用矢量图分析丰田A340E自动变速器动力反传

用矢量图来分析丰田A340E自动变速器动力反传是能直观、快速得知发动机在该档位是否具有制动作用,然后通过试车可以用来判断各个执行元件坏在什么地方。

Estimation of kinetics parameters in Beckmann rearrangement of cyclohexanone oxime using genetic algorithm

Beckmann rearrangement mechanism of cyclohexanone oxime, based on the characteristic of self-catalyzed reaction and polymorphism was proposed. According to the suggested mechanism, the basic approach was the rearrangement of OXH+ while the SO3 acts as dehydrating agent and OXSO3 can turn to CPLSO3 ultimately. Considering self-catalyzed reaction between OXSO3 and CPLH+, kinetic model for Beckmann rearrangement was established. Corresponding parameters were estimated by using float genetic algorithm （GA） and simulation results agree well with the experimental data below -19.3℃. Industrial equipment was simulated and analyzed. Effects of key process parameters such as molar ratio of sulfuric acid to oxime and circulation ratio on the residual oxime are also discussed. The results show that the caprolactam exists as CPLH+ finally in oleum and the minimum molecular ratio of sulfuric acid to oxime can be 0.5 theoretically.

Pressure Fluctuation in the Submerged Circulative Impinging Stream Reactor

Pressure fluctuation in the submerged circulative impinging stream reactor （SCISR） is studied by measuring the dynamic pressure with micro pressure sensors of high accuracy, with water as the process material. Experimental results show that the maximum amplitude of fluctuation can be up to about 1.6kPa. On the power spectra the fluctuation is relatively concentrated in the range of 〈1000Hz, with some weak peeks in acoustic wave range. The space profile of intensive fluctuation region in the reactor is determined. The region is found to take the form of a couple truncated cones of empty core, with coincided bottoms, and is symmetrical with respect to the impinging plane and approximately symmetrical about the axis, essentially independent of u0. The integral intensity of fluctuation increases as the impinging velocity, Uo increasing.

Estimation of Kinetic Parameters for Autocatalytic Oxidation of Cyclohexane Based on a Modified Adaptive Genetic Algorithm

A modified genetic algorithm of multiple selection strategies, crossover strategies and adaptive operator is constructed, and it is used to estimate the kinetic parameters in autocatalytic oxidation of cyclohexane. The influences of selection strategy, crossover strategy and mutation strategy on algorithm performance are discussed. This algorithm with a specially designed adaptive operator avoids the problem of local optimum usually associated with using standard genetic algorithm and simplex method. The kinetic parameters obtained from the modified genetic algorithm are credible and the calculation results using these parameters agree well with experimental data. Furthermore, a new kinetic model of cyclohexane autocatalytic oxidation is established and the kinetic parameters are estimated by using the modified genetic algorithm.

Kinetic study and kinetic parameters of lipase-catalyzed glycerolysis of sardine oil in a homogeneous medium

The production of polyunsaturated fatty acids （PUFAs） concentrates by enzymatic catalysis has gained interest due to their stereospecificity and the milder conditions employed compared to the use of inorganic catalysts. The enzymatic glycerolysis of sardine oil by Lipozymeò435 to get PUFA concentrates in the forms of di‐and monoacylglycerols （DAGs, MAGs） in an optimized amount of tert‐butanol as the organic solvent was studied. First, mass transfer limitation of the reaction sys‐tem was analyzed. The effects of different operating variables such as lipase loading, temperature and feed composition were investigated. A semi‐empirical kinetic model based on the reversible elementary reactions of glycerolysis and hydrolysis of the glycerides was employed to correlate the experimental kinetic data. A molar ratio glycerol：oil of 3：1 was the optimum, which produced more than 84 wt%of MAG at 323 K. A comparison with other glycerolysis systems was performed using MAG yield, reaction rate and significance of kinetic parameters.

COMPLEXITY AND CHAOTIC DYNAMICS OF ROCK FAULTING

Fault is a complex dynamic system controlled by the coupling of rock texture, reaction, fluid flow,stress, and rock deformation mechanism. A coupled reaction-transport- mechanical dynamic model for fault system is established and described in this paper. An example is presented for the Shuikoushan deposit, Hunan. The results of dynamic simulation indicate that the evolution and magnitude of fracture permeability of different rocks are different, and that faulting can enhance the spatial heterogeneity of rock permeability and facilitate fluid flow and mineralization in local fault zone. The pressure for a fault usually shows a variation mode of aperiodic oscillation with time, which reflects the chaotic behavior of the evolution of a fault.

Development of Airfoils Based on Their Aerodynamic Characteristics Using Artificial Neural Networks

One of the main concerns in Engineering nowadays is the development of aircrafts of low consumption and high performance. For this purpose, airfoils are studied and designed to have an elevated lift coefficient and a low drag coefficient, thus generating a highly efficient airfoil. The higher the efficiency value is, the lower the aircraft fuel consumption will be; thus improving its performance. In this sense, this work aims to develop a tool for airfoil creation from some desired characteristics, such as the lift and drag coefficients and maximum efficiency rate, using an algorithm based on an ANN （artificial neural network）. In order to do so, a database of aerodynamic characteristics with a total of 300 airfoils was initially collected from the XFoil software. Then, through a routine implemented in the MATLAB software, network architectures of one, two, three and four modules were trained, using the back propagation algorithm and momentum. The cross-validation technique was applied to analyze the results, evaluating which network possesses the lowest value in RMS （root-mean-square） error. In this case, the best result obtained was from the two-module architecture with two hidden neuron layers. The airfoils developed by this network, in the regions with the lowest RMS, were compared to the same airfoils imported to XFoil. The presented work offers as a contribution, in relation to other works involving ANN applied to fluid mechanics, the development of airfoils from their aerodynamic characteristics.

Prediction of Wing Aerodynamic Performance in Rain Using Neural Net

A new method for prediction of wing aerodynamic performance in rain condition was presented.Three-and four-layer artificial neural networks based on improved algorithm for error Back Propagation(BP)network were respectively built.Detailed approaches to determine the optical parameters for network model were introduced and the specific steps for applying BP network model to predict wing aerodynamic performance in rain were given.On this basis,the established optimal three-and four-layer BP network model was used for this prediction.Results indicate that both of the network models are appropriate for predicting wing aerodynamic performance in rain.The sum of square error level produced by two models is less than 0.2%,and the prediction accuracy by four-layer network model is higher than that of three-layer network.