Prediction of the drag reduction effect of pulsating pipe flow based on machine learning

Prediction of drag reduction effect caused by pulsating pipe flows is examined using machine learning. First, a large set of flow field data is obtained experimentally by measuring turbulent pipe flows with various pulsation patterns. Consequently, more than 7000 waveforms are applied, obtaining a maximum drag reduction rate and maximum energy saving rate of 38.6% and 31.4%, respectively. The results indicate that the pulsating flow effect can be characterized by the pulsation period and pressure gradient during acceleration and deceleration. Subsequently, two machine learning models are tested to predict the drag reduction rate. The results confirm that the machine learning model developed for predicting the time variation of the flow velocity and differential pressure with respect to the pump voltage can accurately predict the nonlinearity of pressure gradients. Therefore, using this model, the drag reduction effect can be estimated with high accuracy.     

基于电化学老化衰退模型的锂离子动力电池外特性

当前锂离子动力电池电化学模型存在模型复杂、建模难度大、计算效率低、老化评估效果差的问题,本文提出一种考虑电池衰退老化的机理模型(ADME).本文首先通过有限差分法对伪二维(P2D)电化学模型进行离散降阶处理,得到简化伪二维(SP2D)模型.在SP2D模型的基础上,基于阴阳两极发生的副反应导致的衰退老化现象,提出一种考虑电池衰退老化的机理模型.其次,使用多变量偏差补偿最小二乘法实现模型参数辨识.最后通过动力电池衰退老化性能循环实验,对比分析了恒流、脉冲工况下SP2D模型和ADME模型的终端电压输出.结果表明:ADME模型较为简单、计算效率和估算精度高,可以有效评估电池容量老化衰退,得到理想的锂离子动力电池外特性曲线.     

Studies on metabolism of total glucosides of paeony from Paeoniae Radix Alba in rats by UPLC‐Q‐TOF‐MS/MS

Total glucosides of paeony are the active constituents of Paeoniae Radix Alba. In this study, a novel strategy was proposed to find more metabolites and the differences between paeoniflorin, albiflorin and total glucosides of paeony (TGP). This strategy was characterized as follows: firstly, the animals were divided into three groups (paeoniflorin, albiflorin and TGP) to identify the source of TGP metabolites from paeoniflorin or albiflorin; secondly, a generic information‐dependent acquisition scan for the low‐level metabolites was triggered by the multiple mass defect filter and dynamic background subtraction; thirdly, the metabolites were identified with a combination of data‐processing methods including mass defect filtering, neutral loss filtering and product ion filtering; finally, a comparative study was used in the metabolism of paeoniflorin, albiflorin and TGP. Based on the strategy, 18 metabolites of TGP, 10 metabolites of paeoniflorin and 13 metabolites of albiflorin were identified respectively. The results indicated that the hydrolysis, conjugation reaction and oxidization were the major metabolic pathways, and the metabolic sites were the glycosidic linkage, the ester bond and the benzene ring. This study is first to explore the metabolism of TGP, and these findings enhance our understanding of the metabolism and the interactions of paeoniflrin and albiflorin in TGP. Copyright © 2015 John Wiley & Sons, Ltd.     

A new family of proximity graphs: Class cover catch digraphs

Motivated by issues in machine learning and statistical pattern classification, we investigate a class cover problem (CCP) with an associated family of directed graphs—class cover catch digraphs (CCCDs). CCCDs are a special case of catch digraphs. Solving the underlying CCP is equivalent to finding a smallest cardinality dominating set for the associated CCCD, which in turn provides regularization for statistical pattern classification. Some relevant properties of CCCDs are studied and a characterization of a family of CCCDs is given.     

