构造8-参数非协调矩形板元的新方法

摆脱常规方法，广义协调元方法及双参数有限元方法等所提供的关于构造单元时形函数空间选择的限制，在基于F－E－M－Test的要求提出了一种构造8－参数非协调矩形板元的简单实用的新方法，并分析了由此法产生的单元与不完全双二次协调矩形板元的关系。     

四节点矩形平面等参非协调元的研究

内参型非协调元由于计算精度高而受到广泛重视，研究成果国丰硕，然而，由于在单元分析阶段要凝聚内部参数，耗用机时较多，本文从实用角度出发，推导了二维规则单元的有关公式，运用该单元，可省去凝聚内参过程，生成单刚的时间与协调元相差无几，但计算精度却远远高于协调元，计算实例表明，该单元的精度明显提高。     

利用校正球进行机器人结构参数识别的方法

机器人末端执行器的运动轨迹是由多个构件共同协调运动决定，构件的结构参数误差必然影响到末端执行器的位姿，所以如何识别结构参数非常重要。中提出一种利用校正球和相应的算法进行结构参数识别的方法，并在西安理工大学研制开发的FMM10-680机器人上进行了验证。     

供需双重不确定下链与链竞争的博弈分析

研究了分别由1个零售商和1个供应商构成的两条供应链之间的竞争问题,讨论了供应中断风险和需求不确定对于竞争的供应链的影响。分析了协调竞争、混合竞争、非协调竞争3种供应链结构下的最优订货量和契约参数。研究发现在一定的收益共享系数范围,供应链协调竞争成立。最后通过数值计算,分析了参数对最优订货量的影响,得到了管理启示。     

600MW机组配煤掺烧过程中满足AGC负荷响应速率的应用

机炉协调控制系统是大型火力发电机组的主控制系统，它将锅炉和汽轮发电机作为一个整体考虑来进行控制，协调并消除锅炉和汽轮机在动态特性方面的差异，使机组既能够适应电网负荷变化的需，尽最大可能发挥机组调频、调峰的能力，又能够保证机组的安全稳定经济运行。本次优化试验的目的是，针对电厂在AGC测试中负荷响应偏慢问题进行分析，通过参数优化调整，在保证机组主要运行参数控制在允许范围的前提下，尽可能的提升机组的负荷响应速率，以满足省调AGC要求。     

带滑移铰空间机械臂协调运动的复合自适应控制

讨论了载体位置不受控制的带滑移铰空间机械臂载体姿态与末端抓手协调运动的控制问题。结合系统动量守恒关系进行的系统运动学、动力学分析表明,系统协调运动的广义Jacobi矩阵及系统的动力学方程可以表示为一组惯性参数的线性函数。以此为基础,对于系统中存在未知惯性参数的情况,设计了载体姿态与末端抓手惯性空间期望轨迹协调运动的自适应控制方案。仿真运算证实了方法的有效性。     

RS-QD联合契约对三级供应链的协调

研究了随机市场需求下由制造商、分销商和零售商组成的三级供应链的协调问题。针对供应链系统的全局协调,得出了系统的最优订购决策;设计了一种RS-QD联合契约协调机制,即在三级供应链中的两个交易过程中分别采取收益共享契约机制和数量折扣契约机制,包括(w,φ,w(q))和(w(q),w,φ)两种形式。证明了通过制定合理的契约参数能够实现三级供应链系统的协调。通过契约参数的合理选择可以实现各企业的双赢,从而有助于改善企业在供应链中的行为决策能力和市场竞争能力,在合理的范围内契约参数的大小与企业的讨价还价能力有关。通过算例验证了RS-QD联合契约机制的有效性。     

具有风险偏好的供应链收入共享契约协调模型

针对一个由风险中性供应商和具有风险偏好的零售商构成的两级供应链系统,建立了由悲观系数和风险厌恶程度两个风险参数描述的基于均值-CVaR决策准则的供应链收入共享契约模型。推导了不同风险偏好(风险厌恶、风险中性和风险喜好)下的零售商最优订货量,分析了不同风险偏好参数下的零售商订货变化情况,给出了基于收入共享契约的最佳协调机制,并讨论了各成员运作策略和绩效随系统参数的变化情况。最后,通过数值计算验证了收入共享契约的有效性。结果表明,收入共享契约不仅能够协调风险中性条件下的供应链,对于考虑不同风险偏好态度的供应链同样能够实现完全协调。与风险中性情况不同,考虑风险偏好下的供应链成员利润将受契约参数和风险参数两方面影响。     

