Optimal design of Functionally Graded Materials using a procedural model and Particle Swarm Optimization

A new method for the optimal design of Functionally Graded Materials (FGM) is proposed in this paper. Instead of using the widely used explicit functional models, a feature tree based procedural model is proposed to represent generic material heterogeneities. A procedural model of this sort allows more than one explicit function to be incorporated to describe versatile material gradations and the material composition at a given location is no longer computed by simple evaluation of an analytic function, but obtained by execution of customizable procedures. This enables generic and diverse types of material variations to be represented, and most importantly, by a reasonably small number of design variables. The descriptive flexibility in the material heterogeneity formulation as well as the low dimensionality of the design vectors help facilitate the optimal design of functionally graded materials. Using the nature-inspired Particle Swarm Optimization (PSO) method, functionally graded materials with generic distributions can be efficiently optimized. We demonstrate, for the first time, that a PSO based optimizer outperforms classical mathematical programming based methods, such as active set and trust region algorithms, in the optimal design of functionally graded materials. The underlying reason for this performance boost is also elucidated with the help of benchmarked examples. © 2011 Elsevier Ltd. All rights reserved.

Frictional flow of damp granular material in a conical centrifuge

An analysis is given of velocity and pressure-dependent sliding flow of a thin layer of damp granular material in a spinning cone. Integral momentum equations for steady state, axisymmetric flow are derived using a boundary layer approximation. These reduce to two coupled first-order differential equations for the radial and circumferential sliding velocities. The influence of viscosity and friction coefficients and inlet boundary conditions is explored by presentation of a range of numerical results. In the absence of any interfacial shear traction the flow would, with increasing radial and circumferential slip, follow a trajectory from inlet according to conservation of angular momentum and kinetic energy. Increasing viscosity or friction reduces circumferential slip and, in general, increases the residence time of a particle in the cone. The residence time is practically insensitive to the inlet velocity. However, if the cone angle is very close to the friction angle then the residence time is extremely sensitive to the relative magnitude of these angles. © 2011 Authors.

The influence of particle shape on the stress-strain and creep response of a fine silica sand

The influence of particle shape on the stress-strain response of fine silica sand is investigated experimentally. Two sands from the same source and with the same particle size distribution were examined using Fourier descriptor analysis for particle shape. Their grains were, on average, found to have similar angularity but different elongation. During triaxial stress path testing, the stress-strain behavior of the sands for both loading and creep stages were found to be influenced by particle elongation. In particular, the behavior of the sand with less elongated grains was more like that of rounded glass beads during creep. The results highlight the role of particle shape in stress transmission in granular packings and suggest that shape should be taken more rigorously into consideration in characterizing geomaterials. © 2005 Taylor & Francis Group.

Particle Image Velocimetry analysis in dynamic centrifuge tests

The Particle Image Velocimetry (PIV) technique is an image processing tool to obtain instantaneous velocity measurements during an experiment. The basic principle of PIV analysis is to divide the image into small patches and calculate the locations of the individual patches in consecutive images with the help of cross correlation functions. This paper focuses on the application of the PIV analysis in dynamic centrifuge tests on small scale tunnels in loose, dry sand. Digital images were captured during the application of the earthquake loading on tunnel models using a fast digital camera capable of taking digital images at 1000 frames per second at 1 Megapixel resolution. This paper discusses the effectiveness of the existing methods used to conduct PIV analyses on dynamic centrifuge tests. Results indicate that PIV analysis in dynamic testing requires special measures in order to obtain reasonable deformation data. Nevertheless, it was possible to obtain interesting mechanisms regarding the behaviour of the tunnels from PIV analyses. © 2010 Taylor & Francis Group, London.

Single-particle probing of edge-state formation in a graphene nanoribbon

We investigate the effect of a perpendicular magnetic field on the single-particle charging spectrum of a graphene quantum dot embedded inline with a nanoribbon. We observe uniform shifts in the single-particle spectrum which coincide with peaks in the magnetoconductance, implicating Landau level condensation and edge state formation as the mechanism underlying magnetic field-enhanced transmission through graphene nanostructures. The experimentally determined ratio of bulk to edge states is supported by single-particle band-structure simulations, while a fourfold beating of the Coulomb blockade transmission amplitude points to many-body interaction effects during Landau level condensation of the ν=0 state. © 2012 American Physical Society.

Vehicle trajectory linearisation to enable efficient optimisation of the constant speed racing line

A driver model is presented capable of optimising the trajectory of a simple dynamic nonlinear vehicle, at constant forward speed, so that progression along a predefined track is maximised as a function of time. In doing so, the model is able to continually operate a vehicle at its lateral-handling limit, maximising vehicle performance. The technique used forms a part of the solution to the motor racing objective of minimising lap time. A new approach of formulating the minimum lap time problem is motivated by the need for a more computationally efficient and robust tool-set for understanding on-the-limit driving behaviour. This has been achieved through set point-dependent linearisation of the vehicle model and coupling the vehicle-track system using an intrinsic coordinate description. Through this, the geometric vehicle trajectory had been linearised relative to the track reference, leading to new path optimisation algorithm which can be formed as a computationally efficient convex quadratic programming problem. © 2012 Copyright Taylor and Francis Group, LLC.

