To address the issue of extreme thermal-induced arching in CRTS II slab tracks due to joint damage,an optimized joint repair model was proposed.First,the formula for calculating the safe temperature rise of the track ...To address the issue of extreme thermal-induced arching in CRTS II slab tracks due to joint damage,an optimized joint repair model was proposed.First,the formula for calculating the safe temperature rise of the track was derived based on the principle of stationary potential energy.Considering interlayer evolution and structural crack propagation,an optimized joint repair model for the track was established and validated.Subsequently,the impact of joint repair on track damage and arch stability under extreme temperatures was studied,and a comprehensive evaluation of the feasibility of joint repair and the evolution of damage after repair was conducted.The results show that after the joint repair,the temperature rise of the initial damage of the track structure can be increased by 11℃.Under the most unfavorable heating load with a superimposed temperature gradient,the maximum stiffness degradation index SDEG in the track structure is reduced by about 81.16%following joint repair.The joint repair process could effectively reduce the deformation of the slab arching under high temperatures,resulting in a reduction of 93.96%in upward arching deformation.After repair,with the damage to interfacing shear strength,the track arch increases by 2.616 mm.展开更多
With the wide application of condition based maintenance(CBM) in aircraft maintenance practice, the joint optimization of maintenance and inventory management, which can take full advantage of CBM and reduce the aircr...With the wide application of condition based maintenance(CBM) in aircraft maintenance practice, the joint optimization of maintenance and inventory management, which can take full advantage of CBM and reduce the aircraft operational cost, is receiving increasing attention. In order to optimize the inspection interval, maintenance decision and spare provisioning together for aircraft deteriorating parts, firstly, a joint inventory management strategy is presented, then, a joint optimization of maintenance inspection and spare provisioning for aircraft parts subject to the Wiener degradation process is proposed based on the strategy.Secondly, a combination of the genetic algorithm(GA) and the Monte Carol method is developed to minimize the total cost rate.Finally, a case study is conducted and the proposed joint optimization model is compared with the existing optimization model and the airline real case. The results demonstrate that the proposed model is more beneficial and effective. In addition, the sensitivity analysis of the proposed model shows that the lead time has higher influence on the optimal results than the urgent order cost and the corrective maintenance cost, which is consistent with the actual situation of aircraft maintenance practices and inventory management.展开更多
The joint optimization of detection threshold and waveform parameters for target tracking which comes from the idea of cognitive radar is investigated for the modified probabilistic data association(MPDA)filter.The tr...The joint optimization of detection threshold and waveform parameters for target tracking which comes from the idea of cognitive radar is investigated for the modified probabilistic data association(MPDA)filter.The transmitted waveforms and detection threshold are adaptively selected to enhance the tracking performance.The modified Riccati equation is adopted to predict the error covariance which is used as the criterion function,while the optimization problem is solved through the genetic algorithm(GA).The detection probability,false alarm probability and measurement noise covariance are all considered together,which significantly improves the tracking performance of the joint detection and tracking system.Simulation results show that the proposed adaptive waveform-detection threshold joint optimization method outperforms the adaptive threshold method and the fixed parameters method,which will reduce the tracking error.The average reduction of range error between the adaptive joint method and the fixed parameters method is about 0.6 m,while that between the adaptive joint method and the adaptive threshold only method is about 0.3 m.Similar error reduction occurs for the velocity error and acceleration error.展开更多
Based on a method combined artificial neural network (ANN) with particle swarm optimization (PSO) algorithm, the thermo-mechanical fatigue reliability of plastic ball grid array (PBGA) solder joints was studied. The s...Based on a method combined artificial neural network (ANN) with particle swarm optimization (PSO) algorithm, the thermo-mechanical fatigue reliability of plastic ball grid array (PBGA) solder joints was studied. The simulation experiments of accelerated thermal cycling test were performed by ANSYS software. Based on orthogonal array experiments, a back-propagation artificial neural network (BPNN) was used to establish the nonlinear multivariate relationship between thermo-mechanical fatigue reliability and control factors. Then, PSO was applied to obtaining the optimal levels of control factors by using the output of BPNN as the affinity measure. The results show that the control factors, such as print circuit board (PCB) size, PCB thickness, substrate size, substrate thickness, PCB coefficient of thermal expansion (CTE), substrate CTE, silicon die CTE, and solder joint CTE, have a great influence on thermo-mechanical fatigue reliability of PBGA solder joints. The ratio of signal to noise of ANN-PSO method is 51.77 dB and its error is 33.3% less than that of Taguchi method. Moreover, the running time of ANN-PSO method is only 2% of that of the BPNN. These conclusions are verified by the confirmative experiments.展开更多
