Coal bump is a dynamic process,thus it is necessary to reveal the process validly.2D-ball code is an efficient approach developed by the authors based on the basicDEM rationale proposed by Cundall.Numerical simulation...Coal bump is a dynamic process,thus it is necessary to reveal the process validly.2D-ball code is an efficient approach developed by the authors based on the basicDEM rationale proposed by Cundall.Numerical simulations show that the coal bump experiencesa process of energy accumulation,sudden release of energy and energy decrease.The stiffness of coal particles has a great influence on the coal bump morphosisand particle velocity.Generally,the larger the stiffness of particles,the longer the shootingoff period and the larger the bump velocity.This is in agreement with the results of laboratoryexperiment and in-situ studies.However,the stiffness of particles has an influence onthe quantity value energy and no influence on the releasing energy pattern of the coalbump.展开更多
Uncertain local flexural stiffness is recognized as one of the main barriers against the application of existing damage detection and performance degradation alarming techniques to real-world beams.Therefore,damage lo...Uncertain local flexural stiffness is recognized as one of the main barriers against the application of existing damage detection and performance degradation alarming techniques to real-world beams.Therefore,damage localization of beams with original uncertainty has been investigated to ensure their safety.For the beam before serving,it should be simply supported and subject to static load.Based on the concept of suppositional partition,a new loading pattern and mid-span displacement data processing method has been proposed.Actual local flexural stiffness value of each partition can be obtained by solving a set of linear equations.The obtained stiffness data can be used to establish the finite element model of beams.Subsequently,dynamic excitation and mode identification should be carried out for the beam in service.Mode shape curvature index is employed to detect the position of damage.It was validated by example that actual damage and original uncertainty of local flexural stiffness can be differentiated by this new method effectively.The combination of static load and dynamic excitation can keep the serviceability of beam.展开更多
Satellite communication develops rapidly due to its global coverage and is unrestricted to the ground environment. However, compared with the traditional ground TCP/IP network, a satellite-to-ground link has a more ex...Satellite communication develops rapidly due to its global coverage and is unrestricted to the ground environment. However, compared with the traditional ground TCP/IP network, a satellite-to-ground link has a more extensive round trip time(RTT) and a higher packet loss rate,which takes more time in error recovery and wastes precious channel resources. Forward error correction(FEC) is a coding method that can alleviate bit error and packet loss, but how to achieve high throughput in the dynamic network environment is still a significant challenge. Inspired by the deep learning technique, this paper proposes a signal-to-noise ratio(SNR) based adaptive coding modulation method. This method can maximize channel utilization while ensuring communication quality and is suitable for satellite-to-ground communication scenarios where the channel state changes rapidly. We predict the SNR using the long short-term memory(LSTM) network that considers the past channel status and real-time global weather. Finally, we use the optimal matching rate(OMR) to evaluate the pros and cons of each method quantitatively. Extensive simulation results demonstrate that our proposed LSTM-based method outperforms the state-of-the-art prediction algorithms significantly in mean absolute error(MAE). Moreover, it leads to the least spectrum waste.展开更多
基金Supported by the National Natural Science Fundation of China(50534080,50674063)Taishan Scholar Engineering Construction Fund of Shandong Province of China(J06N04)
文摘Coal bump is a dynamic process,thus it is necessary to reveal the process validly.2D-ball code is an efficient approach developed by the authors based on the basicDEM rationale proposed by Cundall.Numerical simulations show that the coal bump experiencesa process of energy accumulation,sudden release of energy and energy decrease.The stiffness of coal particles has a great influence on the coal bump morphosisand particle velocity.Generally,the larger the stiffness of particles,the longer the shootingoff period and the larger the bump velocity.This is in agreement with the results of laboratoryexperiment and in-situ studies.However,the stiffness of particles has an influence onthe quantity value energy and no influence on the releasing energy pattern of the coalbump.
基金Scientific and Technological Research Projects in Henan,China(No.122102210165)
文摘Uncertain local flexural stiffness is recognized as one of the main barriers against the application of existing damage detection and performance degradation alarming techniques to real-world beams.Therefore,damage localization of beams with original uncertainty has been investigated to ensure their safety.For the beam before serving,it should be simply supported and subject to static load.Based on the concept of suppositional partition,a new loading pattern and mid-span displacement data processing method has been proposed.Actual local flexural stiffness value of each partition can be obtained by solving a set of linear equations.The obtained stiffness data can be used to establish the finite element model of beams.Subsequently,dynamic excitation and mode identification should be carried out for the beam in service.Mode shape curvature index is employed to detect the position of damage.It was validated by example that actual damage and original uncertainty of local flexural stiffness can be differentiated by this new method effectively.The combination of static load and dynamic excitation can keep the serviceability of beam.
基金supported by the National High Technology Research and Development Program of China (No. 2020YFB1806004)。
文摘Satellite communication develops rapidly due to its global coverage and is unrestricted to the ground environment. However, compared with the traditional ground TCP/IP network, a satellite-to-ground link has a more extensive round trip time(RTT) and a higher packet loss rate,which takes more time in error recovery and wastes precious channel resources. Forward error correction(FEC) is a coding method that can alleviate bit error and packet loss, but how to achieve high throughput in the dynamic network environment is still a significant challenge. Inspired by the deep learning technique, this paper proposes a signal-to-noise ratio(SNR) based adaptive coding modulation method. This method can maximize channel utilization while ensuring communication quality and is suitable for satellite-to-ground communication scenarios where the channel state changes rapidly. We predict the SNR using the long short-term memory(LSTM) network that considers the past channel status and real-time global weather. Finally, we use the optimal matching rate(OMR) to evaluate the pros and cons of each method quantitatively. Extensive simulation results demonstrate that our proposed LSTM-based method outperforms the state-of-the-art prediction algorithms significantly in mean absolute error(MAE). Moreover, it leads to the least spectrum waste.
