Role of interface curvature on stress distribution under indentation for ZrN/Zr multilayer coating

Contact damage in curved interface nano-layeredmetal/nitride (150 (ZrN)/10 (Zr) nm) multilayer is investigated in order to understand the role of interface morphology on contact damage under indentation. A finite element method (FEM) model was formulated with different wavelengths of 1000 nm, 500 nm, 250 nm and common height of 50 nm, which gives insight on the effect of different curvature on stress field generated under indentation. Elastic-plastic properties were assigned to the metal layer and substrate while the nitride layer was assigned perfectly elastic properties. Curved interface multilayers show delamination along the metal/nitride interface and vertical cracks emanating from the ends of the delamination. FEM revealed the presence of tensile stress normal to the interface even under the contact, along with tensile radial stresses, both present at the valley part of the curve, which leads to vertical cracks associated with interfacial delamination. Stress enhancement was seen to be relatively insensitive to curvature. (C) 2014 Elsevier B.V. All rights reserved.

Bearing Capacity of Circular Footings on Reinforced Soils

A method is presented for determining the ultimate bearing capacity of a circular footing reinforced with a horizontal circular sheet of reinforcement placed over granular and cohesive-frictional soils. It was assumed that the reinforcement sheet could bear axial tension but not the bending moment. The analysis was performed based on the lower-bound theorem of the limit analysis in combination with finite elements and linear optimization. The present research is an extension of recent work with strip foundations reinforced with different layers of reinforcement. To incorporate the effect of the reinforcement, the efficiency factors eta(gamma) and eta(c), which need to be multiplied by the bearing capacity factors N-gamma and N-c, were established. Results were obtained for different values of the soil internal friction angle (phi). The optimal positions of the reinforcements, which would lead to a maximum improvement in the bearing capacity, were also determined. The variations of the axial tensile force in the reinforcement sheet at different radial distances from the center were also studied. The results of the analysis were compared with those available from literature. (C) 2014 American Society of Civil Engineers.

Giant actuation in bulk carbon nanotubes under coupled electric and magnetic fields

We report an enhanced actuation in bulk carbon nanotubes (CNTs) under coupled electric and magnetic fields, which is much higher than that evaluated in the presence of individual fields. Coupled electric and magnetic fields induce a directional actuation demonstrating a transformation from polarity independent to dependent actuation behavior of CNTs. Both qualitative and quantitative analyses are performed to understand this transformation in the bulk CNTs. Moreover, actuations along radial and axial directions of CNTs have also demonstrated a similar directional behavior.

Acoustic response of vortex breakdown modes in a coaxial isothermal unconfined swirling jet

The present experimental work is concerned with the study of amplitude dependent acoustic response of an isothermal coaxial swirling jet. The excitation amplitude is increased in five distinct steps at the burner's Helmholtz resonator mode (i.e., 100 Hz). Two flow states are compared, namely, sub-critical and super-critical vortex breakdown (VB) that occur before and after the critical conical sheet breakdown, respectively. The geometric swirl number is varied in the range 2.14-4.03. Under the influence of external pulsing, global response characteristics are studied based on the topological changes observed in time-averaged 2D flow field. These are obtained from high resolution 2D PIV (particle image velocimetry) in the longitudinal-mid plane. PIV results also illustrate the changes in the normalized vortex core coordinates (r(vcc)/(r(vcc))(0) (Hz), y(vcc)/(y(vcc))(0) (Hz)) of internal recirculation zone (IRZ). A strong forced response is observed at 100 Hz (excitation frequency) in the convectively unstable region which get amplified based on the magnitude of external forcing. The radial extent of this forced response region at a given excitation amplitude is represented by the acoustic response region (b). The topological placement of the responsive convectively unstable region is a function of both the intensity of imparted swirl (characterized by swirl number) and forcing amplitude. It is observed that for sub-critical VB mode, an increase in the excitation amplitude till a critical value shifts the vortex core centre (particularly, the vortex core moves downstream and radially outwards) leading to drastic fanning-out/widening of the IRZ. This is accompanied by similar to 30% reduction in the recirculation velocity of the IRZ. It is also observed that b < R (R: radial distance from central axis to outer shear layer-OSL). At super-critical amplitudes, the sub-critical IRZ topology transits back (the vortex core retracts upstream and radially inwards) and finally undergoes a transverse shrinkage ((r(vcc))/(r(vcc))(0 Hz) decreases by similar to 20%) when b >= R. In contrast, the vortex core of super-critical breakdown mode consistently spreads radially outwards and is displaced further downstream. Finally, the IRZ fans-out at the threshold excitation amplitude. However, the acoustic response region b is still less than R. This is explained based on the characteristic geometric swirl number (S-G) of the flow regimes. The super-critical flow mode with higher S-G (hence, higher radial pressure drop due to rotational effect which scales as Delta P similar to rho u theta(2) and acts inwards towards the center line) compared to sub-critical state imposes a greater resistance to the radial outward spread of b. As a result, the acoustic energy supplied to the super-critical flow mode increases the degree of acoustic response at the pulsing frequency and energizes its harmonics (evident from power spectra). As a disturbance amplifier, the stronger convective instability mode within the flow structure of super-critical VB causes the topology to widen/fan-out severely at threshold excitation amplitude. (C) 2015 AIP Publishing LLC.

