Spectral properties of diesel fuel droplets

Absorption spectra of several types of diesel fuel are studied experimentally. Index of refraction of these fuels is calculated using subtractive Kramers-Krönig analysis. The ageing process of fuels is simulated by prolonged boiling. Radiative properties of diesel fuel droplets are calculated using the Mie theory and a simplified approach, based on approximations of absorption and scattering efficiency factors. It is pointed out that the accuracy of the simplified approach is sufficient for practical applications in the visible and infrared ranges, for various types of diesel fuel, and for droplet radii in the range from 5 to 50 μm. The monodisperse approximation is shown to be applicable for the analysis of infrared radiative properties of realistic polydisperse diesel fuel sprays.     

Classification of audio radar signals using radial basis function neural networks

Radial basis function (RBF) neural networks are used to classify real-life audio radar signals that are collected by a ground surveillance radar mounted on a tank. Currently, a human operator is required to operate the radar system to discern among signals bouncing off tanks, vehicles, planes, and so on. The objective of this project is to investigate the possibility of using a neural network to perform this target recognition task, with the aim of reducing the number of personnel required in a tank. Different signal classification methods in the neural net literature are considered. The first method employs a linear autoregressive (AR) model to extract linear features of the audio data, and then perform classification on these features, i.e, the AR coefficients. AR coefficient estimations based on least squares and higher order statistics are considered in this study. The second approach uses nonlinear predictors to model the audio data and then classifies the signals according to the prediction errors. The real-life audio radar data set used here was collected by an AN/PPS-15 ground surveillance radar and consists of 13 different target classes, which include men marching, a man walking, airplanes, a man crawling, and boats, etc. It is found that each classification method has some classes which are difficult to classify. Overall, the AR feature extraction approach is most effective and has a correct classification rate of 88% for the training data and 67% for data not used for training.     

Mechanical spectroscopy in commercial Fe–6 wt.% Si alloys between 400 and 1000 K

Mechanical spectroscopy, neutron diffraction and differential scanning calorimetry (DSC) were performed on commercial Fe–6 wt.% Si alloy after quenching from high temperature. The damping spectrum shows a peak at around 800 K and an associated modulus defect. The modulus shows an increase during the second and subsequent heating runs. In addition, an anomaly in the modulus behavior has been found at around 400 K. Different thermal treatments allows to obtain two different recovery degrees of the quenched-in defects. The influence of the recovery degree on the 800 K internal friction peak and on the anelastic modulus has been evaluated and confirm the validity of the grain boundary mechanism associated to this peak. Experimental results are discussed on the basis of recovery and ordering processes.     

Extractive Properties of Synergistic Mixtures of Dipicolinic Acid Diamides and Chlorinated Cobalt Dicarbollide

Extraction of Cs, Sr, Eu, U, Np, and Am with mixtures of dipicolinic acid diamides with chlorinated cobalt dicarbollide was studied. A synergistic effect was revealed.     

An Acoustic Converter Used to Measure Ionizing Radiation Energy Loss

A monitor is proposed based on ultrasonic production when ionizing radiation passes through a medium. The recording element is a 0.2 mm aluminum plate mounted in a ceramic acoustic converter AC in the form of a wedge of thickness 2 mm. The low plate thickness minimizes the beam parameter distortion, while special technology used in the AC provides high sensitivity. The device has been calibrated in the proton beam from the ITEP accelerator at 200 MeV with 2·10⁹–6·10¹⁰ particles in a pulse and a pulse length of 70 nsec.     

An investigation of sugar extraction methods and the use of microwave power for date syrup processing: efficiency and color related considerations.

This study investigates the effect of extraction methods on the color of date syrup and the potential use of microwave power for syrup processing. Sugar solutions were extracted from dates by boiling, soaking and blending. Color and sugar content of the extracted solutions were measured, and the percentage of sugar extracted form the total fruit sugar determined. Boiling was found to be the most efficient method of extraction whereby 74% of total samples sugar was extracted. In contrast, only 54.2% of fruit sugar was extracted by blending and 42% by soaking. In addition, solutions extracted by soaking and blending had a foaming problem in the subsequent concentration process. The extraction method had no effect on the product final color. The extracted solution was concentrated using two heating methods: conventional and microwave heating at a 600 W capacity and a frequency of 2450 MHz applied at three power levels: 10, 7, and 6. In the heating process, 180 minutes were needed to achieve a 77% degrees Brix using convective heating, while it took 81, 138, and 166 minutes of microwave heating at power level 10, 7, and 6, respectively to achieve the same concentration. Water activity of the syrup was measured within a sugar content range of 50 to 80% degrees Brix and the sugar concentration at which the product is shelf stable was determined at 76%.     

Reactions Between Ingredients in Binary Silicate Glasses

It is demonstrated that the density of binary glasses upon variation of the molar content of the modifier in their compositions obeys a parabolic dependence, whose parameters can be used to estimate the extent and type of reactions between the components. The reaction parameters in glasses that are prone to liquation are lower by an order of magnitude and have the negative sign.     

Modeling of the Solubility of Solid High-Molecular-Weight Organic Substances in Supercritical Fluids

A method is proposed to calculate the solubility of solid high-molecular-weight substances in organic supercritical fluids on the basis of the Soave and Peng–Robinson equations of state. The mixing rules are modified taking into account the Gibbs energy of mixing calculated for a particular equation of state. The accuracy of calculation of the concentration of the substance dissolved in supercritical fluids is analyzed for different mixing rules. The modeling results are compared with observed data.