The vibration response and noise caused by subway trains can affect the safety and comfort of superstructures.To study the dynamic response characteristics of subway stations and superstructures under train loads with...The vibration response and noise caused by subway trains can affect the safety and comfort of superstructures.To study the dynamic response characteristics of subway stations and superstructures under train loads with a hard combination,a numerical model is developed in this study.The indoor model test verified the accuracy of the numerical model.The influence laws of different hard combinations,train operating speeds and modes were studied and evaluated accordingly.The results show that the frequency corresponding to the peak vibration acceleration level of each floor of the superstructure property is concentrated at 10–20 Hz.The vibration response decreases in the high-frequency parts and increases in the lowfrequency parts with increasing distance from the source.Furthermore,the factors,such as train operating speed,operating mode,and hard combination type,will affect the vibration of the superstructure.The vibration response under the reversible operation of the train is greater than that of the unidirectional operation.The operating speed of the train is proportional to its vibration response.The vibration amplification area appears between the middle and the top of the superstructure at a higher train speed.Its vibration acceleration level will exceed the limit value of relevant regulations,and vibration-damping measures are required.Within the scope of application,this study provides some suggestions for constructing subway stations and superstructures.展开更多
The wireless signals emitted by base stations serve as a vital link connecting people in today’s society and have been occupying an increasingly important role in real life.The development of the Internet of Things(I...The wireless signals emitted by base stations serve as a vital link connecting people in today’s society and have been occupying an increasingly important role in real life.The development of the Internet of Things(IoT)relies on the support of base stations,which provide a solid foundation for achieving a more intelligent way of living.In a specific area,achieving higher signal coverage with fewer base stations has become an urgent problem.Therefore,this article focuses on the effective coverage area of base station signals and proposes a novel Evolutionary Particle Swarm Optimization(EPSO)algorithm based on collective prediction,referred to herein as ECPPSO.Introducing a new strategy called neighbor-based evolution prediction(NEP)addresses the issue of premature convergence often encountered by PSO.ECPPSO also employs a strengthening evolution(SE)strategy to enhance the algorithm’s global search capability and efficiency,ensuring enhanced robustness and a faster convergence speed when solving complex optimization problems.To better adapt to the actual communication needs of base stations,this article conducts simulation experiments by changing the number of base stations.The experimental results demonstrate thatunder the conditionof 50 ormore base stations,ECPPSOconsistently achieves the best coverage rate exceeding 95%,peaking at 99.4400%when the number of base stations reaches 80.These results validate the optimization capability of the ECPPSO algorithm,proving its feasibility and effectiveness.Further ablative experiments and comparisons with other algorithms highlight the advantages of ECPPSO.展开更多
1.Introduction As China’s first floating production platform in ultra-deepwater,the“Deep Sea No.1”energy station is a milestone in China’s deepwater resource utilization.The energy station is located in the LS17-2...1.Introduction As China’s first floating production platform in ultra-deepwater,the“Deep Sea No.1”energy station is a milestone in China’s deepwater resource utilization.The energy station is located in the LS17-2 gas field,150 km off the southeast coast of Hainan Island,China.It is a semi-submersible platform(Fig.1)with a displacement of 101 thousand tonnes and an operational draft of 35 to 40 m.The platform is permanently moored in 1422 m water by 16 chain-polyester-chain mooring lines in a 4×4 pattern,and six steel catenary risers(SCRs)are attached to the platform.It is the world’s first and only semi-submersible platform with the function of condensate storage,so it can be regarded as a floating production storage and offloading(FPSO)unit.With the ability to produce 3 billion m3 of natural gas each year(enough for over 10 million families),the Deep Sea No.1 energy station is a key step toward China’s energy independence.The LS17-2 gas field,where the Deep Sea No.1 energy station is located,was discovered in 2014.Plans for its development were made in 2015,followed by research and a preliminary design.Deep Sea No.1 went into operation on June 25,2021,and will operate onsite continuously without dry-docking for 30 years.展开更多
The microwave wireless power transmission technologies for space solar power station are a crucial field in the international space sector,where various countries are competing in its development.This paper surveys th...The microwave wireless power transmission technologies for space solar power station are a crucial field in the international space sector,where various countries are competing in its development.This paper surveys the research experiments and development efforts related to space solar power stations and microwave wireless power transmission technologies worldwide.The objective is to assess the progress and current state of this technological foundation,determine the necessary focus for developing high-power microwave wireless power transmission technology,and provide clarity on the direction of future technology development in these areas.Finally,a distributed space solar power station plan that is immediately feasible is proposed.展开更多
