Hybrid and multi-field variational principles for geometrically exact three-dimensional beams

This paper addresses the development of several alternative novel hybrid/multi-field variational formulations of the geometrically exact three-dimensional elastostatic beam boundary-value problem. In the framework of the complementary energy-based formulations, a Legendre transformation is used to introduce the complementary energy density in the variational statements as a function of stresses only. The corresponding variational principles are shown to feature stationarity within the framework of the boundary-value problem. Both weak and linearized weak forms of the principles are presented. The main features of the principles are highlighted, giving special emphasis to their relationships from both theoretical and computational standpoints.     

火试金法配料过程自动化的探索和应用

火试金法中配料方式采用的是传统的人工配料,针对人工配料方式的不足,设计了一款自动化程度较高的自动配料机,通过对配料机的准确性、效率及可靠性实验,结果表明配料机检测称量误差在±0.2 g以内,效率为人工配料的2~3倍,检测结果与人工配料的相一致。与此同时,应用此设备改善了工作环境,避免了人为失误造成的检测质量问题,降低了复检率,为企业降低了成本,提高了效益,在业内具有广泛应用前景。     

弹塑性摩擦接触问题形状设计灵敏度分析

提出了一种计算二维有限变形弹塑性摩擦接触问题形状设计灵敏度的算法. 采用主动集策略和mortar方法处理接触边线上的约束条件. 在mortar接触边线的切线和法线方向上采用相同的名义罚函数,提出基于名义罚函数的移动摩擦锥算法来正则化接触约束条件,发展了一种新的二维多体有限变形摩擦接触算法. 在此基础上, 通过将离散形式的摩擦接触问题控制方程对形状设计变量微分,得到了该路径相关问题的直接微分法解析设计灵敏度计算格式, 其节点位移灵敏度方程在每个增量步不用迭代、直接求解. 与国际上现有的二维多体有限变形摩擦接触问题的解析设计灵敏度算法相比,本算法不需分解为法向和切向推导,表达式较简洁,便于编程实现. 数值算例验证了算法的精度和有效性.      

遗传算法求解约束非线性规划及Matlab实现

对于约束非线性规划问题,传统的方法:可行方向法、惩罚函数法计算烦琐且精度不高.用新兴的遗传算法来解决约束非线性规划,核心是惩罚函数的构造.以前的惩罚函数遗传算法有的精度较低,有的过于复杂.本文在两个定义的基础上构造了新的惩罚函数,并在新的惩罚函数的基础上,提出了一种解决约束非线性最优化问题的方法.通过两个例子应用Matlab说明了这个算法的可行性.     

旅行商问题的基因整合算法

本文针对旅行商问题提出了基因整合算法。它是通过设置扰动矩阵构造与原商问题等价的近似问题，使用最优罚函数选择回路分枝得到一系列局部最优回路，从中提取频度高的分技——基因进行整合，得到更优的回路。该算法计算量小，对大规模问题计算效果显著。利用该算法对CHN144问题给出了目前最件的结果。     

再生核空间W_2~1[a,b]中线性微分方程组初值问题的数值求解

再生核方法在某些方程(组)解的表示和逼近中具有独特的优势,用一种新的再生核讨论线性微分方程组初值问题解的精确表示与近似计算.较之以往的同类文章,对一些重要定理进行了更简单有效的证明.另外本文的再生核由于其结构简单,易于算法实现.最后的算例充分的显示了基于的再生核方法的有效性.     

一个改进的SQP型算法

本文建立非线性等式和不等式约束规划问题的一个序列二次规划(SQP)型算法.算法的每次迭代只需解一个确实可解的二次规划，然后对其解进行简单的显式校正，便可产生关于罚函数是下降的搜索方向，克服Maratos效应.在适当的假设条件下，还论证了算法的全局收敛性和超级收敛性.     

On a class of Riemann surfaces

It is considered the class of Riemann surfaces with dimT1 = 0, where T1 is a subclass of exact harmonic forms which is one of the factors in the orthogonal decomposition of the spaceΩH of harmonic forms of the surface, namely The surfaces in the class OHD and the class of planar surfaces satisfy dimT1 = 0. A.Pfluger posed the question whether there might exist other surfaces outside those two classes. Here it is shown that in the case of finite genus g, we should look for a surface S with dimT1 = 0 among the surfaces of the form Sg\K , where Sg is a closed surface of genus g and K a compact set of positive harmonic measure with perfect components and very irregular boundary.     

Speeding up the FMMR perfect sampling algorithm: A case study revisited

In a previous paper by the second author, two Markov chain Monte Carlo perfect sampling algorithms—one called coupling from the past (CFTP) and the other (FMMR) based on rejection sampling—are compared using as a case study the move‐to‐front (MTF) self‐organizing list chain. Here we revisit that case study and, in particular, exploit the dependence of FMMR on the user‐chosen initial state. We give a stochastic monotonicity result for the running time of FMMR applied to MTF and thus identify the initial state that gives the stochastically smallest running time; by contrast, the initial state used in the previous study gives the stochastically largest running time. By changing from worst choice to best choice of initial state we achieve remarkable speedup of FMMR for MTF; for example, we reduce the running time (as measured in Markov chain steps) from exponential in the length n of the list nearly down to n when the items in the list are requested according to a geometric distribution. For this same example, the running time for CFTP grows exponentially in n. © 2003 Wiley Periodicals, Inc. Random Struct. Alg., 2003     

初始点任意的一个非线性优化的广义梯度投影法

广义投影算法的优点是避免转轴运算。它成功地给出了线性约束问题、初始点任意的只带非线性不等式约束问题，以及利用辅助规划来处理带等式与不等式约束问题的算法．后者完满地解决了投影算法对于非线性等式约束问题的处理，但要求满足不等式约束的初始点．本文据此利用广义投影与罚函数技巧给出了一个初始点任意的等式与不等式约束问题的算法，省去了求初始解的计算，并保持了上述方法的优点，证明了算法的全局收敛性