RESEARCH ON THE CONSTRAINT MAPPING FROM FUNCTION TO ASSEMBLY

Assembly sketch is not only the visualization of abstract function, but alsothe template of detail design. Two kinds of information are needed to create assembly sketch:structure and assembly constraint. Most researches are aimed at bow to obtain Structures fromfunction, but the problem of how to obtain assembly constraint from function is ignored. Followingthe definition of assembly unit and the classification of function, a hierarchical mapping methodfrom function to assembly constraint is put forward, and the mapping method includes two steps. Thefirst step is the mapping from function to assembly semantics which is assembly expression andaccordant with engineer's design habit. The second one is the mapping from assembly semantics tobasic assembly constraints that are convenient for computer to handle. The mapping method is appliedto DDMS (design, drafting and management system) successfully.

Rheological Behaviour for Polymer Melts and Concentrated SolutionsPart Ⅱ: Material Function with Nagai Chain Constraints and Determination of Their Parameters from Flow Curves

An integral constitutive equation and a set of material functions for describing the strain history of polymer melts were formulated in terms of the Cauchy-Green and Finger tensors. A simple memory function and the dependence of ηo and τt on M3.4 were derived from the theory of non-linear viscoelasticity with constraints of entanglements for polymer melts and substituted into the Oldroye-Walters-Fredickson constitutive equation. An integral constitutive equation for polymer melts was consequently obtained. Some material functions of the constitutive equation related to certain 'test flow' are examined as follows : (1) simple steady shear flow; (2) steady elongation flow; (3) small-amplitude oscillatory shear flow; (4) stress growth upon the inception of steady shear elongation flow; (5) stress relaxation (modulus and compllance). These theoretical relations for simple steady shear flow were compared with experimental data from our laboratory and references for various polymer melts and concentrated solutions. A good agreement between the theory and experiment was achieved.

Moult intensity constraints along the complete moult sequence of the House Sparrow(Passer domesticus)

Sequence and intensity are two essential components of bird moult.While the moult sequences of remex tracts are highly homogenous across passerines,other tracts apparently show a high variability.Moreover,order of moult activation among tracts are insufficiently known.Likewise,dynamics of moult intensity as moult progresses remains poorly known.Here,we provide detailed quantitative description of moult sequence and intensity in the House Sparrow(Passer domesticus).To understand their role,we tested two hypotheses on the:1) protection function of moult sequence,and 2) aerodynamic and physiological constraints on moult intensity.We scored percentage growth of 313 captured sparrows using the mass of the feathers of each tract(also length for remiges)to monitor moult intensity throughout the complete moult progress,which is defined as the fraction of new and growing feathers in a moulting bird relative to the total plumage.Moult sequence was highly variable both within wing coverts and among feather tracts,with moult sequence differing among all birds to some degree.We only found support for the protection function between greater coverts and both tertials and secondaries.Remex-moult intensity conformed to theoretical predictions,therefore lending support to the aerodynamic-constraint hypothesis.Furthermore,remex-moult speed plateaued during the central stages of moult progress.However,overall plumage-moult speed did not fit predictions of the physiological-constraint hypothesis,showing that the remex moult is only constrained by aerodynamics.Our results indicate that aerodynamic loss is not simply the inevitable effect of moult,but that moult is finely regulated to reduce aerodynamic loss.We propose that the moult of the House Sparrow is controlled through sequence and intensity adjustments in order to:1) avoid body and wing growth peaks;2) fulfil the protection function between some key feather tracts;3) reduce detrimental effects on flight ability;4) keep remex sequence fixed;and 5) relax remex replacement to last the whole moult duration.

Constraint-induced movement therapy promotes brain functional reorganization in stroke patients with hemiplegia

Stroke patients with hemiplegia exhibit flexor spasms in the upper limb and extensor spasms in the lower limb, and their movement patterns vary greatly. Constraint-induced movement therapy is an upper limb rehabilitation technique used in stroke patients with hemiplegia; however, studies of lower extremity rehabilitation are scarce. In this study, stroke patients with lower limb hemiplegia underwent conventional Bobath therapy for 4 weeks as baseline treatment, followed by constraint-induced movement therapy for an additional 4 weeks. The 10-m maximum walking speed and Berg balance scale scores significantly improved following treatment, and lower extremity motor function also improved. The results of functional MRI showed that constraint-induced movement therapy alleviates the reduction in cerebral functional activation in patients, which indicates activation of functional brain regions and a significant increase in cerebral blood perfusJon. These results demonstrate that constraint-induced movement therapy promotes brain functional reorganization in stroke patients with lower limb hemiplegia.