Released in September 2024 by an oversight committee of the US National Aeronautics and Space Administration(NASA),a safety report about the International Space Station(ISS)cited,in addition to 50 other“areas of conc...Released in September 2024 by an oversight committee of the US National Aeronautics and Space Administration(NASA),a safety report about the International Space Station(ISS)cited,in addition to 50 other“areas of concern,”a troublesome leak first detected six years ago in one of the station’s modules[1].Given the persistent leak,called“a top safety risk”[2],and the fact that the space sta-tion has outlived its original life expectancy by more than 10 years,the agency’s current plans call for decommissioning the ISS in 2031 by dragging it into the Pacific Ocean[3].展开更多
The Hongyancun subway station in Chongqing,China,is 116 meters deep and the difference in air pressure often leaves users with clogged(堵塞的)ears when accessed via its elevator.When the air pressure outside the eardr...The Hongyancun subway station in Chongqing,China,is 116 meters deep and the difference in air pressure often leaves users with clogged(堵塞的)ears when accessed via its elevator.When the air pressure outside the eardrum(耳膜)becomes different than the pressure inside,you experience ear barotrauma(气压伤).It occurs most often during steep ascents and descents and is usually associated with plane take⁃offs and landings,or driving up or down mountains.Most subway stations dont usually cause ear barotrauma,because they arent deep or steep enough for your ears to register a significant enough difference in air pressure.But taking the elevator to reach Chinas deepest subway station might actually clog up your ears.Thats because it is located 116 meters below the surface,which is the equivalent of about 40 floors underground.展开更多
The implementation of the standard is expected to help electric vehicle battery swap stations to adapt to diversified needs and vehicle models,promoting the industry’s orderly and healthy development.
This article focuses on the municipal prefabricated bathroom station.It elaborates on its modular design concept,including key design points such as spatial layout,functional modules,and determination of key parameter...This article focuses on the municipal prefabricated bathroom station.It elaborates on its modular design concept,including key design points such as spatial layout,functional modules,and determination of key parameters;introduces the optimization of intelligent production processes,precision control,and integration of construction technology,and also mentions the verification of full lifecycle applications and quality control;as well as emphasizes the importance of BIM+IoT platform and looks forward to the future.展开更多
Ground fissure,as a common geo-hazard,impairs the integrity of the site soil and affects the seismic performance of engineering structures.In this paper,a finite element(FE)model for subway stations in a ground fissur...Ground fissure,as a common geo-hazard,impairs the integrity of the site soil and affects the seismic performance of engineering structures.In this paper,a finite element(FE)model for subway stations in a ground fissure area was developed and validated by using experimental results.Numerical analyses were conducted to investigate the seismic response and failure mode of subway stations in a ground fissure area with different locations.Effects of ground fissure on deformations and internal forces of a station,soil pressures and soil plastic strains were discussed.The results showed that the seismic response of the station was significantly amplified by the ground fissure,and stations in the ground fissure area displayed obvious rocking deformation during earthquakes as compared to those in the area without fissures.It also was found that the soil yielding around the station,the dislocation occurring in the ground fissure area,and the dynamic amplification effect were more significant under vertical ground motion,which weakened the station’s ductility and accelerated its destruction process.展开更多
As the core facility of offshore wind power systems,the structural safety of offshore booster stations directly impacts the stable operation of entire wind farms.With the global energy transition toward green and lowc...As the core facility of offshore wind power systems,the structural safety of offshore booster stations directly impacts the stable operation of entire wind farms.With the global energy transition toward green and lowcarbon goals,offshore wind power has emerged as a key renewable energy source,yet its booster stations face harsh marine environments,including persistent wave impacts,salt spray corrosion,and equipment-induced vibrations.Traditional monitoring methods relying on manual inspections and single-dimensional sensors suffer from critical limitations:low efficiency,poor real-time performance,and inability to capture millinewton-level stress fluctuations that signal early structural fatigue.To address these challenges,this study proposes a biomechanics-driven structural safety monitoring system integrated with deep learning.Inspired by biological stress-sensing mechanisms,the system deploys a distributedmulti-dimensional force sensor network to capture real-time stress distributions in key structural components.A hybrid convolutional neural network-radial basis function(CNN-RBF)model is developed:the CNN branch extracts spatiotemporal features from multi-source sensing data,while the RBF branch reconstructs the nonlinear stress field for accurate anomaly diagnosis.The three-tier architectural design—data layer(distributed sensor array),function layer(CNN-RBF modeling),and application layer(edge computing terminal)—enables a closedloop process from high-resolution data collection to real-time early warning,with data processing delay controlled within 200 ms.Experimental validation against traditional SOM-based systems demonstrates significant performance improvements:monitoring accuracy increased by 19.8%,efficiency by 23.4%,recall rate by 20.5%,and F1 score by 21.6%.Under extreme weather(e.g.,typhoons and winter storms),the system’s stability is 40% higher,with user satisfaction improving by 17.2%.The biomechanics-inspired sensor design enhances survival rates in salt fog(85.7%improvement)and dynamic loads,highlighting its robust engineering applicability for intelligent offshore wind farm maintenance.展开更多
