The improved element-free Galerkin method for two-dimensional elastodynamics problems

In this paper, we derive an improved element-free Galerkin (IEFG) method for two-dimensional linear elastodynamics by employing the improved moving least-squares (IMLS) approximation. In comparison with the conventional moving least-squares (MLS) approximation function, the algebraic equation system in IMLS approximation is well-conditioned. It can be solved without having to derive the inverse matrix. Thus the IEFG method may result in a higher computing speed. In the IEFG method for two-dimensional linear elastodynamics, we employed the Galerkin weak form to derive the discretized system equations, and the Newmark time integration method for the time history analyses. In the modeling process, the penalty method is used to impose the essential boundary conditions to obtain the corresponding formulae of the IEFG method for two-dimensional elastodynamics. The numerical studies illustrated that the IEFG method is efficient by comparing it with the analytical method and the finite element method.     

Interpolymer radical coupling: A toolbox complementary to controlled radical polymerization

The current review focuses on the relevance and practical benefit of interpolymer radical coupling methods. The latter are developing rapidly and constitute a perfectly complementary macromolecular engineering toolbox to the controlled radical polymerization techniques (CRP). Indeed, all structures formed by CRP are likely to be prone to radical coupling reactions, which multiply the available synthetic possibilities. Basically, the coupling systems can be divided in two main categories. The first one, including the atom transfer radical coupling (ATRC), silane radical atom abstraction (SRAA) and cobalt-mediated radical coupling (CMRC), relies on the recombination of macroradicals produced from a dormant species. The second one, including atom transfer nitroxide radical coupling (ATNRC), single electron transfer nitroxide radical coupling (SETNRC), enhanced spin capturing polymerization (ESCP) and nitrone/nitroso mediated radical coupling (NMRC), makes use of a radical scavenger in order to promote the conjugation of the polymer chains. More than a compilation of macromolecular engineering achievements, the present review additionally aims to emphasize the particularities, synthetic potential and present limitations of each system.     

Synthesis of Ultra-high Weight Average Molecular Mass of Poly-L-lactide

High purity in high yield L-lactide was prepared using a new purification method, and poly-L-lactide (PLLA) with ultra-high weight average molecular mass and narrow polydispersity index was synthesized by ring-opening polymerization. The effects of the purification method on the purity and yield of L-lactide were investigated, and the influences of initiator concentration, polymerization temperature and polymerization time on the weight average molecular mass of PLLA were also studied. A synthetic purification method involving a water bath and two times recrystallization could improve the purity of L-lactide to 100%. The yield of L-lactide reached 40.6% and increased 12.1% compared with the recrystallization method. Poly-L-lactide with a weight average molecular mass of about 102.4 × 10⁴ and a polydispersity index of 1.16 was obtained when polymerization was conducted with molar ratio of monomer to initiator ([M]/[I]) of 12000 for 24 h at 140°C.     

A new method to deal with fuzzy classification problems by tuning membership functions for fuzzy classification systems

Abstract

This paper presents a new method to construct and tune membership functions and generate fuzzy classification rules from training instances for handling the Iris data classification problem. First, we find two attributes of the Iris data from the training instances that are suitable to serve as classification criteria. Then, we construct and tune the membership functions of these two attributes and generate fuzzy classification rules from the training instances. The proposed method generates the same number of fuzzy classification rules as the number of species of the training instances. It generates fewer fuzzy classification rules and can get a higher average classification accuracy rate than the existing methods.     