Stability of Filaments in Star-Forming Clouds and the Formation of Prestellar Cores in Them

The exact process(es) that generate(s) dense filaments which then form prestellar cores within them is unclear. Here we study the formation of a dense filament using a relatively simple set-up of a pressure-confined, uniform-density cylinder. We examine if its propensity to form a dense filament and further, to the formation of prestellar cores along this filament, bears on the gravitational state of the initial volume of gas. We report a radial collapse leading to the formation of a dense filamentary cloud is likely when the initial volume of gas is at least critically stable (characterised by the approximate equality between the mass line-density for this volume and its maximum value). Though self-gravitating, this volume of gas, however, is not seen to be in free-fall. This post-collapse filament then fragments along its length due to the growth of a Jeans-like instability to form prestellar cores. We suggest dense filaments in typical star-forming clouds classified as gravitationally super-critical under the assumption of: (i) isothermality when in fact, they are not, and (ii) extended radial profiles as against pressure-truncated, that significantly over-estimates their mass line-density, are unlikely to experience gravitational free-fall. The radial density and temperature profile derived for this post-collapse filament is consistent with that deduced for typical filamentary clouds mapped in recent surveys of nearby star-forming regions.

Use of Data Driven Techniques for Short Lead Time Streamflow Forecasting in Mahanadi basin

Streamflow forecasts at daily time scale are necessary for effective management of water resources systems. Typical applications include flood control, water quality management, water supply to multiple stakeholders, hydropower and irrigation systems. Conventionally physically based conceptual models and data-driven models are used for forecasting streamflows. Conceptual models require detailed understanding of physical processes governing the system being modeled. Major constraints in developing effective conceptual models are sparse hydrometric gauge network and short historical records that limit our understanding of physical processes. On the other hand, data-driven models rely solely on previous hydrological and meteorological data without directly taking into account the underlying physical processes. Among various data driven models Auto Regressive Integrated Moving Average (ARIMA), Artificial Neural Networks (ANNs) are most widely used techniques. The present study assesses performance of ARIMA and ANNs methods in arriving at one-to seven-day ahead forecast of daily streamflows at Basantpur streamgauge site that is situated at upstream of Hirakud Dam in Mahanadi river basin, India. The ANNs considered include Feed-Forward back propagation Neural Network (FFNN) and Radial Basis Neural Network (RBNN). Daily streamflow forecasts at Basantpur site find use in management of water from Hirakud reservoir. (C) 2015 The Authors. Published by Elsevier B.V.

Simulations using meshfree methods

In this paper, attempt is made to solve a few problems using the Polynomial Point Collocation Method (PPCM), the Radial Point Collocation Method (RPCM), Smoothed Particle Hydrodynamics (SPH), and the Finite Point Method (FPM). A few observations on the accuracy of these methods are recorded. All the simulations in this paper are three dimensional linear elastostatic simulations, without accounting for body forces.