Cross-border e-commerce usually involves multiple links such as online shopping platforms,payment systems,logistics services,customs clearance,and cross-border sales.From 2015 to 2023,China-Europe cross-border e-comme...Cross-border e-commerce usually involves multiple links such as online shopping platforms,payment systems,logistics services,customs clearance,and cross-border sales.From 2015 to 2023,China-Europe cross-border e-commerce has experienced rapid growth.Demand among Chinese consumers for European products has increased significantly,while European interest in Chinese goods has also steadily risen.Many small and medium-sized enterprises and cross-border e-commerce platforms have begun to enter this market.This article explores how independent e-commerce integrator platforms can leverage efficient,cost-effective supply chain services and brand advantages to attract Chinese and German SMEs.By doing so,these platforms can strengthen their market presence,reduce operational costs for SMEs,expand transaction volume,and ultimately create a win-win situation for all stakeholders.展开更多
In 2022,China’s space station completed construction and entered the application and development phase.With the ISS set to decommission in 2030,China’s space station will become the sole low-orbit space station.The ...In 2022,China’s space station completed construction and entered the application and development phase.With the ISS set to decommission in 2030,China’s space station will become the sole low-orbit space station.The selection of astronauts from Hong Kong,Macao,and Pakistan highlights the necessity of establishing a clear code of conduct.Drawing on the ISS experience,China’s space station should establish a code of conduct(CoC)with a legal framework that respects international law and emphasizes peaceful use and mutual benefit.Against this backdrop,it is of importance to design a legal framework,addressing key issues including but not limited to,jurisdiction,ethical standards for research,intellectual property protection and international collaboration mechanisms.This article is among the first attempts to answer those questions.展开更多
This paper begins with an overview of base station antennas,focusing on their structure and basic technical parameters.It then investigates the technical characteristics of three types of antennas—panel,Luneburg lens...This paper begins with an overview of base station antennas,focusing on their structure and basic technical parameters.It then investigates the technical characteristics of three types of antennas—panel,Luneburg lens,and innovative integrated antennas—in the context of railway 5G-R base station specifications.The advantages and disadvantages of these antenna types are compared and analyzed,and recommendations for the selection of 5G-R base station antennas are provided.Based on the special application scenarios of railway 5G-R base stations,this paper proposes connection methods between antennas and RRUs,and conducts a comparative analysis of antenna interface types.Furthermore,recommendations are provided for configuring the antenna information management module to meet the intelligent operation and maintenance requirements of the 5G-R system.The findings can serve as a reference for the selection and operation of antennas at railway 5G-R base stations.展开更多
In bridge engineering,monitoring pier offsets is crucial for ensuring both structural safety and construction quality.The total station measurement method using a reflector is widely employed,offering significant adva...In bridge engineering,monitoring pier offsets is crucial for ensuring both structural safety and construction quality.The total station measurement method using a reflector is widely employed,offering significant advantages in specific scenarios.During measurements,errors are influenced by various factors.Initially,misalignment causes the lateral relative error to increase before decreasing,while longitudinal relative errors fluctuate due to instrument characteristics and operational factors.Lateral movements have a more pronounced impact on these errors.Investigating the positioning layout of pier offsets holds substantial importance as it enables precise displacement monitoring,prevents accidents,aids in maintenance planning,provides valuable references for design and construction,and enhances the pier’s resistance to deflection.Controlling and correcting subsequent errors is essential to ensure the overall safety of the bridge structure.展开更多
