Boiling: Size Distribution of Bubbles as Demanded by the Principle of Maximum Information

The principle of maximum informational entropy is used to find the probability density function for the departure radius of a bubble in boiling on a solid surface. A general relation is derived, which leads to particular expressions.     

The Effect of Structural Defects on the Thermal Conductivity of ZnS, ZnSe, and CdTe Polycrystals

ZnS, ZnSe, and CdTe polycrystals are experimentally investigated. Mechanisms are treated which restrict the thermal conductivity in samples prepared by recrystallization pressing and by deposition from the vapor phase and subjected to additional strain. Anomalies are observed on the temperature dependences of the thermal resistance of investigated samples, which are due to the special features of their phonon spectra and to the variation of the contribution made by longitudinal and transverse phonon branches to the heat transfer in the Debye temperature region and higher.     

Filtration of Non-Newtonian Hydrocarbon Fluid in a High-Frequency Electromagnetic Field

The paper gives the results of experimental investigations of the initial pressure gradient of bituminous oil and the time dependences of variation of the temperature in a formation model and of the well production rate in a microwave-frequency electromagnetic field. The effect of strong decay of the non-Newtonian properties of bituminous oil is revealed. The nonuniformity of temperature distribution over the formation thickness is demonstrated, which depends on the initial production rate of the well and on the duration of stimulation of the bottom-hole zone of formation.     

Application of autoregressive spectral analysis to missing data problems

Time series solutions for spectral analysis in missing data problems use reconstruction of the missing data, or a maximum likelihood approach that analyzes only the available measured data. Maximum likelihood estimation yields the most accurate spectra. An approximate maximum likelihood algorithm is presented that uses only previous observations falling in a finite interval to compute the likelihood, instead of all previous observations. The resulting nonlinear estimation algorithm requires no user-provided initial solution, is suited for order selection, and can give very accurate spectra even if less than 10% of the data remains.     

Finite sample properties of ARMA order selection

The cost of order selection is defined as the loss in model quality due to selection. It is the difference between the quality of the best of all available candidate models that have been estimated from a finite sample of N observations and the quality of the model that is actually selected. The order selection criterion itself has an influence on the cost because of the penalty factor for each additionally selected parameter. Also, the number of competitive candidate models for the selection is important. The number of candidates is, of itself, small for the nested and hierarchical autoregressive/moving average (ARMA) models. However, intentionally reducing the number of selection candidates can be beneficial in combined ARMA(p,q) models, where two separate model orders are involved: the AR order p and the MA order q. The selection cost can be diminished by creating a nested sequence of ARMA(r,r-1) models. Moreover, not evaluating every combination (p,q) of the orders considerably reduces the required computation time. The disadvantage may be that the true ARMA(p,q) model is no longer among the nested candidate models. However, in finite samples, this disadvantage is largely compensated for by the reduction in the cost of order selection by considering fewer candidates. Thus, the quality of the selected model remains acceptable with only hierarchically nested ARMA(r,r-1) models as candidates.     

Dynamic error correction of a digitizer for time-domain metrology

A method for numerical correction of distortion in a digitizer used for metrology applications is described. Investigation of the digitizer's error behavior in the phase plane leads to the development of an analytic error model that describes the digitizer's distortion behavior. Of particular significance is the model's ability to describe nonlinear error in the fundamental spectral component manifested as amplitude and frequency-dependent gain and phase error. When fitted only to the harmonic distortion content of the digitizer's output data, the model generates an amount of fundamental that correctly accounts for the error in the digitizer's gain that is not due to linear system response. The model is therefore able to improve not just the total harmonic distortion (THD) performance of the digitizer but its ac root mean square measurement accuracy as well. At 1 MHz, the model linearizes the digitizer to 70 /spl mu/V/V over a range of 1 to 8 V and reduces harmonic distortion by >20 dB. It is believed that this is the first time that results of this nature have been reported in the literature.     

Implementation of a mechanics-based system for estimating the strength of timber

The most accurate way of determining the strength of lumber requires destructive testing. An intelligent mechanics-based lumber-grading system was developed to provide a better estimation of the strength of a board nondestructively. This system processed X-ray-extracted geometric features (of 1080 boards that eventually underwent destructive strength testing) by using finite element methods to generate associated stress fields. The stress fields were then fed to a feature-extracting-processor, which produced 26 strength predicting features. The best strength predicting features were determined from the coefficient of determination (correlation r/sup 2/) between the features and actual strengths of the boards. The coefficients of determination of each feature (or combination of features), with the actual strength of the board, were calculated and compared. A coefficient of determination of 0.4158 was achieved by using a longitudinal (along the local grain angle) maximum stress concentration (MSC) feature to predict the estimated strength of lumber.     

Design optimization of radially magnetized, iron-cored, tubular permanent-magnet machines and drive systems

In this paper we deduce, from analytical field solutions, the influence of leading design parameters on the performance of a radially magnetized, iron-cored, tubular permanent-magnet machine and its drive system. We derive analytical formulas for predicting the open-circuit electromotive force, the thrust force, the iron loss, and the winding resistance and inductances, as well as the converter losses. The force density, the machine and drive system efficiencies, and the power factor and converter volt-ampere (VA) rating are established as functions of a set of machine dimensional ratios, with due account of magnetic saturation and subject to a specified thermal constraint. We validate the utility and accuracy of the analytically derived formulas by finite-element calculations. Finally, we show that the design optimization of such a linear drive system must account for the losses and VA rating of the converter as well as the design parameters of the tubular machine.     

Effect of magnetic hysteresis on rotational losses in heteropolar magnetic bearings

This paper extends a method for predicting rotational losses for laminated rotors of heteropolar magnetic bearings by using an eddy-current model to include the effect of magnetic hysteresis in the rotor material. It compares the modeling results to the experimental data that were used earlier to assess the loss model neglecting hysteresis. The correction to the total electromagnetic loss in the rotor due to the hysteresis is significant at rotational speeds below 6000 revolutions per minute (RPM), where the model including hysteresis effects provides much better agreement with existing experimental data.