Gas amplification in proportional counters

The variation of gas amplification with applied voltage is an important characteristic of a proportional counter. Results of studies on gas amplification for gas fillings of argon quenched with ethane and carbon dioxide are given. The effects of (a) pressure, (b) quenching agent and (c) concentration on A are discussed briefly.

Single-File Diffusion of Confined Water Inside SWNTs: An NMR Study

We report a nuclear magnetic resonance (NMR) study of confined water inside similar to 1.4 nm diameter single-walled carbon nanotubes (SWNTs). We show that the confined water does not freeze even up to 223 K. A pulse field gradient (PFG) NMR method is used to determine the mean squared displacement (MSD) of the water molecules inside the nanotubes at temperatures below 273 K, where the bulk water outside the nanotubes freezes and hence does not contribute to the proton NMR signal. We show that the mean squared displacement varies as the square root of time, predicted for single-file diffusion in a one-dimensional channel. We propose a qualitative understanding of our results based on available molecular dynamics simulations.

Single-File Diffusion of Water Inside Narrow Carbon Nanorings

We use atomistic molecular dynamics (MD) simulations to study the diffusion of water molecules confined inside narrow (6,6) carbon nanorings. The water molecules form two oppositely polarized chains. It is shown that the effective interaction between these two chains is repulsive in nature. The computed mean-squared displacement (MSD) clearly shows a scaling with time similar to t(1/2), which is consistent with single-file diffusion (SFD). The time up to which the water molecules undergo SFD is shown to be the lifetime of the water molecules inside these chains. Simulations of "uncharged" water molecules inside the nanoring show the formation of several water chains and yield SFD. These observations conclusively prove that the diffusion is Fickian when there is a single chain of water and SFD is observed only when two or more chains are present.

Stabilizing hadron resonance gas models

We examine the stability of hadron resonance gas models by extending them to include undiscovered resonances through the Hagedorn formula. We find that the influence of unknown resonances on thermodynamics is large but bounded. We model the decays of resonances and investigate the ratios of particle yields in heavy-ion collisions. We find that observables such as hydrodynamics and hadron yield ratios change little upon extending the model. As a result, heavy-ion collisions at the RHIC and LHC are insensitive to a possible exponential rise in the hadronic density of states, thus increasing the stability of the predictions of hadron resonance gas models in this context. Hadron resonance gases are internally consistent up to a temperature higher than the crossover temperature in QCD, but by examining quark number susceptibilities we find that their region of applicability ends below the QCD crossover.

Image reconstruction by inhomogeneous diffusion for positron emission tomography

In positron emission tomography (PET), image reconstruction is a demanding problem. Since, PET image reconstruction is an ill-posed inverse problem, new methodologies need to be developed. Although previous studies show that incorporation of spatial and median priors improves the image quality, the image artifacts such as over-smoothing and streaking are evident in the reconstructed image. In this work, we use a simple, yet powerful technique to tackle the PET image reconstruction problem. Proposed technique is based on the integration of Bayesian approach with that of finite impulse response (FIR) filter. A FIR filter is designed whose coefficients are determined based on the surface diffusion model. The resulting reconstructed image is iteratively filtered and fed back to obtain the new estimate. Experiments are performed on a simulated PET system. The results show that the proposed approach is better than recently proposed MRP algorithm in terms of image quality and normalized mean square error.

Development of thermoelectric gas sensors for volatile organic compounds

This paper describes the design and development of a thermoelectric gas sensor suitable for the detection of Volatile Organic Compounds (VOCs). In order to enhance the seebeck coefficient of the sensor, we have deposited chromium metal films on a limited area of the glass substrate. Tin oxide thin film was deposited on top of these metal films. The resulting metal/semiconductor film exhibits a high seebeck coefficient of 400 mu V/ degrees C. Platinum catalyst film deposited on the oxide film to create the necessary temperature gradient resulted in further enhancement in the sensitivity of the sensor to target gases. The sensor shows high sensitivity to ppm-change in the concentration of target hydrocarbons at a relatively low temperature of 120 degrees C.

