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
The uplift resistance of the soil overlying shield tunnels significantly impacts their anti-floating stability.However,research on uplift resistance concerning special-shaped shield tunnels is limited.This study combi...The uplift resistance of the soil overlying shield tunnels significantly impacts their anti-floating stability.However,research on uplift resistance concerning special-shaped shield tunnels is limited.This study combines numerical simulation with machine learning techniques to explore this issue.It presents a summary of special-shaped tunnel geometries and introduces a shape coefficient.Through the finite element software,Plaxis3D,the study simulates six key parameters—shape coefficient,burial depth ratio,tunnel’s longest horizontal length,internal friction angle,cohesion,and soil submerged bulk density—that impact uplift resistance across different conditions.Employing XGBoost and ANN methods,the feature importance of each parameter was analyzed based on the numerical simulation results.The findings demonstrate that a tunnel shape more closely resembling a circle leads to reduced uplift resistance in the overlying soil,whereas other parameters exhibit the contrary effects.Furthermore,the study reveals a diminishing trend in the feature importance of buried depth ratio,internal friction angle,tunnel longest horizontal length,cohesion,soil submerged bulk density,and shape coefficient in influencing uplift resistance.展开更多
Underground engineering projects such as deep tunnel excavation often encounter rockburst disasters accompanied by numerous microseismic events.Rapid interpretation of microseismic signals is crucial for the timely id...Underground engineering projects such as deep tunnel excavation often encounter rockburst disasters accompanied by numerous microseismic events.Rapid interpretation of microseismic signals is crucial for the timely identification of rockbursts.However,conventional processing encompasses multi-step workflows,including classification,denoising,picking,locating,and computational analysis,coupled with manual intervention,which collectively compromise the reliability of early warnings.To address these challenges,this study innovatively proposes the“microseismic stethoscope"-a multi-task machine learning and deep learning model designed for the automated processing of massive microseismic signals.This model efficiently extracts three key parameters that are necessary for recognizing rockburst disasters:rupture location,microseismic energy,and moment magnitude.Specifically,the model extracts raw waveform features from three dedicated sub-networks:a classifier for source zone classification,and two regressors for microseismic energy and moment magnitude estimation.This model demonstrates superior efficiency compared to traditional processing and semi-automated processing,reducing per-event processing time from 0.71 s to 0.49 s to merely 0.036 s.It concurrently achieves 98%accuracy in source zone classification,with microseismic energy and moment magnitude estimation errors of 0.13 and 0.05,respectively.This model has been well applied and validated in the Daxiagu Tunnel case in Sichuan,China.The application results indicate that the model is as accurate as traditional methods in determining source parameters,and thus can be used to identify potential geomechanical processes of rockburst disasters.By enhancing the signal processing reliability of microseismic events,the proposed model in this study presents a significant advancement in the identification of rockburst disasters.展开更多
Offshore structures are constantly subjected to the complex forces of the marine environment,including wind,sea waves,currents,and seismic loadings.Among these,wind and sea wave forces persist throughout the structure...Offshore structures are constantly subjected to the complex forces of the marine environment,including wind,sea waves,currents,and seismic loadings.Among these,wind and sea wave forces persist throughout the structure’s lifetime.This study proposes a dynamic analysis approach that incorporates both time and frequency domain methods to investigate the structural responses of offshore structures under the combined effects of wind and wave forces.A wind wave-pier coupling dynamic model is first developed using a small-scale single pier,with corresponding dynamic equilibrium equations established.Fluctuating wind and sea waves are simulated using the weighted amplitude wave superposition(WAWS)method and linear superposition,respectively.Wind and wave load histories are then derived via Fourier transforms.The structural dynamic responses under different loading scenarios(wind only,wave only,and combined wind and wave)are analyzed using the Newmarkβmethod.Additionally,the effects of varying wind and wave parameters on structural responses are evaluated.The simulation results demonstrate that the structural responses to wind-wave coupling are smaller than the superimposed effects of wind and wave forces acting independently.When wind speeds are relatively low,wave forces dominate structural displacement and serve as the primary source of vibration.展开更多
Under earthquake action, different site conditions have a notable impact on the dynamic response of high-speed railway bridges after earthquakes, which in turn poses a threat to the running stability of trains in the ...Under earthquake action, different site conditions have a notable impact on the dynamic response of high-speed railway bridges after earthquakes, which in turn poses a threat to the running stability of trains in the post-earthquake period. Therefore, establishing a calculation method for the post-earthquake train speed threshold that considers the influence of different site characteristics is of great engineering significance. Taking the CRTS Ⅲ slab track as the research object, this study is based on the track irregularity root mean square rate(TRR), which the authors proposed earlier to quantify the track regularity level. Using the nonlinear least squares fitting method, the mapping relationship between the TRR and the postearthquake train running performance indicators on bridges is established. Furthermore, the influence of laws governing site categories and train speeds on post-earthquake train running performance on bridges is analyzed, and a train speed threshold for bridges based on running performance under random site conditions is proposed. The research results indicate that all train running performance indicators increase significantly with the increase of train operating speed;different site categories have a significant impact on post-earthquake track residual deformation and train running stability. The greater the amplitude of postearthquake track alignment residual deformation, the lower the threshold for the stable running speed of trains after the earthquake, with the speed threshold decreasing by up to 20%. The research outcomes can provide technical references for the post-earthquake safe operation and maintenance of high-speed railway bridges under complex site conditions, as well as the formulation of targeted train speed control schemes.展开更多