Quantifying the post-earthquake functional recovery of railway stations presents significant challenges.This paper first establishes a post-earthquake function calculation method for railway stations,encompassing the ...Quantifying the post-earthquake functional recovery of railway stations presents significant challenges.This paper first establishes a post-earthquake function calculation method for railway stations,encompassing the establishment of relationships between the station’s function and the damage state,function loss,and failure probability of components and professional equipment in each layer.Also,the“4 stages-6 sequences”post-earthquake repair method is present,taking into account the functional and structural characteristics of railway stations.Additionally,a novel piecewise function for the post-earthquake functional dynamic recovery of railway stations is developed.A case study is conducted on a typical railway station to demonstrate the analysis procedure.Results indicate that under fortification,rare,and extremely rare earthquake scenarios,the interlayer drift ratio(IDR)of the railway station were 1/276,1/143,and 1/52,respectively,and corresponding peak floor acceleration(PFA)were 6.31 m/s^(2),7.82 m/s^(2),and 8.57 m/s^(2),respectively.The post-earthquake function of the railway station was 93.21%,82.33%,and 64.16%of its initial function.The repair times were 6.66 days,18.65 days,and 37.42 days.The displacement-sensitive,non-structural components were identified as the most vulnerable to damage.And the first repair stage(R_(1))which was mainly used to repair structural components and non-structural transport components,accounted for the highest proportion of total repair time.展开更多
The next-generation gravity satellite mission equipped with the Cold Atom Interferometry(CAI)gradiometer has great potential for the Earth's gravity field estimation.Deploying a CAI gradiometer on the Chinese Tian...The next-generation gravity satellite mission equipped with the Cold Atom Interferometry(CAI)gradiometer has great potential for the Earth's gravity field estimation.Deploying a CAI gradiometer on the Chinese Tiangong Space Station launched for long-term Earth science research not only reduces the cost compared to a dual-satellite constellation but also enhances interdisciplinary collaboration in the Earth's gravity field detection.In this study,we conducted gravity gradient-based simulations to assess the contribution of deploying a CAI gradiometer on the Tiangong Space Station to collaboratively observe the Earth's gravity field with a polar-orbit gravity satellite.The simulation results demonstrate that whether utilizing V_(yy) component,three diagonal components or full components,the derived gravity field models show significant improvements within 100 degree and above 200 degree after incorporating Tiangong Space Station.In particular,the gravity field solution recovered from three diagonal components achieves the best accuracy.In the case of using diagonal components,the collaboration observation scheme effectively reduced the cumulative geoid height error by approximately 5.3 cm(300 d/o).In the spatial domain,the incorporation of the Tiangong Space Station primarily impacts the estimated gravity field within the orbital coverage area of the space station,and this effect is particularly pronounced when just employing V_(yy) component.However,due to the limitation of angular velocity observation inaccuracy associated with the CAI gradiometer in nadir mode,there is no substantial accuracy improvement observed above 200 degree when adding gradient components.展开更多
Electric Vehicles(EVs)have emerged as a cleaner,low-carbon,and environmentally friendly alternative to traditional internal combustion engine(ICE)vehicles.With the increasing adoption of EVs,they are expected to event...Electric Vehicles(EVs)have emerged as a cleaner,low-carbon,and environmentally friendly alternative to traditional internal combustion engine(ICE)vehicles.With the increasing adoption of EVs,they are expected to eventually replace ICE vehicles entirely.However,the rapid growth of EVs has significantly increased energy demand,posing challenges for power grids and infrastructure.This surge in energy demand has driven advancements in developing efficient charging infrastructure and energy management solutions to mitigate the risks of power outages and disruptions caused by the rising number of EVs on the road.To address these challenges,various deep learning(DL)models,such as Recurrent Neural Networks(RNNs)and Long Short-Term Memory(LSTM)networks,have been employed for predicting energy demand at EV charging stations(EVCS).However,these models face certain limitations.They often lack interpretability,treating all input steps equally without assigning greater importance to critical patterns that are more relevant for prediction.Additionally,these models process data sequentially,which makes them computationally slower and less efficient when dealing with large datasets.In the context of these limitations,this paper introduces a novel Attention-Augmented Long Short-Term Memory(AA-LSTM)model.The proposed model integrates an attention mechanism to focus on the most relevant time steps,thereby enhancing its ability to capture long-term dependencies and improve prediction accuracy.By combining the strengths of LSTM networks in handling sequential data with the interpretability and efficiency of the attention mechanism,the AA-LSTM model delivers superior performance.The attention mechanism selectively prioritizes critical parts of the input sequence,reducing the computational burden and making the model faster and more effective.The AA-LSTM model achieves impressive results,demonstrating a Mean Absolute Percentage Error(MAPE)of 3.90%and a Mean Squared Error(MSE)of 0.40,highlighting its accuracy and reliability.These results suggest that the AA-LSTM model is a highly promising solution for predicting energy demand at EVCS,offering improved performance and efficiency compared to contemporary approaches.展开更多