Taking into Account of Functional Constraints in Optimization of Modes of Power Systems by Genetic Algorithms

The development of the capabilities of computational tools has created up new possibilities for the effective use of a number of classical mathematical methods and algorithms for solving many important problems in the power engineering. In particular, a set of algorithms are developed to optimize the modes of electric power systems based on genetic algorithms. At the same time, the issues of taking into account functional constraints in solving such problems by genetic algorithms need to be improved. In accordance with it in this article the problems of taking into account of different constraints in optimization of modes of power systems using genetic algorithms are considered. The algorithm of optimization by genetic algorithm taking into account of functional constraints in forms of equality and inequality by penalty functions is proposed. The results of research of proposed algorithm’s efficiency in example of optimization of mode of power system with 8 buses, 4 thermal power plants and 3 transmission lines with controlled power flow are presented.

Functional magnetic resonance imaging evaluation of brain function reorganization in cerebral stroke patients after constraint-induced movement therapy

In this study, stroke patients received constraint-induced movement therapy for 3 weeks. Before and after constraint-induced movement therapy, the flexibility of their upper limbs on the affected side was assessed using the Wolf motor function test, and daily use of their affected limbs was assessed using the movement activities log, and cerebral functional reorganization was assessed by functional magnetic resonance imaging. The Wolf motor function test score and the movement activities log quantity and quality scores were significantly increased, while action performance time in the Wolf motor function test was significantly decreased after constraint-induced movement therapy. By functional magnetic resonance imaging examination, only scattered activation points were visible on the affected side before therapy. In contrast, the volume of the activated area was increased after therapy. The activation volume in the sensorimotor area was significantly different before and after therapy, and the activation area increased and appeared adjusted. In addition to the activated area around the lesions being decreased, there were also some new activated areas, including the supplementary movement area, premotor area and the ipsilateral sensorimotor area. Our findings indicate that constraint-induced movement therapy significantly improves the movement ability and daily use of the affected upper limbs in stroke patients and promotes cerebral functional reorganization.

Robust elastic impedance inversion using L1-norm misfit function and constraint regularization

The classical elastic impedance(EI) inversion method,however,is based on the L2-norm misfit function and considerably sensitive to outliers,assuming the noise of the seismic data to be the Guassian-distribution.So we have developed a more robust elastic impedance inversion based on the L1-norm misfit function,and the noise is assumed to be non-Gaussian.Meanwhile,some regularization methods including the sparse constraint regularization and elastic impedance point constraint regularization are incorporated to improve the ill-posed characteristics of the seismic inversion problem.Firstly,we create the Ll-norm misfit objective function of pre-stack inversion problem based on the Bayesian scheme within the sparse constraint regularization and elastic impedance point constraint regularization.And then,we obtain more robust elastic impedances of different angles which are less sensitive to outliers in seismic data by using the IRLS strategy.Finally,we extract the P-wave and S-wave velocity and density by using the more stable parameter extraction method.Tests on synthetic data show that the P-wave and S-wave velocity and density parameters are still estimated reasonable with moderate noise.A test on the real data set shows that compared to the results of the classical elastic impedance inversion method,the estimated results using the proposed method can get better lateral continuity and more distinct show of the gas,verifying the feasibility and stability of the method.

A Penalty Function Algorithm with Objective Parameters and Constraint Penalty Parameter for Multi-Objective Programming

In this paper, we present an algorithm to solve the inequality constrained multi-objective programming (MP) by using a penalty function with objective parameters and constraint penalty parameter. First, the penalty function with objective parameters and constraint penalty parameter for MP and the corresponding unconstraint penalty optimization problem (UPOP) is defined. Under some conditions, a Pareto efficient solution (or a weakly-efficient solution) to UPOP is proved to be a Pareto efficient solution (or a weakly-efficient solution) to MP. The penalty function is proved to be exact under a stable condition. Then, we design an algorithm to solve MP and prove its convergence. Finally, numerical examples show that the algorithm may help decision makers to find a satisfactory solution to MP.

