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.

Patterning of crystalline organic materials by electro-hydrodynamic lithography.

The control of semi-crystalline polymers in thin films and in micrometer-sized patterns is attractive for (opto-)electronic applications. Electro-hydrodynamic lithography (EHL) enables the structure formation of organic crystalline materials on the micrometer length scale while at the same time exerting control over crystal orientation. This gives rise to well-defined micro-patterned arrays of uniaxially aligned polymer crystals. This study explores the interplay of EHL structure formation with crystal alignment and studies the mechanisms that give rise to crystal orientation in EHL-generated structures.

Re-examination of the coefficient of determination (r2) using road materials engineering case studies

The analysis of scientific data is integral to materials engineering and science. The correlation between measured variables is often quantified by estimating the coefficient of determination or the r2 value. This is the recognised procedure for determining linear relationships. The authors review the derivation of the r2 value and derive an associated quantity, termed the relative deviation (RD), which is the ratio of the root mean square of the deviations about the fitted line to the root mean square of the deviations about the y bar line expressed as a percentage. The relative deviation has an advantage over the coefficient of determination in that it has greater numerical sensitivity to changes in the spread of data about the fitted line, especially when the scatter is small. In addition, the relative deviation is able to define, in percentage terms, the reduction in scatter when different independent variables are correlated with a common dependent variable. Four case studies in the materials field (aggregate crushing value, Atterberg limits, permeability and creep of asphalt) from work carried out at the Queensland Main Roads Department are presented to show the use of the new parameter RD.

Nested sampling for materials: the case of hard spheres

The recently introduced nested sampling algorithm allows the direct and efficient calculation of the partition function of atomistic systems. We demonstrate its applicability to condensed phase systems with periodic boundary conditions by studying the three dimensional hard sphere model. Having obtained the partition function, we show how easy it is to calculate the compressibility and the free energy as functions of the packing fraction and local order, verifying that the transition to crystallinity has a very small barrier, and that the entropic contribution of jammed states to the free energy is negligible for packing fractions above the phase transition. We quantify the previously proposed schematic phase diagram and estimate the extent of the region of jammed states. We find that within our samples, the maximally random jammed configuration is surprisingly disordered.

Identification of Materials from Construction Site Images Using Content Based Image Retrieval Techniques

The capability to automatically identify shapes, objects and materials from the image content through direct and indirect methodologies has enabled the development of several civil engineering related applications that assist in the design, construction and maintenance of construction projects. Examples include surface cracks detection, assessment of fire-damaged mortar, fatigue evaluation of asphalt mixes, aggregate shape measurements, velocimentry, vehicles detection, pore size distribution in geotextiles, damage detection and others. This capability is a product of the technological breakthroughs in the area of Image and Video Processing that has allowed for the development of a large number of digital imaging applications in all industries ranging from the well established medical diagnostic tools (magnetic resonance imaging, spectroscopy and nuclear medical imaging) to image searching mechanisms (image matching, content based image retrieval). Content based image retrieval techniques can also assist in the automated recognition of materials in construction site images and thus enable the development of reliable methods for image classification and retrieval. The amount of original imaging information produced yearly in the construction industry during the last decade has experienced a tremendous growth. Digital cameras and image databases are gradually replacing traditional photography while owners demand complete site photograph logs and engineers store thousands of images for each project to use in a number of construction management tasks. However, construction companies tend to store images without following any standardized indexing protocols, thus making the manual searching and retrieval a tedious and time-consuming effort. Alternatively, material and object identification techniques can be used for the development of automated, content based, construction site image retrieval methodology. These methods can utilize automatic material or object based indexing to remove the user from the time-consuming and tedious manual classification process. In this paper, a novel material identification methodology is presented. This method utilizes content based image retrieval concepts to match known material samples with material clusters within the image content. The results demonstrate the suitability of this methodology for construction site image retrieval purposes and reveal the capability of existing image processing technologies to accurately identify a wealth of materials from construction site images.

Numerical analysis of AC loss reduction in HTS superconducting coils using magnetic materials to divert flux

In this paper, the use of magnetic materials to divert flux in high-temperature superconductor superconducting coils and reduce transport ac loss is investigated. This particular technique is preferred over other techniques, such as striation, Roebel transposition, and twisted wires because it does not require modification to the conductor itself, which can be detrimental to the properties of the superconductor. The technique can also be implemented for existing coils. The analysis is carried out using a coil model based on the H formulation and implemented in comsol multiphysics. Both weakly and strongly magnetic materials are investigated, and it is shown that the use of such materials can divert flux and achieve a reduction in transport ac loss, which, in some cases, is quite significant. This analysis acts to provide a foundation for further optimization and experimental work in the future. © 2011 IEEE.

Nanoindentation of biological and biomimetic materials

Nanoindentation techniques have recently been adapted for the study of biological materials. This feature will consider the experimental adaptations required for such studies. Following a brief review of the structure and constitutive behavior of biological materials, we examine the experimental aspects in detail, including working with hydrated samples, time-dependent mechanical behavior and extremely compliant materials. The analysis of experimental data, consistent with the constitutive response of the material, will then be treated. Examples of nanoindentation data collected using commercially-available instruments are shown, including nanoindentation creep curves of biological materials and relaxation responses of biomimetic hydrogels. Finally, we conclude by examining the current state and future needs of the biological nanoindentation community. © 2011, Society for Experimental Mechanics.