In the context of security systems,adequate signal coverage is paramount for the communication between security personnel and the accurate positioning of personnel.Most studies focus on optimizing base station deploym...In the context of security systems,adequate signal coverage is paramount for the communication between security personnel and the accurate positioning of personnel.Most studies focus on optimizing base station deployment under the assumption of static obstacles,aiming to maximize the perception coverage of wireless RF(Radio Frequency)signals and reduce positioning blind spots.However,in practical security systems,obstacles are subject to change,necessitating the consideration of base station deployment in dynamic environments.Nevertheless,research in this area still needs to be conducted.This paper proposes a Dynamic Indoor Environment Beacon Deployment Algorithm(DIE-BDA)to address this problem.This algorithm considers the dynamic alterations in obstacle locations within the designated area.It determines the requisite number of base stations,the requisite time,and the area’s practical and overall signal coverage rates.The experimental results demonstrate that the algorithm can calculate the deployment strategy in 0.12 s following a change in obstacle positions.Experimental results show that the algorithm in this paper requires 0.12 s to compute the deployment strategy after the positions of obstacles change.With 13 base stations,it achieves an effective coverage rate of 93.5%and an overall coverage rate of 97.75%.The algorithm can rapidly compute a revised deployment strategy in response to changes in obstacle positions within security systems,thereby ensuring the efficacy of signal coverage.展开更多
基金National Natural Science Foundation of China under Grant No.51578463。
文摘The vibration response and noise caused by subway trains can affect the safety and comfort of superstructures.To study the dynamic response characteristics of subway stations and superstructures under train loads with a hard combination,a numerical model is developed in this study.The indoor model test verified the accuracy of the numerical model.The influence laws of different hard combinations,train operating speeds and modes were studied and evaluated accordingly.The results show that the frequency corresponding to the peak vibration acceleration level of each floor of the superstructure property is concentrated at 10–20 Hz.The vibration response decreases in the high-frequency parts and increases in the lowfrequency parts with increasing distance from the source.Furthermore,the factors,such as train operating speed,operating mode,and hard combination type,will affect the vibration of the superstructure.The vibration response under the reversible operation of the train is greater than that of the unidirectional operation.The operating speed of the train is proportional to its vibration response.The vibration amplification area appears between the middle and the top of the superstructure at a higher train speed.Its vibration acceleration level will exceed the limit value of relevant regulations,and vibration-damping measures are required.Within the scope of application,this study provides some suggestions for constructing subway stations and superstructures.
基金supported by the National Natural Science Foundation of China(Nos.62272418,62102058)Basic Public Welfare Research Program of Zhejiang Province(No.LGG18E050011)the Major Open Project of Key Laboratory for Advanced Design and Intelligent Computing of the Ministry of Education under Grant ADIC2023ZD001,National Undergraduate Training Program on Innovation and Entrepreneurship(No.202410345054).
文摘The wireless signals emitted by base stations serve as a vital link connecting people in today’s society and have been occupying an increasingly important role in real life.The development of the Internet of Things(IoT)relies on the support of base stations,which provide a solid foundation for achieving a more intelligent way of living.In a specific area,achieving higher signal coverage with fewer base stations has become an urgent problem.Therefore,this article focuses on the effective coverage area of base station signals and proposes a novel Evolutionary Particle Swarm Optimization(EPSO)algorithm based on collective prediction,referred to herein as ECPPSO.Introducing a new strategy called neighbor-based evolution prediction(NEP)addresses the issue of premature convergence often encountered by PSO.ECPPSO also employs a strengthening evolution(SE)strategy to enhance the algorithm’s global search capability and efficiency,ensuring enhanced robustness and a faster convergence speed when solving complex optimization problems.To better adapt to the actual communication needs of base stations,this article conducts simulation experiments by changing the number of base stations.The experimental results demonstrate thatunder the conditionof 50 ormore base stations,ECPPSOconsistently achieves the best coverage rate exceeding 95%,peaking at 99.4400%when the number of base stations reaches 80.These results validate the optimization capability of the ECPPSO algorithm,proving its feasibility and effectiveness.Further ablative experiments and comparisons with other algorithms highlight the advantages of ECPPSO.
文摘1.Introduction As China’s first floating production platform in ultra-deepwater,the“Deep Sea No.1”energy station is a milestone in China’s deepwater resource utilization.The energy station is located in the LS17-2 gas field,150 km off the southeast coast of Hainan Island,China.It is a semi-submersible platform(Fig.1)with a displacement of 101 thousand tonnes and an operational draft of 35 to 40 m.The platform is permanently moored in 1422 m water by 16 chain-polyester-chain mooring lines in a 4×4 pattern,and six steel catenary risers(SCRs)are attached to the platform.It is the world’s first and only semi-submersible platform with the function of condensate storage,so it can be regarded as a floating production storage and offloading(FPSO)unit.With the ability to produce 3 billion m3 of natural gas each year(enough for over 10 million families),the Deep Sea No.1 energy station is a key step toward China’s energy independence.The LS17-2 gas field,where the Deep Sea No.1 energy station is located,was discovered in 2014.Plans for its development were made in 2015,followed by research and a preliminary design.Deep Sea No.1 went into operation on June 25,2021,and will operate onsite continuously without dry-docking for 30 years.