含纯弯场的平面四结点矩形广义协调膜元

本文以点移场（３个刚体位移场，３个常应变场，２个纯弯场）作为单元内插值函数的基底，并通过组合型点协调条件直接求得广义位移参数由结点位移表示的显式关系式，从而避免了大量的矩阵求逆运算，提高了计算的效率。     

数量折扣契约对三阶层供应链的协调

研究了数量折扣契约对三阶层供应链的协调问题.首先针对供应链系统的全局协调.得出了契约参数以及最优订购量;引入利润分配系数,得出实现供应链完美协调的条件.通过数值实验得出如下结论:三阶层供应链的数量折扣契约下,制造商和零售商的批发价格不仅与各自的利润分配系数相关.而且随着订购量的变化而变化;实现全局协调的基础上,系统的完美协调取决于利润分配系数的取值.     

钢铁企业CIMS生产计划管理的递阶体系

钢铁生产的复杂性决定了钢铁企业计划管理的复杂性，因而有必要采用大系统分解协调理论对钢铁生产计划系统进行时间分解与空间分解，建立生产计划的递阶体系。本文提出了ＣＩＭＳ下钢铁生产计划管理的递阶体系结构模式，研究了对计划系统进行空间分解与时间分解的原则。     

USE OF COUNTERPROPAGATION NEURAL NETWORKS TO ENHANCE THE CONCURRENT SUBSPACE OPTIMIZATION STRATEGY

The paper explores the use of artificial neural networks in a concurrent optimization strategy that derives from a decomposition based approach to design of large-scale engineering systems. These problems are characterized by complex couplings that render parametric design methods inappropriate as solution tools. Decomposition methods reduce the large dimensionality problem into a sequence of smaller, more tractable optimization problems, each with a smaller set of design variables and constraints. The decomposed subproblems are rarely decoupled completely, and design changes in one subproblem have a profound influence on changes in another subproblem. Essential components of decomposition based design methods are strategies to identify a topology for problem decomposition, and to develop coordination strategies which account for couplings among the decomposed problems. The paper examines the effectiveness of artificial neural networks as a tool to both account for the coupling, and to develop methods to coordinate the solution in the different subproblems to a converged optimal design     

Parameters Compressing in Deep Learning

With the popularity of deep learning tools in image decomposition and natural language processing, how to support and store a large number of parameters required by deep learning algorithms has become an urgent problem to be solved. These parameters are huge and can be as many as millions. At present, a feasible direction is to use the sparse representation technique to compress the parameter matrix to achieve the purpose of reducing parameters and reducing the storage pressure. These methods include matrix decomposition and tensor decomposition. To let vector take advance of the compressing performance of matrix decomposition and tensor decomposition, we use reshaping and unfolding to let vector be the input and output of Tensor-Factorized Neural Networks. We analyze how reshaping can get the best compress ratio. According to the relationship between the shape of tensor and the number of parameters, we get a lower bound of the number of parameters. We take some data sets to verify the lower bound.     

DECOMPOSITION ANALYSIS AND OPTIMIZATION OF AN AUTOMOTIVE POWERTRAIN DESIGN MODEL

Decomposition methods in mathematical programming typically apply a coordination strategy based on an identifiable structure in the problem. Decomposition analysis is a rigorous method for discovering how to (i) partition an original model so that the resulting problem structure matches the one required by a general coordination strategy, and (ii) implement the most suitable such strategy. Automated partitioning has received significant attention recently but implementation of coordination strategies based on decomposition analysis is still scarce. This article presents a complete analysis for partitioning and coordinated solution of an automotive powertrain design problem. The model offers a practical approach for accommodating control and geometry variables simultaneously. A variable complexity coordination strategy is proposed and implemented.     

