用广义协调Coons混合曲面元分析中厚板的振动

利用文献[1]的厚薄板通用广义协调元Coons混合曲面法分析了中厚板的振动,其优点是自由度少、精度高、程序简便、收敛快。算例计算出了四边简支方板的前几阶频率,其结果与文献[2]的结果符合良好。     

中厚板稳定分析

根据广义协调原理,利用文献[1]的厚薄板通用广义协调元Coons混合曲面法分析了中厚板稳定,算例计算出了不同厚跨比、不同支承条件的方板的稳定系数,其结果与文献2的结果符合良好,证明本单元可以计算稳定问题,且具有自由度少、精度高、程序简便、收敛快等优点.     

建构城市协调单元

分析了现代城市的现状以及所存在的问题，介绍了解决问题的措施，即：建构城市的协调单元，论证了协调单元的可实施性，既保证了人性化的生活空间，又与城市的快节奏、大范围相融合。     

New Synthetic Control Charts for Monitoring Process Mean and Process Dispersion

A statistical quality control chart is widely recognized as a potentially powerful tool that is frequently used in many manufacturing and service industries to monitor the quality of the product or manufacturing processes. In this paper, we propose new synthetic control charts for monitoring the process mean and the process dispersion. The proposed synthetic charts are based on ranked set sampling (RSS), median RSS (MRSS), and ordered RSS (ORSS) schemes, named synthetic‐RSS, synthetic‐MRSS, and synthetic‐ORSS charts, respectively. Average run lengths are used to evaluate the performances of the control charts. It is found that the synthetic‐RSS and synthetic‐MRSS mean charts perform uniformly better than the Shewhart mean chart based on simple random sampling (Shewhart‐SRS), synthetic‐SRS, double sampling‐SRS, Shewhart‐RSS, and Shewhart‐MRSS mean charts. The proposed synthetic charts generally outperform the exponentially weighted moving average (EWMA) chart based on SRS in the detection of large mean shifts. We also compare the performance of the synthetic‐ORSS dispersion chart with the existing powerful dispersion charts. It turns out that the synthetic‐ORSS chart also performs uniformly better than the Shewhart‐R, Shewhart‐S, synthetic‐R, synthetic‐S, synthetic‐D, cumulative sum (CUSUM) ln S², CUSUM‐R, CUSUM‐S, EWMA‐ln S², and change point CUSUM charts for detecting increases in the process dispersion. A similar trend is observed when the proposed synthetic charts are constructed under imperfect RSS schemes. Illustrative examples are used to demonstrate the implementation of the proposed synthetic charts. Copyright © 2014 John Wiley & Sons, Ltd.     

Port reduction in parametrized component static condensation: approximation and a posteriori error estimation

We introduce a port (interface) approximation and a posteriori error bound framework for a general component‐based static condensation method in the context of parameter‐dependent linear elliptic partial differential equations. The key ingredients are as follows: (i) efficient empirical port approximation spaces—the dimensions of these spaces may be chosen small to reduce the computational cost associated with formation and solution of the static condensation system; and (ii) a computationally tractable a posteriori error bound realized through a non‐conforming approximation and associated conditioner—the error in the global system approximation, or in a scalar output quantity, may be bounded relatively sharply with respect to the underlying finite element discretization. Our approximation and a posteriori error bound framework is of particular computational relevance for the static condensation reduced basis element (SCRBE) method. We provide several numerical examples within the SCRBE context, which serve to demonstrate the convergence rate of our port approximation procedure as well as the efficacy of our port reduction error bounds. Copyright © 2013 John Wiley & Sons, Ltd.     

An np‐control chart for inspection errors and repeated classifications

The np‐control chart has been used to monitor the conforming fraction in process production, and it is assumed that no classification errors occur during the inspection process. Increases in the sample size and/or the number of repeated classifications of the inspected items can reduce the impact of the classification errors. In this paper, an np ‐control chart is proposed, and the monitored statistics are based on the results of independent repeated classifications with classification errors during the inspection process. The aim of the proposed control chart is to have the same performance as a control chart without classification errors. Numerical examples illustrate the proposal. Copyright © 2011 John Wiley & Sons, Ltd.     

椭圆型方程的一种新型混合有限元格式

基于实际问题对通量较低的正则性要求,本文建立了椭圆型方程的一种新型混合变分形式.在鞍点问题框架下,通过验证LBB条件,证明了该混合形式解的存在唯一性.由于压力空间不再是传统的H(div),而是平方可积空间,因此混合元的选取变得简单容易.同时本文给出了相应的有限元逼近形式,并对于由分片常数速度元和分片线性压力元构成的协调...     

压力容器接管区应力场有限元分析

针对压力容器接管区局部高应力高应变区的状态和裂纹的断裂规律特征,对多种孔径的异型板应力应变场应用弱协调元,建立单元间位移弱连续条件的协调有限元模型,不需要应力满足平衡条件,因此可以解决常规有限元难以适应的奇异性领域.本文分别就不带裂纹和带有裂纹的异型板进行应力分类数值分析,为压力容器接管部位的设计和裂纹疲劳扩展分析提供了可靠依据.     

Geometric Charts with Estimated Control Limits

The geometric control chart has been shown to be more effective than p and np‐charts for monitoring the proportion of nonconforming items, especially for high‐quality Bernoulli processes. When implementing a geometric control chart, the in‐control proportion nonconforming is typically unknown and must be estimated. In this article, we used the standard deviation of the average run length (SDARL) and the standard deviation of the average number of inspected items to signal, SDARL*, to show that much larger phase I sample sizes are needed in practice than implied by previous research. The SDARL (or SDARL*) was used because practitioners would estimate the control limits based on different phase I samples. Thus, there would be practitioner‐to‐practitioner variability in the in‐control ARL (or ARL*). In addition, we recommend a Bayes estimator for the in‐control proportion nonconforming to take advantage of practitioners' knowledge and to avoid estimation problems when no nonconforming items are observed in the phase I sample. If the in‐control proportion nonconforming is low, then the required phase I sample size may be prohibitively large. In this case, we recommend an approach to identify a more informative continuous variable to monitor. Copyright © 2012 John Wiley & Sons, Ltd.