基金Entrusted Fund of National Institute of Information and Communications Technology(NICT),Japan(JPJ012368C02401)。
文摘The microwave wireless power transmission technologies for space solar power station are a crucial field in the international space sector,where various countries are competing in its development.This paper surveys the research experiments and development efforts related to space solar power stations and microwave wireless power transmission technologies worldwide.The objective is to assess the progress and current state of this technological foundation,determine the necessary focus for developing high-power microwave wireless power transmission technology,and provide clarity on the direction of future technology development in these areas.Finally,a distributed space solar power station plan that is immediately feasible is proposed.
文摘Released in September 2024 by an oversight committee of the US National Aeronautics and Space Administration(NASA),a safety report about the International Space Station(ISS)cited,in addition to 50 other“areas of concern,”a troublesome leak first detected six years ago in one of the station’s modules[1].Given the persistent leak,called“a top safety risk”[2],and the fact that the space sta-tion has outlived its original life expectancy by more than 10 years,the agency’s current plans call for decommissioning the ISS in 2031 by dragging it into the Pacific Ocean[3].
文摘The Hongyancun subway station in Chongqing,China,is 116 meters deep and the difference in air pressure often leaves users with clogged(堵塞的)ears when accessed via its elevator.When the air pressure outside the eardrum(耳膜)becomes different than the pressure inside,you experience ear barotrauma(气压伤).It occurs most often during steep ascents and descents and is usually associated with plane take⁃offs and landings,or driving up or down mountains.Most subway stations dont usually cause ear barotrauma,because they arent deep or steep enough for your ears to register a significant enough difference in air pressure.But taking the elevator to reach Chinas deepest subway station might actually clog up your ears.Thats because it is located 116 meters below the surface,which is the equivalent of about 40 floors underground.
文摘The implementation of the standard is expected to help electric vehicle battery swap stations to adapt to diversified needs and vehicle models,promoting the industry’s orderly and healthy development.
文摘This article focuses on the municipal prefabricated bathroom station.It elaborates on its modular design concept,including key design points such as spatial layout,functional modules,and determination of key parameters;introduces the optimization of intelligent production processes,precision control,and integration of construction technology,and also mentions the verification of full lifecycle applications and quality control;as well as emphasizes the importance of BIM+IoT platform and looks forward to the future.
基金National Natural Science Foundation of China under Grant No.52108473Project of Shaanxi Engineering Technology Research Center for Urban Geology and Underground Space under Grant No.2025KT-03Key Project of Education Department of Shaanxi Province under Grant No.23JY042。
文摘Ground fissure,as a common geo-hazard,impairs the integrity of the site soil and affects the seismic performance of engineering structures.In this paper,a finite element(FE)model for subway stations in a ground fissure area was developed and validated by using experimental results.Numerical analyses were conducted to investigate the seismic response and failure mode of subway stations in a ground fissure area with different locations.Effects of ground fissure on deformations and internal forces of a station,soil pressures and soil plastic strains were discussed.The results showed that the seismic response of the station was significantly amplified by the ground fissure,and stations in the ground fissure area displayed obvious rocking deformation during earthquakes as compared to those in the area without fissures.It also was found that the soil yielding around the station,the dislocation occurring in the ground fissure area,and the dynamic amplification effect were more significant under vertical ground motion,which weakened the station’s ductility and accelerated its destruction process.
基金supported by the Science and Technology Project of China Huaneng Group Co.,Ltd.Research on Key Technologies for Monitoring and Protection of Offshore Wind Power Underwater Equipment(HNKJ21-H40).
文摘As the core facility of offshore wind power systems,the structural safety of offshore booster stations directly impacts the stable operation of entire wind farms.With the global energy transition toward green and lowcarbon goals,offshore wind power has emerged as a key renewable energy source,yet its booster stations face harsh marine environments,including persistent wave impacts,salt spray corrosion,and equipment-induced vibrations.Traditional monitoring methods relying on manual inspections and single-dimensional sensors suffer from critical limitations:low efficiency,poor real-time performance,and inability to capture millinewton-level stress fluctuations that signal early structural fatigue.To address these challenges,this study proposes a biomechanics-driven structural safety monitoring system integrated with deep learning.Inspired by biological stress-sensing mechanisms,the system deploys a distributedmulti-dimensional force sensor network to capture real-time stress distributions in key structural components.A hybrid convolutional neural network-radial basis function(CNN-RBF)model is developed:the CNN branch extracts spatiotemporal features from multi-source sensing data,while the RBF branch reconstructs the nonlinear stress field for accurate anomaly diagnosis.The three-tier architectural design—data layer(distributed sensor array),function layer(CNN-RBF modeling),and application layer(edge computing terminal)—enables a closedloop process from high-resolution data collection to real-time early warning,with data processing delay controlled within 200 ms.Experimental validation against traditional SOM-based systems demonstrates significant performance improvements:monitoring accuracy increased by 19.8%,efficiency by 23.4%,recall rate by 20.5%,and F1 score by 21.6%.Under extreme weather(e.g.,typhoons and winter storms),the system’s stability is 40% higher,with user satisfaction improving by 17.2%.The biomechanics-inspired sensor design enhances survival rates in salt fog(85.7%improvement)and dynamic loads,highlighting its robust engineering applicability for intelligent offshore wind farm maintenance.