基于自适应速度趋势函数的约束层速度反演方法

论文研究了复杂构造区初始层速度约束反演问题。首先得出初始层速度模型的精度对偏移速度建模的质量和迭代稳定尤为重要,常规方法在构造复杂区使初始速度模型产生的误差易导致最终偏移速度模型地质意义失真、真实构造特征掩盖等问题。提升初始速度模型与地下地质特征的匹配和精度成为关键。基于此,论文提出了基于自适应速度趋势函数的约束层速度反演方法。在常规方法的基础上,利用复相关法在时间域剖面上获得地质构造的连续性与变化,并将其作为构造响应算子形成针对性的影响域和权重融入速度趋势函数中,使该函数自适应地质构造特征,提升初始速度模型的精度。再通过对基准速度和速度趋势对深度的梯度进行样条拟合,构建趋势函数的全局高频异常约束,有效预防在构造突变区产生异常高频,进一步增强算法的稳健和可靠性。理论模型和实际数据的测试,验证了本文方法的有效性,反演得到的层速度模型更符合地质规律,并能更好地解决构造复杂区层速度模型的连续性问题,有利于提高复杂构造叠前深度偏移成像精度。

基于改进哈里斯鹰算法的无人飞行器路径规划

针对无人飞行器三维路径规划问题,提出一种基于哈里斯鹰优化(Harris hawks optimization,HHO)算法的无人飞行器三维路径规划算法。首先根据路径规划代价指标和无人飞行器自身性能,建立路径规划模型确立代价函数和约束条件。接着针对传统HHO算法的不足,引入非线性能量因子来平衡全局搜索和局部搜索的关系,使算法避免陷入局部最小值;引入混沌映射对HHO算法进行初始化种群并对其进行局部混沌搜索,增强算法种群多样性和搜索能力。最后通过仿真实验证明,改进的哈里斯鹰优化(improvement Harris hawks optimization,IHHO)算法可以有效规划出安全的无人飞行器航线,并且能够跳出局部最小值和具备较优的收敛速度。

基于GA-SA组合算法的山区复杂环境无人机起降点选址

针对山区复杂环境下的物流链前端无人机货运起降点选址和任务分配进行研究。首先以建设成本最小和运输时间满意度最大为目标,综合考虑无人机自身性能和禁飞空域等因素,构建多约束条件下多目标函数的起降点选址和任务分配模型。采用遗传算法(genetic algorithm, GA)和模拟退火算法(simulated annealing algorithm, SA)的组合算法进行求解,首先通过遗传算法得出较优的可行解,再以此解作为退火算法的初始解进行模型求解。仿真结果表明,构建的多约束模型能够实现预期效果,并且采用的算法解决此类问题时具有良好的适用性。

基于多目标进化的超限超重货物运输专列路径优化方法

针对超限超重货物运输专列路径优化问题,引入限界改造和桥梁加固要素,以铁路运能损失、运输时间和运输费用的最小化为优化目标,构建铁路超限超重货物运输专列路径优化模型;考虑专列同时运送多件超限超重货物的特点,设计货物综合投影算法,并以Pareto支配关系框架下的NSGA-Ⅱ多目标进化算法为基础,结合基于移动不可行解的自适应惩罚函数的约束处理技术及超限超重货物运输专列开行特征,提出一种基于多目标进化的铁路超限超重货物运输专列路径优化算法。实例分析结果表明:该方法能高效合理地处理路径优化任务中的多个目标;与常用的3种约束多目标算法相比,设计的优化算法能使计算耗时降低0.24%~29.94%、超体积指标值提高4.25%~13.11%,并得到一组收敛性和多样性更好的相对最优方案。该方法克服了传统专列路径优化中单纯依靠经验或从备选方案中择优的弊端,可为铁路超限超重货物运输专列路径决策提供技术支持。

一种基于高频噪声定量约束函数的地震高分辨率处理方法

系统分析了现有地震数据高分辨率处理方法的适用性及不足,探索了一种基于高频噪声定量约束函数的高分辨率处理方法,有效且保真地提高地震资料信噪比与分辨率。通过分析叠后地震数据有效信号带宽,设计了压制高频噪声的最大概率准则和定量约束函数,通过多次迭代压制噪声,提高全频带信号的信噪比,逐步分级拓宽地震有效频带宽度,循环迭代求取反射系数,将提取的地震子波与反射系数褶积得到高分辨率地震数据体。测试校验对比其它高分辨率地震处理结果,处理后的数据体具有垂向分辨率高、主频高且频带宽的特点,有效视主频由50 Hz提高至100 Hz左右,地质目标视分辨率相应提高近1倍。基于该提频数据与波阻抗反演实现了2~5 m地质目标的定性与定量预测,钻井验证符合率90%以上,有效指导井位部署。该方法弥补了在传统“有效带宽”内提高地震高频信号的不足,实现了全频带内重构高、低频有效信号的目的。

