Application of Romero García method to the degradation process of DGEBA/ETDA filled with ultra fine metallic copper

Summary The thermal properties of an epoxy resin (diglycidyl ether Bisphenol A, DGEBA) cured with a primary amine (ethylenediamine, ETDA) and filled with 10, 20 and 30 wt. % of ultra fine copper particles were analyzed. The thermal results were evaluated by means of the Romero-Garcia method, which allowed to obtain the resin degradation kinetic parameters, as well as the possible decomposition mechanism. From the obtained results is possible to infer that higger copper content strongly affects the degradation process of the epoxy resin, which causes a drop off on the composites thermal stability. This behavior could be attributed to water presence, being this effect less pronounced for the resin with 10 wt. % copper and unfilled resin. Regarding to decomposition mechanism, three way transport showed the best correlation for all samples.     

Effective parameters of static coupled physicomechanical field in matrix composites

Conclusions It is shown that the problem of evaluating the effective parameters of composites for a wide range of stationary coupled fields is reduced to examining uncoupled fields.The multiparticle method of the effective field was generalized with special reference to the problems of examining the static coupled physicomechanical fields in composites.Translated from Fiziko-Khimicheskaya Mekhanika Materialov, Vol. 27, No. 4, pp. 105–111, July–August, 1991.     

MODELING WATER LOSS DURING FRYING OF POTATO STRIPS: EFFECT OF SOLUTE IMPREGNATION

The effect of solute impregnation on water loss and oil uptake during potato strip frying was studied. Blanched potato strips were impregnated at 25°C by soaking in a solution of sucrose-NaCl-water, 20-5-75% by weight. After rinsing and air drying, strips were deep fried in sunflower oil at 160, 170 and 180°C. A control treatment, consisting of potato strips blanched but not soaked and later air dried was also conducted. Solute impregnation provided a decrease of the oil uptake. Two models, based on Fick's law were used to describe water loss during frying. The first one is the classic model with an effective moisture diffusion coefficient assumed a constant value. The second model considers that diffusion coefficient varies during the frying process. For a given frying temperature, constant diffusion coefficient for control potatoes resulted in lower values than the impregnated ones. The variable diffusivity model showed a two-stage behavior: during the first stage of frying, diffusion coefficient increased with frying temperatures, but from a given time on an inverse behavior began. This last fact was found to be related to an increase of the measured peak force needed to penetrate the potato crust.     

Ti-silicalite as catalyst for gas-phase ammoximation of cyclohexanone with molecular oxygen

The catalyst behaviour of titanium silicalite, which was found the most active and selective catalyst for liquid-phase ammoximation of cyclohexanone to the corresponding oxime with hydrogen peroxide, was investigated in the gas-phase ammoximation with molecular oxygen in and compared with those of pure silicalite and samples of vanadium and chromium silicalites. The results showed that Ti-silicalite is a selective catalyst not only in the reaction with hydrogen peroxide but also in the reaction with molecular oxygen. However, a big limitation was found in the poor activity of the silicalites which do not allow to reach high oxime yields.     

Spectral predictions for pulse interval and width modulation

An expression for the frequency spectrum of pulse interval and width modulation (PIWM) is presented. Experimental results obtained have shown close agreement with spectral predictions from the formula. Performance figures are also included from a practical PIWM optical-fibre transmission system intended for use with TV and video signals.<>     

Laser stimulated low-temperature crystallization of amorphous silicon

Laser annealing of amorphous silicon (a-Si) at different initial temperatures (77 and 300 K) has been studied. It is established that the laser-stimulated crystallization of silicon is possible at relatively low temperatures. A theoretical model is proposed, which explains this phenomenon by melting via the electron mechanism followed by recrystallization.     

Efficient particle filter-based processing algorithm for clutter suppression and IR point targets enhancement

A novel soft decision-based median subtraction filter is presented for clutter suppression and infrared (IR) point targets enhancement. The decision is made based on a jump Markov model and its state and parameter estimation using a particle filter. The scheme is compared with other conventional clutter background removal techniques and good results are obtained.     

Application of the blind source separation method to feature extraction of machine sound signals

As the result of vibration emission in air, a machine sound signal carries important information about the working condition of machinery. But in practice, the sound signal is typically received with a very low signal-to-noise ratio. To obtain features of the original sound signal, uncorrelated sound signals must be removed and the wavelet coefficients related to fault condition must be retrieved. In this paper, the blind source separation technique is used to recover the wavelet coefficients of a monitored source from complex observed signals. Since in the proposed blind source separation (BSS) algorithms it is generally assumed that the number of sources is known, the Gerschgorin disk estimator method is introduced to determine the number of sound sources before applying the BSS method. This method can estimate the number of sound sources under non-Gaussian and non-white noise conditions. Then, the partial singular value analysis method is used to select these significant observations for BSS analysis. This method ensures that signals are separated with the smallest distortion. Afterwards, the time-frequency separation algorithm, converted to a suitable BSS algorithm for the separation of a non-stationary signal, is introduced. The transfer channel between observations and sources and the wavelet coefficients of the source signals can be blindly identified via this algorithm. The reconstructed wavelet coefficients can be used for diagnosis. Finally, the separation results obtained from the observed signals recorded in a semi-anechoic chamber demonstrate the effectiveness of the presented methods .