authorization regime and short-line railway policies present a viable pathway for market opening but face significant operational and institutional barriers to implementation.Originality/value-This research offers a timely and critical assessment of a pivotal moment in Brazilian railway policy.It moves beyond a simplistic evaluation of volume growth to a structural analysis of market failures and the interplay between concession renewal and regulatory innovation.The findings provide actionable insights for policymakers in Brazil and other emerging economies seeking to balance private investment with public interest goals in railway infrastructure,highlighting the necessity of complementary,pro-competitive measures alongside financial investment.
基金supported in part by the National Natural Science Foundation of China under Grant 52432012in part by the Shanghai Science and Technology Project with 25ZR1402508。
文摘The stator of the maglev track plays a crucial role in the operation of the maglev system.Currently,the efficiency of maglev track inspection is limited by several factors,including the large span of elevated structures,manual visual inspection,short inspection window times,and limited GPS positioning accuracy.To address these issues,this paper proposes a deep learning-based method for detecting and locating stator surface damage.This study establishes a maglev track stator surface image dataset,trains different object detection models,and compares their performance.Ultimately,YOLO and ByteTrack object tracking algorithms were chosen as the basic framework and enhanced to achieve automatic identification of high-speed maglev track stator surface damage images and track and count stator surface localization feature images.By matching the identified damaged images with their corresponding stator segment and beam segment sequence numbers,the location of the damage is pinpointed to the corresponding stator segment,enabling rapid and accurate identification and localization of complex damage to the maglev track stator surface.
基金supported by the National Natural Science Foundation of China(Grant Nos.42525201 and 42230710).
文摘Bio-carbonation of reactive MgO has been regarded as a promising and eco-friendly method for construction and demolition waste(CDW)cementation in various geotechnical engineering applications.However,the beneficial effect of bio-carbonation of reactive MgO cemented CDW(BCM-samples)can be altered when exposed to wetting-drying cycles induced by extreme climate changes or groundwater fluctuations.To better understand the durability of BCM-samples and their underlying deterioration mechanisms,a series of BCM-samples was prepared to investigate their physical-mechanical performance and microstructure evolution subjected to the wetting-drying cycles.The results indicated that the wetting-drying cycles can deteriorate the BCM-samples,and their physical-mechanical behaviors change quickly at the cycle beginning and then smoothly after 2 cycles.With the increase in cycling,the apparent deterioration with efflorescence and microcrack development can be observed.The mass loss and water absorption rates increased while the dry density,compressional wave velocity,and unconfined compression strength decreased.Urea pre-hydrolysis treatment can significantly improve the durability of BCM-samples,as the more hydrated magnesia carbonates(HMCs)enhance the cementing effects.After 10 cycles,the UCS of pre-hydrolyzed samples decreased 25.4%to 4.45 MPa,while that of ordinary samples decreased 50.7%to 1.20 MPa.The deterioration of BCM-samples caused by wetting-drying cycles can be attributed to two factors.One of the main factors is the structural integrity changes caused by the rapid loss of soluble material at the initial cycling stages.Another factor is the decrease in cementation induced by the loss of brucite and HMCs at the following cycle stages.
基金supported by the National Natural Science Foundation of China(Nos.52170070,52400022,and 52200088)the Youth S&T Talent Support Programme of Guangdong Provincial Association for Science and Technology(GDSTA)(No.SKXRC202406)+1 种基金the“One hundred Youth”Science and Technology Plan,Guangdong University of Technology,China(No.263113906)China Postdoctoral Science Foundation(No.2023M740754).
