This paper focuses on the high-temperature tensile failure mechanism of RTM(resin transfer moulding)-made symmetric and asymmetric composite T-joints.The failure modes as well as the load-displacement curves of symmet...This paper focuses on the high-temperature tensile failure mechanism of RTM(resin transfer moulding)-made symmetric and asymmetric composite T-joints.The failure modes as well as the load-displacement curves of symmetric(three specimens)and asymmetric(three specimens)composite T-joints were determined by tensile tests at room and high temperatures.Progressive damage models(PDMs)of symmetric and asymmetric composite T-joints at room and high temperatures were established based on mixed criteria,and the result predicted from the aforementioned PDMs were compared with experimental data.The predicted initial and final failure loads and failure modes are in good agreement with the experimental results.The failure mechanisms of composite T-joints at different temperatures were investigated by scanning electron microscopy.The results reveal that while the failure mode of asymmetric T-joints at high temperatures resembles that at room temperature,there is a difference in the failure modes of symmetric T-joints.The ultimate failure load of symmetric and asymmetric T-joints at elevated temperatures increases and reduces by 18.4%and 4.97%,albeit with a more discrete distri-bution.This work is expected to provide us with more knowledge about the usability of composite T-joints in elevated temperature environments.展开更多
The axial flow fan is a kind of turbomachinery equipment to provide compressed gas and the statorblade adjusting mechanism is the key to the whole system. Taking the stator blade adjustment electro-hydraulicservo syst...The axial flow fan is a kind of turbomachinery equipment to provide compressed gas and the statorblade adjusting mechanism is the key to the whole system. Taking the stator blade adjustment electro-hydraulicservo system as the research object, the traditional hydraulic servo system is vulnerable to oil pollution, high fail-ure rate and low energy conversion efficiency. To solve the above-mentioned problems, the Direct drive volumecontrol hydraulic system for stator blade adjustment is designed, the hydraulic power source of the system is com-posed of servo motor and bidirectional quantitative pump. The working principle of this system is analyzed, thesimulation model of hydraulic system is built and solved. The results show that the new system has higher energyefficiency, the structure is more compact, the machine power is smaller and the control is more automatic and in-telligent as compared to the traditional one.展开更多
RFID-based human activity recognition(HAR)attracts attention due to its convenience,noninvasiveness,and privacy protection.Existing RFID-based HAR methods use modeling,CNN,or LSTM to extract features effectively.Still...RFID-based human activity recognition(HAR)attracts attention due to its convenience,noninvasiveness,and privacy protection.Existing RFID-based HAR methods use modeling,CNN,or LSTM to extract features effectively.Still,they have shortcomings:1)requiring complex hand-crafted data cleaning processes and 2)only addressing single-person activity recognition based on specific RF signals.To solve these problems,this paper proposes a novel device-free method based on Time-streaming Multiscale Transformer called TransTM.This model leverages the Transformer's powerful data fitting capabilities to take raw RFID RSSI data as input without pre-processing.Concretely,we propose a multiscale convolutional hybrid Transformer to capture behavioral features that recognizes singlehuman activities and human-to-human interactions.Compared with existing CNN-and LSTM-based methods,the Transformer-based method has more data fitting power,generalization,and scalability.Furthermore,using RF signals,our method achieves an excellent classification effect on human behaviorbased classification tasks.Experimental results on the actual RFID datasets show that this model achieves a high average recognition accuracy(99.1%).The dataset we collected for detecting RFID-based indoor human activities will be published.展开更多
基金supported by the Natural Science Foundation of Shanghai(Grant No.24ZR1401700)Fundamental Research Funds for the Central Universities(Grant No.2232022D-28)the Young Elite Scientists Sponsorship Program by the China Association for Science and Technology(Grant No.2016QNRC001).
文摘This paper focuses on the high-temperature tensile failure mechanism of RTM(resin transfer moulding)-made symmetric and asymmetric composite T-joints.The failure modes as well as the load-displacement curves of symmetric(three specimens)and asymmetric(three specimens)composite T-joints were determined by tensile tests at room and high temperatures.Progressive damage models(PDMs)of symmetric and asymmetric composite T-joints at room and high temperatures were established based on mixed criteria,and the result predicted from the aforementioned PDMs were compared with experimental data.The predicted initial and final failure loads and failure modes are in good agreement with the experimental results.The failure mechanisms of composite T-joints at different temperatures were investigated by scanning electron microscopy.The results reveal that while the failure mode of asymmetric T-joints at high temperatures resembles that at room temperature,there is a difference in the failure modes of symmetric T-joints.The ultimate failure load of symmetric and asymmetric T-joints at elevated temperatures increases and reduces by 18.4%and 4.97%,albeit with a more discrete distri-bution.This work is expected to provide us with more knowledge about the usability of composite T-joints in elevated temperature environments.
基金supported by National Natural Science Foundation of China,Project No. 51175148
文摘The axial flow fan is a kind of turbomachinery equipment to provide compressed gas and the statorblade adjusting mechanism is the key to the whole system. Taking the stator blade adjustment electro-hydraulicservo system as the research object, the traditional hydraulic servo system is vulnerable to oil pollution, high fail-ure rate and low energy conversion efficiency. To solve the above-mentioned problems, the Direct drive volumecontrol hydraulic system for stator blade adjustment is designed, the hydraulic power source of the system is com-posed of servo motor and bidirectional quantitative pump. The working principle of this system is analyzed, thesimulation model of hydraulic system is built and solved. The results show that the new system has higher energyefficiency, the structure is more compact, the machine power is smaller and the control is more automatic and in-telligent as compared to the traditional one.
基金the Strategic Priority Research Program of Chinese Academy of Sciences(Grant No.XDC02040300)for this study.
文摘RFID-based human activity recognition(HAR)attracts attention due to its convenience,noninvasiveness,and privacy protection.Existing RFID-based HAR methods use modeling,CNN,or LSTM to extract features effectively.Still,they have shortcomings:1)requiring complex hand-crafted data cleaning processes and 2)only addressing single-person activity recognition based on specific RF signals.To solve these problems,this paper proposes a novel device-free method based on Time-streaming Multiscale Transformer called TransTM.This model leverages the Transformer's powerful data fitting capabilities to take raw RFID RSSI data as input without pre-processing.Concretely,we propose a multiscale convolutional hybrid Transformer to capture behavioral features that recognizes singlehuman activities and human-to-human interactions.Compared with existing CNN-and LSTM-based methods,the Transformer-based method has more data fitting power,generalization,and scalability.Furthermore,using RF signals,our method achieves an excellent classification effect on human behaviorbased classification tasks.Experimental results on the actual RFID datasets show that this model achieves a high average recognition accuracy(99.1%).The dataset we collected for detecting RFID-based indoor human activities will be published.
