聚铝碳硅烷的流变性和纺丝性研究

采用单孔纺丝装置对不同铝含量的聚铝碳硅烷(PACS)的流变性和流变性进行研究.结果表明:随着温度升高,PACS熔体的流体特性逐渐接近牛顿流体;PACS熔体粘度对温度有强烈的依赖性,其软化点在190℃～220℃范围时,其粘流活化能在190～260kJ/mol之间;当PACS的粘度在100Pa·s左右时可纺性好;铝含量对PACS的流变性能和可纺性有重要的影响,随着铝含量的增加,PACS熔体的粘度增大,因而PACS的纺丝温度更高,可纺性变差.     

光学阵列器件的慢刀伺服车削加工技术

慢刀伺服技术是相对于快刀伺服提出的方法.采用C轴、X轴、Z轴联动的方法在极坐标或圆柱坐标内进行加工.光学阵列如微透镜阵列、微反射镜阵列在高速数据、声音和视频信号传输中具有重要作用.将光学阵列看作一个自由曲面,使用慢刀伺服车削技术一次加工成形,可以解决传统加工中将光学阵列分块加工后拼装和调整的困难.但是由于光学阵列表面形状复杂,其表面法线的突变可能会使机床运动超出伺服轴执行能力.根据慢刀伺服加工技术的特点,建立了伺服轴执行能力限制曲线,研究了不同刀具半径补偿方式对加工的影响.实验结果表明,根据机床伺服轴执,厅能力合理选择刀具半径补偿方式可实现微光学阵列器件高精度加工.     

一款0.18μm CMOS辐射加固差分压控振荡器

基于对称负载压控振荡器(VCO)的单粒子瞬变(SET)失效机理,应用设计加固(RHBD)技术分别改进了偏置电路和环形振荡器,设计和实现了一款0.18μm CMOS辐射加固差分VCO.模拟结果表明:加固VCO的SET敏感性大幅降低,同时还降低了抖动对于电源噪声的敏感性.虽然电路结构变化会导致频率下降,但可以通过调整电路尺寸而解决.此外,加固VCO面积开销有所降低,优于其他加固方法.     

基于矩阵运算的光学零件磁流变加工的驻留时间算法

提出了一种光学零件磁流变加工的驻留时间计算方法.该算法以矩阵运算为基础,首先确定工件上各个控制节点的高度余量,并将磁流变抛光模对各控制节点的材料去除能力体现到去除矩阵中,然后利用非负最小二乘法求解驻留时间向量.采用该算法在自行研制的磁流变抛光机床上进行抛光实验,经过2次迭代加工后,有效口径为145mm的球面镜P-V值达到40.5nm(约为λ/15),RMS值达到5nm(约为λ/125),表面粗糙度Ra值达到0.57nm.     

有色Petri网在车辆综电系统总线建模中的应用

针对运用解析法对车辆电子系统进行建模分析困难这一问题,运用CPNs构建综合电子系统模型.提出了系统的建模分析方法,运用CPN_Tools进行建模,得出了某型车辆总线的系统模型.实验结果证明,基于CPNs的车辆综合电子系统总线建模的正确性与可行性.     

Influence of active constrained layer damping on the coupled vibration response of functionally graded magneto-electro-elastic plates with skewed edges

This article makes the first attempt in assessing the influence of active constrained layer damping (ACLD) treatment towards precise control of frequency responses of functionally graded skew-magneto-electro-elastic (FGSMEE) plates by employing finite element methods. The materials are functionally graded across the thickness of the plate in terms of modest power-law distributions. The principal equations of motion of FGSMEE are derived via Hamilton’s principle and solved using condensation technique. The effect of ACLD patches are modelled by following the complex modulus approach (CMA). Additionally, distinctive emphasis is laid to evaluate the influence of geometrical skewness on the attenuation capabilities of the plate. The accuracy of the current analysis is corroborated with comparison of previous researches of similar kind. Additionally, a complete parametric study is directed to understand the combined impacts of various factors like coupling fields, patch location, fiber orientation of piezoelectric patch in association with skew angle and power-law index.     