文摘In this study,the effects of low-dose sodium hypochlorite disinfection on water quality and biofilm growth in drinking water distribution systems(DWDS)after ultrafiltration pretreatment was investigated.The influence of pipeline hydraulic residence time(HRT)on disinfection efficiency,by-product formation,microbial activity,and biofilm growth were considered.The results show that both microbial activities and metabolite secretion were stimulated by increasing HRT,aggravating the potential risk of microbial pollution in DWDS.The enhanced microbial metabolism could further weaken disinfection efficiency by consuming extra residual Chlorine,after which the formation of disinfection by-products was facilitated.Residual Chlorine was found negatively correlated with HRT.With prolonging HRT from 5 to 40 h,the concentration of disinfection by-products(Chlorate,Chlorite,and Trichloromethane)was on a continuously increasing trend by 37%,140%,and 75%,respectively.But the water kept in pipeline still reliably satisfied the Standards for drinking water quality in China(GB5749–2022).Besides,more biofilm with denser morphologies developed on rubber pipeline gaskets rather than the iron/plastic ones.Rubber material was inappropriate for DWDS due to its potential risk of secondary biological pollution.Prolonging HRT also enhanced the accumulation of dominant bacteria(e.g.Bradyrhizobium and Obscuribacter)and decreased microbial diversity.
基金supported in part by the Technical Service for the Development and Application of an Intelligent Visual Management Platformfor Expressway Construction Progress Based on BIM Technology(grant NO.JKYZLX-2023-09)in partby the Technical Service for the Development of an Early Warning Model in the Research and Application of Key Technologies for Tunnel Operation Safety Monitoring and Early Warning Based on Digital Twin(grant NO.JK-S02-ZNGS-202412-JISHU-FA-0035)sponsored by Yunnan Transportation Science Research Institute Co.,Ltd.
文摘With the rapid development of transportation infrastructure,ensuring road safety through timely and accurate highway inspection has become increasingly critical.Traditional manual inspection methods are not only time-consuming and labor-intensive,but they also struggle to provide consistent,high-precision detection and realtime monitoring of pavement surface defects.To overcome these limitations,we propose an Automatic Recognition of PavementDefect(ARPD)algorithm,which leverages unmanned aerial vehicle(UAV)-based aerial imagery to automate the inspection process.The ARPD framework incorporates a backbone network based on the Selective State Space Model(S3M),which is designed to capture long-range temporal dependencies.This enables effective modeling of dynamic correlations among redundant and often repetitive structures commonly found in road imagery.Furthermore,a neck structure based on Semantics and Detail Infusion(SDI)is introduced to guide cross-scale feature fusion.The SDI module enhances the integration of low-level spatial details with high-level semantic cues,thereby improving feature expressiveness and defect localization accuracy.Experimental evaluations demonstrate that theARPDalgorithm achieves a mean average precision(mAP)of 86.1%on a custom-labeled pavement defect dataset,outperforming the state-of-the-art YOLOv11 segmentation model.The algorithm also maintains strong generalization ability on public datasets.These results confirm that ARPD is well-suited for diverse real-world applications in intelligent,large-scale highway defect monitoring and maintenance planning.
基金National Natural Science Foundation of China under Grant Nos.52478488 and 51908013the National Key Basic Research and Development Program of China under Grant No.2018YFC1504305。
文摘To enhance the deformation capacity of vertical support columns of underground structures and improve their overall seismic performance,a new truncated column connected by unbonded prestressed tendons is proposed,inspired by the concepts of the toughness seismic resistance and rocking design.Although many experimental and numerical studies have focused on underground structures,research on the behavior of truncated columns remains limited.This paper develops threedimensional(3D)finite element(FE)models for various columns,including cast-in-place column(CIPC)and prestressed tendon truncated column(PTTC),to evaluate the effects of three parameters,including axial compression ratio(ACR),initial tendon stress,and the effect of hole diameter on mechanical performance—specifically deformation capacity,strength,residual deformation and gap width.The results indicate that the deformability and self-centering ability of the prestressed tendon truncated column is obviously superior to the cast-in-place column,but its strength was comparatively lower.The axial compression ratio has obvious effects on seismic performance,especially deformation and residual deformation,while initial tendon stress and hole diameter influence performance only in the case of a small axial compression ratio.This study systematically identifies the influence of various factors on seismic performance.Additionally,this study proposes a method to evaluate the self-centering capability of structures and establishes an empirical relationship between maximum recoverable deformation and the axial compression ratio.The developed numerical model can serve as a tool for future studies to predict the seismic responses of overall subway stations that feature truncated columns.