Multi-carrier faster-than-Nyquist(MFTN)can improve the spectrum efficiency(SE).In this paper,we first analyze the benefit of time frequency packing MFTN(TFP-MFTN).Then,we propose an efficient digital implementation fo...Multi-carrier faster-than-Nyquist(MFTN)can improve the spectrum efficiency(SE).In this paper,we first analyze the benefit of time frequency packing MFTN(TFP-MFTN).Then,we propose an efficient digital implementation for TFP-MFTN based on filter bank multicarrier modulation.The time frequency packing ratio pair in our proposed implementation scheme is optimized with the SE criterion.Next,the joint optimization for the coded modulation MFTN based on extrinsic information transfer(EXIT)chart is performed.The Monte-Carlo simulations are carried out to verify performance gain of the joint inner and outer code optimization.Simulation results demonstrate that the TFPMFTN has a 0.8 dB and 0.9 dB gain comparing to time packing MFTN(TP-MFTN)and higher order Nyquist at same SE,respectively;the TFP-MFTN with optimized low density parity check(LDPC)code has a 2.9 dB gain comparing to that with digital video broadcasting(DVB)LDPC.Compared with previous work on TFP-MFTN(SE=1.55 bit/s/Hz),the SE of our work is improved by 29%and our work has a 4.1 dB gain at BER=1×10^(-5).展开更多
隐藏社区检测有助于揭示网络深层次功能和结构特征,是一个具有挑战性的研究领域。隐藏社区由弱关系连接而成,受具有较强连接关系的显性社区影响,在网络中不易被检测到。当前的隐藏社区发现算法对节点属性信息和全局拓扑结构的综合利用...隐藏社区检测有助于揭示网络深层次功能和结构特征,是一个具有挑战性的研究领域。隐藏社区由弱关系连接而成,受具有较强连接关系的显性社区影响,在网络中不易被检测到。当前的隐藏社区发现算法对节点属性信息和全局拓扑结构的综合利用仍显不足,为解决这一问题,提出了一种基于双重图卷积神经网络(GCN)联合优化隐藏社区发现算法——HCDGCN(hidden community detection based on dual GCN)。HCDGCN融合节点局部和全局结构特征,通过两个GCN共同迭代优化一个损失函数,并逐步削弱权重,使得弱关系社区变得清晰可见,实现了隐藏社区发现。在真实数据集上的实验结果表明,HCDGCN在隐藏社区发现方面优于现有基准方法,实现了更快的收敛速度和更优的社区划分。展开更多
基金Project(K2022G038)supported by the Science Technology Research and Development Program of China State Railway Group Co.,LtdProject(52178405)supported by the National Natural Science Foundation of China。
文摘To address the issue of extreme thermal-induced arching in CRTS II slab tracks due to joint damage,an optimized joint repair model was proposed.First,the formula for calculating the safe temperature rise of the track was derived based on the principle of stationary potential energy.Considering interlayer evolution and structural crack propagation,an optimized joint repair model for the track was established and validated.Subsequently,the impact of joint repair on track damage and arch stability under extreme temperatures was studied,and a comprehensive evaluation of the feasibility of joint repair and the evolution of damage after repair was conducted.The results show that after the joint repair,the temperature rise of the initial damage of the track structure can be increased by 11℃.Under the most unfavorable heating load with a superimposed temperature gradient,the maximum stiffness degradation index SDEG in the track structure is reduced by about 81.16%following joint repair.The joint repair process could effectively reduce the deformation of the slab arching under high temperatures,resulting in a reduction of 93.96%in upward arching deformation.After repair,with the damage to interfacing shear strength,the track arch increases by 2.616 mm.
基金supported by the Fundamental Research Funds for the Central Universities(NS2015072)
文摘With the wide application of condition based maintenance(CBM) in aircraft maintenance practice, the joint optimization of maintenance and inventory management, which can take full advantage of CBM and reduce the aircraft operational cost, is receiving increasing attention. In order to optimize the inspection interval, maintenance decision and spare provisioning together for aircraft deteriorating parts, firstly, a joint inventory management strategy is presented, then, a joint optimization of maintenance inspection and spare provisioning for aircraft parts subject to the Wiener degradation process is proposed based on the strategy.Secondly, a combination of the genetic algorithm(GA) and the Monte Carol method is developed to minimize the total cost rate.Finally, a case study is conducted and the proposed joint optimization model is compared with the existing optimization model and the airline real case. The results demonstrate that the proposed model is more beneficial and effective. In addition, the sensitivity analysis of the proposed model shows that the lead time has higher influence on the optimal results than the urgent order cost and the corrective maintenance cost, which is consistent with the actual situation of aircraft maintenance practices and inventory management.
