With Al2O3 and SiO2 as polishing medium, under different polishing conditions, e.g. with different polishing pressure, polishing time and polishing fluid, the influences of polishing treatment on the return loss of op...With Al2O3 and SiO2 as polishing medium, under different polishing conditions, e.g. with different polishing pressure, polishing time and polishing fluid, the influences of polishing treatment on the return loss of optical fiber connectors were investigated. The return loss of optical fiber connectors is 32CD*238dB before polishing. The results show that dry polishing（i.e. no polishing fluid） with Al2O3 has less influence on return loss of optical fiber connectors, while dry polishing with SiO2 reduces return loss to about 20dB because of the end-face of optical fiber contaminated. The wet polishing（i.e. using distilled water as polishing fluid） with Al2O3 or SiO2 can increase return loss to 45CD*250dB, but wet polishing with Al2O3 may produce optical fiber undercut depth of 80CD*2140nm. Wet polishing with SiO2 should be preferentially selected for optical fiber connectors and polishing time should be controlled within 20CD*230s.展开更多
High-frequency(HF)and ultrahigh-frequency(UHF)dual-band radio frequency identification(RFID)tags with both near-field and farfield communication can meet different application scenarios.However,it is time-consuming to...High-frequency(HF)and ultrahigh-frequency(UHF)dual-band radio frequency identification(RFID)tags with both near-field and farfield communication can meet different application scenarios.However,it is time-consuming to calculate the return loss of a UHF antenna in a dualband tag antenna using electromagnetic(EM)simulators.To overcome this,the present work proposes a model of a multi-scale convolutional neural network stacked with long and short-term memory(MSCNN-LSTM)for predicting the return loss of UHF antennas instead of EM simulators.In the proposed MSCNN-LSTM,the MSCNN has three branches,which include three convolution layers with different kernel sizes and numbers.Therefore,MSCNN can extract fine-grain localized information of the antenna and overall features.The LSTM can effectively learn the EM characteristics of different structures of the antenna to improve the prediction accuracy of the model.Experimental results show that the mean absolute error(0.0073),mean square error(0.00032),and root mean square error(0.01814)of theMSCNNLSTM are better than those of other prediction methods.In predicting the return loss of 100UHFantennas,compared with the simulation time of 4800 s for High Frequency Structure Simulator(HFSS),MSCNN-LSTM takes only 0.927519 s under the premise of ensuring prediction accuracy,significantly reducing the calculation time,which provides a basis for the rapid design of HF-UHF RFID tag antenna.ThenMSCNN-LSTM is used to determine the dimensions of the UHF antenna quickly.The return loss of the designed dualband RFID tag antenna is−58.76 and−22.63 dB at 13.56 and 915 MHz,respectively,achieving the desired goal.展开更多
The so-called“Hang's Mudding-off”technique is critical to keeping the dynamic pressure balance and guaranteeing the sufficient safe operation time in wellbore.However,for lack of dynamic mathematical model analy...The so-called“Hang's Mudding-off”technique is critical to keeping the dynamic pressure balance and guaranteeing the sufficient safe operation time in wellbore.However,for lack of dynamic mathematical model analysis methods for reflecting the changes of annulus liquid level in the borehole during the“Hang's Mudding-off”operation,the actual operation is basically conducted blindly without reasonable engineering basis.According to the actual conditions,a mathematical model for the safe time of the“Hang's Mudding-off”was,for the first time,built up by using the dynamic borehole leakage analysis method.Then,the integral results of leak-off rates were calculated.Finally,the calculation results were verified by field cases.It is shown that the calculation results are highly accordant with the actual data,indicating the reliability of the mathematical model.The safe operation time can be increased by increasing mud amount or reducing mud density appropriately.With this model,the safe time of“Hang's Mudding-off”operation can be calculated accurately.This research result is of great significance to avoiding well control risk of absorption wells,optimizing the“Hang's Mudding-off”technique and reducing project cost.展开更多
