充液挠性航天器俯仰运动 1:1:1 内共振动力学分析

采用已推导的俯仰运动矩形贮箱受控刚-液-弹耦合系统在外力矩作用下的耦合动力 学模型,在刚体上加入控制项,详细分析了系统固有频率的精确解与近似解. 应用多尺 度法对耦合系统1:1:1内共振进行解析分析,与数值解比较验证解析解的正确性. 通过近 似解析分析得到刚-液-弹之间的耦合作用机理：1) 液深影响整个系统的软硬特性,当液体发 生软硬特性转化时,处于液体原多值频率区域的刚体和弹性体幅频曲线分支峰值会减弱,且 具有相同的特性转化趋势;处于液体新多值频率区域的刚体和弹性体幅频曲线分支峰值会增 强,且具有相反的特性转化趋势. 2) 刚体和弹性体幅频曲线的峰值均在以受控刚体和弹性体 为主的耦合系统固有频率处,以液体为主固有频率激励,刚体和弹性体振幅较小.     

PTC: Full and Drift Particle Orbit Tracing Code for α Particles in Tokamak Plasmas

Fusion born α particle confinement is one of the most important issues in burning plasmas,such as ITER and CFETR.However,it is extremely complex due to the nonequilibrium characteristics,and multiple temporal and spatial scales coupling with background plasma.A numerical code using particle orbit tracing method(PTC)has been developed to study energetic particle confinement in tokamak plasmas.Both full orbit and drift orbit solvers are implemented to analyze the Larmor radius effects on α particle confinement.The elastic collisions between alpha particles and thermal plasma are calculated by a Monte Carlo method.A triangle mesh in poloidal section is generated for electromagnetic fields expression.Benchmark between PTC and ORBIT has been accomplished for verification.For CFETR burning plasmas,PTC code is used for α particle source and slowing down process calculation in 2D equilibrium.In future work,3D field like toroidal field ripples,Alfven and magnetohydrodynamics instabilities perturbation inducing α particle transport will be analyzed.     

无压浸渗SiC/Al复合材料的摩擦磨损性能研究

采用无压浸渗法制备不同碳化硅粒度和体积分数的SiC/Al复合材料,利用销-盘摩擦磨损试验机考察了碳化硅的粒度和体积分数等对SiC/Al复合材料干摩擦磨损性能的影响,采用扫描电子显微镜观察磨损表面形貌并分析其磨损机理.结果表明,SiC/Al复合材料的磨损率随碳化硅体积分数增加而降低.与灰铸铁配副时,材料的摩擦系数与磨损率明显依赖于碳化硅粒度,二者均随碳化硅粒度增加而降低.复合材料的磨损机制以碳化硅颗粒的碎裂、脱落和表面犁沟为主要特征.     

一道2020年全国大学生数学竞赛题的多种推广

对最近一道2020年全国大学生数学竞赛题从多个角度进行推广,由此不但丰富了课堂例题,拓展了教学内容,而且激发了同学们的学习热情,促进了同学们创新思维能力的提升.     

国有商业银行企业不良贷款的主因子分析

论文首先在银行企业不良贷款成因的研究成果进行回顾梳理基础上,从探究现行发展环境下,影响企业不良贷款的主要原因的角度,通过对国有商业银行贷款部的中高层访谈问卷调查,运用探索性因子分析模型,对不良贷款主成因进行萃取和诠释,最后构建银行业不良贷款的成因层次构面,以支持国有商业银行授信决策之依据。     

任意信源随机和的一类随机Shannon-McMillan定理

采用构造相容分布与非负上鞅的方法研究任意信源随机和相对熵密度的强极限定理,并由此得出若干任意信源,m阶马氏信源,无记忆信源的随机Shannon-Mcmillan定理.将已有的关于离散信源的结果加以推广.     

Surface-assembled highly flexible Na_3(VOPO_4)_2F nanocube cathode for high-rate binder-free Na-ion batteries

Flexible Na-ion storage cathodes are still very few due to the challenge in achieving both reliable mechanical flexibility and excellent electrochemical performances.Herein,a new type of flexible Na_3(VOPO_4)_2F cathode with nanocubes tightly assembled on carbon cloth is fabricated by a facile solvothe rmal method for the first time.The cathode is able to exhibit superior rate capability and stable cycling performa nce up to 1000 cycles,due to the surface-assembling of crystalline nanocubes on carbon fibers.In addition,it shows good mechanical flexibility,nearly no capacity decay is observed after continuous bending of 500 times.With this novel cathode and a directly-grown Na_2Ti_2O_5 anode,a fully binde r-free Na-ion battery is assembled.It can deliver a high wo rking voltage and increased gravimetric energy/power densities(maximum values:220.2 Wh/kg;5674,7 W/kg),and can power a LED indicator at bending angles fro m 0° to 180°.     

不同排烟方式HAT循环性能对比

对三种不同排烟方式HAT循环的模拟分析表明,在总压比一定时,排烟方式对比功影响很小,采用引风机排烟的HAT循环比直接排烟及回热法排娴的电效率最多分别高出1和1.5个百分点,最高效率时的引风机压比在1.5～1.6左右.引风机排烟带来的压缩耗功下降和湿化器出水温度降低是效率升高的主要原因.水回收率相对偏低,且性能受烟气冷凝温度和引风机压比影响较大.     

Domain Adaptation with Data Uncertainty Measure Based on Evidence Theory

Domain adaptation aims to learn a classifier for a target domain task by using related labeled data from the source domain. Because source domain data and target domain task may be mismatched, there is an uncertainty of source domain data with respect to the target domain task. Ignoring the uncertainty may lead to models with unreliable and suboptimal classification results for the target domain task. However, most previous works focus on reducing the gap in data distribution between the source and target domains. They do not consider the uncertainty of source domain data about the target domain task and cannot apply the uncertainty to learn an adaptive classifier. Aimed at this problem, we revisit the domain adaptation from source domain data uncertainty based on evidence theory and thereby devise an adaptive classifier with the uncertainty measure. Based on evidence theory, we first design an evidence net to estimate the uncertainty of source domain data about the target domain task. Second, we design a general loss function with the uncertainty measure for the adaptive classifier and extend the loss function to support vector machine. Finally, numerical experiments on simulation datasets and real-world applications are given to comprehensively demonstrate the effectiveness of the adaptive classifier with the uncertainty measure.     

Intelligent Fault Diagnosis of Industrial Robot Based on Multiclass Mahalanobis-Taguchi System for Imbalanced Data

One of the biggest challenges for the fault diagnosis research of industrial robots is that the normal data is far more than the fault data; that is, the data is imbalanced. The traditional diagnosis approaches of industrial robots are more biased toward the majority categories, which makes the diagnosis accuracy of the minority categories decrease. To solve the imbalanced problem, the traditional algorithm is improved by using cost-sensitive learning, single-class learning and other approaches. However, these algorithms also have a series of problems. For instance, it is difficult to estimate the true misclassification cost, overfitting, and long computation time. Therefore, a fault diagnosis approach for industrial robots, based on the Multiclass Mahalanobis-Taguchi system (MMTS), is proposed in this article. It can be classified the categories by measuring the deviation degree from the sample to the reference space, which is more suitable for classifying imbalanced data. The accuracy, G-mean and F-measure are used to verify the effectiveness of the proposed approach on an industrial robot platform. The experimental results show that the proposed approach’s accuracy, F-measure and G-mean improves by an average of 20.74%, 12.85% and 21.68%, compared with the other five traditional approaches when the imbalance ratio is 9. With the increase in the imbalance ratio, the proposed approach has better stability than the traditional algorithms.