Dispersion of the stress-optic coefficient in glasses

The stress-optic coefficient (n3/2)(q11-q12) has been determined for a series of 18 optical glasses of different compositions in the wavelength range 5700-3200 Å. The coefficients are negative for all the glasses except for a high-lead-content glass of density 6·7 and refractive index 1·89. The numerical value of the coefficient decreases as one proceeds to the ultraviolet. This behaviour is just the opposite of what is observed in fused silica. By applying Mueller's theory, the strain polarizability constant and its dispersion have been evaluated.

Effect of relative density and confining pressure on Poisson ratio from bender and extender elements tests

By using the bender and extender elements tests, together with measurements of the travel times of shear (S) and primary (P) waves, the variation of Poisson ratio (nu) was determined for dry sands with respect to changes in relative densities and effective confining pressures (sigma(3)). The tests were performed for three different ranges of particle sizes. The magnitude of the Poisson ratio decreases invariably with an increase in both the relative density and the effective confining pressure. The effect of the confining pressure on the Poisson ratio was found to become relatively more significant for fine-grained sand as compared with the coarse-grained sand. For a given material, at a particular value of sigma(3), the magnitude of the Poisson ratio decreases, almost in a linear fashion, with an increase in the value of maximum shear modulus (G(max)). The two widely used correlations in literature, providing the relationships among G(max), void ratio (e) and effective confining pressure (sigma(3)), applicable for angular granular materials, were found to compare reasonably well with the present experimental data for the fine- and medium-grained sands. However, for the coarse-grained sand, these correlations tend to overestimate the values of G(max).

Non-disruptive and null-deflection mass flow measurement by a pressure compensation technique

Accurate mass flow measurement is very important in various monitoring and control applications. This paper proposes a novel method of fluid flow measurement by compensating the pressure drop across the ends of measuring unit using a compensating pump. The pressure drop due to the flow is balanced by a feedback control loop. This is a null-deflection type of measurement. As the insertion of such a measuring unit does not affect the functioning of the systems, this is also a non-disruptive flow measurement method. The implementation and design of such a unit are discussed. The system is modeled and simulated using the bond graph technique and it is experimentally validated. (C) 2009 Elsevier Ltd. All rights reserved.

Contribution of different physical forces to the disjoining pressure of a thin water film being pressed by an oil droplet

With an objective to understand the nature of forces which contribute to the disjoining pressure of a thin water film on a steel substrate being pressed by an oil droplet, two independent sets of experiments were done. (i) A spherical silica probe approaches the three substrates; mica, PTFE and steel, in a 10 mM electrolyte solution at two different pHs (3 and 10). (ii) The silica probe with and without a smeared oil film approaches the same three substrates in water (pH = 6). The surface potential of the oil film/water was measured using a dynamic light scattering experiment. Assuming the capacity of a substrate for ion exchange the total interaction force for each experiment was estimated to include the Derjaguin-Landau-Verwey-Overbeek (DLVO) force, hydration repulsion, hydrophobic attraction and oil-capillary attraction. The best fit of these estimates to the force-displacement characteristics obtained from the two sets of experiment gives the appropriate surface potentials of the substrates. The procedure allows an assessment of the relevance of a specific physical interaction to an experimental configuration. Two of the principal observations of this work are: (i) The presence of a surface at constant charge, as in the presence of an oil film on the probe, significantly enhances the counterion density over what is achieved when both the surfaces allow ion exchange. This raises the corresponding repulsion barrier greatly. (ii) When the substrate surface is wettable by oil, oil-capillary attraction contributes substantially to the total interaction. If it is not wettable the oil film is deformed and squeezed out. (C) 2010 Elsevier Inc. All rights reserved.

Pressure dependence of chlorine nuclear quadrupole resonance in sodium chlorate

The pressure dependence of the chlorine NQR frequency in NaClo3 has been investigated up to 20 k bar hydrostatic pressure. A distinct break in slope in the pressure dependence of the resonance frequency is observed near 11 k bar. This is attributed to a phase transition reported earlier by Bridgman in this pressure region.

Prediction of swelling pressure of soil using artificial intelligence techniques

The swelling pressure of soil depends upon various soil parameters such as mineralogy, clay content, Atterberg's limits, dry density, moisture content, initial degree of saturation, etc. along with structural and environmental factors. It is very difficult to model and analyze swelling pressure effectively taking all the above aspects into consideration. Various statistical/empirical methods have been attempted to predict the swelling pressure based on index properties of soil. In this paper, the computational intelligence techniques artificial neural network and support vector machine have been used to develop models based on the set of available experimental results to predict swelling pressure from the inputs; natural moisture content, dry density, liquid limit, plasticity index, and clay fraction. The generalization of the model to new set of data other than the training set of data is discussed which is required for successful application of a model. A detailed study of the relative performance of the computational intelligence techniques has been carried out based on different statistical performance criteria.

Prediction of swelling pressure of soil using artificial intelligence techniques

The swelling pressure of soil depends upon various soil parameters such as mineralogy, clay content, Atterberg's limits, dry density, moisture content, initial degree of saturation, etc. along with structural and environmental factors. It is very difficult to model and analyze swelling pressure effectively taking all the above aspects into consideration. Various statistical/empirical methods have been attempted to predict the swelling pressure based on index properties of soil. In this paper, the computational intelligence techniques artificial neural network and support vector machine have been used to develop models based on the set of available experimental results to predict swelling pressure from the inputs; natural moisture content, dry density, liquid limit, plasticity index, and clay fraction. The generalization of the model to new set of data other than the training set of data is discussed which is required for successful application of a model. A detailed study of the relative performance of the computational intelligence techniques has been carried out based on different statistical performance criteria.

Pressure sensor based tsunami detection system: A laboratory study

In this paper, we present the study and implementation of a low-cost system to detect the occurrences of tsunamis at significantly smaller laboratory scale. The implementation is easily scalable for real-time deployment. Information reported in this paper includes the experimentally recorded response from the pressure sensor giving an indication as well as an alarm at remote place for the detection of water turbulence similar to the case of tsunami. It has been found that the system developed works very well in the laboratory scale.