New synthetic routes for quantum dots

Various methods for the synthesis of quantum dots of compound semiconductors are discussed. Emphasis is placed on methods involving the decomposition of chalcogenide-containing precursors in tri-n-octylphosphine oxide. The use of simple coordination complexes can avoid the use of pyrophoric precursors. Approaches based on melts or the use of imino-bisdichalcogeno-diphosphinates are also discussed. These routes may be suitable for the production of large quantities of quantum dots.     

基于小波多分辨率分析的时变结构参数识别研究

提出一种小波多分辨率分析的最优尺度选择方法,并将其应用于结构时变物理参数的识别。首先,从函数空间剖分的角度引入WMRA对时变参数进行多分辨率近似展开,将振动微分方程转化成多元线性回归方程,根据时变参数的频率范围及采样频率、线性方程组的个数等确定分解层数取值范围;其次,利用赤池信息准则（AIC）寻求最优分解尺度,为增强数据的稳定性,采用正交最小二乘算法（OLS）代替传统最小二乘算法（LS）对模型中小波系数进行估计并重构时变参数;最后,分别以突变和连续变化的两种时变参数的5层剪切框架模型进行数值模拟。分析结果表明:在预先确立的分解尺度范围内,采用无噪声干扰的响应信号进行识别时,识别精度随着分解尺度的增加而增加;采用噪声干扰的测量信号进行识别时,识别精度与分解尺度的增加无必然联系;通过选择适当的分解尺度,能够准确识别时变参数、提高方法的计算效率并保证很好的抗噪性能。     

The preparation of several new ternary oxides of osmium

Several ternary oxides of osmium were prepared by the thermal decomposition of hydroxide intermediates. X-Ray powder diffraction data, refined cell parameters, and formation and decomposition temperatures for each compound are given.     

Tissue characterization using the continuous wavelet transform. Part I: Decomposition method

In this paper, a novel decomposition of the RF ultrasound signal into its coherent and diffused components is proposed. This decomposition is based on thresholding the energy of the continuous wavelet transform of the RF signal using appropriate wavelets. The two components are modeled separately, and the model parameters are estimated. Previous work (Cohen et al. 1997) required assumptions about the periodicity of the coherent scatterers in the tissue. These assumptions are not necessary in this work. The decomposition algorithm is tested on simulated RF images. The accuracy of the estimated parameters is presented as well as the performance of the algorithm in low coherent-to-diffuse components' energy ratios (SNR)     

用快速筛选仪研究发射药的热分解

文章采用了一种新的热分析仪器——快速筛选仪(RSD),来研究两种发射药改铵铜推进剂和单基8/1推进剂的热分解过程,分析所得数据得到相应的热分解特性参数以及热动力学参数,发现改铵铜的起始分解温度在150~168℃左右,而8/1在175~185℃左右。8/1单基药活化能E=238.30 kJ/mol,指前因子A=3.7×1017s-1;改铵铜推进剂活化能E=216.67 kJ/mol,指前因子A=2.1×1017s-1。     

Synthesis, structural investigation, thermal decomposition mechanism and sensitivity properties of an energetic compound [Cd(DAT)(6)](ClO(4))(2) (DAT=1,5-diaminotetrazole)

An energetic coordination compound [Cd(DAT)(6)](ClO(4))(2) has been synthesized by using 1,5-diaminotetrazole (DAT) as ligand and its structure has been characterized by applying X-ray single crystal diffraction, elemental analysis and FT-IR spectroscopy. The central cadmium(II) cation is coordinated by six N atoms from six DAT molecules to form a six-coordinated and distorted octahedral structure. Di-dimension layer structure was formed and the layers were linked together by the extensive intermolecular hydrogen bonds between DAT ligands and ClO(4)(-) anions. Thermal decomposition mechanism of the title compound was predicted based on DSC, TG-DTG and FT-IR analyses results. The kinetic parameters of the first exothermic process of the title compound were studied by applying the Kissinger's and Ozawa-Doyle's methods. Sensitivity tests reveal that the title compound has sensitive nature.