La对铜合金的电弧侵蚀行为和抗氧化性能的影响（英文）

研究稀土元素La对铜合金的电弧侵蚀行为和氧化行为的影响。结果表明:稀土元素La的加入有利于铜合金抗氧化性能和电弧侵蚀性能的改善,并有效地降低了接触电阻和温升。通过对CuLa合金的高温抗氧化性能机理分析表明,富集在晶界的La元素形成La_2O_3或者CuLa合金,起到了界面包裹的作用,从而抑制了铜的进一步氧化。通过热力学计算可知,CuLa合金中的La择优氧化形成La_2O_3,对铜基体起到了保护作用。动力学分析表明,CuLa合金的激活能较纯铜的高,说明其抗氧化性能更好。

香烟对阻止黄曲霉素B_1诱致小白鼠癌前病变影响的肝细胞核内DNA定量研究

本文将津白2纯系小白鼠60只.随机等数分三组:AFB_1组、AFB_1+香烟熏组和对照组。AFB_1溶于DMSO.5μg/每日/每只量拌于饲料投食,熏烟组以30g/日烟丝熏烟,经半年实验,肝H.E常规切片.发现两实验组.肝细胞有不典型增生,程度难确定,电镜下.肝细胞主要为变质及轻度胶原增生。但肝印片置Leitz MPV Ⅲ型测定肝细胞核DNA含量,发现三组均属多峰型,对照组与AFB_+烟熏组主峰相当4C处.AFB_1组则在8C处.两实验组间从多倍体与异倍体数量看,则有显著差别(P<0.05).证实AFB_1+烟熏组具有阻止AFB_1诱致小白鼠肝癌变的作用。

基于氧传感器信号的用于研究空气/燃料比率变化的统计方法

给出了火花点火式发动机排气氧传感器(EGO)输出信号的实验结果。实验中采用V6、3.8 L、BUICK发动机且每个气缸中安装有一个氧传感器,以研究影响发动机消耗燃料的因素。应用LabView数据采集装置记录单个气缸废气以及主流尾气氧传感器的输出电压信号。对来自6个气缸变量的平均值采用统计的方法进行处理后,并与主流的EGO电压进行比较,确定了产生系统误差的因素。对左右两侧气缸信号平均值的差别进行比较发现,采用此种排气管结构的气缸中空气—燃料混合气平均值存在一些明显差别。根据数据和图表解释了统计的结果。研究表明,V字形排列的发动机两侧的气缸的空气和燃料混合气是不同的;在低速、高负荷和高辛烷燃料的情况下,右侧气缸具有比较稀的混合气;而在某些情况下两侧气缸具有相同的混合气。基于统计估计的方法,提出了一个可以用于估计V字形排列发动机左右两侧气缸中空气—燃料混合气的简单模型。此方法还可以应用于分析进气管和排气管的缺陷。

Teaching the User By Learning From the User:Personalizing Movement Control in Physical Human-robot Interaction

This paper proposes a novel approach for physical human-robot interactions(pHRI), where a robot provides guidance forces to a user based on the user performance. This framework tunes the forces in regards to behavior of each user in coping with different tasks, where lower performance results in higher intervention from the robot. This personalized physical human-robot interaction(p2HRI) method incorporates adaptive modeling of the interaction between the human and the robot as well as learning from demonstration(LfD) techniques to adapt to the users' performance. This approach is based on model predictive control where the system optimizes the rendered forces by predicting the performance of the user. Moreover, continuous learning of the user behavior is added so that the models and personalized considerations are updated based on the change of user performance over time. Applying this framework to a field such as haptic guidance for skill improvement, allows a more personalized learning experience where the interaction between the robot as the intelligent tutor and the student as the user,is better adjusted based on the skill level of the individual and their gradual improvement. The results suggest that the precision of the model of the interaction is improved using this proposed method,and the addition of the considered personalized factors to a more adaptive strategy for rendering of guidance forces.