基金supported in part by the National Natural Science Foundation of China under Grant 52432012in part by the Shanghai Science and Technology Project with 25ZR1402508。
文摘The use of Unmanned Aerial Vehicles(UAVs)for defect detection on railway slopes is becoming increasingly widespread due to their ability to capture high-resolution images over large,inaccessible,and topographically complex areas.However,current UAV-based detection methods face several critical limitations,including constrained deployment frequency,limited availability of annotated defect data,and the lack of mature risk assessment frameworks.To address these challenges,this study introduces a novel approach that integrates diffusion models with Large Language Models(LLMs)to generate highquality synthetic defect images tailored to railway slope scenarios.Furthermore,an improved transformerbased architecture is proposed,incorporating attention mechanisms and LLM-guided diffusion-generated imagery to enhance defect recognition performance under complex environmental conditions.Experimental evaluations conducted on a dataset of 300 field-collected images from high-risk railway slopes demonstrate that the proposed method significantly outperforms existing baselines in terms of precision,recall,and robustness,indicating strong applicability for real-world railway infrastructure monitoring and disaster prevention.
基金National Natural Science Foundation of China,Grant/Award Numbers:12172230,52422403,U22A20166,52304097National Science and Technology Major Project,Grant/Award Number:2024ZD1003903+2 种基金Department of Science and Technology of Guangdong Province,Grant/Award Number:2019ZT08G315Guangdong Basic and Applied Basic Research Foundation,Grant/Award Numbers:2023A1515012654,2022A1515110030Young Elite Scientists Sponsorship Program by CAST,Grant/Award Number:2023QNRC001。
文摘Understanding the microscopic time-dependent mechanical behavior of shale is critical for assessing macroscopic creep and engineering applications.Grid nanoindentation experiments and nanoindentation creep tests were systematically conducted to investigate microscopic creep behaviors in shale.The indentation creep displacements and creep rates of the shale's soft,intermediate,and hard phases showed the same evolution patterns.The creep deformation was much higher in the soft phase than in the other two phases.However,the difference in the steady-state creep rates between the three mechanical phases was negligible.A linear relationship was observed between the microscopic contact creep modulus and the microscopic Young's modulus,hardness,creep displacement,and creep rate.The primary mechanism of microscopic creep in shale revealed by the creep strain rate sensitivity parameter was the extension and closure of microcracks.The differences in the microscopic creep parameters derived from the experimental data using the deconvolution methods and representative point methods were evaluated,and the applicability of the two methods was described.The performances of commonly used creep models to predict the microscopic creep behaviors were evaluated.The Burgers model provided the best performance in predicting the steady-state creep deformation and creep rate.The ability of the Mori-Tanaka and Voigt-Reuss-Hill models to derive macroscopic parameters from microscopic mechanical parameters was compared.Both methods provided macroscopic Young's modulus values close to the experimental values;however,neither could predict macroscopic creep parameters based on microscopic creep parameters.
文摘Reliable traffic flow prediction is crucial for mitigating urban congestion.This paper proposes Attentionbased spatiotemporal Interactive Dynamic Graph Convolutional Network(AIDGCN),a novel architecture integrating Interactive Dynamic Graph Convolution Network(IDGCN)with Temporal Multi-Head Trend-Aware Attention.Its core innovation lies in IDGCN,which uniquely splits sequences into symmetric intervals for interactive feature sharing via dynamic graphs,and a novel attention mechanism incorporating convolutional operations to capture essential local traffic trends—addressing a critical gap in standard attention for continuous data.For 15-and 60-min forecasting on METR-LA,AIDGCN achieves MAEs of 0.75%and 0.39%,and RMSEs of 1.32%and 0.14%,respectively.In the 60-min long-term forecasting of the PEMS-BAY dataset,the AIDGCN out-performs the MRA-BGCN method by 6.28%,4.93%,and 7.17%in terms of MAE,RMSE,and MAPE,respectively.Experimental results demonstrate the superiority of our pro-posed model over state-of-the-art methods.