【目的】明确不同培肥措施对麦玉轮作模式下作物产量、氮肥利用率及农田氮损失的影响,为土壤培肥提供科学依据。【方法】以中国麦玉轮作区为研究区域,在中国知网、Web of Science平台,搜集并筛选出64篇文献,提取其中的产量、氮素损失(...【目的】明确不同培肥措施对麦玉轮作模式下作物产量、氮肥利用率及农田氮损失的影响,为土壤培肥提供科学依据。【方法】以中国麦玉轮作区为研究区域,在中国知网、Web of Science平台,搜集并筛选出64篇文献,提取其中的产量、氮素损失(氨挥发、N2O排放、硝态氮淋溶)数据,采用整合分析(Metaanalysis)方法,对比分析常规单施化肥、常规化肥配合秸秆还田(秸秆还田)、有机肥替代部分化肥(有机替代)以及秸秆还田+有机替代4种施肥措施对作物产量、氮肥利用率以及农田氮损失的影响。【结果】常规单施化肥措施下,小麦和玉米产量均值分别为6.06和7.79 t/hm^(2),氮肥利用率分别为36.3%和34.2%;农田氮损失以淋溶和NH3挥发为主,且农田氮损失主要发生在玉米季,约占全年氮损失的57.7%。与常规单施化肥相比,秸秆还田显著提高小麦产量21.8%、玉米产量6.1%,但增加NH3挥发和N2O排放的风险。与常规单施化肥相比,有机替代显著降低了农田硝态氮淋失(小麦季39.6%、玉米季27.7%)和玉米季N2O排放(21.2%),但小麦产量存在较大波动,以20%~40%的替代比例增产效果最佳(3.6%)。与常规单施化肥相比,秸秆还田+有机替代小麦平均增产16.4%、玉米产量提高17.7%,玉米季硝态氮淋溶降低24.1%;与秸秆还田相比,秸秆还田+有机替代虽然显著提高了作物产量(小麦5.7%、玉米13.4%),但增加了玉米季N_(2)O排放(61.9%)。【结论】常规化肥措施下,秸秆还田、有机替代及秸秆还田+有机替代措施均能提高麦玉轮作体系的作物产量。不同措施的环境效应存在差异:秸秆还田虽能增产,但会导致农田氮排放量增加;有机替代措施具有较好的氮减排效果,但需合适的替代比例才能实现增产与减排的双重效益。值得注意的是,秸秆还田结合有机替代的增产效果最佳,但其农田氮减排效果相关研究较少,减排效果和机制尚不明确,有待进一步探究。展开更多
特高频内置传感器布置在气体绝缘金属封闭开关设备(gas insulated switchgear,GIS)内部,可以实时监测局部放电产生的特高频(ultra high frequency,UHF)电磁波信号,然而长期运行过程中受到设备振动、环境温度等因素的影响,内置传感器自...特高频内置传感器布置在气体绝缘金属封闭开关设备(gas insulated switchgear,GIS)内部,可以实时监测局部放电产生的特高频(ultra high frequency,UHF)电磁波信号,然而长期运行过程中受到设备振动、环境温度等因素的影响,内置传感器自身性能可能会发生劣化,从而导致无法准确监测到局部放电信号,因此有必要研究内置传感器的现场校验方法,便于定期对运行中的内置传感器的性能开展评估。文中根据GIS特高频内置传感器的结构原理和多端口网络理论,分析了内置传感器回波损耗的物理意义,确认回波损耗可有效反映内置传感器的运行状态。根据GIS典型气室的结构尺寸,建立了特高频内置传感器等比例的三维仿真模型,并通过回波损耗曲线的仿真结果与现场实测数据对比,验证了仿真模型的正确性。进一步仿真研究了内置传感器介质层绝缘劣化、馈电杆接触不良两种典型缺陷时的回波损耗曲线特征,为运行中的内置传感器现场校验与缺陷诊断提供了参考。展开更多
文摘With Al2O3 and SiO2 as polishing medium, under different polishing conditions, e.g. with different polishing pressure, polishing time and polishing fluid, the influences of polishing treatment on the return loss of optical fiber connectors were investigated. The return loss of optical fiber connectors is 32CD*238dB before polishing. The results show that dry polishing（i.e. no polishing fluid） with Al2O3 has less influence on return loss of optical fiber connectors, while dry polishing with SiO2 reduces return loss to about 20dB because of the end-face of optical fiber contaminated. The wet polishing（i.e. using distilled water as polishing fluid） with Al2O3 or SiO2 can increase return loss to 45CD*250dB, but wet polishing with Al2O3 may produce optical fiber undercut depth of 80CD*2140nm. Wet polishing with SiO2 should be preferentially selected for optical fiber connectors and polishing time should be controlled within 20CD*230s.
基金The research work is carried out under the Beijing Natural Science Foundation-Beijing Education Commission Joint Project(KZ202210015020)Discipline Construction and Postgraduate Education Project of BIGC(No.21090122005)BIGC Project(Ee202204).
文摘High-frequency(HF)and ultrahigh-frequency(UHF)dual-band radio frequency identification(RFID)tags with both near-field and farfield communication can meet different application scenarios.However,it is time-consuming to calculate the return loss of a UHF antenna in a dualband tag antenna using electromagnetic(EM)simulators.To overcome this,the present work proposes a model of a multi-scale convolutional neural network stacked with long and short-term memory(MSCNN-LSTM)for predicting the return loss of UHF antennas instead of EM simulators.In the proposed MSCNN-LSTM,the MSCNN has three branches,which include three convolution layers with different kernel sizes and numbers.Therefore,MSCNN can extract fine-grain localized information of the antenna and overall features.The LSTM can effectively learn the EM characteristics of different structures of the antenna to improve the prediction accuracy of the model.Experimental results show that the mean absolute error(0.0073),mean square error(0.00032),and root mean square error(0.01814)of theMSCNNLSTM are better than those of other prediction methods.In predicting the return loss of 100UHFantennas,compared with the simulation time of 4800 s for High Frequency Structure Simulator(HFSS),MSCNN-LSTM takes only 0.927519 s under the premise of ensuring prediction accuracy,significantly reducing the calculation time,which provides a basis for the rapid design of HF-UHF RFID tag antenna.ThenMSCNN-LSTM is used to determine the dimensions of the UHF antenna quickly.The return loss of the designed dualband RFID tag antenna is−58.76 and−22.63 dB at 13.56 and 915 MHz,respectively,achieving the desired goal.
