多级离心压缩机性能预测软件设计

为了缩短设计和生产周期,降低设计成本,在保证性能可靠的基础上,实现多级离心式压缩机的系列化、标准化和通用化,研究了采用模型级法设计的多级离心压缩机的整机性能进行快速预测的方法。并基于MATLAB平台,设计了多级离心压缩机性能预测软件。软件可根据各级模型机的试验性能数据计算整机性能曲线,以及在特定设计运行工况下的整机和各级性能参数。软件界面简洁,操作方便,结果显示直观,并能以文本形式输出,能帮助设计师提高模化选型效率。

双零级模型法测定地塞米松植入剂的释放度

在地塞米松植入剂(dexamethasone implants,DI)的释放度实验中,地塞米松(dexamethasone,DXM)的降解不可避免,导致流池法测定的释放度结果仅达到70%~80%时即发生释放度曲线下降的现象。研究表明,DI在释放度实验每个取样区间制剂中的药物呈近似零级释放,并且DXM在释放介质水(含0.05 mg·mL-1苯扎氯铵)中按零级速率降解。依据上述结果,本文建立的双零级模型推导出每个取样区间的释放度Ri的计算公式为[Rim-R(i-1)m×(Cin/Ci0)]×2/(1+Cin/Ci0)。在每个取样区间,只需要测定初期和末期的释放介质,以及同法实验的原料液溶液中的主药量,即可计算包括降解药物在内的药物释放总量。本文还分析了双零级模型法测定的释放度曲线产生波动的原因和误差来源,并提出解决方案。结果表明,双零级模型较好地解决了DI在经典释放度测定法中遇到的问题,可以为长效注射剂释放度实验中药物降解的定量表征提供一种方案。

Nonlinear Auto-Companding Method for Behavioral Modeling of Switched-Current Circuits

A wavelet collocation method with nonlinear auto companding is proposed for behavioral modeling of switched current circuits.The companding function is automatically constructed according to the initial error distribution obtained through approximating the input output function of the SI circuit by conventional wavelet collocation method.In practical applications,the proposed method is a general purpose approach,by which both the small signal effect and the large signal effect are modeled in a unified formulation to ease the process of modeling and simulation.Compared with the published modeling approaches,the proposed nonlinear auto companding method works more efficiently not only in controlling the error distribution but also in reducing the modeling errors.To demonstrate the promising features of the proposed method,several SI circuits are employed as examples to be modeled and simulated.

Application of the catastrophe progression method in predicting coal and gas outburst

Based on catastrophe theory,we used the catastrophe progression method to predict the risk of coal and gas outbursts in coal mines.According to the major factors affecting coal and gas outbursts,we built a comprehensive evaluation index system and a coal and gas outburst prediction model.In addition,we performed a standard transformation for each index system;based on the degree the various indices affect the risk of an outburst,to make the data dimensionless.Based on the outburst data from eight mines,we determined catastrophe progression values and verified these values.The results show that:1) converting multi-dimensional problems into one-dimensional problems using this catastrophe progression method can simplify the steps of predicting coal and gas outbursts;2) when pre-determined catastrophe progression values are used to predict coal and gas outbursts,the predicting accuracy rate can be as high as 87.5%;3) the various coal mines have different factors inducing outbursts with varying importance of these factors and 4) the catastrophe progression values,calculated based on these factors,can be used effectively to predict the risk of outbursts in coal mines.

Gate-Capacitance-Shift Approach and Compact Modeling for Quantum Mechanical Effects in Poly-Gates

A new approach,gate-capacitance-shift (GCS) approach,is described for compact modeling.This approach is piecewise for various physical effects and comprises the gate-bias-dependent nature of corrections in the nanoscale regime.Additionally,an approximate-analytical solution to the quantum mechanical (QM) effects in polysilicon (poly)-gates is obtained based on the density gradient model.It is then combined with the GCS approach to develop a compact model for these effects.The model results tally well with numerical simulation.Both the model results and simulation results indicate that the QM effects in poly-gates of nanoscale MOSFETs are non-negligible and have an opposite influence on the device characteristics as the poly-depletion (PD) effects do.

Performance Prediction of Structured Packing Column for Cryogenic Air Separation with Hybrid Model

A detailed investigation of a thermodynamic process in a structured packing distillation column is of great impor- tance in prediction of process efficiency. In order to keep the simplicity of an equilibrium stage model and the accu- racy of a non-equilibrium stage model, a hybrid model is developed to predict the structured packing column in cryogenic air separation. A general solution process for the equilibrium stage model is developed to solve the set of equations of the hybrid model, in which a separation efficiency function is introduced to obtain the resulting tri-diagonal matrix and its solution by the Thomas algorithm. As an example, the algorithm is applied to analyze an upper column of a cryogenic air separation plant with the capacity of 17000 m3·h-1. Rigorous simulations are conducted using Aspen RATEFRAC module to validate the approach. The temperature and composition distributions are in a good agreement with the two methods. The effects of inlet/outlet position and flow rate on the temperature and composition distributions in the column are analyzed. The results demonstrate that the hybrid model and the solution algorithms are effective in analvzin~ the distillation process for a a cryogenic structured packing column.