During the use of robotics in applications such as antiterrorism or combat,a motion-constrained pursuer vehicle,such as a Dubins unmanned surface vehicle(USV),must get close enough(within a prescribed zero or positive...During the use of robotics in applications such as antiterrorism or combat,a motion-constrained pursuer vehicle,such as a Dubins unmanned surface vehicle(USV),must get close enough(within a prescribed zero or positive distance)to a moving target as quickly as possible,resulting in the extended minimum-time intercept problem(EMTIP).Existing research has primarily focused on the zero-distance intercept problem,MTIP,establishing the necessary or sufficient conditions for MTIP optimality,and utilizing analytic algorithms,such as root-finding algorithms,to calculate the optimal solutions.However,these approaches depend heavily on the properties of the analytic algorithm,making them inapplicable when problem settings change,such as in the case of a positive effective range or complicated target motions outside uniform rectilinear motion.In this study,an approach employing a high-accuracy and quality-guaranteed mixed-integer piecewise-linear program(QG-PWL)is proposed for the EMTIP.This program can accommodate different effective interception ranges and complicated target motions(variable velocity or complicated trajectories).The high accuracy and quality guarantees of QG-PWL originate from elegant strategies such as piecewise linearization and other developed operation strategies.The approximate error in the intercept path length is proved to be bounded to h^(2)/(4√2),where h is the piecewise length.展开更多
Investigating the wind-sand flow response regularity in the longitudinal slope sections of desert highways provides a scientific basis for selecting the slope of desert roads.This study uses the Tengger Desert section...Investigating the wind-sand flow response regularity in the longitudinal slope sections of desert highways provides a scientific basis for selecting the slope of desert roads.This study uses the Tengger Desert section of the Wuhai-Maqin Expressway as a case study,employing CFD numerical simulation methods to calculate and analyze the wind-sand flow field distribution characteristics in different longitudinal slope sections.The results show that:(1)Along with the direction of the incoming flow,the windward and leeward slope toes of the embankment are low-wind-speed zones,with the wind speed at the leeward slope toe being even lower.The higher the embankment,the larger the low-wind-speed zone at the windward and leeward slope toes.As the longitudinal slope increases,the extent of the lowwind-speed zone at the same location along the route also increases.(2)Along the route direction,the wind speed at the windward and leeward slope toes decreases as embankment height increases.At the embankment toe,sand particles are transported from the top to the bottom of the longitudinal slope,and the greater the longitudinal slope,the stronger the transport effect.(3)Along the route direction,the sand accumulation around the embankment gradually gathers toward the bottom of the longitudinal slope as the slope increases.When the longitudinal slope is 3%and 4%,the trend of sand accumulation moving from the windward side at the end of the route to the leeward side at the start of the route is more significant.When the longitudinal slope is less than or equal to 3%,severe sand accumulation within the embankment range is reduced by 86.4%or more compared to when the slope is 4%.(4)Under the same longitudinal slope,the higher the embankment height,the smaller its transport rate.When the embankment height is the same,the greater the longitudinal slope,the greater the embankment transport rate.展开更多
This study explores theoretical insights and experimental results on monitoring load-carrying capacity degradation in bridge spans through frequency analysis.Experiments were conducted on real bridge structures,includ...This study explores theoretical insights and experimental results on monitoring load-carrying capacity degradation in bridge spans through frequency analysis.Experiments were conducted on real bridge structures,including the Binh Thuan Bridge,focusing on analyzing the power spectral density(PSD)of vibration signals under random traffic loads.Detailed digital models of various bridge spans with different structural designs and construction periods were developed to ensure diversity.The study utilized PSD to analyze the vibration signals from the bridge spans under various loading conditions,identifying the vibration frequencies and the corresponding response regions.The research correlated the observed frequency changes of PSD with the actual deterioration of the bridges over time,identifying patterns that indicate a reduction in stiffness.Experiments demonstrated that frequency changes,particularly in high-frequency regions,are directly related to a reduction in the stiffness of bridge spans.This supports the hypothesis that natural frequencies can serve as effective indicators of structural damage.Furthermore,the emergence and shift of resonant frequency regions provide valuable insights into the extent of damage in actual bridge spans,highlighting the potential for using changes in resonant frequency regions as a new tool for structural damage detection.展开更多
In real-world autonomous driving tests,unexpected events such as pedestrians or wild animals suddenly entering the driving path can occur.Conducting actual test drives under various weather conditions may also lead to...In real-world autonomous driving tests,unexpected events such as pedestrians or wild animals suddenly entering the driving path can occur.Conducting actual test drives under various weather conditions may also lead to dangerous situations.Furthermore,autonomous vehicles may operate abnormally in bad weather due to limitations of their sensors and GPS.Driving simulators,which replicate driving conditions nearly identical to those in the real world,can drastically reduce the time and cost required for market entry validation;consequently,they have become widely used.In this paper,we design a virtual driving test environment capable of collecting and verifying SiLS data under adverse weather conditions using multi-source images.The proposed method generates a virtual testing environment that incorporates various events,including weather,time of day,and moving objects,that cannot be easily verified in real-world autonomous driving tests.By setting up scenario-based virtual environment events,multi-source image analysis and verification using real-world DCUs(Data Concentrator Units)with V2X-Car edge cloud can effectively address risk factors that may arise in real-world situations.We tested and validated the proposed method with scenarios employing V2X communication and multi-source image analysis.展开更多
Traffic at urban intersections frequently encounters unexpected obstructions,resulting in congestion due to uncooperative and priority-based driving behavior.This paper presents an optimal right-turn coordination syst...Traffic at urban intersections frequently encounters unexpected obstructions,resulting in congestion due to uncooperative and priority-based driving behavior.This paper presents an optimal right-turn coordination system for Connected and Automated Vehicles(CAVs)at single-lane intersections,particularly in the context of left-hand side driving on roads.The goal is to facilitate smooth right turns for certain vehicles without creating bottlenecks.We consider that all approaching vehicles share relevant information through vehicular communications.The Intersection Coordination Unit(ICU)processes this information and communicates the optimal crossing or turning times to the vehicles.The primary objective of this coordination is to minimize overall traffic delays,which also helps improve the fuel consumption of vehicles.By considering information from upcoming vehicles at the intersection,the coordination system solves an optimization problem to determine the best timing for executing right turns,ultimately minimizing the total delay for all vehicles.The proposed coordination system is evaluated at a typical urban intersection,and its performance is compared to traditional traffic systems.Numerical simulation results indicate that the proposed coordination system significantly enhances the average traffic speed and fuel consumption compared to the traditional traffic system in various scenarios.展开更多