基金Project(61171133) supported by the National Natural Science Foundation of ChinaProject(11JJ1010) supported by the Natural Science Fund for Distinguished Young Scholars of Hunan Province,China
文摘The joint optimization of detection threshold and waveform parameters for target tracking which comes from the idea of cognitive radar is investigated for the modified probabilistic data association(MPDA)filter.The transmitted waveforms and detection threshold are adaptively selected to enhance the tracking performance.The modified Riccati equation is adopted to predict the error covariance which is used as the criterion function,while the optimization problem is solved through the genetic algorithm(GA).The detection probability,false alarm probability and measurement noise covariance are all considered together,which significantly improves the tracking performance of the joint detection and tracking system.Simulation results show that the proposed adaptive waveform-detection threshold joint optimization method outperforms the adaptive threshold method and the fixed parameters method,which will reduce the tracking error.The average reduction of range error between the adaptive joint method and the fixed parameters method is about 0.6 m,while that between the adaptive joint method and the adaptive threshold only method is about 0.3 m.Similar error reduction occurs for the velocity error and acceleration error.
基金Project(60371046) supported by the National Natural Science Foundation of ChinaProject(9140C0301060C03001) supported by the National Defense Science and Technology Foundation of Key Laboratory, China
文摘Based on a method combined artificial neural network (ANN) with particle swarm optimization (PSO) algorithm, the thermo-mechanical fatigue reliability of plastic ball grid array (PBGA) solder joints was studied. The simulation experiments of accelerated thermal cycling test were performed by ANSYS software. Based on orthogonal array experiments, a back-propagation artificial neural network (BPNN) was used to establish the nonlinear multivariate relationship between thermo-mechanical fatigue reliability and control factors. Then, PSO was applied to obtaining the optimal levels of control factors by using the output of BPNN as the affinity measure. The results show that the control factors, such as print circuit board (PCB) size, PCB thickness, substrate size, substrate thickness, PCB coefficient of thermal expansion (CTE), substrate CTE, silicon die CTE, and solder joint CTE, have a great influence on thermo-mechanical fatigue reliability of PBGA solder joints. The ratio of signal to noise of ANN-PSO method is 51.77 dB and its error is 33.3% less than that of Taguchi method. Moreover, the running time of ANN-PSO method is only 2% of that of the BPNN. These conclusions are verified by the confirmative experiments.
基金supported by the National Natural Science Foundation of China(61961014,61561017)。
文摘Multi-carrier faster-than-Nyquist(MFTN)can improve the spectrum efficiency(SE).In this paper,we first analyze the benefit of time frequency packing MFTN(TFP-MFTN).Then,we propose an efficient digital implementation for TFP-MFTN based on filter bank multicarrier modulation.The time frequency packing ratio pair in our proposed implementation scheme is optimized with the SE criterion.Next,the joint optimization for the coded modulation MFTN based on extrinsic information transfer(EXIT)chart is performed.The Monte-Carlo simulations are carried out to verify performance gain of the joint inner and outer code optimization.Simulation results demonstrate that the TFPMFTN has a 0.8 dB and 0.9 dB gain comparing to time packing MFTN(TP-MFTN)and higher order Nyquist at same SE,respectively;the TFP-MFTN with optimized low density parity check(LDPC)code has a 2.9 dB gain comparing to that with digital video broadcasting(DVB)LDPC.Compared with previous work on TFP-MFTN(SE=1.55 bit/s/Hz),the SE of our work is improved by 29%and our work has a 4.1 dB gain at BER=1×10^(-5).
文摘隐藏社区检测有助于揭示网络深层次功能和结构特征,是一个具有挑战性的研究领域。隐藏社区由弱关系连接而成,受具有较强连接关系的显性社区影响,在网络中不易被检测到。当前的隐藏社区发现算法对节点属性信息和全局拓扑结构的综合利用仍显不足,为解决这一问题,提出了一种基于双重图卷积神经网络(GCN)联合优化隐藏社区发现算法——HCDGCN(hidden community detection based on dual GCN)。HCDGCN融合节点局部和全局结构特征,通过两个GCN共同迭代优化一个损失函数,并逐步削弱权重,使得弱关系社区变得清晰可见,实现了隐藏社区发现。在真实数据集上的实验结果表明,HCDGCN在隐藏社区发现方面优于现有基准方法,实现了更快的收敛速度和更优的社区划分。