基于回归模型的高职院校生均成本研究

MATLAB是一种高度集成的计算机语言,具有强大的科学计算功能及灵活的程序设计流程。文中充分利用MATLAB的优势,通过非线性回归分析函数nlinfit建立了两个非线性回归模型,对我国高职院校的生均成本进行了一些研究。     

Changes in Molecular Characteristics of Cereal Carbohydrates after Processing and Digestion

Different extraction, purification and digestion methods were used to investigate the molecular properties of carbohydrates in arabinoxylan and β-glucan concentrates, dietary fiber (DF) rich breads and ileum content of bread fed pigs. The breads studied were: a low DF wheat bread (WF), whole meal rye bread (GR), rye bread with kernels (RK), wheat bread supplemented with wheat arabinoxylan concentrate (AX) and wheat bread supplemented with oat β-glucan concentrate (BG). The weight average molecular weight (M_w) of extractable carbohydrates in β-glucan concentrate decreased eight-fold after inclusion in the BG bread when exposed to in vitro digestion, while the M_w of purified extractable carbohydrates in AX bread was reduced two-fold, and remained almost unaffected until reaching the terminal ileum of pigs. Similarly, the M_w of purified extractable carbohydrates in GR and RK bread was not significantly changed in the ileum. The AX bread resulted in the highest concentration of dissolved arabinoxylan in the ileum among all the breads that caused a substantial increased in ileal AX viscosity. Nevertheless, for none of the breads, the M_w of extractable carbohydrates was related neither to the bread extract nor ileal viscosity.     

Estimation and forecasting of machine health condition using ARMA/GARCH model

This paper proposes the hybrid model of autoregressive moving average (ARMA) and generalized autoregressive conditional heteroscedasticity (GARCH) to estimate and forecast the machine state based on vibration signal. The main idea in this study is to employ the linear ARMA model and the nonlinear GARCH model to explain the wear and fault condition of machine, respectively. The successful outcomes of the ARMA/GARCH prediction model can give obvious explanation for future states of machine, which enhance the worth of machine condition monitoring as well as condition-based maintenance in practical applications. The advance of the proposed model is verified in empirical results as applying for a real system of a methane compressor in a petrochemical plant.     

On multiple portmanteau tests*

Abstract. The portmanteau statistic based on the first m residual autocorrelations is used for diagnostic checks on the adequacy of fitting a model with varying m. In this article, we propose an approximation of the joint probability of multiple portmanteau tests with different degrees of freedom (DF). This distribution is easy to compute when all DF are even integers; its empirical behaviour is clarified in terms of asymptotic theory.     

An Approach to Analyse Errors Introduced in the Random Grid Strain Measurement Method

Abstract: The present work refers to the errors imposed by the recently introduced random‐grid mesh‐free full field strain measurement method. Excluding systematic errors of the digital camera, the method itself is not an error‐free procedure. A possible cause of errors could be the misplacement of the spot‐centre (centroid) with regard of the spot boundaries. Another cause of errors is the limited order of approximation in the field function. A third one, emerges from the so‐called ‘sub‐pixel effect’. This kind of error is difficult to trace, so direct comparison between the results of the method and exact solutions is required. In the present work, proper analytical or numerical derivations of those errors are presented and reasonable upper limits are estimated. Finally, numerical and experimental examples are presented to demonstrate the accuracy of the method.     

Smart utilization of renewable energy sources in a microgrid system integrated with plug‐in hybrid electric vehicles

Mass roll‐out of plug‐in hybrid electric vehicles (PHEVs) and significant penetration of renewable energy sources in distribution system play a major role in delivering low carbon environment. However, placing and utilizing these units randomly result in overloading, increased power loss, and reduced voltage profile. This paper responds to these technical challenges by using a strategic placement method for locating the distributed generation (DG) and the charging station (CS) of PHEVs in a multi‐zone distribution system. For simultaneously scheduling of these units in each zone, the smart energy management framework is proposed in this paper. Apart from usual energy management constraints, this paper also incorporates the real‐time constraints involving the capacity of PHEV batteries, the mobility pattern, and the power level of the charging infrastructure. The simulation studies are carried out for each hour of a day. To cope with this time constraint execution, particle swarm optimization algorithm‐based approach is used. The proposed framework is tested in IEEE 33 and IEEE 69 bus radial distribution system. The obtained results imply that the presented energy management framework provides maximum profits for the vehicle owner, and meanwhile it fulfills preferences of the user in each zone simultaneously.