Neural network prediction of the shunt current in resistance spot welding

An error back propagation （BP） neural network prediction model was established for the shunt current compensation in series resistance spot welding. The input variables for the neural network consist of the resistivity of the material, the thickness of workpiece and the spot spacing, and the shunt rate is outputted. A simplified calculation for the shunt rate was presented based on the feature of the constant-current resistance spot welding and the variation of the resistance in resistance spot welding process, and then the data generated by simplified calculation were used to train and adjust the neural network model. The neural network model proposed was used to predict the shunt rate in the spot welding of 20# mlid steel （in Chinese classification） （in 2. 0 mm thickness） and 10# mild steel （in 1.5 mm and 1.0 mm thickness）. The maximum relative prediction errors are, respectively, 2. 83%, 1.77% and 3.67%. Shunt current compensation experiments were peoCormed based on the neural network prediction model proposed to check the diameter difference of nuggets. Experimental results show that maximum nugget diameter deviation is less than 4% for both 10# and 20# mlid steels with spot spacing of 30 mm and 50 mm.

Transfer of Global Measures of Dependence into Cumulative Local

We explore an idea of transferring some classic measures of global dependence between random variables Χ1, Χ2, L, Χn into cumulative measures of dependence relative at any point?(χ1, χ2, L, χn)?in the sample space. It allows studying the behavior of these measures throughout the sample space, and better understanding and use of dependence. Some examples on popular copula distributions are also provided.

Development of Fuel Economy Gear Oil Technology

Vehicle fuel economy will continue to increase in importance as world vehicle production grows and fuel supplies become more limited year by year.As OEMs strive to produce cars and trucks with greater fuel efficiency and extended durability,additive technology developers are increasingly being asked to contribute to these goals from the lubricant side.Axle inefficiency can account for as much as 10% of the overall losses in an automotive driveline so improvements in axle efficiency can contribute greatly to improving vehicle fuel economy.For good durability,low axle oil operating temperatures are also needed to minimize oxidative and thermal degradation of the oil,reduce deposits and sludge formation,and extend oil drain intervals.To develop gear oils that can increase axle efficiency significantly while maintaining stable operating temperatures requires rig tests that are fast,precise and reproducible.This paper documents the development of a new axle test rig and test procedures and presents test results on several gear oils.The test results show the contributions of base oil viscosity,base oil chemistry,and additive chemistry on the fuel economy and temperature of the various oils.Having a dependable tool is enabling the development of new fuel-efficient and durable gear oil technology.

In Vitro Immersion Behavior of Cold Sprayed Hydroxyapatite/Titanium Composite Coatings

In previous study, dense and homogenous 20wt% HAP/Ti composite coatings were successfully deposited on Ti substrates by cold gas dynamic spray technique. The results revealed that the phase composition of the HAP in the deposit is identical to that of the precursor powder and the bonding strength of the deposit is comparable/better to that of the plasma sprayed HAP. A relatively higher corrosion current of HAP/Ti composite than that of pure Ti coating in simulated body fluid indicates a good bioactivity for composite coating. In the present study, in vitro immersion test is carried out for various period of time and the formation of apatite layer on surface of composite coating proves the good bioactivity of the composite coating further. The cold sprayed HAP/Ti composite can be anticipated to be a promising load-bearing implant material for biomedical applications.

Synthesis, Characterization and Performance Evaluation of an Advanced Solid Electrolyte and Air Cathode for Rechargeable Lithium-Air Batteries

Synthesis and characterization of a tri-layered solid electrolyte and oxygen permeable solid air cathode for lithium-air battery cells were carried out in this investigation. Detailed fabrication procedures for solid electrolyte, air cathode and real-world lithium-air battery cell are described. Materials characterizations were performed through FTIR and TGA measurement. Based on the experimental four-probe conductivity measurement, it was found that the tri-layered solid electrolyte has a very high conductivity at room temperature, 23。C, and it can be reached up to 6 times higher at 100。C. Fabrication of real-world lithium-air button cells was performed using the synthesized tri-layered solid electrolyte, an oxygen permeable air cathode, and a metallic lithium anode. The lithium-air button cells were tested under dry air with 0.1 mA - 0.2 mA discharge/ charge current at elevated temperatures. Experimental results showed that the lithium-air cell performance is very sensitive to the oxygen concentration in the air cathode. The experimental results also revealed that the cell resistance was very large at room temperature but decreased rapidly with increasing temperatures. It was found that the cell resistance was the prime cause to show any significant discharge capacity at room temperature. Experimental results suggested that the lack of robust interfacial contact among solid electrolyte, air cathode and lithium metal anode were the primary factors for the cell’s high internal resistances. It was also found that once the cell internal resistance issues were resolved, the discharge curve of the battery cell was much smoother and the cell was able to discharge at above 2.0 V for up to 40 hours. It indicated that in order to have better performing lithium-air battery cell, interfacial contact resistances issue must have to be resolved very efficiently.