The Context and Diffusion of Knowledge in the Finnish Jewellery Industry - The role of the House of Fabergé

Researchers within the fields of economic geography and organizational management have extensively studied learning and the prerequisites and impediments for knowledge transfer. This paper combines two discourses within the two subjects: the-communities-of-practice and the learning region approaches, merging them through the so-called ecology of knowledge-approach, which is used to examine the knowledge transfer from the House of Fabergé to the Finnish jewellery industry. We examine the pre-revolution St Petersburg jewellery cluster and the post-revolution Helsinki, and the transfer of knowledge between these two locations through the components of communities of people, institutions and industry. The paper shows that the industrial dynamics of the Finnish modern-day goldsmith industry was inherently shaped both through the transfer and the non-transfer of knowledge. It also contends that the “knowledge-economy” is not anchored in and exclusive for the high technology sector of the late 20th century.

Nonlinear intrinsic instability of solid propellant combustion including gas-phase thermal inertia

The problem of homogeneous solid propellant combustion instability is studied with a one-dimensional flame model, including the effects of gas-phase thermal inertia and nonlinearity. Computational results presented in this paper show nonlinear instabilities inherent in the equations, due to which periodic burning is found even under steady ambient conditions such as pressure. The stability boundary is obtained in terms of Denison-Baum parameters. It is found that inclusion of gas-phase thermal inertia stabilizes the combustion. Also, the effect of a distributed heat release in the gas phase, compared to the flame sheet model, is to destabilize the burning. Direct calculations for finite amplitude pressure disturbances show that two distinct resonant modes exist, the first one near the natural frequency as obtained from intrinsic instability analysis and a second mode occurring at a much higher driving frequency. It is found that er rn in the low frequency region, the response of the propellant is significantly affected by the specific type of gas-phase chemical heat-release model employed. Examination of frequency response function reveals that the role of gas-phase thermal inertia is to stabilize the burning near the first resonant mode. Calculations made for different amplitudes of driving pressure show that the mean burning rate decreases with increasing amplitude. Also, with an increase in the driving amplitude, higher harmonics are generated in the burning rate.

Critical micelle concentration from a lattice gas model

The temperature dependence of the critical micelle concentration (CMC) and a closed-loop coexistence curve are obtained, via Monte Carlo simulations, in the water surfactant limit of a two-dimensional version of a statistical mechanical model for micro-emulsions, The CMC and the coexistence curve reproduce various experimental trends as functions of the couplings. In the oil-surfactant limit, there is a conventional coexistence cure with an upper consolute point that allows for a region of three-phase coexistence between oil-rich, water-rich and microemulsion phases.

Unsteady mixed convection with double diffusion over a horizontal cylinder and a sphere within a porous medium

The combined effects of the permeability of the medium, magnetic field, buoyancy forces and dissipation on the unsteady mixed convection flow over a horizontal cylinder and a sphere embedded in a porous medium have been studied. The nonlinear coupled partial differential equations with three independent variables have been solved numerically using an implicit finite-difference scheme in combination with the quasilinearization technique. The skin friction, heat transfer and mass transfer increase with the permeability of the medium, magnetic field and buoyancy parameter. The heat and mass transfer continuously decrease with the stream-wise distance, whereas the skin friction increases from zero, attains a maximum and then decreases to zero. The skin friction, heat transfer and mass transfer are significantly affected by the free stream velocity distribution. The effect of dissipation parameter is found to be more pronounced on the heat transfer than on the skin friction and mass transfer

Gas turbine diagnostics using a soft computing approach

A fuzzy system is developed using a linearized performance model of the gas turbine engine for performing gas turbine fault isolation from noisy measurements. By using a priori information about measurement uncertainties and through design variable linking, the design of the fuzzy system is posed as an optimization problem with low number of design variables which can be solved using the genetic algorithm in considerably low amount of computer time. The faults modeled are module faults in five modules: fan, low pressure compressor, high pressure compressor, high pressure turbine and low pressure turbine. The measurements used are deviations in exhaust gas temperature, low rotor speed, high rotor speed and fuel flow from a base line 'good engine'. The genetic fuzzy system (GFS) allows rapid development of the rule base if the fault signatures and measurement uncertainties change which happens for different engines and airlines. In addition, the genetic fuzzy system reduces the human effort needed in the trial and error process used to design the fuzzy system and makes the development of such a system easier and faster. A radial basis function neural network (RBFNN) is also used to preprocess the measurements before fault isolation. The RBFNN shows significant noise reduction and when combined with the GFS leads to a diagnostic system that is highly robust to the presence of noise in data. Showing the advantage of using a soft computing approach for gas turbine diagnostics.