Low-Velocity Impact Damage Simulation of Biaxial Warp-Knitted Flexible Composite with Simplified Microstructure Model

Applied Composite Materials - In this paper, the low-velocity impact deformation behavior of biaxial warp-knitted flexible composite was investigated. A simplified finite element model (FEM) of the...     

Fabrication and characterizations of Cr3+-doped ZnGa2O4 transparent ceramics with persistent luminescence

0.5 at.% Cr:ZnGa₂O₄ precursor was synthesized by the co-precipitation method with nitrates as raw materials, using ammonium carbonate as the precipitant. Low-agglomerated Cr:ZnGa₂O₄ powders with an average particle size of 43 nm were obtained by calcining the precursor at 900℃ for 4 h. Using the powders as starting materials, 0.5 at.% Cr:ZnGa₂O₄ ceramics with an average grain size of about 515 nm were prepared by presintering at 1150℃ for 5 h in air and HIP post-treatment at 1100℃ for 3 h under 200 MPa Ar. The in-line transmittance of 0.5 at.% Cr:ZnGa₂O₄ ceramics with a thickness of 1.3 mm reaches 59.5% at the wavelength of 700 nm. The Cr:ZnGa₂O₄ ceramics can be effectively excited by visible light and produce persistent luminescence at 700 nm. For Cr:ZnGa₂O₄ transparent ceramics, the brightness of afterglow was larger than 0.32 mcd/m² after 30 min, which is far superior to that of Cr:ZnGa₂O₄ persistent luminescence powders.     

DISPERSION COMPENSATION CFBG IN100km 10Gbit／s RECIRCULATING SYSTEMS

A 10Gbit/s recirculating system is configured with Chirped Fiber Bragg Grating (CFBG) for the dispersion compensation. For the first time, the transmission distance in the loop reaches 1000km with bit error rate of 10-9. The effect of the group delay ripple of the fiber grating is also investigated in the recirculating systems, and it is shown that the transmission distance is limited to 4 cycles (4×167.1km ) in the loop with the power penalty fluctuation below 1.0dB. Thus the group delay ripple should be reduced to allow for the wavelength drift of±5GHz. At the end of this letter, the principles are given for designing long haul recirculating systems with dispersion compensation CFBG.     

地下输水管网的腐蚀调查

介绍了中国石油天然气股份有限公司大庆石化分公司地下输水管网的腐蚀现状与调查分析情况,提出了对地下输水管网实施以深井阳极地床外加电流阴极保护为主、局部欠保护区辅以镁合金牺牲阳极的阴极保护方案。经分析,采取上述防护措施后,每年可产生2488万元的经济效益。     

硅中硼离子注入校准样品的研制

本文主要介绍了硅中硼离子注入校准样品的制备与研究。分别用三台SIMS仪器对样品进行了深度剖析与比对,并对用作校准目的的样品主要参数进行了定值。     

高炉煤气喷水降温控制方法

用ＫＭＭ调节器根据温控偏差和喷水量计算两个调节参数，对水量调节阀进行开度调节来控制最终喷水量，从而达到准确有效控制布袋除尘器入口煤气温度的目的。     

Stock Price Forecasting: An Echo State Network Approach

Forecasting stock prices using deep learning models suffers from problems such as low accuracy, slow convergence, and complex network structures. This study developed an echo state network (ESN) model to mitigate such problems. We compared our ESN with a long short-term memory (LSTM) network by forecasting the stock data of Kweichow Moutai, a leading enterprise in China’s liquor industry. By analyzing data for 120, 240, and 300 days, we generated forecast data for the next 40, 80, and 100 days, respectively, using both ESN and LSTM. In terms of accuracy, ESN had the unique advantage of capturing nonlinear data. Mean absolute error (MAE) was used to present the accuracy results. The MAEs of the data forecast by ESN were 0.024, 0.024, and 0.025, which were, respectively, 0.065, 0.007, and 0.009 less than those of LSTM. In terms of convergence, ESN has a reservoir state-space structure, which makes it perform faster than other models. Root-mean-square error (RMSE) was used to present the convergence time. In our experiment, the RMSEs of ESN were 0.22, 0.27, and 0.26, which were, respectively, 0.08, 0.01, and 0.12 less than those of LSTM. In terms of network structure, ESN consists only of input, reservoir, and output spaces, making it a much simpler model than the others. The proposed ESN was found to be an effective model that, compared to others, converges faster, forecasts more accurately, and builds time-series analyses more easily.     

Reciprocal bi-directional generative adversarial network for cross-modal pedestrian re-identification

To improve the accuracy of cross-modal pedestrian re-identification,a reciprocal bi-directional generative adversarial network-based method is proposed.First,we build two generative adversarial networks to generate cross-modal heterogeneous images.Second,an associated loss is designed to pull close the distribution of features in latent space during the image translation between visible and infrared images so as to help the networks generate fake heterogeneous images that have high similarity with the real images.Finally,by concatenating the original and generated heterogeneous pedestrian images into the discriminative feature extraction network,images from different modalities can be unified into a common modality,thus suppressing the cross-modal gap.Representation learning and metric learning are utilized to achieve more discriminative pedestrian features.Comparative experiments are conducted on SYSU-MM01 and RegDB datasets to analyze the accuracy with different loss functions.Compared with other state-of-the-art cross-modal pedestrian re-identification methods,the proposed method achieves a higher accuracy and stronger robustness.     

原位合成莫来石晶须及其微观结构的研究

本文通过以高岭土、工业氢氧化铝为原料,添加适量AlF3和V2O5,在高温下原位合成了莫来石晶须,采用扫描电镜（SEM）研究了合成的莫来石晶须的微观形貌,探讨了莫来石晶须的生长机理,并讨论了影响莫来石晶须生长的相关因素.在综合考虑影响莫来石晶须生长的相关因素后,制备出晶须多、长径比大、分布均匀的莫来石晶须样品.     

基于模型参考自适应系统理论的异步电机矢量控制系统研究

采用模型参考自适应系统对系统转速进行估算,实现了异步电机的无速度传感器控制.在一个4kW的三相异步电动机上进行了实验,异步电机结果表明:该系统具有快速的动态响应能力和良好的稳定性.