The main cable is the primary load-bearing component of a suspension bridge,continuously exposed to harsh environmental conditions,such as wind and rain,throughout the year.These adverse conditions contribute to varyi...The main cable is the primary load-bearing component of a suspension bridge,continuously exposed to harsh environmental conditions,such as wind and rain,throughout the year.These adverse conditions contribute to varying degrees of degradation and damage to the main cable,necessitating regular inspections to prevent catastrophic failures.Traditional manual inspection methods not only suffer from low efficiency but also pose significant safety risks to personnel.To address these challenges and ensure the safe and effective inspection of suspension bridge main cables,this study introduces a novel cooperative climbing robot,designated as Main Cable Robot Version II(CCRobot-M-II),inspired by the locomotion of the inchworm.The robot employs an alternating opening and closing mechanism of four gripper sets,mimicking the inchworm's movement to achieve efficient crawling along the suspension bridge handrails.This paper provides a comprehensive analysis of the structural design,key components,and motion mechanisms of CCRobot-M-II.A detailed force analysis of the robot's crawling process is also presented,followed by the design of the control system and the development of an efficient motion control algorithm.Laboratory experiments demonstrate that the robot achieves a positional error of 00.64%during crawling,with a maximum average crawling speed of 7.6 m/min.Furthermore,the biomimetic design enables the robot to overcome obstacles up to 30 mm in height and possess the capability to handle suspension bridge cables with spans ranging from 740 to 1100 mm.Finally,CCRobot-M-II successfully conducted an inspection of the main cable on a suspension bridge,marking the world's first successful deployment of a climbing robot for main cable inspection on a suspension bridge.展开更多
This study investigates the performance of high-strength cable bolts under impact loading conditions representative of rock bursts in underground environments.Although widely used,the dynamic behaviour of these cable ...This study investigates the performance of high-strength cable bolts under impact loading conditions representative of rock bursts in underground environments.Although widely used,the dynamic behaviour of these cable bolts has received limited experimental attention,and their effectiveness in seismically active zones remains a subject of ongoing debate.To address this gap,a reverse pull-out test machine integrated with a drop hammer rig was employed.Tests were conducted on 70-t SUMO bulbed and non-bulbed cable bolts with encapsulation lengths of 300 and 450 mm,subjected to an impact energy of 14.52 k J.Results indicate that non-bulbed cables,despite showing lower initial peak loads(average 218 vs.328 k N for bulbed cables at 300 mm encapsulation),demonstrated superior energy absorption(average 11.26 vs.8.75 k J)and displacement capacity(average 48.40 vs.36.25 mm).Increasing the encapsulation length for bulbed cables led to a reduction in initial peak load but improved displacement and energy absorption.The dominant failure mechanism was debonding at the cable-grout interface,characterised by frictional sliding and cable rotation.These findings provide new insights into the energy dissipation mechanisms of cables and support the development of more resilient ground support systems for dynamically active conditions.展开更多
In-situ enlargement of super-large-span tunnels can intensify excavation-induced unloading in the surrounding rock,increasing deformation demand and failure risk during construction.This study combines laboratory mode...In-situ enlargement of super-large-span tunnels can intensify excavation-induced unloading in the surrounding rock,increasing deformation demand and failure risk during construction.This study combines laboratory model tests with FLAC3D simulations to evaluate the stabilizing role of prestressed anchor cables and to establish an energy-balance framework for support optimization.Comparative model tests of existing and enlarged tunnel sections,with and without anchors,show that reinforcement increases load-carrying capacity,reduces displacement,and confines damage to more localized zones.The numerical simulations reproduce displacement fields,shear-strain localization,and plastic-zone evolution with good agreement against the experimental observations.The energy framework is implemented in the in-situ simulations by quantifying unloading-related energy release in the rock mass and reinforcement work contributed by the anchors,and by introducing an energy release–reinforcement ratio as a stability indicator.Parametric analyses indicate that anchor length,spacing,and prestress influence stability in a nonlinear manner,with diminishing returns once reinforcement extends beyond the mechanically dominant deformation zone.An efficient parameter window is identified that improves deformation and yielding control while avoiding unnecessary reinforcement.The results provide an energy-consistent and design-oriented basis for prestressed anchorage selection in large-span tunnel expansion.展开更多
Wi-Fi technology has evolved significantly since its introduction in 1997,advancing to Wi-Fi 6 as the latest standard,with Wi-Fi 7 currently under development.Despite these advancements,integrating machine learning in...Wi-Fi technology has evolved significantly since its introduction in 1997,advancing to Wi-Fi 6 as the latest standard,with Wi-Fi 7 currently under development.Despite these advancements,integrating machine learning into Wi-Fi networks remains challenging,especially in decentralized environments with multiple access points(mAPs).This paper is a short review that summarizes the potential applications of federated reinforcement learning(FRL)across eight key areas of Wi-Fi functionality,including channel access,link adaptation,beamforming,multi-user transmissions,channel bonding,multi-link operation,spatial reuse,and multi-basic servic set(multi-BSS)coordination.FRL is highlighted as a promising framework for enabling decentralized training and decision-making while preserving data privacy.To illustrate its role in practice,we present a case study on link activation in a multi-link operation(MLO)environment with multiple APs.Through theoretical discussion and simulation results,the study demonstrates how FRL can improve performance and reliability,paving the way for more adaptive and collaborative Wi-Fi networks in the era of Wi-Fi 7 and beyond.展开更多
基金Shenzhen Science and Technology Program(Grant No.20220817171811004)(Grant No.RCBS20231211090816033)+4 种基金the Major Key Project of PCL,China under Grant PCL2025A13Longgang District,Shenzhen's"Ten-Action Plan"for Supporting Innovation Projects(Grant No.LGKCSDPT2024002,LGKCSDPT2024003,LGKCSDPT2024004)the"Zhiguo"Action of Guangxi Science and Technology Program(Grant No.ZG2503980003)Guangdong S&T Program under(Grant No.2025B0909040003)Guangdong Provincial Leading Talent Program(Grant No.2024TX08Z319).