基金Project(42077244)supported by the National Natural Science Foundation of ChinaProject(2020-05)supported by the Open Research Fund of Guangdong Provincial Key Laboratory of Deep Earth Sciences and Geothermal Energy Exploitation and Utilization,China。
文摘Accurate prediction of rockburst intensity levels is crucial for ensuring the safety of deep hard rock engineering construction.This paper introduced an expert system for rockburst intensity level prediction that employs machine learning algorithms as the basis for its inference rules.The system comprises four modules:a database,a repository,an inference engine,and an interpreter.A database containing 1114 rockburst cases was used to construct 357 datasets that serve as the repository for the expert system.Additionally,19 types of machine learning algorithms were used to establish 6783 micro-models to construct cognitive rules within the inference engine.By integrating probability theory and marginal analysis,a fuzzy scoring method based on the SoftMax function was developed and applied to the interpreter for rockburst intensity level prediction,effectively restoring the continuity of rockburst characteristics.The research results indicate that ensemble algorithms based on decision trees are more effective in capturing the characteristics of rockburst.Key factors for accurate prediction of rockburst intensity include uniaxial compressive strength,elastic energy index,the maximum principal stress,tangential stress,and their composite indicators.The accuracy of the proposed rockburst intensity level prediction expert system was verified using 20 engineering rockburst cases,with predictions aligning closely with the actual rockburst intensity levels.
基金supported by the Japan Society for the Promotion of Science(JSPS)KAKENHI(Grant Nos.JP23KK0182,JP23K26356,and JP24K00971).
文摘Stony debris flows,characterized by coarse boulders embedded in a sediment-laden matrix,greatly amplify destructive potential by altering flow dynamics and impact forces.Conventional single-phase particle-fluidmixture models often struggle to capture the complexities introduced by coarse boulders and multi-phase interactions,while strong-coupling methods can be computationally prohibitive for practical hazard assessments.In this study,we propose a semi-hybrid,fully resolved coupling numerical framework for modeling boulder-laden debris flows.This framework conceptualizes debris flows as a composite system comprising a continuous viscous fluidphase(including finesediments)and a discrete phase of arbitrarily shaped coarse particles.The continuous phase is treated as a generalized nonlinear Coulomb-viscoplastic fluidusing the smoothed particle hydrodynamics(SPH)method,while coarse particles are modeled via the distributed contact discrete element method(DCDEM).These two phases are coupled through an efficienttwo-way resolved scheme,ensuring accurate simulation of flow-boulder interactions within a unifiedtimeframe.We validate the proposed method against two physical experiments:(1)gravity-driven concrete flows and(2)debris flowinteracting with slit-type barriers.Results confirmthe method's robustness in accurately capturing fluid-solid-structureinteractions and deposition processes.Its capabilities are further showcased through the simulation of a stony debris-flowevent inWenchuan County,China,highlighting its promise for real-world engineering applications and validating the effectiveness of the existing cascade dam system in mitigating debrisflowimpact and energy dissipation.
基金support of the National Natural Science Foundation of China(Grant Nos.52179116 and 51991392)the support of Key Deployment Projects of Chinese Academy of Sciences(Grant No.ZDRW-ZS-2021-3).