As a cornerstone for applications such as autonomous driving,3D urban perception is a burgeoning field of study.Enhancing the performance and robustness of these perception systems is crucial for ensuring the safety o...As a cornerstone for applications such as autonomous driving,3D urban perception is a burgeoning field of study.Enhancing the performance and robustness of these perception systems is crucial for ensuring the safety of next-generation autonomous vehicles.In this work,we introduce a novel neural scene representation called Street Detection Gaussians(SDGs),which redefines urban 3D perception through an integrated architecture unifying reconstruction and detection.At its core lies the dynamic Gaussian representation,where time-conditioned parameterization enables simultaneous modeling of static environments and dynamic objects through physically constrained Gaussian evolution.The framework’s radar-enhanced perception module learns cross-modal correlations between sparse radardata anddense visual features,resulting ina22%reduction inocclusionerrors compared tovisiononly systems.A breakthrough differentiable rendering pipeline back-propagates semantic detection losses throughout the entire 3D reconstruction process,enabling the optimization of both geometric and semantic fidelity.Evaluated on the Waymo Open Dataset and the KITTI Dataset,the system achieves real-time performance(135 Frames Per Second(FPS)),photorealistic quality(Peak Signal-to-Noise Ratio(PSNR)34.9 dB),and state-of-the-art detection accuracy(78.1%Mean Average Precision(mAP)),demonstrating a 3.8×end-to-end improvement over existing hybrid approaches while enabling seamless integration with autonomous driving stacks.展开更多
This study investigates the influence of loading frequency on the fatigue behavior of ballastless track concrete for high-speed railways,aiming to support the development of concrete capable of withstanding higher ope...This study investigates the influence of loading frequency on the fatigue behavior of ballastless track concrete for high-speed railways,aiming to support the development of concrete capable of withstanding higher operational speeds.Fatigue tests were conducted at loading frequencies ranging from 5 to 40 Hz,with a focus on fatigue life,damage evolution,energy dissipation,and residual fatigue strain in the concrete.The results indicate that between 5 and 15 Hz,the fatigue life and energy dissipation remain relatively stable,with minimal damage evolution and small residual strains.As the frequency increases to 15-20 Hz,the fatigue life and energy dissipation gradually decrease,while damage accumulation and residual strain increase.Beyond 20 Hz,both fatigue life and energy dissipation decrease rapidly,damage accumulation becomes more pronounced,and residual strain continues to rise.These phenomena are primarily attributed to the increased strain rate and load change rate at higher frequencies,which affect the microstructure evolution and lead to reduced fatigue performance.展开更多
Global climate change is intensifying the impact of slope hazards,particularly rainfall-induced landslide hazards(RILH),on mountain road networks(MRNs).However,effective quantitative models for dynamically assessing M...Global climate change is intensifying the impact of slope hazards,particularly rainfall-induced landslide hazards(RILH),on mountain road networks(MRNs).However,effective quantitative models for dynamically assessing MRNs vulnerability under RILH disturbances are still lacking.To bridge this gap,this study develops a Cascading Failure Model for Rainfall-Induced Landslide Hazard(CFM-RILH).Validation via a case study of the GarzêTibetan Autonomous Prefecture Road Network(GTPRNs)reveals key characteristics of MRNs system vulnerability under RILH disturbances:(1)Under the disturbance effects of RILH,the vulnerability of the MRNs system follows a nonlinear phase transition law that intensifies with increasing disturbance intensity,exhibiting a distinct critical threshold.When the disturbance intensity exceeds this threshold,the system undergoes a global cascading failure phenomenon analogous to an“avalanche.”(2)Under RILH disturbances,the robustness of the MRNs system possesses a distinct safety boundary.Exceeding this boundary not only fails to improve hazard resistance but instead substantially elevates the risk of large-scale cascading failure.(3)Increasing network redundancy may be considered one of the primary engineering measures for enhancing MRNs resilience against such disturbances.Based on these findings,we propose a“Two-Stage Emergency Response and Hierarchical Fortification”strategy specifically to improve the resilience of GTPRNs impacted by RILH.The CFM-RILH model provides an effective tool for assessing road network vulnerability under such hazards.Furthermore,its modeling framework can also inform vulnerability assessment and resilience strategy development for road networks affected by other types of slope hazards.展开更多
Amphibious vehicles are more prone to attitude instability compared to ships,making it crucial to develop effective methods for monitoring instability risks.However,large inclination events,which can lead to instabili...Amphibious vehicles are more prone to attitude instability compared to ships,making it crucial to develop effective methods for monitoring instability risks.However,large inclination events,which can lead to instability,occur frequently in both experimental and operational data.This infrequency causes events to be overlooked by existing prediction models,which lack the precision to accurately predict inclination attitudes in amphibious vehicles.To address this gap in predicting attitudes near extreme inclination points,this study introduces a novel loss function,termed generalized extreme value loss.Subsequently,a deep learning model for improved waterborne attitude prediction,termed iInformer,was developed using a Transformer-based approach.During the embedding phase,a text prototype is created based on the vehicle’s operation log data is constructed to help the model better understand the vehicle’s operating environment.Data segmentation techniques are used to highlight local data variation features.Furthermore,to mitigate issues related to poor convergence and slow training speeds caused by the extreme value loss function,a teacher forcing mechanism is integrated into the model,enhancing its convergence capabilities.Experimental results validate the effectiveness of the proposed method,demonstrating its ability to handle data imbalance challenges.Specifically,the model achieves over a 60%improvement in root mean square error under extreme value conditions,with significant improvements observed across additional metrics.展开更多
The safe driving and operation of trains is a necessary condition for ensuring the safe operation of trains.In particular,heavy-haul trains are characterized by the difficulty in driving and operation.Considering the ...The safe driving and operation of trains is a necessary condition for ensuring the safe operation of trains.In particular,heavy-haul trains are characterized by the difficulty in driving and operation.Considering the uncertainties in train driving and operation,this paper analyzes the relationship between the safety of heavy-haul electric locomotive hauled trains and driving and operation.It studies the auxiliary intelligent driving safety operation control methods.Through K-means to identify the characteristics of drivers'driving manipulation,the hidden Markov model adaptively adjusts the train driving and operation sequence,and conducts auxiliary driving reconstruction for heavy-haul locomotive driving and operation.Based on the train running curve and the locomotive traction/braking characteristics,it smoothly controls the exertion of the traction/braking force of heavy-haul locomotives,thereby optimizing the driving safety control of heavy-haul trains in the vehicle-environment-track system.Finally,the train operation simulation and optimized driving verification are carried out by simulating some track sections.The results show that the proposed method can correct and pre-optimize driving operations,improving the smoothness of heavy-haul trains by approximately 10%.It verifies the effectiveness of the proposed train assisted driving control reconstruction method,facilitating the smooth and safe operation of heavy-haul trains.展开更多