Automated Computation of the Fundamental Matrix for Vision-Based Construction Site Applications

Estimating the fundamental matrix (F), to determine the epipolar geometry between a pair of images or video frames, is a basic step for a wide variety of vision-based functions used in construction operations, such as camera-pair calibration, automatic progress monitoring, and 3D reconstruction. Currently, robust methods (e.g., SIFT + normalized eight-point algorithm + RANSAC) are widely used in the construction community for this purpose. Although they can provide acceptable accuracy, the significant amount of required computational time impedes their adoption in real-time applications, especially video data analysis with many frames per second. Aiming to overcome this limitation, this paper presents and evaluates the accuracy of a solution to find F by combining the use of two speedy and consistent methods: SURF for the selection of a robust set of point correspondences and the normalized eight-point algorithm. This solution is tested extensively on construction site image pairs including changes in viewpoint, scale, illumination, rotation, and moving objects. The results demonstrate that this method can be used for real-time applications (5 image pairs per second with the resolution of 640 × 480) involving scenes of the built environment.

The Gaussian mixture MCMC particle algorithm for dynamic cluster tracking

We present a novel filtering algorithm for tracking multiple clusters of coordinated objects. Based on a Markov chain Monte Carlo (MCMC) mechanism, the new algorithm propagates a discrete approximation of the underlying filtering density. A dynamic Gaussian mixture model is utilized for representing the time-varying clustering structure. This involves point process formulations of typical behavioral moves such as birth and death of clusters as well as merging and splitting. For handling complex, possibly large scale scenarios, the sampling efficiency of the basic MCMC scheme is enhanced via the use of a Metropolis within Gibbs particle refinement step. As the proposed methodology essentially involves random set representations, a new type of estimator, termed the probability hypothesis density surface (PHDS), is derived for computing point estimates. It is further proved that this estimator is optimal in the sense of the mean relative entropy. Finally, the algorithm's performance is assessed and demonstrated in both synthetic and realistic tracking scenarios. © 2012 Elsevier Ltd. All rights reserved.

A backward-simulation based Rao-Blackwellized particle smoother for conditionally linear Gaussian models

In this article, we develop a new Rao-Blackwellized Monte Carlo smoothing algorithm for conditionally linear Gaussian models. The algorithm is based on the forward-filtering backward-simulation Monte Carlo smoother concept and performs the backward simulation directly in the marginal space of the non-Gaussian state component while treating the linear part analytically. Unlike the previously proposed backward-simulation based Rao-Blackwellized smoothing approaches, it does not require sampling of the Gaussian state component and is also able to overcome certain normalization problems of two-filter smoother based approaches. The performance of the algorithm is illustrated in a simulated application. © 2012 IFAC.

Characteristics of blood flow in microchannels and relevant impact on modelling blood behaviour in biochip separators

This paper reports a perspective investigation of computational modelling of blood fluid in microchannel devices as a preparation for future research on fluid-structure interaction (FSI) in biofluid mechanics. The investigation is carried out through two aspects, respectively on physical behaviours of blood flow in microchannels and appropriate methodology for modelling. The physics of blood flow is targeted to the challenges for describing blood flow in microchannels, including rheology of blood fluid, suspension features of red blood cells (RBCs), laminar hydrodynamic influence and effect of surface roughness. The analysis shows that due to the hyperelastic property of RBC and its comparable dimension with microchannels, blood fluid shows complex behaviours of two phase flow. The trajectory and migration of RBCs require accurate description of RBC deformation and interaction with plasma. Following on a discussion of modelling approaches, i.e. Eulerian method and Lagrangian method, the main stream modelling methods for multiphase flow are reviewed and their suitability to blood flow is analysed. It is concluded that the key issue for blood flow modelling is how to describe the suspended blood cells, modelled by Lagrangian method, and couple them with the based flow, modelled by Eulerian method. The multiphase flow methods are thereby classified based on the number of points required for describing a particle, as follows: (i) single-point particle methods, (ii) mutli-point particle methods, (iii) functional particle methods, and (iv) fluid particle methods. While single-point particle methods concentrate on particle dynamic movement, multipoint and functional particle methods can take into account particle mechanics and thus offer more detailed information for individual particles. Fluid particle methods provide good compromise between two phases, but require additional information for particle mechanics. For furthermore detailed description, we suggest to investigate the possibility using two domain coupling method, in which particles and base flow are modelled by two separated solvers. It is expected that this paper could clarify relevant issues in numerical modelling of blood flow in microchannels and induce some considerations for modelling blood flow using multiphase flow methods. © 2012 IEEE.