The effect of dopants on the twist elastic constant and the rotational viscosity coefficient for nematics

The twist elastic constant, K2, and the rotational viscosity coefficient, γ1, are of importance when the response lime for the in-plane switching mode is studied. Since adding dopants is one technique to improve the response characteristics, the effect of dopants on these physical properties is significant. The effect on K2 and γ1 of adding alkyl(alkoxy) phenylcyclopentenones and alkyl(alkoxy) cyanobiphenyls to the base mixture ZLI-4792 together with their temperature dependence have been investigated using different temperature scales. The reduced temperature scale showed the effect of these dopants on K2 is small. On the other hand, the temperature dependence of γ1 depends on both the absolute temperature scale and the reduced temperature scale. Therefore, it is clear that the choice of temperature scale with which to compare γ1 for different systems raises fundamental questions which way not have a unique answer. 2000 OPA (Overseas Publishers Association) N.V. Published by license under the Gordon and Breach Science Publishers imprint.

Measurement of coefficient of consolidation during reconsolidation of liquefied sand

Saturated sands particularly at low relative density commonly exhibit rises in excess pore pressure when subjected to earthquake loading. The excess pore pressure can approach a maximum value, limited by the initial vertical effective stress. After the completion of earthquake shaking, these excess pore pressures dissipate according to the consolidation equation, which can be solved to produce a Fourier series solution. It will be shown by manipulation of this Fourier series that excess pore pressure traces provide a method for back-calculation of coefficient of consolidation Cv. This method is validated against dissipation curves generated using known values of C v and seen to be more accurate in the middle of the layer. The method is then applied to data recorded in centrifuge tests to evaluate Cv throughout the reconsolidation process following liquefaction conditions. C v is seen to fit better as a function of excess pore pressure ratio than effective stress for the stress levels considered. For the soil investigated, Cv is about three times smaller at excess pore pressure ratio of 0.9 compared to excess pore pressure ratio of 0. Copyright © 1996-2011 ASTM.

Re-examination of the coefficient of determination (r2) using road materials engineering case studies

The analysis of scientific data is integral to materials engineering and science. The correlation between measured variables is often quantified by estimating the coefficient of determination or the r2 value. This is the recognised procedure for determining linear relationships. The authors review the derivation of the r2 value and derive an associated quantity, termed the relative deviation (RD), which is the ratio of the root mean square of the deviations about the fitted line to the root mean square of the deviations about the y bar line expressed as a percentage. The relative deviation has an advantage over the coefficient of determination in that it has greater numerical sensitivity to changes in the spread of data about the fitted line, especially when the scatter is small. In addition, the relative deviation is able to define, in percentage terms, the reduction in scatter when different independent variables are correlated with a common dependent variable. Four case studies in the materials field (aggregate crushing value, Atterberg limits, permeability and creep of asphalt) from work carried out at the Queensland Main Roads Department are presented to show the use of the new parameter RD.

A dependent partition-valued process for multitask clustering and time evolving network modelling

The fundamental aim of clustering algorithms is to partition data points. We consider tasks where the discovered partition is allowed to vary with some covariate such as space or time. One approach would be to use fragmentation-coagulation processes, but these, being Markov processes, are restricted to linear or tree structured covariate spaces. We define a partition-valued process on an arbitrary covariate space using Gaussian processes. We use the process to construct a multitask clustering model which partitions datapoints in a similar way across multiple data sources, and a time series model of network data which allows cluster assignments to vary over time. We describe sampling algorithms for inference and apply our method to defining cancer subtypes based on different types of cellular characteristics, finding regulatory modules from gene expression data from multiple human populations, and discovering time varying community structure in a social network.