A non‐intrusive model reduction approach for polynomial chaos expansion using proper orthogonal decomposition

In this paper, a non‐intrusive stochastic model reduction scheme is developed for polynomial chaos representation using proper orthogonal decomposition. The main idea is to extract the optimal orthogonal basis via inexpensive calculations on a coarse mesh and then use them for the fine‐scale analysis. To validate the developed reduced‐order model, the method is implemented to: (1) the stochastic steady‐state heat diffusion in a square slab; (2) the incompressible, two‐dimensional laminar boundary‐layer over a flat plate with uncertainties in free‐stream velocity and physical properties; and (3) the highly nonlinear Ackley function with uncertain coefficients. For the heat diffusion problem, the thermal conductivity of the slab is assumed to be a stochastic field with known exponential covariance function and approximated via the Karhunen–Loève expansion. In all three test cases, the input random parameters are assumed to be uniformly distributed, and a polynomial chaos expansion is found using the regression method. The Sobol's quasi‐random sequence is used to generate the sample points. The numerical results of the three test cases show that the non‐intrusive model reduction scheme is able to produce satisfactory results for the statistical quantities of interest. It is found that the developed non‐intrusive model reduction scheme is computationally more efficient than the classical polynomial chaos expansion for uncertainty quantification of stochastic problems. The performance of the developed scheme becomes more apparent for the problems with larger stochastic dimensions and those requiring higher polynomial order for the stochastic discretization. Copyright © 2015 John Wiley & Sons, Ltd.     

Mode I–III Decomposition of the J‐integral from DIC Displacement Data

This paper presents the implementation of the decomposition method on digital image correlation (DIC) obtained displacement fields to obtain J‐integral results (J) and respective stress intensity factors (SIFs). DIC is increasingly used with the J‐integral approach in experimental mechanics to obtain J estimates from complex fracture processes. In this approach, the decomposition method is applied to DIC displacement fields for the first time. Here, displacement fields are separated before stresses and strains are computed, so that subsequent computation of separate J or SIF components may follow the classical full‐field J‐integral approach. The sensitivity of the decomposition method to experimental errors is investigated using synthetically generated errors imposed on crack tip displacement fields (Williams' series), from which improvements to the procedure are proposed. The method is experimentally tested on PMMA Arcan specimens under mode I, II, and III, and mixed‐mode I–III loading. Test results were compared to fracture toughness values obtained from ASTM tests and literature with close agreement.     

纳米铜修饰多壁碳纳米管/石蜡相变驱动复合材料的制备及热性能

以油胺为分散稳定剂,在石蜡中热分解甲酸铜-碳纳米管复合物前驱体,单步制备了纳米铜修饰多壁碳纳米管(Cu-MWCNTs)/石蜡复合材料。通过XRD、TEM和DSC对Cu-MWCNTs/石蜡复合材料的物相、微观形貌及相变行为进行了表征和分析,并对其热敏性、热膨胀性和热稳定性及影响因素进行了分析研究。结果表明:纳米Cu原位沉积在MWCNTs外壁上,粒径为2~35nm。与纯石蜡相比,Cu-MWCNTs/石蜡复合材料的相变温度和相变潜热均明显降低。Cu-MWCNTs含量为0.2wt%的Cu-MWCNTs/石蜡复合材料具有较短的升温时间,体膨胀率降低较小,且多次加热后稳定性较好,可作为此类热敏微驱动器的理想材料。     

A 3D domain decomposition approach for the identification of spatially varying elastic material parameters

The post‐treatment of (3D) displacement fields for the identification of spatially varying elastic material parameters is a large inverse problem that remains out of reach for massive 3D structures. We explore here the potential of the constitutive compatibility method for tackling such an inverse problem, provided an appropriate domain decomposition technique is introduced. In the method described here, the statically admissible stress field that can be related through the known constitutive symmetry to the kinematic observations is sought through minimization of an objective function, which measures the violation of constitutive compatibility. After this stress reconstruction, the local material parameters are identified with the given kinematic observations using the constitutive equation. Here, we first adapt this method to solve 3D identification problems and then implement it within a domain decomposition framework which allows for reduced computational load when handling larger problems. Copyright © 2015 John Wiley & Sons, Ltd.     

