Influence of surfactant solubility on the deformation and breakup of a bubble or capillary jet in a viscous fluid

In a previous study [M. Hameed, J. Fluid Mech. 594, 307 (2008)] the authors investigated the influence of insoluble surfactant on the evolution of a stretched, inviscid bubble surrounded by a viscous fluid via direct numerical simulation of the Navier-Stokes equations, and showed that the presence of surfactant can cause the bubble to contract and form a quasisteady slender thread connecting parent bubbles, instead of proceeding directly toward pinch-off as occurs for a surfactant-free bubble. Insoluble surfactant significantly retards pinch-off and the thread is stabilized by a balance between internal pressure and reduced capillary pressure due to a high concentration of surfactant that develops during the initial stage of contraction. In the present study we investigate the influence of surfactant solubility on thread formation. The adsorption-desorption kinetics for solubility is in the diffusion controlled regime. A long-wave model for the evolution of a capillary jet is also studied in the Stokes flow limit, and shows dynamics that are similar to those of the evolving bubble. With soluble surfactant, depending on parameter values, a slender thread forms but can pinch-off later due to exchange of surfactant between the interface and exterior bulk flow. © 2009 American Institute of Physics.

Relaxation and fracture characteristics in Co-based amorphous alloys

In this article a study of the fracture characteristics of Co66Fe4Mo2Si16B12 amorphous ribbon in the as-quenched state and after relaxation is presented. In the as-quenched state, the morphology of the crack surface shows a 'vein pattern' structure that corresponds to a large amount of plastic flow. After relaxation the surface morphology of the crack shows that when the temperature of the thermal annealing increases the plastic flow involved in the crack decreases. In the as-quenched state dynamic fracture characteristics (crack branching and stress wave induced crack) have been observed. These dynamic characteristics have not been observed in the relaxed samples but in the samples annealed at 250 °C for 20 min apart from the main crack, a crack along the width of the ribbon has been observed. © 2006 Elsevier B.V. All rights reserved.

Moderate energy impact analysis combining phenomenological contact law with localised damage and integral equation method

A computational impact analysis methodology has been developed, based on modal analysis and a local contact force-deflection model. The contact law is based on Hertz contact theory while contact stresses are elastic, defines a modified contact theory to take account of local permanent indentation, and considers elastic recovery during unloading. The model was validated experimentally through impact testing of glass-carbon hybrid braided composite panels. Specimens were mounted in a support frame and the contact force was inferred from the deceleration of the impactor, measured by high-speed photography. A Finite Element analysis of the panel and support frame assembly was performed to compute the modal responses. The new contact model performed well in predicting the peak forces and impact durations for moderate energy impacts (15 J), where contact stresses locally exceed the linear elastic limit and damage may be deemed to have occurred. C-scan measurements revealed substantial damage for impact energies in the range of 30-50 J. For this regime the new model predictions might be improved by characterisation of the contact law hysteresis during the unloading phase, and a modification of the elastic vibration response in line with damage levels acquired during the impact. © 2011 Elsevier Ltd. All rights reserved.

Robust modelling of noisy ARMA signals

In this paper methods are developed for enhancement and analysis of autoregressive moving average (ARMA) signals observed in additive noise which can be represented as mixtures of heavy-tailed non-Gaussian sources and a Gaussian background component. Such models find application in systems such as atmospheric communications channels or early sound recordings which are prone to intermittent impulse noise. Markov Chain Monte Carlo (MCMC) simulation techniques are applied to the joint problem of signal extraction, model parameter estimation and detection of impulses within a fully Bayesian framework. The algorithms require only simple linear iterations for all of the unknowns, including the MA parameters, which is in contrast with existing MCMC methods for analysis of noise-free ARMA models. The methods are illustrated using synthetic data and noise-degraded sound recordings.

