面向流屑角突变建模的切削状态参数经验公式的获得及应用

从提高流屑角突变模型的预测精度出发,建立了切削状态参数与3个切削控制参数之间关系的新经验公式。提出了一种通过迭代法准确设定有限元仿真软件刀-屑摩擦因数的方法,并通过直角切削Al6061-T6工件的有限元仿真试验,获得了一组不同切削控制参数组合条件下的切削状态参数数据。根据该数据拟合出剪切角φ、刀-屑摩擦角β、剪切应力τs关于刀具前角γ0、进给量f和切削速度v的经验公式,并通过一组直角切削试验,验证了所得经验公式的有效性。将新建经验公式应用于流屑角突变建模过程后,所得模型关于突变临界切削宽度的平均预测误差减小了27.2%。     

Extending SSD Lifespan with Comprehensive Non-Volatile Memory-Based Write Buffers

Journal of Computer Science and Technology - New non-volatile memory (NVM) technologies are expected to replace main memory DRAM (dynamic random access memory) in the near future. NAND flash...     

基于状态观测器的电镀液温度状态反馈控制系统

针对电镀液温度控制系统,引入状态反馈控制。相对于传统的反馈控制,本方法可以获得更优异的性能。另外,考虑到镀液温度控制具有纯迟延的特点,提出了一种消去纯迟延的方法。仿真验证结果显示,控制效果良好。     

Calorimetric study of ytterbium orthovanadate YbVO4 polycrystalline ceramics

The heat capacity of ytterbium orthovanadate was first measured by adiabatic calorimetry in the temperature range T?=?12.28–344.06?K. No obvious anomalies were observed on the curve obtained. The values of standard thermodynamic functions in the temperature range T?=?0–400 K were calculated. Based on low-temperature calorimetry data obtained, previously published data on the high-temperature heat capacity of ytterbium orthovanadate were corrected. The anomalous contribution to heat capacity for YbVO₄ was compared with the data known for YbPO₄.     

The influence of activated carbon as an additive in anode materials for low temperature solid oxide fuel cells

The effects of activated carbon (AC) as an additive in multi-oxide nano composite LiNiCuZn–O for application as anode in solid oxide fuel cell (SOFC) is reported. The composite was synthesized using solid state reactions method with varying content of AC in range 0.1%–0.9% for use as anode in the cell. The cell was composed of the synthesized composite as anode, LiNiCuZn–O as cathode and Samaria doped ceria (SDC) as electrolyte. The prepared composites were characterized for morphology and crystal structure by scanning electron microscope (SEM) and x-ray diffraction (XRD) respectively. Furthermore, the crystallite sizes of LiNiCuZn–O and LiNiCuZn–O with AC as an additive have been found in the range from 50 nm to 70 nm. The prepared composite materials were observed porous and the porosity of the sample having 0.5% additive was found highest. The conductivity and power density of the SOFC were studied at temperature of 600 °C. The maximum value of conductivity was found as 4.79 S/cm for the composite containing 0.5% AC as measured by using 4-probe method. The maximum value of power density of the fuel cell with anode comprising of 0.5% AC along with the mentioned cathode and the electrolyte was 455 mW/cm². Therefore, out of the compositions studied, the composite comprising of LiNiCuZn–O with 0.5% AC offered best performance for anode in the cell. This oxide composite is reported as a potential candidate for use as anode in low temperature SOFCs.     

A mixed collector system for phosphate flotation

Flotation has been used in industry for more than a half century as the primary technique for upgrading phosphate. While the flotation of phosphate was inefficient when oleic acid was used alone as a collector, therefore a mixed collector of oleic acid (HOl), linoleic acid (LA) and linolenic acid (LNA) was employed to improve the recovery of phosphate flotation. The batch flotation results showed that the optimal composition of the mixed collector was 54 wt.% HOl, 36 wt.% LA and 10 wt.% LNA. Additionally, the effect of pH on the mixed collector application was studied while considering the surface tension, contact angle and micro-flotation. The results showed that the mixed collector should be used at a pH of 9.5. Above a pH of 9.5, the adsorption of fatty acids dimers on the apatite surface hindered phosphate flotation. The influence of the mixed collector assembly on apatite flotation was also investigated. It was demonstrated that due to its low critical micelle concentration, a sufficiently hydrophobic apatite surface could be generated at a collector concentration of 60 mg/L. In addition, zeta potential experiments suggested that collector adsorption was governed by chemisorption. FTIR and XPS spectra studies further indicated that the chemical reaction involved the carboxyl groups of fatty acids and Ca species at the apatite surface for each fatty acid in the mixed collector.     

