Rocks will suffer different degree of damage under freeze-thaw(FT)cycles,which seriously threatens the long-term stability of rock engineering in cold regions.In order to study the mechanism of rock FT damage,energy c...Rocks will suffer different degree of damage under freeze-thaw(FT)cycles,which seriously threatens the long-term stability of rock engineering in cold regions.In order to study the mechanism of rock FT damage,energy calculation method and energy self-inhibition model are introduced to explore their energy characteristics in this paper.The applicability of the energy self-inhibition model was verified by combining the data of FT cycles and uniaxial compression tests of intact and pre-cracked sandstone samples,as well as published reference data.In addition,the energy evolution characteristics of FT damaged rocks were discussed accordingly.The results indicate that the energy self-inhibition model perfectly characterizes the energy accumulation characteristics of FT damaged rocks under uniaxial compression before the peak strength and the energy dissipation characteristics before microcrack unstable growth stage.Taking the FT damaged cyan sandstone sample as an example,it has gone through two stages dominated by energy dissipation mechanism and energy accumulation mechanism,and the energy rate curve of the pre-cracked sample shows a fall-rise phenomenon when approaching failure.Based on the published reference data,it was found that the peak total input energy and energy storage limit conform to an exponential FT decay model,with corresponding decay constants ranging from 0.0021 to 0.1370 and 0.0018 to 0.1945,respectively.Finally,a linear energy storage equation for FT damaged rocks was proposed,and its high reliability and applicability were verified by combining published reference data,the energy storage coefficient of different types of rocks ranged from 0.823 to 0.992,showing a negative exponential relationship with the initial UCS(uniaxial compressive strength).In summary,the mechanism by which FT weakens the mechanical properties of rocks has been revealed from an energy perspective in this paper,which can provide reference for related issues in cold regions.展开更多
Damage detection in structures is performed via vibra-tion based structural identification. Modal information, such as fre-quencies and mode shapes, are widely used for structural dama-ge detection to indicate the hea...Damage detection in structures is performed via vibra-tion based structural identification. Modal information, such as fre-quencies and mode shapes, are widely used for structural dama-ge detection to indicate the health conditions of civil structures.The deep learning algorithm that works on a multiple layer neuralnetwork model termed as deep autoencoder is proposed to learnthe relationship between the modal information and structural stiff-ness parameters. This is achieved via dimension reduction of themodal information feature and a non-linear regression against thestructural stiffness parameters. Numerical tests on a symmetri-cal steel frame model are conducted to generate the data for thetraining and validation, and to demonstrate the efficiency of theproposed approach for vibration based structural damage detec-tion.展开更多
针对航空设备在恶劣环境下工作存在使用寿命大为缩短的问题,利用健康监测系统监测航空设备工作情况并预测该设备的剩余可靠工作时间,通过分析目标设备硬件组成,设计故障检测程序,确定主要失效机理。结合目前广泛应用的健康监测系统结构...针对航空设备在恶劣环境下工作存在使用寿命大为缩短的问题,利用健康监测系统监测航空设备工作情况并预测该设备的剩余可靠工作时间,通过分析目标设备硬件组成,设计故障检测程序,确定主要失效机理。结合目前广泛应用的健康监测系统结构和成熟的TF(time to fail)模型,提出了利用物理模型实现大致推算机载航空质量流量计可靠工作时间的方法,可完成目标设备的故障预测,较传统方法有明显优势而具有良好的应用前景。展开更多
基金Project(52174088)supported by the National Natural Science Foundation of ChinaProject(104972024JYS0007)supported by the Independent Innovation Research Fund Graduate Free Exploration,Wuhan University of Technology,China。
文摘Rocks will suffer different degree of damage under freeze-thaw(FT)cycles,which seriously threatens the long-term stability of rock engineering in cold regions.In order to study the mechanism of rock FT damage,energy calculation method and energy self-inhibition model are introduced to explore their energy characteristics in this paper.The applicability of the energy self-inhibition model was verified by combining the data of FT cycles and uniaxial compression tests of intact and pre-cracked sandstone samples,as well as published reference data.In addition,the energy evolution characteristics of FT damaged rocks were discussed accordingly.The results indicate that the energy self-inhibition model perfectly characterizes the energy accumulation characteristics of FT damaged rocks under uniaxial compression before the peak strength and the energy dissipation characteristics before microcrack unstable growth stage.Taking the FT damaged cyan sandstone sample as an example,it has gone through two stages dominated by energy dissipation mechanism and energy accumulation mechanism,and the energy rate curve of the pre-cracked sample shows a fall-rise phenomenon when approaching failure.Based on the published reference data,it was found that the peak total input energy and energy storage limit conform to an exponential FT decay model,with corresponding decay constants ranging from 0.0021 to 0.1370 and 0.0018 to 0.1945,respectively.Finally,a linear energy storage equation for FT damaged rocks was proposed,and its high reliability and applicability were verified by combining published reference data,the energy storage coefficient of different types of rocks ranged from 0.823 to 0.992,showing a negative exponential relationship with the initial UCS(uniaxial compressive strength).In summary,the mechanism by which FT weakens the mechanical properties of rocks has been revealed from an energy perspective in this paper,which can provide reference for related issues in cold regions.
文摘Damage detection in structures is performed via vibra-tion based structural identification. Modal information, such as fre-quencies and mode shapes, are widely used for structural dama-ge detection to indicate the health conditions of civil structures.The deep learning algorithm that works on a multiple layer neuralnetwork model termed as deep autoencoder is proposed to learnthe relationship between the modal information and structural stiff-ness parameters. This is achieved via dimension reduction of themodal information feature and a non-linear regression against thestructural stiffness parameters. Numerical tests on a symmetri-cal steel frame model are conducted to generate the data for thetraining and validation, and to demonstrate the efficiency of theproposed approach for vibration based structural damage detec-tion.
文摘针对航空设备在恶劣环境下工作存在使用寿命大为缩短的问题,利用健康监测系统监测航空设备工作情况并预测该设备的剩余可靠工作时间,通过分析目标设备硬件组成,设计故障检测程序,确定主要失效机理。结合目前广泛应用的健康监测系统结构和成熟的TF(time to fail)模型,提出了利用物理模型实现大致推算机载航空质量流量计可靠工作时间的方法,可完成目标设备的故障预测,较传统方法有明显优势而具有良好的应用前景。