一种低复杂度的激光打标拐点检测算法

为了改善激光打标系统中图像解算的拐点检测率,提高激光标刻质量,采用一种基于斜率差的拐点检测算法,进行了理论分析和实验验证。该算法计算出图像数据中相邻两点间偏移坐标的斜率,并以此相邻坐标点连线斜率之差作为判决条件检测提取拐点。结果表明,新算法较传统算法而言,在拐点检测更为准确的同时,具有较小的运算复杂度;应用该算法能够修正传统打标系统中存在的拐点工艺问题,使图像拐点在提取过程中能够更节省存储空间,减少了运算量。     

基于稀疏分解和混沌理论的微弱信号检测

针对数字锁定放大器中稀疏分解算法检测精度受限的缺点,结合非线性方法进行补偿,采用混沌检测联合稀疏分解的算法设计了数字锁定放大器。数字锁定放大器借助稀疏分解算法估计信号参数,根据估计得到的参数设计对应混沌系统;利用混沌系统检测信号的过程中产生间歇性混沌状态,并通过测量间歇性混沌状态的周期,精确检测信号。最终,在信号的信噪比低至-20 dB时可以成功检测信号,频率精度达到0.05 Hz,提供了一种非线性微弱信号检测方法。     

基于等价型模糊神经网络的战场辐射源识别算法

针对多变量、环境干扰复杂的现代战场电子对抗辐射源识别非线性系统,应用早期的识别方法已经无法满足辐射源识别系统的精度要求,采用等价型模糊神经网络,产生模糊规则和隶属函数,再基于这些规则产生模糊逻辑推理来构造模式识别算法.仿真结果表明:该算法与传统模式识别方法相比具有更高的识别能力和较强的抗干扰能力,大大提高了战场辐射源识别的正确率和可靠性.     

某型火箭炮捷联惯导在线标定方案研究

针对火箭炮在射前准备阶段里只能进行两自由度的角运动,造成部分参数不可观的缺陷,在基于对火箭炮进行制导化改造的背景下,提出了在射前准备阶段加入横滚运动的标定方案以及相应的可观测度分析方法。首先建立了21 维误差模型;而后运用可观测度分析方法对误差参数的可观测度进行了分析,对三个阶段进行了比较,表明横滚运动可使多个参数变得可观,并且其他参数可观测度也大幅提升;最后,采用奇异值分解的方法对所提出的标定方案和可观测度分析方法进行仿真验证,结果表明:除x 轴陀螺刻度系数误差外,其余参数奇异值基本都大于1,与可观测度分析方法的结论一致,充分体现了横滚运动对误差参数估计的有效性以及可观测度分析方法的可行性。     

气溶胶偏振探测仪检偏器方位角优化

非理想透镜组的偏振效应引起偏振测量系统的测量矩阵改变,导致系统最佳配置漂移.为了最大化气溶胶偏振探测仪的信噪比,利用Jones矩阵的方法计算前置光学透镜组的起偏度,并分别以系统分析矩阵的条件数和参数Tr(BBT)为优化参数对检偏器的放置角度进行优化.经过优化,得到检偏器的最佳方位角,在670 nm通道系统分析矩阵的条件数由1.836 0降为1.689 4,在1 641 nm通道系统分析矩阵的条件数由1.977 7降为1.771 4.结果表明,两种优化方法的结果基本一致,经过优化之后两个偏振测量通道的信噪比都提升10%左右.     

基于矩阵分解的多输入多输出雷达解相关算法

多输入多输出(Multi-input Multi-output,MIMO)雷达的多发射正交波形自相关和互相关特性会影响目标参数估计的性能,完全正交的多组波形又很难获得,针对此,提出一种基于矩阵分解的双基地MIMO雷达多发射波形解相关算法,使不完全正交的多组波形解相关.本算法通过对多发射波形相关矩阵做矩阵分解和迭代运算,实现波形解相关.通过对收发角度联合估计精度的分析,验证了所提算法的可行性和有效性.