Classification and regression models of audio and vibration signals for machine state monitoring in precision machining systems

We present a data-driven method for monitoring machine status in manufacturing processes. Audio and vibration data from precision machining are used for inference in two operating scenarios: (a) variable machine health states (anomaly detection); and (b) settings of machine operation (state estimation). Audio and vibration signals are first processed through Fast Fourier Transform and Principal Component Analysis to extract transformed and informative features. These features are then used in the training of classification and regression models for machine state monitoring. Specifically, three classifiers (K-nearest neighbors, convolutional neural networks and support vector machines) and two regressors (support vector regression and neural network regression) were explored, in terms of their accuracy in machine state prediction. It is shown that the audio and vibration signals are sufficiently rich in information about the machine that 100% state classification accuracy could be accomplished. Data fusion was also explored, showing overall superior accuracy of data-driven regression models.     

Solid state reactions between SiC and Ir

Reactivity between SiC and Ir as a function of SiC-crystallinity was investigated by diffusion bonding technique under a vacuum and over the temperature range of 1200–1450 °C. As reaction products, various Ir-silicides and free unreacted-C were detected. Reactivity is strongly affected by the temperature and SiC-crystallinity involving a series of interactions, from “no reaction” to “massive exothermic reactions”. In particular, interfacial phenomena are more pronounced by the presence of defects and grain boundaries.Solid state reactions result in formation of fine C-precipitates rearranged in a quasi-periodic microstructure. On the contrary, clustering of highly ordered C-precipitates (C-graphitized) occurs after “massive reactions” take place.A relationship between the degree of graphitization (from 1 to multi-layers of graphene), temperature and SiC crystallinity was found by Raman spectroscopy. 2D-layering phenomenon is enhanced in polycrystalline SiC at high temperature.     

A Novel Beam Search to Improve Neural Machine Translation for English-Chinese

Neural Machine Translation (NMT) is an end-to-end learning approach for automated translation, overcoming the weaknesses of conventional phrase-based translation systems. Although NMT based systems have gained their popularity in commercial translation applications, there is still plenty of room for improvement. Being the most popular search algorithm in NMT, beam search is vital to the translation result. However, traditional beam search can produce duplicate or missing translation due to its target sequence selection strategy. Aiming to alleviate this problem, this paper proposed neural machine translation improvements based on a novel beam search evaluation function. And we use reinforcement learning to train a translation evaluation system to select better candidate words for generating translations. In the experiments, we conducted extensive experiments to evaluate our methods. CASIA corpus and the 1,000,000 pairs of bilingual corpora of NiuTrans are used in our experiments. The experiment results prove that the proposed methods can effectively improve the English to Chinese translation quality.     

Active disturbance rejection based trajectory linearization control for hypersonic reentry vehicle with bounded uncertainties

This paper investigates a novel compound control scheme combined with the advantages of trajectory linearization control (TLC) and alternative active disturbance rejection control (ADRC) for hypersonic reentry vehicle (HRV) attitude tracking system with bounded uncertainties. Firstly, in order to overcome actuator saturation problem, nonlinear tracking differentiator (TD) is applied in the attitude loop to achieve fewer control consumption. Then, linear extended state observers (LESO) are constructed to estimate the uncertainties acting on the LTV system in the attitude and angular rate loop. In addition, feedback linearization (FL) based controllers are designed using estimates of uncertainties generated by LESO in each loop, which enable the tracking error for closed-loop system in the presence of large uncertainties to converge to the residual set of the origin asymptotically. Finally, the compound controllers are derived by integrating with the nominal controller for open-loop nonlinear system and FL based controller. Also, comparisons and simulation results are presented to illustrate the effectiveness of the control strategy.