Preparation of tetrahedral amorphous carbon films by filtered cathodic vacuum arc deposition

Tetrahedrally bonded amorphous carbon (ta-C) and nitrogen doped (ta-C:N) films were obtained at room temperature in a filtered cathodic vacuum arc (FCVA) system incorporating an off-plane double bend (S-bend) magnetic filter. The influence of the negative bias voltage applied to substrates (from -20 to -350 V) and the nitrogen background pressure (up to 10-3 Torr) on film properties was studied by scanning electron microscopy (SEM), electron energy loss spectroscopy (EELS), Raman spectroscopy, X-ray photoemission spectroscopy (XPS), secondary ion mass spectroscopy (SIMS) and X-ray reflectivity (XRR). The ta-C films showed sp3 fractions between 84% and 88%, and mass densities around 3.2 g/cm3 in the wide range of bias voltage studied. In contrast, the compressive stress showed a maximum value of 11 GPa for bias voltages around -90 V, whereas for lower and higher bias voltages the stress decreased to 6 GPa. As for the ta-C:N films grown at bias voltages below -200 V and with N contents up to 7%, it has been found that the N atoms were preferentially sp3 bonded to the carbon network with a reduction in stress below 8 GPa. Further increase in bias voltage or N content increased the sp2 fraction, leading to a reduction in film density to 2.7 g/cm3.

AC losses of superconducting racetrack coil in various magnetic conditions

High-temperature superconductors have created the opportunity for a step change in the technology of power applications. Racetrack superconducting coils made from YBCO coated conductors have been used in several engineering applications including SMES, rotor or stator windings of electric machines. AC loss is one of the most important factors that determine the design and performance of superconducting devices. In this paper, a numerical model is developed to calculate the AC losses in superconducting racetrack coils in different magnetic conditions. This paper first discusses the AC losses of the coils in self-field or external field only. It then goes to investigate the AC losses of the coils being exposed to AC ripple field and a DC background field. Finally, the AC losses of the coils carrying DC current and being exposed to AC field are calculated. These two scenarios correspond to using superconducting coils as the rotor field winding of an electric machine. © 2010 IEEE.

A computer algorithm for determining the tensile strength of float glass

The extrinsic tensile strength of glass can be determined explicitly if the characteristics of the critical surface flaw are known, or stochastically if the critical flaw characteristics are unknown. This paper makes contributions to both these approaches. Firstly it presents a unified model for determining the strength of glass explicitly, by accounting for both the inert strength limit and the sub-critical crack growth threshold. Secondly, it describes and illustrates the use of a numerical algorithm, based on the stochastic approach, that computes the characteristic tensile strength of float glass by piecewise summation of the surface stresses. The experimental validation and sensitivity analysis reported in this paper show that the proposed computer algorithm provides an accurate and efficient means of determining the characteristic strength of float glass. The algorithm is particularly useful for annealed and thermally treated float glass used in the construction industry. © 2012 Elsevier Ltd.

Enhancement of Construction Equipment Detection in Video Frames by Combining with Tracking

Vision-based object detection has been introduced in construction for recognizing and locating construction entities in on-site camera views. It can provide spatial locations of a large number of entities, which is beneficial in large-scale, congested construction sites. However, even a few false detections prevent its practical applications. In resolving this issue, this paper presents a novel hybrid method for locating construction equipment that fuses the function of detection and tracking algorithms. This method detects construction equipment in the video view by taking advantage of entities' motion, shape, and color distribution. Background subtraction, Haar-like features, and eigen-images are used for motion, shape, and color information, respectively. A tracking algorithm steps in the process to make up for the false detections. False detections are identified by catching drastic changes in object size and appearance. The identified false detections are replaced with tracking results. Preliminary experiments show that the combination with tracking has the potential to enhance the detection performance.

Modeling nonlinearities in MEMS oscillators

We present a mathematical model of a microelectromechanical system (MEMS) oscillator that integrates the nonlinearities of the MEMS resonator and the oscillator circuitry in a single numerical modeling environment. This is achieved by transforming the conventional nonlinear mechanical model into the electrical domain while simultaneously considering the prominent nonlinearities of the resonator. The proposed nonlinear electrical model is validated by comparing the simulated amplitude¿frequency response with measurements on an open-loop electrically addressed flexural silicon MEMS resonator driven to large motional amplitudes. Next, the essential nonlinearities in the oscillator circuit are investigated and a mathematical model of a MEMS oscillator is proposed that integrates the nonlinearities of the resonator. The concept is illustrated for MEMS transimpedance-amplifier-based square-wave and sine-wave oscillators. Closed-form expressions of steady-state output power and output frequency are derived for both oscillator models and compared with experimental and simulation results, with a good match in the predicted trends in all three cases. © 1986-2012 IEEE.