Research on simultaneous localization and mapping for AUV by an improved method: Variance reduction FastSLAM with simulated annealing

At present, simultaneous localization and mapping (SLAM) for an autonomous underwater vehicle (AUV) is a research hotspot. Aiming at the problem of non-linear model and non-Gaussian noise in AUV motion, an improved method of variance reduction fast simultaneous localization and mapping (FastSLAM) with simulated annealing is proposed to solve the problems of particle degradation, particle depletion and particle loss in traditional FastSLAM, which lead to the reduction of AUV location estimation accuracy. The adaptive exponential fading factor is generated by the anneal function of simulated annealing algorithm to improve the effective particle number and replace resampling. By increasing the weight of small particles and decreasing the weight of large particles, the variance of particle weight can be reduced, the number of effective particles can be increased, and the accuracy of AUV location and feature location estimation can be improved to some extent by retaining more information carried by particles. The experimental results based on trial data show that the proposed simulated annealing variance reduction FastSLAM method avoids particle degradation, maintains the diversity of particles, weakened the degeneracy and improves the accuracy and stability of AUV navigation and localization system.     

MABAC method for multiple attribute group decision making under q-rung orthopair fuzzy environment

As the generalization of intuitionistic fuzzy set (IFS) and Pythagorean fuzzy set (PFS), the q-rung orthopair fuzzy set (q-ROFS) has emerged as a more meaningful and effective tool to solve multiple attribute group decision making (MAGDM) problems in management and scientific domains. The MABAC (multi-attributive border approximation area comparison) model, which handles the complex and uncertain decision making issues by computing the distance between each alternative and the bored approximation area (BAA), has been investigated by an increasing number of researchers more recent years. In our article, consider the conventional MABAC model and some fundamental theories of q-rung orthopair fuzzy set (q-ROFS), we shall introduce the q-rung orthopair fuzzy MABAC model to solve MADM problems. at first, we briefly review some basic theories related to q-ROFS and conventional MABAC model. Furthermore, the q-rung orthopair fuzzy MABAC model is built and the decision making steps are described. In the end, An actual MADM application has been given to testify this new model and some comparisons between this novel MABAC model and two q-ROFNs aggregation operators are provided to further demonstrate the merits of the q-rung orthopair fuzzy MABAC model.     

Exact analysis of (R,s, S) inventory control systems with lost sales and zero lead time

We study an (R, s, S) inventory control policy with stochastic demand, lost sales, zero lead‐time and a target service level to be satisfied. The system is modeled as a discrete time Markov chain for which we present a novel approach to derive exact closed‐form solutions for the limiting distribution of the on‐hand inventory level at the end of a review period, given the reorder level (s) and order‐up‐to level (S). We then establish a relationship between the limiting distributions for adjacent values of the reorder point that is used in an efficient recursive algorithm to determine the optimal parameter values of the (R, s, S) replenishment policy. The algorithm is easy to implement and entails less effort than solving the steady‐state equations for the corresponding Markov model. Point‐of‐use hospital inventory systems share the essential characteristics of the inventory system we model, and a case study using real data from such a system shows that with our approach, optimal policies with significant savings in inventory management effort are easily obtained for a large family of items.     

DEA models for two‐stage processes: Game approach and efficiency decomposition

Data envelopment analysis (DEA) is a method for measuring the efficiency of peer decision making units (DMUs). This tool has been utilized by a number of authors to examine two‐stage processes, where all the outputs from the first stage are the only inputs to the second stage. The current article examines and extends these models using game theory concepts. The resulting models are linear, and imply an efficiency decomposition where the overall efficiency of the two‐stage process is a product of the efficiencies of the two individual stages. When there is only one intermediate measure connecting the two stages, both the noncooperative and centralized models yield the same results as applying the standard DEA model to the two stages separately. As a result, the efficiency decomposition is unique. While the noncooperative approach yields a unique efficiency decomposition under multiple intermediate measures, the centralized approach is likely to yield multiple decompositions. Models are developed to test whether the efficiency decomposition arising from the centralized approach is unique. The relations among the noncooperative, centralized, and standard DEA approaches are investigated. Two real world data sets and a randomly generated data set are used to demonstrate the models and verify our findings. © 2008 Wiley Periodicals, Inc. Naval Research Logistics, 2008