Effect of viscosity and surface tension on breakup and coalescence of bicomponent sprays

This work deals with an experimental study of the breakup characteristics of liquids with different surface tension and viscosity from a hollow cone hydraulic injector nozzle induced by pressure-swirl. The experiments were conducted at Reynolds numbers Re-p=9500-23,000. The surface tension and viscosity of the surrogate fuels were altered from 72 to 30 mN/m and 1.1 to 1.6 mN s/m(2), respectively. High speed photography and Phase Doppler Particle Anemometry were utilized to study the atomization process. Velocity and drop size measurements of the spray using PDPA in both axial and radial directions indicate a dependency on surface tension. However, these effects are dominant only at low Reynolds numbers and are negligible at high Reynolds number. Downstream of the nozzle, coalescence of droplets due to collision was also found to be significant and the diameters were compared for different liquids. For viscous fluids up to 1.6 cP, the independent effects of viscosity and injection pressure are studied. In general, the spray cone angle increases with increase in pressure. At high pressures, an increase in viscosity leads to higher drop sizes following primary and secondary breakup compared to water. This study will extend our understanding of surrogate fuel film breakup and highlight the importance of long and short wavelength instabilities. (C) 2013 Elsevier Ltd. All rights reserved

Chemical-free graphene by unzipping carbon nanotubes using cryo-milling

Current paper reports synthesis of chemical free graphene by unzipping of the carbon nanotubes (CNTs) using high strain rate deformation at 150K. A specially designed cryomill operating at 150 K was used for the experiments. The mechanism of unzipping was further explored using molecular dynamics (MD) simulations. Both experimental and simulation results reveal two modes of unzipping through radial and shear loading. (C) 2015 Elsevier Ltd. All rights reserved.

Molecular dynamics insight to phase transition in n-alkanes with carbon nanofillers

The present work aims to investigate the phase transition, dispersion and diffusion behavior of nanocomposites of carbon nanotube (CNT) and straight chain alkanes. These materials are potential candidates for organic phase change materials(PCMs) and have attracted flurry of research recently. Accurate experimental evaluation of the mass, thermal and transport properties of such composites is both difficult as well as economically taxing. Additionally it is crucial to understand the factors that results in modification or enhancement of their characteristic at atomic or molecular level. Classical molecular dynamics approach has been extended to elucidate the same. Bulk atomistic models have been generated and subjected to rigorous multistage equilibration. To reaffirm the approach, both canonical and constant-temperature, constant-pressure ensembles were employed to simulate the models under consideration. Explicit determination of kinetic, potential, non-bond and total energy assisted in understanding the enhanced thermal and transport property of the nanocomposites from molecular point of view. Crucial parameters including mean square displacement and simulated self diffusion coefficient precisely define the balance of the thermodynamic and hydrodynamic interactions. Radial distribution function also reflected the density variation, strength and mobility of the nanocomposites. It is expected that CNT functionalization could improve the dispersion within n-alkane matrix. This would further ameliorate the mass and thermal properties of the composite. Additionally, the determined density was in good agreement with experimental data. Thus, molecular dynamics can be utilized as a high throughput technique for theoretical investigation of nanocomposites PCMs. (C) 2015 Author(s). All article content, except where otherwise noted, is licensed under a Creative Commons Attribution 3.0 Unported License.

Pulse transit time differential measurement by fiber Bragg grating pulse recorder

The present study reports a noninvasive technique for the measurement of the pulse transit time differential (PTTD) from the pulse pressure waveforms obtained at the carotid artery and radial artery using fiber Bragg grating pulse recorders (FBGPR). PTTD is defined as the time difference between the arrivals of a pulse pressure waveform at the carotid and radial arterial sites. The PTTD is investigated as an indicator of variation in the systolic blood pressure. The results are validated against blood pressure variation obtained from a Mindray Patient Monitor. Furthermore, the pulse wave velocity computed from the obtained PTTD is compared with the pulse wave velocity obtained from the color Doppler ultrasound system and is found to be in good agreement. The major advantage of the PTTD measurement via FBGPRs is that the data acquisition system employed can simultaneously acquire pulse pressure waveforms from both FBGPRs placed at carotid and radial arterial sites with a single time scale, which eliminates time synchronization complexity. (C) 2015 Society of Photo-Optical Instrumentation Engineers (SPIE)

