WAVES IN 2D ANISOTROPIC L-C LATTICE METAMATERIALS:PHENOMENOLOGY AND PROPERTIES

Anisotropic metamaterials composed of 2D periodic infi- nite and finite periodic lattices of lumped inductor (L) and capacitor (C) circuits have been explored. The unique features of wave channeling on such anisotropic lattices and scattering at their interfaces and edges are reviewed and illustrated by the examples of the specific arrangements. The lattice unit cells composed of inductors and capacitors (basic mesh) as well as of assemblies comprised of double series, double parallel, and mixed parallel-series L-C circuits are discussed.

2D-drop model applied to the calculation of step formation energies on a (111) substrate

A model is presented for obtaining the step formation energy for metallic islands on (1 1 1) surfaces from Monte Carlo simulations. This model is applied to homo (Cu/Cu(1 1 1), Ag/Ag(1 1 1)) and heteroepitaxy (Ag/Pt(1 1 1)) systems. The embedded atom method is used to represent the interaction between the particles of the system, but any other type of potential could be used as well. The formulation can also be employed to consider the case of other single crystal surfaces, since the higher barriers for atom motion on other surfaces are not a hindrance for the simulation scheme proposed.

Automated mixed dimensional modelling from 2D and 3D CAD models

The motivation for this paper is to present procedures for automatically creating idealised finite element models from the 3D CAD solid geometry of a component. The procedures produce an accurate and efficient analysis model with little effort on the part of the user. The technique is applicable to thin walled components with local complex features and automatically creates analysis models where 3D elements representing the complex regions in the component are embedded in an efficient shell mesh representing the mid-faces of the thin sheet regions. As the resulting models contain elements of more than one dimension, they are referred to as mixed dimensional models. Although these models are computationally more expensive than some of the idealisation techniques currently employed in industry, they do allow the structural behaviour of the model to be analysed more accurately, which is essential if appropriate design decisions are to be made. Also, using these procedures, analysis models can be created automatically whereas the current idealisation techniques are mostly manual, have long preparation times, and are based on engineering judgement. In the paper the idealisation approach is first applied to 2D models that are used to approximate axisymmetric components for analysis. For these models 2D elements representing the complex regions are embedded in a 1D mesh representing the midline of the cross section of the thin sheet regions. Also discussed is the coupling, which is necessary to link the elements of different dimensionality together. Analysis results from a 3D mixed dimensional model created using the techniques in this paper are compared to those from a stiffened shell model and a 3D solid model to demonstrate the improved accuracy of the new approach. At the end of the paper a quantitative analysis of the reduction in computational cost due to shell meshing thin sheet regions demonstrates that the reduction in degrees of freedom is proportional to the square of the aspect ratio of the region, and for long slender solids, the reduction can be proportional to the aspect ratio of the region if appropriate meshing algorithms are used.

Mesophases in Nearly 2D Room-Temperature Ionic Liquids

Computer simulations of (i) a [C(12)mim][Tf2N] film of nanometric thickness squeezed at kbar pressure by a piecewise parabolic confining potential reveal a mesoscopic in-plane density and composition modulation reminiscent of mesophases seen in 3D samples of the same room-temperature ionic liquid (RTIL). Near 2D confinement, enforced by a high normal load, as well as relatively long aliphatic chains are strictly required for the mesophase formation, as confirmed by computations for two related systems made of (ii) the same [C(12)mim][Tf2N] adsorbed at a neutral solid surface and (iii) a shorter-chain RTIL ([C(4)mim][Tf2N]) trapped in the potential well of part i. No in-plane modulation is seen for ii and iii. In case ii, the optimal arrangement of charge and neutral tails is achieved by layering parallel to the surface, while, in case iii, weaker dispersion and packing interactions are unable to bring aliphatic tails together into mesoscopic islands, against overwhelming entropy and Coulomb forces. The onset of in-plane mesophases could greatly affect the properties of long-chain RTILs used as lubricants.

Optical transmission properties and electric field distribution of interacting 2D silver nanorod Arrays

Silver nanorods have been grown by electrodeposition into thin film porous alumina templates (AAO). Optical transmission measurements using p-polarized incident white light shows clear plasmon resonance extinction peaks. We successfully model the dependence on angle in incidence of extinction peak height and position using a multiple-multipoles (MMP) approach with the different spectral features being clearly associated with the effective electric field distribution and coupling between individual nanorods.

A spatio-temporal 2D-models framework for human pose recovery in monocular sequences

This paper addresses the pose recovery problem of a particular articulated object: the human body. In this model-based approach, the 2D-shape is associated to the corresponding stick figure allowing the joint segmentation and pose recovery of the subject observed in the scene. The main disadvantage of 2D-models is their restriction to the viewpoint. To cope with this limitation, local spatio-temporal 2D-models corresponding to many views of the same sequences are trained, concatenated and sorted in a global framework. Temporal and spatial constraints are then considered to build the probabilistic transition matrix (PTM) that gives a frame to frame estimation of the most probable local models to use during the fitting procedure, thus limiting the feature space. This approach takes advantage of 3D information avoiding the use of a complex 3D human model. The experiments carried out on both indoor and outdoor sequences have demonstrated the ability of this approach to adequately segment pedestrians and estimate their poses independently of the direction of motion during the sequence. (c) 2008 Elsevier Ltd. All rights reserved.

Exploiting spatio-temporal constraints for robust 2D pose tracking

We present a Spatio-temporal 2D Models Framework (STMF) for 2D-Pose tracking. Space and time are discretized and a mixture of probabilistic "local models" is learnt associating 2D Shapes and 2D Stick Figures. Those spatio-temporal models generalize well for a particular viewpoint and state of the tracked action but some spatio-temporal discontinuities can appear along a sequence, as a direct consequence of the discretization. To overcome the problem, we propose to apply a Rao-Blackwellized Particle Filter (RBPF) in the 2D-Pose eigenspace, thus interpolating unseen data between view-based clusters. The fitness to the images of the predicted 2D-Poses is evaluated combining our STMF with spatio-temporal constraints. A robust, fast and smooth human motion tracker is obtained by tracking only the few most important dimensions of the state space and by refining deterministically with our STMF.

2D silhouette and 3D skeletal models for human detection and tracking

In this paper we propose a statistical model for detection and tracking of human silhouette and the corresponding 3D skeletal structure in gait sequences. We follow a point distribution model (PDM) approach using a Principal Component Analysis (PCA). The problem of non-lineal PCA is partially resolved by applying a different PDM depending of pose estimation; frontal, lateral and diagonal, estimated by Fisher's linear discriminant. Additionally, the fitting is carried out by selecting the closest allowable shape from the training set by means of a nearest neighbor classifier. To improve the performance of the model we develop a human gait analysis to take into account temporal dynamic to track the human body. The incorporation of temporal constraints on the model increase reliability and robustness.