文摘The so-called“Hang's Mudding-off”technique is critical to keeping the dynamic pressure balance and guaranteeing the sufficient safe operation time in wellbore.However,for lack of dynamic mathematical model analysis methods for reflecting the changes of annulus liquid level in the borehole during the“Hang's Mudding-off”operation,the actual operation is basically conducted blindly without reasonable engineering basis.According to the actual conditions,a mathematical model for the safe time of the“Hang's Mudding-off”was,for the first time,built up by using the dynamic borehole leakage analysis method.Then,the integral results of leak-off rates were calculated.Finally,the calculation results were verified by field cases.It is shown that the calculation results are highly accordant with the actual data,indicating the reliability of the mathematical model.The safe operation time can be increased by increasing mud amount or reducing mud density appropriately.With this model,the safe time of“Hang's Mudding-off”operation can be calculated accurately.This research result is of great significance to avoiding well control risk of absorption wells,optimizing the“Hang's Mudding-off”technique and reducing project cost.
文摘【目的】明确不同培肥措施对麦玉轮作模式下作物产量、氮肥利用率及农田氮损失的影响,为土壤培肥提供科学依据。【方法】以中国麦玉轮作区为研究区域,在中国知网、Web of Science平台,搜集并筛选出64篇文献,提取其中的产量、氮素损失(氨挥发、N2O排放、硝态氮淋溶)数据,采用整合分析(Metaanalysis)方法,对比分析常规单施化肥、常规化肥配合秸秆还田(秸秆还田)、有机肥替代部分化肥(有机替代)以及秸秆还田+有机替代4种施肥措施对作物产量、氮肥利用率以及农田氮损失的影响。【结果】常规单施化肥措施下,小麦和玉米产量均值分别为6.06和7.79 t/hm^(2),氮肥利用率分别为36.3%和34.2%;农田氮损失以淋溶和NH3挥发为主,且农田氮损失主要发生在玉米季,约占全年氮损失的57.7%。与常规单施化肥相比,秸秆还田显著提高小麦产量21.8%、玉米产量6.1%,但增加NH3挥发和N2O排放的风险。与常规单施化肥相比,有机替代显著降低了农田硝态氮淋失(小麦季39.6%、玉米季27.7%)和玉米季N2O排放(21.2%),但小麦产量存在较大波动,以20%~40%的替代比例增产效果最佳(3.6%)。与常规单施化肥相比,秸秆还田+有机替代小麦平均增产16.4%、玉米产量提高17.7%,玉米季硝态氮淋溶降低24.1%;与秸秆还田相比,秸秆还田+有机替代虽然显著提高了作物产量(小麦5.7%、玉米13.4%),但增加了玉米季N_(2)O排放(61.9%)。【结论】常规化肥措施下,秸秆还田、有机替代及秸秆还田+有机替代措施均能提高麦玉轮作体系的作物产量。不同措施的环境效应存在差异:秸秆还田虽能增产,但会导致农田氮排放量增加;有机替代措施具有较好的氮减排效果,但需合适的替代比例才能实现增产与减排的双重效益。值得注意的是,秸秆还田结合有机替代的增产效果最佳,但其农田氮减排效果相关研究较少,减排效果和机制尚不明确,有待进一步探究。
文摘特高频内置传感器布置在气体绝缘金属封闭开关设备(gas insulated switchgear,GIS)内部,可以实时监测局部放电产生的特高频(ultra high frequency,UHF)电磁波信号,然而长期运行过程中受到设备振动、环境温度等因素的影响,内置传感器自身性能可能会发生劣化,从而导致无法准确监测到局部放电信号,因此有必要研究内置传感器的现场校验方法,便于定期对运行中的内置传感器的性能开展评估。文中根据GIS特高频内置传感器的结构原理和多端口网络理论,分析了内置传感器回波损耗的物理意义,确认回波损耗可有效反映内置传感器的运行状态。根据GIS典型气室的结构尺寸,建立了特高频内置传感器等比例的三维仿真模型,并通过回波损耗曲线的仿真结果与现场实测数据对比,验证了仿真模型的正确性。进一步仿真研究了内置传感器介质层绝缘劣化、馈电杆接触不良两种典型缺陷时的回波损耗曲线特征,为运行中的内置传感器现场校验与缺陷诊断提供了参考。