Autonomous Star Camera Calibration and Spacecraft Attitude Determination

This paper presents two methods of star camera calibration to determine camera calibrating parameters (like principal point, focal length etc) along with lens distortions (radial and decentering). First method works autonomously utilizing star coordinates in three consecutive image frames thus independent of star identification or biased attitude information. The parameters obtained in autonomous self-calibration technique helps to identify the imaged stars with the cataloged stars. Least Square based second method utilizes inertial star coordinates to determine satellite attitude and star camera parameters with lens radial distortion, both independent of each other. Camera parameters determined by the second method are more accurate than the first method of camera self calibration. Moreover, unlike most of the attitude determination algorithms where attitude of the satellite depend on the camera calibrating parameters, the second method has the advantage of computing spacecraft attitude independent of camera calibrating parameters except lens distortions (radial). Finally Kalman filter based sequential estimation scheme is employed to filter out the noise of the LS based estimation.

Human Action Recognition in Compressed Domain using PBL-McRBFN Approach

Large variations in human actions lead to major challenges in computer vision research. Several algorithms are designed to solve the challenges. Algorithms that stand apart, help in solving the challenge in addition to performing faster and efficient manner. In this paper, we propose a human cognition inspired projection based learning for person-independent human action recognition in the H.264/AVC compressed domain and demonstrate a PBL-McRBEN based approach to help take the machine learning algorithms to the next level. Here, we use gradient image based feature extraction process where the motion vectors and quantization parameters are extracted and these are studied temporally to form several Group of Pictures (GoP). The GoP is then considered individually for two different bench mark data sets and the results are classified using person independent human action recognition. The functional relationship is studied using Projection Based Learning algorithm of the Meta-cognitive Radial Basis Function Network (PBL-McRBFN) which has a cognitive and meta-cognitive component. The cognitive component is a radial basis function network while the Meta-Cognitive Component(MCC) employs self regulation. The McC emulates human cognition like learning to achieve better performance. Performance of the proposed approach can handle sparse information in compressed video domain and provides more accuracy than other pixel domain counterparts. Performance of the feature extraction process achieved more than 90% accuracy using the PTIL-McRBFN which catalyzes the speed of the proposed high speed action recognition algorithm. We have conducted twenty random trials to find the performance in GoP. The results are also compared with other well known classifiers in machine learning literature.

Action Recognition from Motion Capture Data using Meta-cognitive RBF Network Classifier

Action recognition plays an important role in various applications, including smart homes and personal assistive robotics. In this paper, we propose an algorithm for recognizing human actions using motion capture action data. Motion capture data provides accurate three dimensional positions of joints which constitute the human skeleton. We model the movement of the skeletal joints temporally in order to classify the action. The skeleton in each frame of an action sequence is represented as a 129 dimensional vector, of which each component is a 31) angle made by each joint with a fixed point on the skeleton. Finally, the video is represented as a histogram over a codebook obtained from all action sequences. Along with this, the temporal variance of the skeletal joints is used as additional feature. The actions are classified using Meta-Cognitive Radial Basis Function Network (McRBFN) and its Projection Based Learning (PBL) algorithm. We achieve over 97% recognition accuracy on the widely used Berkeley Multimodal Human Action Database (MHAD).

Analysis of Wrist Pulse Signals Using Spatial Features in Time Domain

Wrist pulse signal contains more important information about the health status of a person and pulse signal diagnosis has been employed in oriental medicine since very long time. In this paper we have used signal processing techniques to extract information from wrist pulse signals. For this purpose we have acquired radial artery pulse signals at wrist position noninvasively for different cases of interest. The wrist pulse waveforms have been analyzed using spatial features. Results have been obtained for the case of wrist pulse signals recorded for several subjects before exercise and after exercise. It is shown that the spatial features show statistically significant changes for the two cases and hence they are effective in distinguishing the changes taking place due to exercise. Support vector machine classifier is used to classify between the groups, and a high classification accuracy of 99.71% is achieved. Thus this paper demonstrates the utility of the spatial features in studying wrist pulse signals obtained under various recording conditions. The ability of the model to distinguish changes occurring under two different recording conditions can be potentially used for health care applications.