基于MATLAB(SIMULINK)的电弧炉电极调节系统FUZZY-PD控制器的仿真

介绍了采用MATLAB V5.2提供的模糊逻辑工具箱来设计研究电孤纺电极调节系统中的模糊－－PD控制器，讨论了在SIMULINK环境下模糊－PD控制器的参数自调速原理、结构、建立模糊控制规则库和模糊推论方法，并给出仿真结果与结论。     

广义线性模型(六)

本讲座是广义线性模型这个题目的一个比较系统的介绍。主要分 3部分 :建模、统计分析与模型选择和诊断。写作时依据的主要参考资料是L .Fahrmeir等人的 :《MultivariateStatisticalModel ingBasedonGeneralizedLinearModles》。     

Multi-scale Young measures

We introduce multi-scale Young measures to deal with problems where multi-scale phenomena are relevant. We prove some interesting representation results that allow the use of these families of measures in practice, and illustrate its applicability by treating, from this perspective, multi-scale convergence and homogenization of multiple integrals.

     

Reference priors for exponential families with simple quadratic variance function

Reference analysis is one of the most successful general methods to derive noninformative prior distributions. In practice, however, reference priors are often difficult to obtain. Recently developed theory for conditionally reducible natural exponential families identifies an attractive reparameterization which allows one, among other things, to construct an enriched conjugate prior. In this paper, under the assumption that the variance function is simple quadratic, the order-invariant group reference prior for the above parameter is found. Furthermore, group reference priors for the mean- and natural parameter of the families are obtained. A brief discussion of the frequentist coverage properties is also presented. The theory is illustrated for the multinomial and negative-multinomial family. Posterior computations are especially straightforward due to the fact that the resulting reference distributions belong to the corresponding enriched conjugate family. A substantive application of the theory relates to the construction of reference priors for the Bayesian analysis of two-way contingency tables with respect to two alternative parameterizations.     

A Generalized Markov Sampler

A recent development of the Markov chain Monte Carlo (MCMC) technique is the emergence of MCMC samplers that allow transitions between different models. Such samplers make possible a range of computational tasks involving models, including model selection, model evaluation, model averaging and hypothesis testing. An example of this type of sampler is the reversible jump MCMC sampler, which is a generalization of the Metropolis–Hastings algorithm. Here, we present a new MCMC sampler of this type. The new sampler is a generalization of the Gibbs sampler, but somewhat surprisingly, it also turns out to encompass as particular cases all of the well-known MCMC samplers, including those of Metropolis, Barker, and Hastings. Moreover, the new sampler generalizes the reversible jump MCMC. It therefore appears to be a very general framework for MCMC sampling. This paper describes the new sampler and illustrates its use in three applications in Computational Biology, specifically determination of consensus sequences, phylogenetic inference and delineation of isochores via multiple change-point analysis.     

Entropic criterion for model selection

Model or variable selection is usually achieved through ranking models according to the increasing order of preference. One of methods is applying Kullback–Leibler distance or relative entropy as a selection criterion. Yet that will raise two questions, why use this criterion and are there any other criteria. Besides, conventional approaches require a reference prior, which is usually difficult to get. Following the logic of inductive inference proposed by Caticha [Relative entropy and inductive inference, in: G. Erickson, Y. Zhai (Eds.), Bayesian Inference and Maximum Entropy Methods in Science and Engineering, AIP Conference Proceedings, vol. 707, 2004 (available from arXiv.org/abs/physics/0311093)], we show relative entropy to be a unique criterion, which requires no prior information and can be applied to different fields. We examine this criterion by considering a physical problem, simple fluids, and results are promising.     

Dispersion of silica nano-particles in sol-gel hybrid resins for fabrication of multi-scale hybrid nanocomposite

Multi-scale hybrid nanocomposites containing both ∼15 nm silica colloids and ∼2 nm oligosiloxanes in a methacryl polymer matrix were newly designed and fabricated. Colloidal silica sols were dispersed in methacryl oligosiloxanes nano-hybrid resins synthesized by sol-gel reaction of methacryloxypropylmethoxysilane and diphenylsilanediol. On the basis of TEM and SANS analyses, it was confirmed that the silica colloids were compatibly dispersed and different sizes of colloidal silica and oligosiloxanes co-exist in the solutions. Multi-scale hybrid nanocomposites fabricated by UV and thermal curing with incorporation of silica colloids in the nano-hybrid materials show enhanced mechanical and thermal characteristics.     

Viscoelastic response and interlaminar delamination resistance of epoxy/glass fiber/functionalized graphene oxide multi-scale composites

Graphene oxide (GO) was functionalized using three different diamines, namely ethylenediamine (EDA), 4,4′-diaminodiphenyl sulfone (DDS) and p-phenylenediamine (PPD) to reinforce an epoxy/glass fiber (EP/GF) composite laminate, with the aim of improving the overall composite mechanical performance. Different mechanical characterization techniques were used to determine the mechanical performance, including: tensile stress strain, double cantilever beam (DCB) mode-I fracture toughness and dynamic mechanical thermal analysis (DMTA). Scanning electron microscopy (SEM) was used to support the results and conclusions. The results demonstrated remarkable enhancements in the mechanical performance of EP/GF composite laminates by incorporation of functionalized graphene oxide (FGO) nanofiller, whilst the mechanical performance of the GO reinforced composite only improved marginally. Finally, the mechanical performance of the EP/GF/FGO multi-scale composites was found to be dependent on the type of FGO functional groups; of which EDA exhibited the highest performance. These investigations confirmed that the EDA-FGO-reinforced EP/GF composites possess excellent potential to be used as multifunctional engineering materials in industrial applications.     

MASS TRANSFER EXPERIMENTS ON SINGLE IRREGULAR-SHAPED PARTICLES

Mass transfer from irregular-shaped naphthalene particles (100-200 inn in size) was studitd in an electrodynamic balance. Charged particles were suspended in an electrostatic field directly in line with a calibrated air jet. Mass and size change histories were obtained under ambient conditions, and under steady- and pulsed-flow conditions. For natural convection, the time-averaged Sherwood number was similar to that for spheres. Forced-convection Sherwood number under steady-flow conditions was strongly dependent on particle shape and panicle Reynolds number, and was consistently higher than values predicted for spheres at comparable Reynolds numbers. This study validates the technique and indicates the shape effect on mass transfer form single particles.     

Identification,characterization and evolution of non-local quasi-Lagrangian structures in turbulence

The recent progress on non-local Lagrangian and quasi-Lagrangian structures in turbulence is reviewed. The quasi-Lagrangian structures, e.g., vortex surfaces in vis-cous flow, gas-liquid interfaces in multi-phase flow, and flame fronts in premixed combustion, can show essential Lagrangian following properties, but they are able to have topological changes in the temporal evolution. In addition, they can represent or influence the turbulent flow field. The challenges for the investigation of the non-local structures include their identification, characterization, and evolution. The improving understanding of the quasi-Lagrangian struc-tures is expected to be helpful to elucidate crucial dynamics and develop structure-based predictive models in turbulence.