文摘Shield tunneling in saturated ground poses challenges due to the potential risk of ground collapse resulting from seepage force and inadequate support pressure.This study employed a laboratory model test and a theoretical validation to elucidate the mechanisms of face failure and subsequent ground collapse in saturated ground during slurry pressure-balanced shield(SPBS)tunneling operations.A slurry circulation system was developed to ensure steady shield tunneling and to replicate the phenomena of ground collapse.Investigations into shield tunneling parameters and ground responses,including soil pressure,pore water pressure,and surface subsidence,were conducted to understand the mechanisms of face failure and subsequent ground collapse.The theoretical solution for the critical collapse pressure of the tunnel face,based on the rotational failure mechanism,was validated through the comparison with the experimentally determined critical collapse pressure.The results indicate that:(1)appropriate adjustments of tunneling parameters are crucial for promoting filtercake formation,maintaining chamber pressure,and minimizing ground subsidence;(2)chamber pressure,soil pressure,pore water pressure,and ground subsidence are closely correlated with shield tunneling parameters and the formation of filter cake;(3)ground collapse follows a continuous failure mode due to the destruction of filtercake and the decrease in chamber pressure;(4)the soil pressure at the cutterhead is more sensitive to disturbances from shield tunneling than chamber pressure;and(5)experimentally determined critical collapse pressures is consistent with the theoretical solution of limit analysis.
基金supported by the National Natural Science Foundation of China(Grant Nos.42407267 and 52374152)the Natural Science Foundation of Jiangsu Province,China(Grant No.BK20220975).
文摘Time-delayed blasting is widely utilized in engineering to mitigate induced vibration hazards and enhance fragmentation.The underlying vibration reduction principle is the decrease of the charge weight per delay,while the potential for further vibration reduction remains debated,largely due to unclear underlying mechanisms.In light of the popularization of electronic detonators and the representativeness of double-hole configurationsfor multiple blastholes,it is essential to investigate the vibration characteristics induced by time-delayed double blastholes.Therefore,a series of doubleborehole experimental blasts was conducted in an underground roadway to clarify the variation in vibration from single-hole to dual-hole conditions.Based on the experimental data and inherent limitations,an exact full-fieldtheoretical model was further employed to systematically analyze the effects of delay time,charge length,and borehole inclination angle on vibrations induced by various doublehole configurations.The experimental data and theoretical analysis reveal that the general scaled distance effectively predicts vibrations in delayed blasting but does not reflectvibration reduction.Increasing delay time causes fluctuatingPPVs,which stabilize slightly above single-hole PPVs as delay times exceed a certain value.The delayed blasting primarily reduces near-fieldfrequencies.Longer charge lengths in double boreholes increase PPV levels and attenuation rates within a certain length,and the vibration behavior of combined long and short charge lengths is governed by the long blasthole.Larger blasthole inclination angles enhance vibration amplitude and reduce PPV attenuation rates.Optimizing inclination angles is more critical than adjusting delay times,and parallel boreholes offer the best vibration control.
基金support from the National Natural Science Foundation of China(Grant Nos.52278432 and 52478475)the Science and Technology Research and Development Plan of China National Railway Group Co.,Ltd.(Grant No.K2023G033)were greatly appreciated.
文摘Understanding the shakedown behavior of fill material is paramount to estimate the deformation stability of railway subgrade.Especially for red mudstone fill material(RMF),the noticeable overestimation of bearing capacity would be encountered if the conventional strength method is used.This paper presents the shakedown analysis on RMF,with a specific emphasis on the effect of water content.A series of cyclic triaxial tests with 50,000 loading cycles was conducted.Two-stage behavior of permanent deformation and dissipated energy responses was clearly characterized,from which an energy-based criterion was proposed to determine the shakedown limits.The proposed energy-based criterion was validated by examining its performance to various geomaterials including cohesive soils and unbound granular materials(UGMs).By applying the proposed method to RMF,the S-shape evolution curve was obtained in terms of shakedown limits with initial suction.Microfabric difference was believed as the main consequence of the S-shape mode.Demonstration was confirmed by the mercury intrusion porosimetry(MIP)and scanning electron microscope(SEM)analyses.By applying the proposed method to different geomaterials,an extensive comparison was made between the shakedown limits and the static shear strength.The ratio of shakedown limits to the static shear strength for saturated RMF specimen fell within the range of soft clays,while that of unsaturated specimen lies within the range of UGMs.