文摘Cross-border e-commerce usually involves multiple links such as online shopping platforms,payment systems,logistics services,customs clearance,and cross-border sales.From 2015 to 2023,China-Europe cross-border e-commerce has experienced rapid growth.Demand among Chinese consumers for European products has increased significantly,while European interest in Chinese goods has also steadily risen.Many small and medium-sized enterprises and cross-border e-commerce platforms have begun to enter this market.This article explores how independent e-commerce integrator platforms can leverage efficient,cost-effective supply chain services and brand advantages to attract Chinese and German SMEs.By doing so,these platforms can strengthen their market presence,reduce operational costs for SMEs,expand transaction volume,and ultimately create a win-win situation for all stakeholders.
基金supported by the National Social Science Fund(22CFX046).
文摘In 2022,China’s space station completed construction and entered the application and development phase.With the ISS set to decommission in 2030,China’s space station will become the sole low-orbit space station.The selection of astronauts from Hong Kong,Macao,and Pakistan highlights the necessity of establishing a clear code of conduct.Drawing on the ISS experience,China’s space station should establish a code of conduct(CoC)with a legal framework that respects international law and emphasizes peaceful use and mutual benefit.Against this backdrop,it is of importance to design a legal framework,addressing key issues including but not limited to,jurisdiction,ethical standards for research,intellectual property protection and international collaboration mechanisms.This article is among the first attempts to answer those questions.
文摘This paper begins with an overview of base station antennas,focusing on their structure and basic technical parameters.It then investigates the technical characteristics of three types of antennas—panel,Luneburg lens,and innovative integrated antennas—in the context of railway 5G-R base station specifications.The advantages and disadvantages of these antenna types are compared and analyzed,and recommendations for the selection of 5G-R base station antennas are provided.Based on the special application scenarios of railway 5G-R base stations,this paper proposes connection methods between antennas and RRUs,and conducts a comparative analysis of antenna interface types.Furthermore,recommendations are provided for configuring the antenna information management module to meet the intelligent operation and maintenance requirements of the 5G-R system.The findings can serve as a reference for the selection and operation of antennas at railway 5G-R base stations.
文摘In bridge engineering,monitoring pier offsets is crucial for ensuring both structural safety and construction quality.The total station measurement method using a reflector is widely employed,offering significant advantages in specific scenarios.During measurements,errors are influenced by various factors.Initially,misalignment causes the lateral relative error to increase before decreasing,while longitudinal relative errors fluctuate due to instrument characteristics and operational factors.Lateral movements have a more pronounced impact on these errors.Investigating the positioning layout of pier offsets holds substantial importance as it enables precise displacement monitoring,prevents accidents,aids in maintenance planning,provides valuable references for design and construction,and enhances the pier’s resistance to deflection.Controlling and correcting subsequent errors is essential to ensure the overall safety of the bridge structure.
基金National Natural Science Foundation of China under Grant No.52278534the Sichuan Provincial Natural Science Foundation of China under Grant No.2022NSFSC0423。
文摘Quantifying the post-earthquake functional recovery of railway stations presents significant challenges.This paper first establishes a post-earthquake function calculation method for railway stations,encompassing the establishment of relationships between the station’s function and the damage state,function loss,and failure probability of components and professional equipment in each layer.Also,the“4 stages-6 sequences”post-earthquake repair method is present,taking into account the functional and structural characteristics of railway stations.Additionally,a novel piecewise function for the post-earthquake functional dynamic recovery of railway stations is developed.A case study is conducted on a typical railway station to demonstrate the analysis procedure.Results indicate that under fortification,rare,and extremely rare earthquake scenarios,the interlayer drift ratio(IDR)of the railway station were 1/276,1/143,and 1/52,respectively,and corresponding peak floor acceleration(PFA)were 6.31 m/s^(2),7.82 m/s^(2),and 8.57 m/s^(2),respectively.The post-earthquake function of the railway station was 93.21%,82.33%,and 64.16%of its initial function.The repair times were 6.66 days,18.65 days,and 37.42 days.The displacement-sensitive,non-structural components were identified as the most vulnerable to damage.And the first repair stage(R_(1))which was mainly used to repair structural components and non-structural transport components,accounted for the highest proportion of total repair time.