文摘The main cable is the primary load-bearing component of a suspension bridge,continuously exposed to harsh environmental conditions,such as wind and rain,throughout the year.These adverse conditions contribute to varying degrees of degradation and damage to the main cable,necessitating regular inspections to prevent catastrophic failures.Traditional manual inspection methods not only suffer from low efficiency but also pose significant safety risks to personnel.To address these challenges and ensure the safe and effective inspection of suspension bridge main cables,this study introduces a novel cooperative climbing robot,designated as Main Cable Robot Version II(CCRobot-M-II),inspired by the locomotion of the inchworm.The robot employs an alternating opening and closing mechanism of four gripper sets,mimicking the inchworm's movement to achieve efficient crawling along the suspension bridge handrails.This paper provides a comprehensive analysis of the structural design,key components,and motion mechanisms of CCRobot-M-II.A detailed force analysis of the robot's crawling process is also presented,followed by the design of the control system and the development of an efficient motion control algorithm.Laboratory experiments demonstrate that the robot achieves a positional error of 00.64%during crawling,with a maximum average crawling speed of 7.6 m/min.Furthermore,the biomimetic design enables the robot to overcome obstacles up to 30 mm in height and possess the capability to handle suspension bridge cables with spans ranging from 740 to 1100 mm.Finally,CCRobot-M-II successfully conducted an inspection of the main cable on a suspension bridge,marking the world's first successful deployment of a climbing robot for main cable inspection on a suspension bridge.
文摘This study investigates the performance of high-strength cable bolts under impact loading conditions representative of rock bursts in underground environments.Although widely used,the dynamic behaviour of these cable bolts has received limited experimental attention,and their effectiveness in seismically active zones remains a subject of ongoing debate.To address this gap,a reverse pull-out test machine integrated with a drop hammer rig was employed.Tests were conducted on 70-t SUMO bulbed and non-bulbed cable bolts with encapsulation lengths of 300 and 450 mm,subjected to an impact energy of 14.52 k J.Results indicate that non-bulbed cables,despite showing lower initial peak loads(average 218 vs.328 k N for bulbed cables at 300 mm encapsulation),demonstrated superior energy absorption(average 11.26 vs.8.75 k J)and displacement capacity(average 48.40 vs.36.25 mm).Increasing the encapsulation length for bulbed cables led to a reduction in initial peak load but improved displacement and energy absorption.The dominant failure mechanism was debonding at the cable-grout interface,characterised by frictional sliding and cable rotation.These findings provide new insights into the energy dissipation mechanisms of cables and support the development of more resilient ground support systems for dynamically active conditions.
基金funded by the National Key R&D Program of China,China(No.2024YFF0507903)the National Key Research and Development Program of China(Grant No.2024YFF0507904)the National Natural Science Foundation of China,China(Grant No.52379114).These supports are gratefully acknowledged.
文摘In-situ enlargement of super-large-span tunnels can intensify excavation-induced unloading in the surrounding rock,increasing deformation demand and failure risk during construction.This study combines laboratory model tests with FLAC3D simulations to evaluate the stabilizing role of prestressed anchor cables and to establish an energy-balance framework for support optimization.Comparative model tests of existing and enlarged tunnel sections,with and without anchors,show that reinforcement increases load-carrying capacity,reduces displacement,and confines damage to more localized zones.The numerical simulations reproduce displacement fields,shear-strain localization,and plastic-zone evolution with good agreement against the experimental observations.The energy framework is implemented in the in-situ simulations by quantifying unloading-related energy release in the rock mass and reinforcement work contributed by the anchors,and by introducing an energy release–reinforcement ratio as a stability indicator.Parametric analyses indicate that anchor length,spacing,and prestress influence stability in a nonlinear manner,with diminishing returns once reinforcement extends beyond the mechanically dominant deformation zone.An efficient parameter window is identified that improves deformation and yielding control while avoiding unnecessary reinforcement.The results provide an energy-consistent and design-oriented basis for prestressed anchorage selection in large-span tunnel expansion.
基金funded by the Deanship of Scientific Research(DSR)at King Abdulaziz University,Jeddah,Saudi Arabia,grant number RG-2-611-42(A.O.A.).
文摘Wi-Fi technology has evolved significantly since its introduction in 1997,advancing to Wi-Fi 6 as the latest standard,with Wi-Fi 7 currently under development.Despite these advancements,integrating machine learning into Wi-Fi networks remains challenging,especially in decentralized environments with multiple access points(mAPs).This paper is a short review that summarizes the potential applications of federated reinforcement learning(FRL)across eight key areas of Wi-Fi functionality,including channel access,link adaptation,beamforming,multi-user transmissions,channel bonding,multi-link operation,spatial reuse,and multi-basic servic set(multi-BSS)coordination.FRL is highlighted as a promising framework for enabling decentralized training and decision-making while preserving data privacy.To illustrate its role in practice,we present a case study on link activation in a multi-link operation(MLO)environment with multiple APs.Through theoretical discussion and simulation results,the study demonstrates how FRL can improve performance and reliability,paving the way for more adaptive and collaborative Wi-Fi networks in the era of Wi-Fi 7 and beyond.
