In this study,a uniaxial cyclic compression test is conducted on coal-rock composite structures under two cyclic loads using MTSE45.104 testing apparatus to investigate the macro-mesoscopic deformation,damage behavior...In this study,a uniaxial cyclic compression test is conducted on coal-rock composite structures under two cyclic loads using MTSE45.104 testing apparatus to investigate the macro-mesoscopic deformation,damage behavior,and energy evolution characteristics of these structures under different cyclic stress disturbances.Three loading and unloading rates(LURs)are tested to examine the damage behaviors and energy-driven characteristics of the composites.The findings reveal that the energy-driven behavior,mechanical properties,and macro-micro degradation characteristics of the composites are significantly influenced by the loading rate.Under the gradual cyclic loading and unloading(CLU)path with a constant lower limit(path I)and the CLU path with variable upper and lower boundaries(path II),an increase in LURs from 0.05 to 0.15 mm/min reduces the average loading time by 32.39%and 48.60%,respectively.Consequently,the total number of cracks in the samples increases by 1.66-fold for path I and 1.41-fold for path II.As LURs further increase,the energy storage limit of samples expands,leading to a higher proportion of transmatrix and shear cracks.Under both cyclic loading conditions,a broader cyclic stress range promotes energy dissipation and the formation of internal fractures.Notably,at higher loading rates,cracks tend to propagate along primary weak surfaces,leading to an increased incidence of intermatrix fractures.This behavior indicates a microscopic feature of the failure mechanisms in composite structures.These results provide a theoretical basis for elucidating the damage and failure characteristics of coal-rock composite structures under cyclic stress disturbances.展开更多
Many countries throughout the world have experienced large earthquakes,which cause building damage or collapse.After such earthquakes,structures must be inspected rapidly to judge whether they are safe to reoccupy.To ...Many countries throughout the world have experienced large earthquakes,which cause building damage or collapse.After such earthquakes,structures must be inspected rapidly to judge whether they are safe to reoccupy.To facilitate the inspection process,the authors previously developed a rapid building safety assessment system using sparse acceleration measurements for steel framed buildings.The proposed system modeled nonlinearity in the measurement data using a calibrated simplified lumped-mass model and convolutional neural networks(CNNs),based on which the buildinglevel damage index was estimated rapidly after earthquakes.The proposed system was validated for a nonlinear 3D numerical model of a five-story steel building,and later for a large-scale specimen of an 18-story building in Japan tested on the E-Defense shaking table.However,the applicability of the safety assessment system for reinforced concrete(RC)structures with complex hysteretic material nonlinearity has yet to be explored;the previous approach based on a simplified lumpedmass model with a Bouc-Wen hysteretic model does not accurately represent the inherent nonlinear behavior and resulting damage states of RC structures.This study extends the rapid building safety assessment system to low-rise RC moment resisting frame structures representing typical residential apartments in Japan.First,a safety classification for RC structures based on a damage index consistent with the current state of practice is defined.Then,a 3D nonlinear numerical model of a two-story moment frame structure is created.A simplified lumped-mass nonlinear model is developed and calibrated using the 3D model,incorporating the Takeda degradation model for the RC material nonlinearity.This model is used to simulate the seismic response and associated damage sensitive features(DSF)for random ground motion.The resulting database of responses is used to train a convolutional neural network(CNN)that performs rapid safety assessment.The developed system is validated using the 3D nonlinear analysis model subjected to historical earthquakes.The results indicate the applicability of the proposed system for RC structures following seismic events.展开更多
Structural health monitoring(SHM)is a vast,interdisciplinary research field whose literature spans several decades with focusing on condition assessment of different types of structures including aerospace,mechanical ...Structural health monitoring(SHM)is a vast,interdisciplinary research field whose literature spans several decades with focusing on condition assessment of different types of structures including aerospace,mechanical and civil structures.The need for quantitative global damage detection methods that can be applied to complex structures has led to vibration-based inspection.Statistical time series methods for SHM form an important and rapidly evolving category within the broader vibration-based methods.In the literature on the structural damage detection,many time series-based methods have been proposed.When a considered time series model approximates the vibration response of a structure and model coefficients or residual error are obtained,any deviations in these coefficients or residual error can be inferred as an indication of a change or damage in the structure.Depending on the technique employed,various damage sensitive features have been proposed to capture the deviations.This paper reviews the application of time series analysis for SHM.The different types of time series analysis are described,and the basic principles are explained in detail.Then,the literature is reviewed based on how a damage sensitive feature is formed.In addition,some investigations that have attempted to modify and/or combine time series analysis with other approaches for better damage identification are presented.展开更多