基金National Key R&D Program of China(2021YFB3900101)the National Natural Science Foundation of China(42174099 and 42192532)It is also partly supported by the Fundamental Research Funds for the Central Universities.
文摘The next-generation gravity satellite mission equipped with the Cold Atom Interferometry(CAI)gradiometer has great potential for the Earth's gravity field estimation.Deploying a CAI gradiometer on the Chinese Tiangong Space Station launched for long-term Earth science research not only reduces the cost compared to a dual-satellite constellation but also enhances interdisciplinary collaboration in the Earth's gravity field detection.In this study,we conducted gravity gradient-based simulations to assess the contribution of deploying a CAI gradiometer on the Tiangong Space Station to collaboratively observe the Earth's gravity field with a polar-orbit gravity satellite.The simulation results demonstrate that whether utilizing V_(yy) component,three diagonal components or full components,the derived gravity field models show significant improvements within 100 degree and above 200 degree after incorporating Tiangong Space Station.In particular,the gravity field solution recovered from three diagonal components achieves the best accuracy.In the case of using diagonal components,the collaboration observation scheme effectively reduced the cumulative geoid height error by approximately 5.3 cm(300 d/o).In the spatial domain,the incorporation of the Tiangong Space Station primarily impacts the estimated gravity field within the orbital coverage area of the space station,and this effect is particularly pronounced when just employing V_(yy) component.However,due to the limitation of angular velocity observation inaccuracy associated with the CAI gradiometer in nadir mode,there is no substantial accuracy improvement observed above 200 degree when adding gradient components.
基金supported by the SC&SS,Jawaharlal Nehru University,New Delhi,India.
文摘Electric Vehicles(EVs)have emerged as a cleaner,low-carbon,and environmentally friendly alternative to traditional internal combustion engine(ICE)vehicles.With the increasing adoption of EVs,they are expected to eventually replace ICE vehicles entirely.However,the rapid growth of EVs has significantly increased energy demand,posing challenges for power grids and infrastructure.This surge in energy demand has driven advancements in developing efficient charging infrastructure and energy management solutions to mitigate the risks of power outages and disruptions caused by the rising number of EVs on the road.To address these challenges,various deep learning(DL)models,such as Recurrent Neural Networks(RNNs)and Long Short-Term Memory(LSTM)networks,have been employed for predicting energy demand at EV charging stations(EVCS).However,these models face certain limitations.They often lack interpretability,treating all input steps equally without assigning greater importance to critical patterns that are more relevant for prediction.Additionally,these models process data sequentially,which makes them computationally slower and less efficient when dealing with large datasets.In the context of these limitations,this paper introduces a novel Attention-Augmented Long Short-Term Memory(AA-LSTM)model.The proposed model integrates an attention mechanism to focus on the most relevant time steps,thereby enhancing its ability to capture long-term dependencies and improve prediction accuracy.By combining the strengths of LSTM networks in handling sequential data with the interpretability and efficiency of the attention mechanism,the AA-LSTM model delivers superior performance.The attention mechanism selectively prioritizes critical parts of the input sequence,reducing the computational burden and making the model faster and more effective.The AA-LSTM model achieves impressive results,demonstrating a Mean Absolute Percentage Error(MAPE)of 3.90%and a Mean Squared Error(MSE)of 0.40,highlighting its accuracy and reliability.These results suggest that the AA-LSTM model is a highly promising solution for predicting energy demand at EVCS,offering improved performance and efficiency compared to contemporary approaches.
文摘In the context of security systems,adequate signal coverage is paramount for the communication between security personnel and the accurate positioning of personnel.Most studies focus on optimizing base station deployment under the assumption of static obstacles,aiming to maximize the perception coverage of wireless RF(Radio Frequency)signals and reduce positioning blind spots.However,in practical security systems,obstacles are subject to change,necessitating the consideration of base station deployment in dynamic environments.Nevertheless,research in this area still needs to be conducted.This paper proposes a Dynamic Indoor Environment Beacon Deployment Algorithm(DIE-BDA)to address this problem.This algorithm considers the dynamic alterations in obstacle locations within the designated area.It determines the requisite number of base stations,the requisite time,and the area’s practical and overall signal coverage rates.The experimental results demonstrate that the algorithm can calculate the deployment strategy in 0.12 s following a change in obstacle positions.Experimental results show that the algorithm in this paper requires 0.12 s to compute the deployment strategy after the positions of obstacles change.With 13 base stations,it achieves an effective coverage rate of 93.5%and an overall coverage rate of 97.75%.The algorithm can rapidly compute a revised deployment strategy in response to changes in obstacle positions within security systems,thereby ensuring the efficacy of signal coverage.