带有神经网络干扰观测器的视线角约束制导

针对具有终端视线(line-of-sight, LOS)角约束的机动目标拦截问题,提出一种基于径向基函数(radial basis function, RBF)神经网络干扰观测器的LOS角约束制导方法。首先,考虑目标机动过程中加速度信息无法获取的情况,给出了一种基于RBF神经网络的干扰观测器,实现了对目标机动的高精度估计;其次,充分考虑终端角度约束,结合超螺旋算法思想,通过幂次项的引入设计了一种改进的滑模制导律,从而有效提升了有限过载情况下的制导精度;在此基础上,通过Lyapunov定理对算法的收敛性和稳定性分别进行了证明;最后,通过仿真验证对比了3种不同方法在4种拦截场景下的制导性能,同时针对所提方法进行了蒙特卡罗打靶仿真,仿真结果表明所给出的LOS角约束制导律对机动目标拦截精度高、鲁棒性强。

基于双重约束的并网逆变器电流自动化控制方法研究

为降低并网逆变器逆变的并网电流畸变率,提出基于双重约束的并网逆变器电流自动化控制方法。以典型的三相LCL并网逆变器为例,分析其运行状态;并确定并网逆变器在进行逆变转换时,谐波对于逆变器并网电流的影响,计算并网逆变器环路增益函数;采用输出电流直接前馈的改进阻尼控制方法实现电流自动化控制,并引入全局-局部稳定双重约束原则,确定最佳的谐振抑制参数,提升电流的控制效果。测试结果显示,该方法的并网逆变器的电流畸变率均低于5%,电流跳变过程中,可在0.2 s内有效控制跳变电流结果。

预设时间性能约束下高超声速飞行器的自适应容错控制

考虑输出误差约束、不确定和执行器故障影响下的高超声速飞行器的跟踪控制问题,提出自适应容错反步控制策略。首先,设计指数型预设时间性能函数,保证输出误差在预设时间内满足约束要求。其次,通过自适应律解决不确定项和升降舵故障。利用跟踪微分器解决“计算爆炸”问题,避免反步控制中对虚拟控制输入的高阶求导。最后,基于Lyapunov理论证明闭环系统的稳定性,并通过仿真验证所提控制策略的有效性。

油田集输系统能耗优化方法研究

为降低油田集输系统的总体能耗,在考虑站点约束、水力约束、热力约束和流程约束的前提下,以总运行费用成本最少的目标函数,以现场实际工况为决策变量,通过不断更新粒子群的位置和速度信息,对决策变量进行了求解。结果表明,当水滴最小分割粒径小于310μm,油滴最小分割粒径小于144μm时,可满足采出液预分离的要求,由此确定站内三相分离器的操作温度;通过沉降实验确定沉降罐的进口温度范围为40~50℃;系统动力消耗有所上升、热力消耗有所下降,冬季的节能效果最佳,日运行费用从15630元降至14016元,全年可节约运行费用51387元。

多元统计分析中一类矩阵迹函数极小化问题的分裂迭代法

研究了来源于多元统计分析中的一类含列正交约束的矩阵迹函数极小化模型,该模型的特殊形式广泛应用于多维标度分析中DEDICOM模型和正交INDSCAL模型最小二乘拟合等问题中。结合变量分裂构造了几类经典的基于分裂的不可行迭代算法求解该约束迹函数极小化模型,并给出算法外层迭代框架和内层子问题的具体求解方案。数值实验验证了算法的有效性。

分布式光伏电站接入配电网继电保护整定优化

为了缓解配电网的供电压力,越来越多的分布式光伏电站接入其中,导致配电网结构发生了改变,因此需要重新整定继电保护的定值,否则,当配电网发生故障时,继电器很难有效发挥其保护作用。提出一种分布式光伏电站接入配电网的继电保护整定优化方法。以继电器协同动作时间总和最小值为优化目标,设置4个约束条件,利用微分进化算法求取目标函数的最优解,得出继电器启动电流和时间整定系数的最优整定值。实验结果表明:在接入分布式光伏电站的两相短路故障时,所提整定优化方法的继电器保护总体动作时间更短,验证了该算法的保护整定效果更好,更有利于继电器迅速排除配电网故障,保护配电网安全。

航天器姿态受限的协同势函数族设计方法

提出一种考虑航天器姿态约束的协同势函数设计方法,在姿态全局收敛的同时,保证姿态在机动过程中始终满足姿态约束.首先,建立航天器姿态指向约束模型,并针对每一个指向约束设计软约束区域;然后,基于“角度扰动”方法设计协同势函数族;接着,通过设计协同势函数族内函数切换规律,在软约束区域内构建满足姿态约束的势函数,并给出区域内势函数临界点分布的调整方法;最后,将所得的势函数用于航天器的避障控制,以比例-微分控制为例,通过数值仿真,验证该方法的有效性.