Purpose-Association of American railroads(AAR)standard automatic couplers are designed for much higher capacity than the normal operating loads.However,failure of knuckles and coupler bodies is still a common occurren...Purpose-Association of American railroads(AAR)standard automatic couplers are designed for much higher capacity than the normal operating loads.However,failure of knuckles and coupler bodies is still a common occurrence.Recent studies have shown that fatigue is the main reason behind such failures below the expected load.Moreover,knuckle failures occur more frequently than coupler body failures,which cause operational disruptions and also influence overall coupler life because of nonconforming contact between a new knuckle and an old coupler.In addition to new and old counterparts,undesired contact conditions are often the case with the new assembly due to casting-based manufacturing inaccuracies.Design/methodology/approach-A study is thus carried out in this paper to understand the variation of load transfer paths and its consequences caused by dimensional variability.A finite element model of an E-type coupler’s knuckle is developed and different possible contact conditions of the knuckle with the coupler head are simulated.Knuckles generally fail in pulling mode,during which the possible contacting elements of knuckle are pulling lugs,pin protector regions and pinholes.Due to dimensional variability,contact conditions may exist where an individual or a combination of these elements are in contact.Findings-Simulation results indicate that under regular operational conditions,having only the pulling lugs in contact reduces the risk of knuckle failure and maintains assembly integrity even if the knuckle fails.However,under extreme loading conditions,the safest scenario is when both pulling lugs and pin protector regions are in contact.Originality/value-These findings are believed to assist in defining the dimensional variability limits to ensure the desired contacts between the mating surfaces of the knuckle and coupler body of railway couplers of AAR type.This work contributes to understanding implications of dimensional variability in the railway couplers.The insight presented are useful in design,manufacturing and maintenance of railway coupler’s knuckle.展开更多
In underwater target search path planning,the accuracy of sonar models directly dictates the accurate assessment of search coverage.In contrast to physics-informed sonar models,traditional geometric sonar models fail ...In underwater target search path planning,the accuracy of sonar models directly dictates the accurate assessment of search coverage.In contrast to physics-informed sonar models,traditional geometric sonar models fail to accurately characterize the complex influence of marine environments.To overcome these challenges,we propose an acoustic physics-informed intelligent path planning framework for underwater target search,integrating three core modules:The acoustic-physical modeling module adopts 3D ray-tracing theory and the active sonar equation to construct a physics-driven sonar detection model,explicitly accounting for environmental factors that influence sonar performance across heterogeneous spaces.The hybrid parallel computing module adopts a message passing interface(MPI)/open multi-processing(Open MP)hybrid strategy for large-scale acoustic simulations,combining computational domain decomposition and physics-intensive task acceleration.The search path optimization module adopts the covariance matrix adaptation evolution algorithm to solve continuous optimization problems of heading angles,which ensures maximum search coverage for targets.Largescale experiments conducted in the Pacific and Atlantic Oceans demonstrate the framework's effectiveness:(1)Precise capture of sonar detection range variations from 5.45 km to 50 km in heterogeneous marine environments.(2)Significant speedup of 453.43×for acoustic physics modeling through hybrid parallelization.(3)Notable improvements of 7.23%in detection coverage and 15.86%reduction in optimization time compared to the optimal baseline method.The framework provides a robust solution for underwater search missions in complex marine environments.展开更多
The squeezing deformation of surrounding rock is an important factor restricting the safe construction and long-term operation of tunnels when a tunnel passes through soft strata with high ground stress.Under such sof...The squeezing deformation of surrounding rock is an important factor restricting the safe construction and long-term operation of tunnels when a tunnel passes through soft strata with high ground stress.Under such soft rock geological conditions,the large deformation of the surrounding rock can easily lead to the failure of supporting structures,including shotcrete cracks,spalling,and steel arch distortion.To improve the lining support performance during the large deformation of squeezed surrounding rock,this work selects aluminum foam with densities of 0.25 g/cm3,0.42 g/cm3 and 0.61 g/cm3 as the buffer layer material and carries out uniaxial confined compression tests.Through the evaluation and analysis of energy absorption and the comparison of the yield pressure of aluminum foam with those of other cushioning materials and yield pressure support systems,the strength,deformation and energy absorption of aluminum foam with a density of 0.25 g/cm3 meet the yield pressure performance requirements.The numerical model of the buffer layer yielding support system is then established via the finite element analysis software ABAQUS,and the influence of the buffer layer setting on the lining support is analyzed.Compared with the conventional support scheme,the addition of an aluminum foam buffer layer can reduce the stress and deformation of the primary support and secondary lining.The maximum and minimum principal stresses of the primary support are reduced by 13%and 15%,respectively.The maximum and minimum principal stresses of the secondary lining are reduced by 15%and 12%,respectively,and the displacement deformation of the secondary lining position is reduced by 15%.In summary,the application of aluminum foam buffer layer can reduce the stress and deformation of the primary support and secondary lining,improve the stress safety of the support and reduce the deformation of the support.展开更多
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Guangzhou Metro Scientific Research Project(No.JT204-100111-23001)Chongqing Municipal Special Project for Technological Innovation and Application Development(No.CSTB2022TIAD-KPX0101)Science and Technology Research and Development Program of China State Railway Group Co.,Ltd.(No.N2023G045)。
文摘The uplift resistance of the soil overlying shield tunnels significantly impacts their anti-floating stability.However,research on uplift resistance concerning special-shaped shield tunnels is limited.This study combines numerical simulation with machine learning techniques to explore this issue.It presents a summary of special-shaped tunnel geometries and introduces a shape coefficient.Through the finite element software,Plaxis3D,the study simulates six key parameters—shape coefficient,burial depth ratio,tunnel’s longest horizontal length,internal friction angle,cohesion,and soil submerged bulk density—that impact uplift resistance across different conditions.Employing XGBoost and ANN methods,the feature importance of each parameter was analyzed based on the numerical simulation results.The findings demonstrate that a tunnel shape more closely resembling a circle leads to reduced uplift resistance in the overlying soil,whereas other parameters exhibit the contrary effects.Furthermore,the study reveals a diminishing trend in the feature importance of buried depth ratio,internal friction angle,tunnel longest horizontal length,cohesion,soil submerged bulk density,and shape coefficient in influencing uplift resistance.
