Order-of-addition experiments: A review and some new thoughts

Abstract

The study of order-of-addition (OofA) experiments is prevalent in many scientific and industrial areas. The statistical design of experiments (DOE) will considerably improve the efficiency of OofA experiments. Designing and modeling the OofA experiments have increasingly received a great deal of attention. In this article, we review the latest work on the design and model of OofA experiments, and introduce some new thoughts. We believe that this article will motivate fruitful applications in real OofA experiments as well as future developments in the methodology.     

Investigation of flow parameters of Reiner–Philippoff nanofluid flow with higher-order slip properties,activation energy,and bioconvection by artificial neural networks

In this study, the flow parameters of Reiner–Philippoff nanofluid flow with high-order slip properties, activation energy, and bioconvection have been analyzed using artificial neural networks (ANNs). Local Nusselt number (LNN), local Sherwood number (LSN), and motile density number (MDN) are considered as flow parameters. Numerical values have been obtained by numerical methods using flow equations. To estimate the flow parameters, three different ANN models have been designed. The Levenberg–Marquardt training algorithm is used in multilayer perceptron network models with 10 neurons in the hidden layers. In all, 70% of the data set has been used for training the models, 15% for validation, and 15% for testing. The performance analysis of the network models has been made by calculating the determined performance parameters. The R values for the LNN, LSN, and MDN parameters have been calculated as 0.99261, 0.98769, and 0.99102, respectively, and the average deviation values are −0.65%, 0.06%, and −0.11%, respectively. The attained outcomes showed that the ANNs can predict the LNN, LSN, and MDN, which are the flow parameters of the Reiner–Philippoff nanofluid flow, with high accuracy.     

Stochastic response of hysteretic systems

This paper deals with approximate stochastic response of hyseretic structures under white noise excitation, based on It stochastic differential equations. Instead of the original system an equivalent nonlinear system is considered, in which the drift vector is given by a series expansion of the order n 1 in terms of the state variables. n = 1 represents the well-known case of equivalent linearization. Components in the drift vector representing the nonanalytical constitutive equations are replaced by a cubic polynomial expansion. The hierarchy of statistical moment equations is closed by a cumulant neglect closure scheme. The method has been applied to a bilinear single degree-of-freedom system subjected to white noise excitation, for which an equivalent system with a cubic series expansion to the constitutive equation is considered. The results obtained are compared with those of numerical simulation and alternative methods, and they provide substantial improvements compared to equivalent linearization.     

基于分数阶Fourier变换累积量的目标检测算法

传统的信号检测和噪声分离方法只限于在时域或是频域进行,如果信号和背景噪声有很强的时频耦合,就难以在时频域得到好的检测结果。对此提出了分数阶Fourier变换累积量算法,该算法具有解除时频耦合和抑制噪声的特性,当选择合适的旋转角度使之与处理信号相匹配,就可以在分数阶Fourier域获得较好的检测结果。仿真结果表明,分数阶Fourier累积量算法的检测性能优于分数阶Fourier变换和4阶累积量算法,展现了分数阶Fourier变换累积量算法有优越的信号处理性能。     

基于三阶循环平稳度准则的盲源分离算法

通过研究循环平稳信号的特性和分析传统的基于二阶统计量的盲源分离算法,在二阶循环平稳度的基础上提出了三阶循环平稳度的概念,并推导出了利用三阶循环累积量平稳度作为分离准则的新盲源分离算法。本算法可以在复杂噪声的情况下有效的分离平稳信号和循环平稳信号。仿真结果表明该算法能够抑制混合信号中的强噪声,算法简单,实时性好。     

Load characterization and power conditioner synthesis using higher-order elements

It is shown that virtually all nonlinear and/or time-varying loads that generate harmonic current distortion can be characterized in terms of so-called higher-order circuit elements. The most relevant higher-order elements exploited in this paper are the memristor, meminductor, and memcapacitor. Such elements naturally arise by introducing constitutive relationships in terms of higher-order voltage and current differentials and integrals. Consequently, the power conditioner necessary to compensate for the load current distortions is synthesized similarly. The new characterization and compensation synthesis is applied to the half-wave rectifier and the controlled bridge converter.     

采用振动台阵的超大跨斜拉桥大比例全模型试验研究

强震作用下超大跨斜拉桥的结构响应与其结构体系密切相关,且受基础和场地土特性影响较大,然而目前为止,因试验条件和技术所限,尚缺乏相关的全桥模型振动台试验研究。以一座试设计的主跨1400m超大跨斜拉桥为原型,设计一座几何相似比为1/70、包括桩基础和场地土的全桥模型;采用振动台阵试验技术,研究El Centro波、人工波、Mexico City波等三种典型地震一致激励下不同结构体系的地震响应特性及影响机理,所研究的结构体系包括：纵向半漂浮体系、纵向弹性约束体系、以及本文作者提出的纵向辅助墩耗能体系和横向耗能体系;探讨不同纵向结构体系的抗震性能以及附加在上塔柱间的耗能构件对斜拉桥横向地震响应的控制效果。试验结果表明：土-结构相互作用对上部结构地震响应的影响不可忽视;主塔地震响应受高阶振型的影响明显;在PGA为0.4g以下的El Centro波和人工波、以及PGA为0.2g的Mexico City波作用下,结构响应仍处于弹性状态;纵向弹性约束体系和纵向辅助墩体耗能系可有效减小主塔位移和塔-梁间纵向相对位移响应,其中作者提出的纵向辅助墩耗能体系的抗震性能更好;附加耗能构件可有效降低主塔的弯矩应变响应,实现分散主塔受力和附加耗能作用,但对主塔加速度和位移响应的控制有限。     

高阶滑模制导律的设计与实现

针对机动目标拦截问题,应用高阶滑模控制方法,设计了高精度制导律。在制导律设计过程中,针对目标机动,基于增广比例导引设计了滑模变量,考虑二阶弹体动态特性,设计了二阶滑模制导律。应用高增益扩张状态观测器对制导信息进行估计,完成了制导律的实现。数值仿真结果验证了方法的有效性。     

pFFT方法在波浪与结构作用中的不规则频率消除技术

对于求解波浪与大型结构物作用的pFFT方法,即预修正快速傅里叶变换方法(Pre-corrected Fast Fourier Transform),该文提出了消除"不规则频率"影响,从而保证在各频率下均可得到正确解的求解技术。该方法通过在内水面上配置源点的方法得到了唯一解的积分方程,并通过叠加物体内部积分方程而得到了便于求解的方形矩阵。算例表明:该方法能够消除"不规则频率"的影响,在整个频率内均可得到精确的计算结果;对于大型计算,在计算效率和内存空间的使用上,均较传统的高阶边界元方法有很大优势。     

频偏稳健的分级调制分类算法

通过对观测样本进行非线性变换,提出了一种基于高阶累积量分级调制分类算法,有效解决了频偏引起的相位旋转问题.仿真表明,在归一化频偏小于0.2时,算法具有较好的分类性能.理论分析和仿真结果均证明了算法的正确性和有效性.