基金Project(2023YFC3009003) supported by the National Key R&D Program of ChinaProjects(52130409, 52121003, 52374249, 52204220) supported by the National Natural Science Foundation of ChinaProject(2024JCCXAQ01) supported by the Fundamental Research Funds for the Central Universities,China。
文摘In this study,a uniaxial cyclic compression test is conducted on coal-rock composite structures under two cyclic loads using MTSE45.104 testing apparatus to investigate the macro-mesoscopic deformation,damage behavior,and energy evolution characteristics of these structures under different cyclic stress disturbances.Three loading and unloading rates(LURs)are tested to examine the damage behaviors and energy-driven characteristics of the composites.The findings reveal that the energy-driven behavior,mechanical properties,and macro-micro degradation characteristics of the composites are significantly influenced by the loading rate.Under the gradual cyclic loading and unloading(CLU)path with a constant lower limit(path I)and the CLU path with variable upper and lower boundaries(path II),an increase in LURs from 0.05 to 0.15 mm/min reduces the average loading time by 32.39%and 48.60%,respectively.Consequently,the total number of cracks in the samples increases by 1.66-fold for path I and 1.41-fold for path II.As LURs further increase,the energy storage limit of samples expands,leading to a higher proportion of transmatrix and shear cracks.Under both cyclic loading conditions,a broader cyclic stress range promotes energy dissipation and the formation of internal fractures.Notably,at higher loading rates,cracks tend to propagate along primary weak surfaces,leading to an increased incidence of intermatrix fractures.This behavior indicates a microscopic feature of the failure mechanisms in composite structures.These results provide a theoretical basis for elucidating the damage and failure characteristics of coal-rock composite structures under cyclic stress disturbances.
基金supported by a fellowship from Design Department of Taisei Corporation。
文摘Many countries throughout the world have experienced large earthquakes,which cause building damage or collapse.After such earthquakes,structures must be inspected rapidly to judge whether they are safe to reoccupy.To facilitate the inspection process,the authors previously developed a rapid building safety assessment system using sparse acceleration measurements for steel framed buildings.The proposed system modeled nonlinearity in the measurement data using a calibrated simplified lumped-mass model and convolutional neural networks(CNNs),based on which the buildinglevel damage index was estimated rapidly after earthquakes.The proposed system was validated for a nonlinear 3D numerical model of a five-story steel building,and later for a large-scale specimen of an 18-story building in Japan tested on the E-Defense shaking table.However,the applicability of the safety assessment system for reinforced concrete(RC)structures with complex hysteretic material nonlinearity has yet to be explored;the previous approach based on a simplified lumpedmass model with a Bouc-Wen hysteretic model does not accurately represent the inherent nonlinear behavior and resulting damage states of RC structures.This study extends the rapid building safety assessment system to low-rise RC moment resisting frame structures representing typical residential apartments in Japan.First,a safety classification for RC structures based on a damage index consistent with the current state of practice is defined.Then,a 3D nonlinear numerical model of a two-story moment frame structure is created.A simplified lumped-mass nonlinear model is developed and calibrated using the 3D model,incorporating the Takeda degradation model for the RC material nonlinearity.This model is used to simulate the seismic response and associated damage sensitive features(DSF)for random ground motion.The resulting database of responses is used to train a convolutional neural network(CNN)that performs rapid safety assessment.The developed system is validated using the 3D nonlinear analysis model subjected to historical earthquakes.The results indicate the applicability of the proposed system for RC structures following seismic events.
文摘Structural health monitoring(SHM)is a vast,interdisciplinary research field whose literature spans several decades with focusing on condition assessment of different types of structures including aerospace,mechanical and civil structures.The need for quantitative global damage detection methods that can be applied to complex structures has led to vibration-based inspection.Statistical time series methods for SHM form an important and rapidly evolving category within the broader vibration-based methods.In the literature on the structural damage detection,many time series-based methods have been proposed.When a considered time series model approximates the vibration response of a structure and model coefficients or residual error are obtained,any deviations in these coefficients or residual error can be inferred as an indication of a change or damage in the structure.Depending on the technique employed,various damage sensitive features have been proposed to capture the deviations.This paper reviews the application of time series analysis for SHM.The different types of time series analysis are described,and the basic principles are explained in detail.Then,the literature is reviewed based on how a damage sensitive feature is formed.In addition,some investigations that have attempted to modify and/or combine time series analysis with other approaches for better damage identification are presented.