基金supported by the National Natural Science Foundation of China(Grant Nos.42130719 and 42177173)the Doctoral Direct Train Project of Chongqing Natural Science Foundation(Grant No.CSTB2023NSCQ-BSX0029).
文摘Underground engineering projects such as deep tunnel excavation often encounter rockburst disasters accompanied by numerous microseismic events.Rapid interpretation of microseismic signals is crucial for the timely identification of rockbursts.However,conventional processing encompasses multi-step workflows,including classification,denoising,picking,locating,and computational analysis,coupled with manual intervention,which collectively compromise the reliability of early warnings.To address these challenges,this study innovatively proposes the“microseismic stethoscope"-a multi-task machine learning and deep learning model designed for the automated processing of massive microseismic signals.This model efficiently extracts three key parameters that are necessary for recognizing rockburst disasters:rupture location,microseismic energy,and moment magnitude.Specifically,the model extracts raw waveform features from three dedicated sub-networks:a classifier for source zone classification,and two regressors for microseismic energy and moment magnitude estimation.This model demonstrates superior efficiency compared to traditional processing and semi-automated processing,reducing per-event processing time from 0.71 s to 0.49 s to merely 0.036 s.It concurrently achieves 98%accuracy in source zone classification,with microseismic energy and moment magnitude estimation errors of 0.13 and 0.05,respectively.This model has been well applied and validated in the Daxiagu Tunnel case in Sichuan,China.The application results indicate that the model is as accurate as traditional methods in determining source parameters,and thus can be used to identify potential geomechanical processes of rockburst disasters.By enhancing the signal processing reliability of microseismic events,the proposed model in this study presents a significant advancement in the identification of rockburst disasters.
基金Project(2022YFB2302700)supported by the National Key Research and Development Program of China。
文摘Offshore structures are constantly subjected to the complex forces of the marine environment,including wind,sea waves,currents,and seismic loadings.Among these,wind and sea wave forces persist throughout the structure’s lifetime.This study proposes a dynamic analysis approach that incorporates both time and frequency domain methods to investigate the structural responses of offshore structures under the combined effects of wind and wave forces.A wind wave-pier coupling dynamic model is first developed using a small-scale single pier,with corresponding dynamic equilibrium equations established.Fluctuating wind and sea waves are simulated using the weighted amplitude wave superposition(WAWS)method and linear superposition,respectively.Wind and wave load histories are then derived via Fourier transforms.The structural dynamic responses under different loading scenarios(wind only,wave only,and combined wind and wave)are analyzed using the Newmarkβmethod.Additionally,the effects of varying wind and wave parameters on structural responses are evaluated.The simulation results demonstrate that the structural responses to wind-wave coupling are smaller than the superimposed effects of wind and wave forces acting independently.When wind speeds are relatively low,wave forces dominate structural displacement and serve as the primary source of vibration.
基金supported by the Science and Technology Research and Development Program Project of China Railway Group Limited (Grant No.2022-Major-17)the National Natural Science Foundation of China (Grant Nos.52578619,52178180)+2 种基金the National Key Research and Development Program of China (Grant No.2022YFC3004304)the Frontier Cross Research Project of Central South University (Grant No.2023QYJC006)the Natural Science Foundation of Hunan Province Funding Project (Grant No.2023JJ40724)。
文摘Under earthquake action, different site conditions have a notable impact on the dynamic response of high-speed railway bridges after earthquakes, which in turn poses a threat to the running stability of trains in the post-earthquake period. Therefore, establishing a calculation method for the post-earthquake train speed threshold that considers the influence of different site characteristics is of great engineering significance. Taking the CRTS Ⅲ slab track as the research object, this study is based on the track irregularity root mean square rate(TRR), which the authors proposed earlier to quantify the track regularity level. Using the nonlinear least squares fitting method, the mapping relationship between the TRR and the postearthquake train running performance indicators on bridges is established. Furthermore, the influence of laws governing site categories and train speeds on post-earthquake train running performance on bridges is analyzed, and a train speed threshold for bridges based on running performance under random site conditions is proposed. The research results indicate that all train running performance indicators increase significantly with the increase of train operating speed;different site categories have a significant impact on post-earthquake track residual deformation and train running stability. The greater the amplitude of postearthquake track alignment residual deformation, the lower the threshold for the stable running speed of trains after the earthquake, with the speed threshold decreasing by up to 20%. The research outcomes can provide technical references for the post-earthquake safe operation and maintenance of high-speed railway bridges under complex site conditions, as well as the formulation of targeted train speed control schemes.
