Experimental and micromechanical study of size effects in the constrained deformation of metallic foams

Previous investigations have unveiled size effects in the strength of metallic foams under simple shear - the shear strength increases with diminishing specimen size, a phenomena similar to that shown by Fleck et al. (Acta Mat., 1994, Vol. 42, p. 475.) on the torsion tests of copper wires of various radii. In this study, experimental study of the constrained deformation of a foam layer sandwiched between two steel plates has been conducted. The sandwiched plates are subjected to combined shear and normal loading. It is found that measured yield loci of metallic foams in the normal and shear stress space corresponding to various foam layer thicknesses are self-similar in shape but their size increases as the foam layer thickness decreases. Moreover, the strains profiles across the foam layer thickness are parabolic instead of uniform; their values increase from the interfaces between the foam layer and the steel plates and reach their maximum in the middle of the foam layer, yielding boundary layers adjacent to the steel plates. In order to further explore the origin of observed size effects, micromechanics models have been developed, with the foam layer represented by regular and irregular honeycombs. Though the regular honeycomb model is seen to underestimate the size effects, the irregular honeycomb model faithfully captures the observed features of the constrained deformation of metallic foams.

On the relationship between hidden Markov Models and convex functional transforms for simulating scanning probe Microscopy

Models for simulating Scanning Probe Microscopy (SPM) may serve as a reference point for validating experimental data and practice. Generally, simulations use a microscopic model of the sample-probe interaction based on a first-principles approach, or a geometric model of macroscopic distortions due to the probe geometry. Examples of the latter include use of neural networks, the Legendre Transform, and dilation/erosion transforms from mathematical morphology. Dilation and the Legendre Transform fall within a general family of functional transforms, which distort a function by imposing a convex solution.In earlier work, the authors proposed a generalized approach to modeling SPM using a hidden Markov model, wherein both the sample-probe interaction and probe geometry may be taken into account. We present a discussion of the hidden Markov model and its relationship to these convex functional transforms for simulating and restoring SPM images.©2009 SPIE.

High speed electro-thermal models for inverter simulations

This paper presents the application of advanced compact models of the IGBT and PIN diode to the full electrothermal system simulation of a hybrid electric vehicle converter using a look-up table of device losses. The Fourier-based solution model is used, which takes account of features such as local lifetime control and field-stop technology. Device and circuit parameters are extracted from experimental waveforms and device structural data. Matching of the switching waveforms and the resulting generation of the look-up table is presented. An example of the use of the look-up tables in simulation of inverter device temperatures is also given, for a hypothetical electric vehicle subjected to an urban driving cycle. © 2006 IEEE.

Assessment of CFD models for shock boundary-layer interaction

A workshop on the computational fluid dynamics (CFD) prediction of shock boundary-layer interactions (SBLIs) was held at the 48th AIAA Aerospace Sciences Meeting. As part of the workshop numerous CFD analysts submitted solutions to four experimentally measured SBLIs. This paper describes the assessment of the CFD predictions. The assessment includes an uncertainty analysis of the experimental data, the definition of an error metric and the application of that metric to the CFD solutions. The CFD solutions provided very similar levels of error and in general it was difficult to discern clear trends in the data. For the Reynolds Averaged Navier-Stokes methods the choice of turbulence model appeared to be the largest factor in solution accuracy. Large-eddy simulation methods produced error levels similar to RANS methods but provided superior predictions of normal stresses.

Structured discriminative models for noise robust continuous speech recognition

Recently there has been interest in structured discriminative models for speech recognition. In these models sentence posteriors are directly modelled, given a set of features extracted from the observation sequence, and hypothesised word sequence. In previous work these discriminative models have been combined with features derived from generative models for noise-robust speech recognition for continuous digits. This paper extends this work to medium to large vocabulary tasks. The form of the score-space extracted using the generative models, and parameter tying of the discriminative model, are both discussed. Update formulae for both conditional maximum likelihood and minimum Bayes' risk training are described. Experimental results are presented on small and medium to large vocabulary noise-corrupted speech recognition tasks: AURORA 2 and 4. © 2011 IEEE.

A comparison of the value of viscosity for several water models using Poiseuille flow in a nano-channel.

The viscosity-temperature relation is determined for the water models SPC/E, TIP4P, TIP4P/Ew, and TIP4P/2005 by considering Poiseuille flow inside a nano-channel using molecular dynamics. The viscosity is determined by fitting the resulting velocity profile (away from the walls) to the continuum solution for a Newtonian fluid and then compared to experimental values. The results show that the TIP4P/2005 model gives the best prediction of the viscosity for the complete range of temperatures for liquid water, and thus it is the preferred water model of these considered here for simulations where the magnitude of viscosity is crucial. On the other hand, with the TIP4P model, the viscosity is severely underpredicted, and overall the model performed worst, whereas the SPC/E and TIP4P/Ew models perform moderately.

A review on slip models for gas microflows

Accurate modeling of gas microflow is crucial for the microfluidic devices in MEMS. Gas microflows through these devices are often in the slip and transition flow regimes, characterized by the Knudsen number of the order of 10-2∼100. An increasing number of researchers now dedicate great attention to the developments in the modeling of non-equilibrium boundary conditions in the gas microflows, concentrating on the slip model. In this review, we present various slip models obtained from different theoretical, computational and experimental studies for gas microflows. Correct descriptions of the Knudsen layer effect are of critical importance in modeling and designing of gas microflow systems and in predicting their performances. Theoretical descriptions of the gas-surface interaction and gas-surface molecular interaction models are introduced to describe the boundary conditions. Various methods and techniques for determination of the slip coefficients are reviewed. The review presents the considerable success in the implementation of various slip boundary conditions to extend the Navier-Stokes (N-S) equations into the slip and transition flow regimes. Comparisons of different values and formulations of the first- and second-order slip coefficients and models reveal the discrepancies arising from different definitions in the first-order slip coefficient and various approaches to determine the second-order slip coefficient. In addition, no consensus has been reached on the correct and generalized form of higher-order slip expression. The influences of specific effects, such as effective mean free path of the gas molecules and viscosity, surface roughness, gas composition and tangential momentum accommodation coefficient, on the hybrid slip models for gas microflows are analyzed and discussed. It shows that although the various hybrid slip models are proposed from different viewpoints, they can contribute to N-S equations for capturing the high Knudsen number effects in the slip and transition flow regimes. Future studies are also discussed for improving the understanding of gas microflows and enabling us to exactly predict and actively control gas slip. © Springer-Verlag 2012.