Vibration from railways: Can we achieve better than +/-10dB prediction accuracy?

This paper examines the sources of uncertainly in models used to predict vibration from underground railways. It will become clear from this presentation that by varying parameters by a small amount, consistent with uncertainties in measured data, the predicted vibration levels vary significantly, often by more than 10dB. This error cannot be forecast. Small changes made to soil parameters (Compressive and Shear Wave velocities and density), to slab bending stiffness and mass and to the measurement position give rise to changes in vibration levels of more than lOdB. So if 10dB prediction error results from small uncertainties in soil parameters and measurement position it cannot be sensible to rely on prediction models for accuracy better than 10dB. The presentation will demonstrate in real time the use of the new - and freely-available - PiP software for calculating vibration from railway tunnels in real time.

Adaptive modulation induced WDM impairment reduction in optical OFDM PONs

The transmission performance of multi-channel adaptively modulated optical OFDM (AMOOFDM) signals is numerically investigated, for the first time, in optical amplification- and chromatic dispersion compensation-free, intensity-modulation and direct-detection systems incorporating directly modulated DFB lasers (DMLs). It is shown that adaptive modulation not only reduces significantly the nonlinear WDM impairments induced by the effects of cross-phase modulation and four-wave mixing, but also compensates effectively for the DML-induced frequency chirp effect. In comparison with identical modulation, adaptive modulation improves the maximum achievable signal transmission capacity of a central channel by a factor of 1.3 and 3.6 for 40km and 80km SMFs, respectively, with corresponding dynamic input optical power ranges being extended by approximately 5dB. In addition, adaptive modulation also enables cross-channel complementary modulation format mapping, leading to an improved transmission capacity of the entire WDM system. Copyright © 2010 The authors.

On representing chemical environments

We review some recently published methods to represent atomic neighbourhood environments, and analyse their relative merits in terms of their faithfulness and suitability for fitting potential energy surfaces. The crucial properties that such representations (sometimes called descriptors) must have are differentiability with respect to moving the atoms, and invariance to the basic symmetries of physics: rotation, reflection, translation, and permutation of atoms of the same species. We demonstrate that certain widely used descriptors that initially look quite different are specific cases of a general approach, in which a finite set of basis functions with increasing angular wave numbers are used to expand the atomic neighbourhood density function. Using the example system of small clusters, we quantitatively show that this expansion needs to be carried to higher and higher wave numbers as the number of neighbours increases in order to obtain a faithful representation, and that variants of the descriptors converge at very different rates. We also propose an altogether new approach, called Smooth Overlap of Atomic Positions (SOAP), that sidesteps these difficulties by directly defining the similarity between any two neighbourhood environments, and show that it is still closely connected to the invariant descriptors. We test the performance of the various representations by fitting models to the potential energy surface of small silicon clusters and the bulk crystal.

Probability-Matching Predictors for Extreme Extremes

A location- and scale-invariant predictor is constructed which exhibits good probability matching for extreme predictions outside the span of data drawn from a variety of (stationary) general distributions. It is constructed via the three-parameter {\mu, \sigma, \xi} Generalized Pareto Distribution (GPD). The predictor is designed to provide matching probability exactly for the GPD in both the extreme heavy-tailed limit and the extreme bounded-tail limit, whilst giving a good approximation to probability matching at all intermediate values of the tail parameter \xi. The predictor is valid even for small sample sizes N, even as small as N = 3. The main purpose of this paper is to present the somewhat lengthy derivations which draw heavily on the theory of hypergeometric functions, particularly the Lauricella functions. Whilst the construction is inspired by the Bayesian approach to the prediction problem, it considers the case of vague prior information about both parameters and model, and all derivations are undertaken using sampling theory.