基金supported by the National Natural Sci‐ence Foundation of China(Grant No.62306325)。
文摘During the use of robotics in applications such as antiterrorism or combat,a motion-constrained pursuer vehicle,such as a Dubins unmanned surface vehicle(USV),must get close enough(within a prescribed zero or positive distance)to a moving target as quickly as possible,resulting in the extended minimum-time intercept problem(EMTIP).Existing research has primarily focused on the zero-distance intercept problem,MTIP,establishing the necessary or sufficient conditions for MTIP optimality,and utilizing analytic algorithms,such as root-finding algorithms,to calculate the optimal solutions.However,these approaches depend heavily on the properties of the analytic algorithm,making them inapplicable when problem settings change,such as in the case of a positive effective range or complicated target motions outside uniform rectilinear motion.In this study,an approach employing a high-accuracy and quality-guaranteed mixed-integer piecewise-linear program(QG-PWL)is proposed for the EMTIP.This program can accommodate different effective interception ranges and complicated target motions(variable velocity or complicated trajectories).The high accuracy and quality guarantees of QG-PWL originate from elegant strategies such as piecewise linearization and other developed operation strategies.The approximate error in the intercept path length is proved to be bounded to h^(2)/(4√2),where h is the piecewise length.
基金financially supported by Youth Science“Research on Failure Mechanism and Evaluation Method of Sand Control Measures for Railway Machinery in Sandy Area”(12302511)Ningxia Transportation Department Science and Technology Project(20200173)The Central Guidance on Local Science and Technology Development Funds(22ZY1QA005)。
文摘Investigating the wind-sand flow response regularity in the longitudinal slope sections of desert highways provides a scientific basis for selecting the slope of desert roads.This study uses the Tengger Desert section of the Wuhai-Maqin Expressway as a case study,employing CFD numerical simulation methods to calculate and analyze the wind-sand flow field distribution characteristics in different longitudinal slope sections.The results show that:(1)Along with the direction of the incoming flow,the windward and leeward slope toes of the embankment are low-wind-speed zones,with the wind speed at the leeward slope toe being even lower.The higher the embankment,the larger the low-wind-speed zone at the windward and leeward slope toes.As the longitudinal slope increases,the extent of the lowwind-speed zone at the same location along the route also increases.(2)Along the route direction,the wind speed at the windward and leeward slope toes decreases as embankment height increases.At the embankment toe,sand particles are transported from the top to the bottom of the longitudinal slope,and the greater the longitudinal slope,the stronger the transport effect.(3)Along the route direction,the sand accumulation around the embankment gradually gathers toward the bottom of the longitudinal slope as the slope increases.When the longitudinal slope is 3%and 4%,the trend of sand accumulation moving from the windward side at the end of the route to the leeward side at the start of the route is more significant.When the longitudinal slope is less than or equal to 3%,severe sand accumulation within the embankment range is reduced by 86.4%or more compared to when the slope is 4%.(4)Under the same longitudinal slope,the higher the embankment height,the smaller its transport rate.When the embankment height is the same,the greater the longitudinal slope,the greater the embankment transport rate.
文摘This study explores theoretical insights and experimental results on monitoring load-carrying capacity degradation in bridge spans through frequency analysis.Experiments were conducted on real bridge structures,including the Binh Thuan Bridge,focusing on analyzing the power spectral density(PSD)of vibration signals under random traffic loads.Detailed digital models of various bridge spans with different structural designs and construction periods were developed to ensure diversity.The study utilized PSD to analyze the vibration signals from the bridge spans under various loading conditions,identifying the vibration frequencies and the corresponding response regions.The research correlated the observed frequency changes of PSD with the actual deterioration of the bridges over time,identifying patterns that indicate a reduction in stiffness.Experiments demonstrated that frequency changes,particularly in high-frequency regions,are directly related to a reduction in the stiffness of bridge spans.This supports the hypothesis that natural frequencies can serve as effective indicators of structural damage.Furthermore,the emergence and shift of resonant frequency regions provide valuable insights into the extent of damage in actual bridge spans,highlighting the potential for using changes in resonant frequency regions as a new tool for structural damage detection.
基金supported by Institute of Information and Communications Technology Planning and Evaluation(IITP)grant funded by the Korean government(MSIT)(No.2019-0-01842,Artificial Intelligence Graduate School Program(GIST))supported by Korea Planning&Evaluation Institute of Industrial Technology(KEIT)grant funded by the Ministry of Trade,Industry&Energy(MOTIE,Republic of Korea)(RS-2025-25448249+1 种基金Automotive Industry Technology Development(R&D)Program)supported by the Regional Innovation System&Education(RISE)programthrough the(Gwangju RISE Center),funded by the Ministry of Education(MOE)and the Gwangju Metropolitan City,Republic of Korea(2025-RISE-05-001).
文摘In real-world autonomous driving tests,unexpected events such as pedestrians or wild animals suddenly entering the driving path can occur.Conducting actual test drives under various weather conditions may also lead to dangerous situations.Furthermore,autonomous vehicles may operate abnormally in bad weather due to limitations of their sensors and GPS.Driving simulators,which replicate driving conditions nearly identical to those in the real world,can drastically reduce the time and cost required for market entry validation;consequently,they have become widely used.In this paper,we design a virtual driving test environment capable of collecting and verifying SiLS data under adverse weather conditions using multi-source images.The proposed method generates a virtual testing environment that incorporates various events,including weather,time of day,and moving objects,that cannot be easily verified in real-world autonomous driving tests.By setting up scenario-based virtual environment events,multi-source image analysis and verification using real-world DCUs(Data Concentrator Units)with V2X-Car edge cloud can effectively address risk factors that may arise in real-world situations.We tested and validated the proposed method with scenarios employing V2X communication and multi-source image analysis.
基金supported by the Japan Society for the Promotion of Science(JSPS)Grants-in-Aid for Scientific Research(C)23K03898.
文摘Traffic at urban intersections frequently encounters unexpected obstructions,resulting in congestion due to uncooperative and priority-based driving behavior.This paper presents an optimal right-turn coordination system for Connected and Automated Vehicles(CAVs)at single-lane intersections,particularly in the context of left-hand side driving on roads.The goal is to facilitate smooth right turns for certain vehicles without creating bottlenecks.We consider that all approaching vehicles share relevant information through vehicular communications.The Intersection Coordination Unit(ICU)processes this information and communicates the optimal crossing or turning times to the vehicles.The primary objective of this coordination is to minimize overall traffic delays,which also helps improve the fuel consumption of vehicles.By considering information from upcoming vehicles at the intersection,the coordination system solves an optimization problem to determine the best timing for executing right turns,ultimately minimizing the total delay for all vehicles.The proposed coordination system is evaluated at a typical urban intersection,and its performance is compared to traditional traffic systems.Numerical simulation results indicate that the proposed coordination system significantly enhances the average traffic speed and fuel consumption compared to the traditional traffic system in various scenarios.