Experimental and numerical investigation of fracture mechanics of bitumen beams

This work presents an experimental and numerical investigation to characterise the fracture properties of pure bitumen (the binder in asphalt paving materials). The paper is divided into two parts. The first part describes an experimental study of fracture characterisation parameters of pure bitumen as determined by three-point bend tests. The second part deals with modelling of fracture and failure of bitumen by Finite Element analysis. Fracture mechanics parameters, stress intensity factor, KIC, fracture energy, GIC, and J-integral, JIC, are used for evaluation of bitumen's fracture properties. The material constitutive model developed by Ossa et al. [40,41] which was implemented into a FE code by Costanzi [18] is combined with cohesive zone models (CZM) to simulate the fracture behaviour of pure bitumen. Experimental and numerical results are presented in the form of failure mechanism maps where ductile, brittle and brittle-ductile transition regimes of fracture behaviour are classified. The FE predictions of fracture behaviour match well with experimental results. © 2012 Elsevier Ltd.

Theoretical and experimental magnetization loss comparison between IBAD coils and RABiTS coils

This paper presents a comparative study of ac magnetization losses in two types of 2 G HTS racetrack coils. The magnetic substrate made by RABiTS is the main difference between the two types, because ferromagnetic loss caused by magnetic substrate is accounted into the total ac losses. IBAD and RABiTS tapes were successfully wound into racetrack shape with identical geometry. The measurements were carried out by using electromagnetic method with pick-up coils under a sinusoidally varying external magnetic field, with amplitudes up to 27 mT, ranging from 10 Hz to 100 Hz at a temperature of 77 K. The field was oriented perpendicularly to the surface of the tapes. Experimental measurements were validated by applying theoretical models and the results showed that the magnetization loss in the MAG RABiTS coil is always higher than that in the NON MAG coil due to the presence of the magnetic substrate, which increases the magnetic field penetration into the coil and causes higher magnetic flux density within the penetrated region. © 2002-2011 IEEE.

Multidirectional scattering models for 3-dimensional ultrasound imaging

An ultrasound image is created from backscattered echoes originating from both diffuse and directional scattering. It is potentially useful to separate these two components for the purpose of tissue characterization. This article presents several models for visualization of scattering fields on 3-dimensional (3D) ultrasound imaging. By scanning the same anatomy from multiple directions, we can observe the variation of specular intensity as a function of the viewing angle. This article considers two models for estimating the diffuse and specular components of the backscattered intensity: a modification of the well-known Phong reflection model and an existing exponential model. We examine 2-dimensional implementations and also propose novel 3D extensions of these models in which the probe is not constrained to rotate within a plane. Both simulation and experimental results show that improved performance can be achieved with 3D models. © 2013 by the American Institute of Ultrasound in Medicine.

Theoretical and experimental analysis of pneumatic balloon microactuators

This paper presents a theoretical and experimental analysis of a biologically inspired balloon-type pneumatic microactuator. The operation principle of pneumatic balloon actuators (PBA's) is based on an asymmetric deflection of two PDMS layers with different thicknesses or different Young's moduli that are bonded together. A new analytical 2D model that describes the complex behavior of these actuators is presented and validated using both 3D FEM models and measurements. The actuators have dimensions ranging from 11 mm × 2 mm × 0.24 mm to 4 mm × 1 mm × 0.12 mm. Their fabrication is based on micromolding of PDMS, and can therefore easily be fabricated in high throughput. Measurements showed that the analytical model provides a qualitative description of the actuator behavior, and showed that the larger actuators are capable of delivering a 7 mm stroke at a supply pressure of 70 kPa and a force of max 22 mN at a supply pressure of 105 kPa. © 2011 Elsevier B.V. All rights reserved.

Bayesian parameter identification for vibro-acoustic models with nonparametric uncertainty

Vibration and acoustic analysis at higher frequencies faces two challenges: computing the response without using an excessive number of degrees of freedom, and quantifying its uncertainty due to small spatial variations in geometry, material properties and boundary conditions. Efficient models make use of the observation that when the response of a decoupled vibro-acoustic subsystem is sufficiently sensitive to uncertainty in such spatial variations, the local statistics of its natural frequencies and mode shapes saturate to universal probability distributions. This holds irrespective of the causes that underly these spatial variations and thus leads to a nonparametric description of uncertainty. This work deals with the identification of uncertain parameters in such models by using experimental data. One of the difficulties is that both experimental errors and modeling errors, due to the nonparametric uncertainty that is inherent to the model type, are present. This is tackled by employing a Bayesian inference strategy. The prior probability distribution of the uncertain parameters is constructed using the maximum entropy principle. The likelihood function that is subsequently computed takes the experimental information, the experimental errors and the modeling errors into account. The posterior probability distribution, which is computed with the Markov Chain Monte Carlo method, provides a full uncertainty quantification of the identified parameters, and indicates how well their uncertainty is reduced, with respect to the prior information, by the experimental data. © 2013 Taylor & Francis Group, London.