Calibrating software reliability models when the test environment does not match the user environment

Software failures have become the major factor that brings the system down or causes a degradation in the quality of service. For many applications, estimating the software failure rate from a user's perspective helps the development team evaluate the reliability of the software and determine the release time properly. Traditionally, software reliability growth models are applied to system test data with the hope of estimating the software failure rate in the field. Given the aggressive nature by which the software is exercised during system test, as well as unavoidable differences between the test environment and the field environment, the resulting estimate of the failure rate will not typically reflect the user‐perceived failure rate in the field. The goal of this work is to quantify the mismatch between the system test environment and the field environment. A calibration factor is proposed to map the failure rate estimated from the system test data to the failure rate that will be observed in the field. Non‐homogeneous Poisson process models are utilized to estimate the software failure rate in both the system test phase and the field. For projects that have only system test data, use of the calibration factor provides an estimate of the field failure rate that would otherwise be unavailable. For projects that have both system test data and previous field data, the calibration factor can be explicitly evaluated and used to estimate the field failure rate of future releases as their system test data becomes available. Copyright © 2002 John Wiley & Sons, Ltd.     

风力发电机组变速恒频控制系统研究

全面介绍了一种最新应用于风力发电中的新型电机—无刷双馈电机，并分析了这种新型电机作变速恒频运行的原理并对这种电机进行了动态特性仿真研究，给出了形式简洁的控制方程和易于实现的控制方案。     

Blind Channel Identification Based on Noisy Observation by Stochastic Approximation Method

A stochastic approximation algorithm for estimating multichannel coefficients is proposed, and the estimate is proved to converge to the true parameters a.s. up-to a constant scaling factor. The estimate is updated after receiving each new observation, so the output data need not be collected in advance. The input signal is allowed to be dependent and the observation is allowed to be corrupted by noise, but no noise statistics are used in the estimation algorithm.     

Modeling hyperelastic behavior of rubber: A novel invariant‐based and a review of constitutive models

A constitutive phenomenological model completing the Gent‐Thomas concept is carried out to formulate laws governing the hyperelastic behavior of incompressible rubber materials. It is shown that the phenomenological Gent‐Thomas model (1958) and the constrained chain model (1992) give similar precise results at small to moderate deformation. On the other hand, comparisons of the outcome of the proposed model with that of the molecular model from the combined concepts of Flory‐Erman and Boyce‐Arruda (2000), and with those of the phenomenological models of Ogden (1982), Yeoh‐Fleming (1997), Pucci‐Saccomandi (2002) and Beda (2005) are made. Residual inconveniences raised by attractive continuum models in rubber elasticity literature have been successfully overcome. Results from both the statistical and phenomenological mechanics concepts are compared with the data of some useful classical materials (rubbers of Treloar, Rivlin‐Saunders, Pak‐Flory and Yeoh‐Fleming). The results permit one to see salient equivalence of the two theories for a more reliable prediction of stress‐stretch response for all states of any mode of deformation. A complete and exhaustive analysis of the Mooney plot that combines small and very large extension‐compression has been quite essential in assessing the validity of models. A method of identification of material parameters is presented and data of the simple tension suffice for the determination of the parameter values. It is shown that the ordinary identification procedures, such as the usual least squares, a very much used numerical method in materials investigation, can be unsuitable in some cases of hyperelastic modeling. © 2007 Wiley Periodicals, Inc. J Polym Sci Part B: Polym Phys 45: 1713–1732, 2007     

粒子鉴别中dE/dx和TOF的权重

在北京谱仪数据分析中,粒子鉴别使用了dE/dx和TOF的信息.在利用dE/dx和TOF联合鉴别粒子时,通常的做法是把两者的χ²值等权重相加(χ²方法).在不同的动量区间,dE/dx和TOF对粒子的鉴别能力不同.本文给出两者联合鉴别时不同动量区间的权重,并构造一个新的线性变量来进行粒子鉴别     

Identification of micro-scale calorimetric devices II

The miniaturized calorimetric devices furnish a reduced working flat surface and permits measurements with extremely low-mass quantities. The experimental sensitivity shows relevant position dependence with x-y surface coordinates and with z-distance. The device identification is realized via a 2-D model based in Fourier general equation. Using the Marquardt method the experimental flat surface device can be identified and the fitted parameters used to simulate the behavior of the experimental system. From the model, the effects of several dissipation configurations can be evaluated. Also, via the RC-analogy, a way to 3-D experimental devices is roughly described. This revised version was published online in July 2006 with corrections to the Cover Date.