文摘As a cornerstone for applications such as autonomous driving,3D urban perception is a burgeoning field of study.Enhancing the performance and robustness of these perception systems is crucial for ensuring the safety of next-generation autonomous vehicles.In this work,we introduce a novel neural scene representation called Street Detection Gaussians(SDGs),which redefines urban 3D perception through an integrated architecture unifying reconstruction and detection.At its core lies the dynamic Gaussian representation,where time-conditioned parameterization enables simultaneous modeling of static environments and dynamic objects through physically constrained Gaussian evolution.The framework’s radar-enhanced perception module learns cross-modal correlations between sparse radardata anddense visual features,resulting ina22%reduction inocclusionerrors compared tovisiononly systems.A breakthrough differentiable rendering pipeline back-propagates semantic detection losses throughout the entire 3D reconstruction process,enabling the optimization of both geometric and semantic fidelity.Evaluated on the Waymo Open Dataset and the KITTI Dataset,the system achieves real-time performance(135 Frames Per Second(FPS)),photorealistic quality(Peak Signal-to-Noise Ratio(PSNR)34.9 dB),and state-of-the-art detection accuracy(78.1%Mean Average Precision(mAP)),demonstrating a 3.8×end-to-end improvement over existing hybrid approaches while enabling seamless integration with autonomous driving stacks.
基金sponsored by the National Natural Science Foundation of China(Grant No.52438002)the New Cornerstone Science Foundation through the XPLORER PRIZE.
文摘This study investigates the influence of loading frequency on the fatigue behavior of ballastless track concrete for high-speed railways,aiming to support the development of concrete capable of withstanding higher operational speeds.Fatigue tests were conducted at loading frequencies ranging from 5 to 40 Hz,with a focus on fatigue life,damage evolution,energy dissipation,and residual fatigue strain in the concrete.The results indicate that between 5 and 15 Hz,the fatigue life and energy dissipation remain relatively stable,with minimal damage evolution and small residual strains.As the frequency increases to 15-20 Hz,the fatigue life and energy dissipation gradually decrease,while damage accumulation and residual strain increase.Beyond 20 Hz,both fatigue life and energy dissipation decrease rapidly,damage accumulation becomes more pronounced,and residual strain continues to rise.These phenomena are primarily attributed to the increased strain rate and load change rate at higher frequencies,which affect the microstructure evolution and lead to reduced fatigue performance.
基金financially supported by the National Key R&D Program of China(2024YFE0111900)The National Natural Science Foundation of China(U2468214,52378370,52278372)+1 种基金The National Ten Thousand Talent Program for Young Top-notch Talents(2022QB04978)The Science and Technology Program of Hebei Province(2023HBQZYCSB004)。
文摘Global climate change is intensifying the impact of slope hazards,particularly rainfall-induced landslide hazards(RILH),on mountain road networks(MRNs).However,effective quantitative models for dynamically assessing MRNs vulnerability under RILH disturbances are still lacking.To bridge this gap,this study develops a Cascading Failure Model for Rainfall-Induced Landslide Hazard(CFM-RILH).Validation via a case study of the GarzêTibetan Autonomous Prefecture Road Network(GTPRNs)reveals key characteristics of MRNs system vulnerability under RILH disturbances:(1)Under the disturbance effects of RILH,the vulnerability of the MRNs system follows a nonlinear phase transition law that intensifies with increasing disturbance intensity,exhibiting a distinct critical threshold.When the disturbance intensity exceeds this threshold,the system undergoes a global cascading failure phenomenon analogous to an“avalanche.”(2)Under RILH disturbances,the robustness of the MRNs system possesses a distinct safety boundary.Exceeding this boundary not only fails to improve hazard resistance but instead substantially elevates the risk of large-scale cascading failure.(3)Increasing network redundancy may be considered one of the primary engineering measures for enhancing MRNs resilience against such disturbances.Based on these findings,we propose a“Two-Stage Emergency Response and Hierarchical Fortification”strategy specifically to improve the resilience of GTPRNs impacted by RILH.The CFM-RILH model provides an effective tool for assessing road network vulnerability under such hazards.Furthermore,its modeling framework can also inform vulnerability assessment and resilience strategy development for road networks affected by other types of slope hazards.
基金Supported by the National Defense Basic Scientific Research Program of China.
文摘Amphibious vehicles are more prone to attitude instability compared to ships,making it crucial to develop effective methods for monitoring instability risks.However,large inclination events,which can lead to instability,occur frequently in both experimental and operational data.This infrequency causes events to be overlooked by existing prediction models,which lack the precision to accurately predict inclination attitudes in amphibious vehicles.To address this gap in predicting attitudes near extreme inclination points,this study introduces a novel loss function,termed generalized extreme value loss.Subsequently,a deep learning model for improved waterborne attitude prediction,termed iInformer,was developed using a Transformer-based approach.During the embedding phase,a text prototype is created based on the vehicle’s operation log data is constructed to help the model better understand the vehicle’s operating environment.Data segmentation techniques are used to highlight local data variation features.Furthermore,to mitigate issues related to poor convergence and slow training speeds caused by the extreme value loss function,a teacher forcing mechanism is integrated into the model,enhancing its convergence capabilities.Experimental results validate the effectiveness of the proposed method,demonstrating its ability to handle data imbalance challenges.Specifically,the model achieves over a 60%improvement in root mean square error under extreme value conditions,with significant improvements observed across additional metrics.