Assessing the kinetic model of hydro-distillation and chemical composition ofAquilaria malaccensis leaves essential oil

This study aimed to model the kinetic of hydro-distillation of Aquilaria malaccensis leaves oil in order to understand and optimize the extraction process. In addition, this study, for the first time, aimed to identify the chemical compositions of the A. rnalaccensis leave-oil. By assessing both first-order kinetic model and the model of simultaneous washing and diffusion, the result indicated that the model of simultaneous washing and diffusion better describes the hydro-distillation mechanism of the essential oil from A. rnalaccensis leaves. The optimum time, solid to liquid ratio, and the heating power for extracting the highest amount of essential oil were found to be around 3 h, 1：10 （g. ml-1）, and 300 W respectively. Yellow essential oil with a strong smell and a yield of 0.05 v/w was extracted by hydro-distillation Clevenger apparatus. Chemical compounds of the essential oil were analyzed using gas chromatography-mass spectroscopy （GC/MS）, which resulted in identification of 42 compounds that constitute 93% of essential oil. Among the identified components, Pentadecanal （32.082%）, 9-Octadecenal, （Z） （15.894%）, and Tetradecanal （6.927%） were the major compounds. Considering the fact that all the identified major components possess pesticidal properties, A. malaccensis leaves can be regarded as a promising natural source for producing pesticides.

Discriminant Genetic Algorithm Extended (DGAE) model for seasonal sand and dust storm prediction

Here we use a Discriminant Genetic Algorithm Extended (DGAE) model to diagnose and predict seasonal sand and dust storm (SDS) activities occurring in Northeast Asia. The study employed the regular meteorological data, including surface data, upper air data, and NCEP reanalysis data, collected from 1980–2006. The regional, seasonal, and annual differences of 3-D atmospheric circulation structures and SDS activities in the context of spatial and temporal distributions were given. Genetic algorithms were introduced with the further extension of promoting SDS seasonal predication from multi-level resolution. Genetic probability was used as a substitute for posterior probability of multi-level discriminants, to show the dual characteristics of crossover inheritance and mutation and to build a non-linear adaptability function in line with extended genetic algorithms. This has unveiled the spatial distribution of the maximum adaptability, allowing the forecast field to be defined by the population with the largest probability, and made discriminant genetic extension possible. In addition, the effort has led to the establishment of a regional model for predicting seasonal SDS activities in East Asia. The model was tested to predict the spring SDS activities occurring in North China from 2007 to 2009. The experimental forecast resulted in highly discriminant intensity ratings and regional distributions of SDS activities, which are a meaningful reference for seasonal SDS predictions in the future.

Dynamical analysis of the avian-human influenza epidemic model using multistage analytical method

In this paper, analytical result of avian-human influenza epidemic model has been inves- tigated by applying homotopy analysis method （HAM） and by expanding it to hybrid numeric-analytic method which is known as multistage HAM （MSHAM）. HAM is an algorithm which gives us the approximate solution of the problem in an arrangement of time interims and by modifying it to multistage one. Some advantages such as flexibility of picking the auxiliary linear operator and the auxiliary parameter are emerged, that leads us to achieve some excellent results in this work. Furthermore, in this analyti- cal work, obtained results are compared and reported with numerical ones which were obtained previously from methods such as the Runge-Kutta （RK4） method.

A model for parameter estimation of multistage centrifugal compressor and compressor performance analysis using genetic algorithm

A model for performance prediction of multistage centrifugal compressor is proposed. The model allows the users to predict the compressor performance, e.g. pressure ratio, efficiency and losses using the compressor geometric information and speed by a stage stacking calculation based on the characteristics of each stage. To develop the compressor elemental stage charac- teristics, the compressor losses, such as incidence losses and friction losses, are mathematically modeled. For a composite sys- tems, for instance a gas turbine power plant, the performance of the multistage centrifugal compressor can be evaluated. Since some important parameters of the compressor model, e.g., the slip factor or, shock loss coefficient （and reference diameter DI, are hard to be determined by empirical laws, a genetic algorithm （GA） is used to solve the parameter estimation problem of the proposed model, and in turn the compressor performance analysis and parameters study are performed. The surge line for the multistage centrifugal compressor can also be determined from the simulation results. Furthermore, the model presented here provides a valuable tool for evaluating the multistage centrifugal compressor performance as a function of various operation parameters.