Influence of AC Voltage on the Positive DC Corona Current Pulses in a Wire-cylinder Gap

In the development of hybrid HVDC and HVAC transmission lines,the study of radio interference is an important issue.Positive corona current pulses from high voltage transmission lines are the main source of radio interference.In this paper,the design of a wire-cylinder gap electrode system is presented to study the influence of AC voltage on the characteristics of positive corona current pulses.The study shows that the mode of the current pulses is different from that of either DC or AC corona discharge.Waveform parameters of the pulses,such as rise time,half wave time,duration time,repetition rates,average amplitude,and time intervals of secondary pulses are all statistically analyzed in this study.The empirical formulas for the repetition rates with different AC voltages are presented.A theoretical explanation based on an ion cloud model is given to reveal the mechanism behind the influence of AC voltage on positive corona discharge.The experimental results could provide some references for the prediction of radio interference from hybrid AC/DC transmission lines.

Comparison of the topologies for a hybrid energy-storage system of electric vehicles via a novel optimization method

The combination of batteries and ultracapacitors has become an effective solution to satisfy the requirements of high power density and high energy density for the energy-storage system of electric vehicles.Three aspects of such combination efforts were considered for evaluating the four types of hybrid energy-storage system(HESS)topologies.First,a novel optimization framework was proposed and implemented to optimize the voltage level of a battery pack and an ultracapacitor pack for the four types of HESS topologies.During the optimization process,the dynamic programming(DP)algorithm was iteratively applied to determine the optimal control actions.The simulation results with DP were used to evaluate the energy efficiency of different HESS topologies at different voltage levels.Second,the optimized voltage level of the battery and ultracapacitor in each topology indicates that a higher voltage level usually results in a better system performance.The simulation results also illustrate that the optimized rated voltage level of the battery pack is approximately 499.5 V,while for the ultracapacitor pack,the optimized voltage level is at its maximum allowed value.Note that the constraint of the battery voltage is initialized at200–600 V.Third,the control rules for different HESS topologies were obtained through the systematic analysis of the simulation results.In addition,advantages and disadvantages of the four topologies were summarized through evaluation of the efficiency and operating currents of the batteries and the ultracapacitor.

Two-stage aging trajectory prediction of LFP lithium-ion battery based on transfer learning with the cycle life prediction

With the wide application of the LFP lithium-ion batteries,more attention is paid to the battery life and future aging behaviors as the safety and performance of the battery are guaranteed by accurate battery aging monitoring.In recent years,long-term aging trajectory prediction of the lithium-ion battery is always a challenge due to its complex nonlinear aging behaviors especially the aging behaviors in the two aging stages are quite different when the battery experiences the two-stage aging process under fast-charging conditions.Thus,it is harder to achieve accurate long-term aging trajectory prediction of the LFP lithium-ion batteries on the condition of the two-stage aging process.To address it,a novel transfer learning strategy combined with the cycle life prediction technology is presented in this paper.Specifically,a new cycle life prediction method is proposed based on feature extraction and deep learning technology and achieves accurate cycle life prediction.The transfer learning is started by developing a base aging model offline to learn the information of the two-stage aging process.Then,taking the predicted cycle life as its prior information,the Bayesian model migration technology is employed to predict the aging trajectory accurately,and the uncertainty of the aging trajectory is quantified.Two batches of the battery datasets are used for performance evaluation and comparison with two benchmarks.It is novel to combine the cycle life prediction and transfer learning technique to achieve accurate two-stage aging trajectory prediction with only a few data available(first 30%).