基金Project(U2034211)supported by the National Natural Science Foundation of ChinaProject(20232ACE01013)supported by the Major Scientific and Technological Research and Development Special Project of Jiangxi Province,China。
文摘The safe driving and operation of trains is a necessary condition for ensuring the safe operation of trains.In particular,heavy-haul trains are characterized by the difficulty in driving and operation.Considering the uncertainties in train driving and operation,this paper analyzes the relationship between the safety of heavy-haul electric locomotive hauled trains and driving and operation.It studies the auxiliary intelligent driving safety operation control methods.Through K-means to identify the characteristics of drivers'driving manipulation,the hidden Markov model adaptively adjusts the train driving and operation sequence,and conducts auxiliary driving reconstruction for heavy-haul locomotive driving and operation.Based on the train running curve and the locomotive traction/braking characteristics,it smoothly controls the exertion of the traction/braking force of heavy-haul locomotives,thereby optimizing the driving safety control of heavy-haul trains in the vehicle-environment-track system.Finally,the train operation simulation and optimized driving verification are carried out by simulating some track sections.The results show that the proposed method can correct and pre-optimize driving operations,improving the smoothness of heavy-haul trains by approximately 10%.It verifies the effectiveness of the proposed train assisted driving control reconstruction method,facilitating the smooth and safe operation of heavy-haul trains.
文摘Purpose-Association of American railroads(AAR)standard automatic couplers are designed for much higher capacity than the normal operating loads.However,failure of knuckles and coupler bodies is still a common occurrence.Recent studies have shown that fatigue is the main reason behind such failures below the expected load.Moreover,knuckle failures occur more frequently than coupler body failures,which cause operational disruptions and also influence overall coupler life because of nonconforming contact between a new knuckle and an old coupler.In addition to new and old counterparts,undesired contact conditions are often the case with the new assembly due to casting-based manufacturing inaccuracies.Design/methodology/approach-A study is thus carried out in this paper to understand the variation of load transfer paths and its consequences caused by dimensional variability.A finite element model of an E-type coupler’s knuckle is developed and different possible contact conditions of the knuckle with the coupler head are simulated.Knuckles generally fail in pulling mode,during which the possible contacting elements of knuckle are pulling lugs,pin protector regions and pinholes.Due to dimensional variability,contact conditions may exist where an individual or a combination of these elements are in contact.Findings-Simulation results indicate that under regular operational conditions,having only the pulling lugs in contact reduces the risk of knuckle failure and maintains assembly integrity even if the knuckle fails.However,under extreme loading conditions,the safest scenario is when both pulling lugs and pin protector regions are in contact.Originality/value-These findings are believed to assist in defining the dimensional variability limits to ensure the desired contacts between the mating surfaces of the knuckle and coupler body of railway couplers of AAR type.This work contributes to understanding implications of dimensional variability in the railway couplers.The insight presented are useful in design,manufacturing and maintenance of railway coupler’s knuckle.
基金supported by Natural Science Foundation of Hu'nan Province(2024JJ5409)。
文摘In underwater target search path planning,the accuracy of sonar models directly dictates the accurate assessment of search coverage.In contrast to physics-informed sonar models,traditional geometric sonar models fail to accurately characterize the complex influence of marine environments.To overcome these challenges,we propose an acoustic physics-informed intelligent path planning framework for underwater target search,integrating three core modules:The acoustic-physical modeling module adopts 3D ray-tracing theory and the active sonar equation to construct a physics-driven sonar detection model,explicitly accounting for environmental factors that influence sonar performance across heterogeneous spaces.The hybrid parallel computing module adopts a message passing interface(MPI)/open multi-processing(Open MP)hybrid strategy for large-scale acoustic simulations,combining computational domain decomposition and physics-intensive task acceleration.The search path optimization module adopts the covariance matrix adaptation evolution algorithm to solve continuous optimization problems of heading angles,which ensures maximum search coverage for targets.Largescale experiments conducted in the Pacific and Atlantic Oceans demonstrate the framework's effectiveness:(1)Precise capture of sonar detection range variations from 5.45 km to 50 km in heterogeneous marine environments.(2)Significant speedup of 453.43×for acoustic physics modeling through hybrid parallelization.(3)Notable improvements of 7.23%in detection coverage and 15.86%reduction in optimization time compared to the optimal baseline method.The framework provides a robust solution for underwater search missions in complex marine environments.
基金the support of the National Natural Science Foundation of China(Grant No.42207199)Scientific Research Project of Education of Zhejiang Province(No.Y202351343)+1 种基金Zhejiang Postdoctoral Scientific Research Project(Grant Nos.ZJ2022155,ZJ2022156)Zhejiang Province International Science and Technology Cooperation Base Open Fund Project(IBGDP-2023-01)。
文摘The squeezing deformation of surrounding rock is an important factor restricting the safe construction and long-term operation of tunnels when a tunnel passes through soft strata with high ground stress.Under such soft rock geological conditions,the large deformation of the surrounding rock can easily lead to the failure of supporting structures,including shotcrete cracks,spalling,and steel arch distortion.To improve the lining support performance during the large deformation of squeezed surrounding rock,this work selects aluminum foam with densities of 0.25 g/cm3,0.42 g/cm3 and 0.61 g/cm3 as the buffer layer material and carries out uniaxial confined compression tests.Through the evaluation and analysis of energy absorption and the comparison of the yield pressure of aluminum foam with those of other cushioning materials and yield pressure support systems,the strength,deformation and energy absorption of aluminum foam with a density of 0.25 g/cm3 meet the yield pressure performance requirements.The numerical model of the buffer layer yielding support system is then established via the finite element analysis software ABAQUS,and the influence of the buffer layer setting on the lining support is analyzed.Compared with the conventional support scheme,the addition of an aluminum foam buffer layer can reduce the stress and deformation of the primary support and secondary lining.The maximum and minimum principal stresses of the primary support are reduced by 13%and 15%,respectively.The maximum and minimum principal stresses of the secondary lining are reduced by 15%and 12%,respectively,and the displacement deformation of the secondary lining position is reduced by 15%.In summary,the application of aluminum foam buffer layer can reduce the stress and deformation of the primary support and secondary lining,improve the stress safety of the support and reduce the deformation of the support.
