Imaging the femoral cortex: Thickness, density and mass from clinical CT

There is growing evidence that focal thinning of cortical bone in the proximal femur may predispose a hip to fracture. Detecting such defects in clinical CT is challenging, since cortices may be significantly thinner than the imaging system's point spread function. We recently proposed a model-fitting technique to measure sub-millimetre cortices, an ill-posed problem which was regularized by assuming a specific, fixed value for the cortical density. In this paper, we develop the work further by proposing and evaluating a more rigorous method for estimating the constant cortical density, and extend the paradigm to encompass the mapping of cortical mass (mineral mg/cm 2) in addition to thickness. Density, thickness and mass estimates are evaluated on sixteen cadaveric femurs, with high resolution measurements from a micro-CT scanner providing the gold standard. The results demonstrate robust, accurate measurement of peak cortical density and cortical mass. Cortical thickness errors are confined to regions of thin cortex and are bounded by the extent to which the local density deviates from the peak, averaging 20% for 0.5mm cortex. © 2012 Elsevier B.V.

On representing chemical environments

We review some recently published methods to represent atomic neighbourhood environments, and analyse their relative merits in terms of their faithfulness and suitability for fitting potential energy surfaces. The crucial properties that such representations (sometimes called descriptors) must have are differentiability with respect to moving the atoms, and invariance to the basic symmetries of physics: rotation, reflection, translation, and permutation of atoms of the same species. We demonstrate that certain widely used descriptors that initially look quite different are specific cases of a general approach, in which a finite set of basis functions with increasing angular wave numbers are used to expand the atomic neighbourhood density function. Using the example system of small clusters, we quantitatively show that this expansion needs to be carried to higher and higher wave numbers as the number of neighbours increases in order to obtain a faithful representation, and that variants of the descriptors converge at very different rates. We also propose an altogether new approach, called Smooth Overlap of Atomic Positions (SOAP), that sidesteps these difficulties by directly defining the similarity between any two neighbourhood environments, and show that it is still closely connected to the invariant descriptors. We test the performance of the various representations by fitting models to the potential energy surface of small silicon clusters and the bulk crystal.

Performing quantitative MFM measurements on soft magnetic nanostructures.

We have extended our previous work (Rawlings et al 2010 Phys. Rev. B 82 085404) on simulating magnetic force microscopy (MFM) images for magnetically soft samples to include an accurate representation of coated MFM tips. We used an array of square 500 nm nanomagnets to evaluate our improved MFM model. A quantitative comparison between model and experiment was performed for lift heights ranging from 20 to 100 nm. No fitting parameters were used in our comparison. For all lift heights the qualitative agreement between model and experiment was significantly improved. At low lift heights, where the magnetic signal was strong, the difference between theory and experiment was less than 30%.

An analytical model for guided wave inspection optimization for prismatic structures of any cross section.

This paper presents an analytical modeling technique for the simulation of long-range ultrasonic guided waves in structures. The model may be used to predict the displacement field in a prismatic structure arising from any excitation arrangement and may therefore be used as a tool to design new inspection systems. It is computationally efficient and relatively simple to implement, yet gives accuracy similar to finite element analysis and semi-analytical finite element analysis methods. The model has many potential applications; one example is the optimization of part-circumferential arrays where access to the full circumference of the pipe is restricted. The model has been successfully validated by comparison with finite element solutions. Experimental validation has also been carried out using an array of piezoelectric transducer elements to measure the displacement field arising from a single transducer element in an 88.9-mm-diameter pipe. Good agreement has been obtained between the two models and the experimental data.

Flaw sizing in pipes using long-range guided wave testing

The absence of adequate inspection data from difficult-to-access areas on pipelines, such as cased-road crossings, makes determination of fitness for continued service and compliance with increasingly stringent regulatory requirements problematic. Screening for corrosion using long-range guided wave testing is a relatively new inspection technique. The complexity of the possible modes of vibration means the technique can be difficult to implement effectively but this also means that it has great potential for both detecting and characterizing flaws. The ability to determine flaw size would enable the direct application of standard procedures for determining fitness-for-service, such as ASME B31G, RSTRENG, or equivalent for tens of metres of pipeline from a single inspection location. This paper presents a new technique for flaw sizing using guided wave inspection data. The technique has been developed using finite element models and experimentally validated on 6'' Schedule 40 steel pipe. Some basic fitness-for-service assessments have been carried out using the measured values and the maximum allowable operating pressure was accurately determined. © 2011 American Institute of Physics.

Stiffness of sands through a laboratory test database

Deformations of sandy soils around geotechnical structures generally involve strains in the range small (0·01%) to medium (0·5%). In this strain range the soil exhibits non-linear stress-strain behaviour, which should be incorporated in any deformation analysis. In order to capture the possible variability in the non-linear behaviour of various sands, a database was constructed including the secant shear modulus degradation curves of 454 tests from the literature. By obtaining a unique S-shaped curve of shear modulus degradation, a modified hyperbolic relationship was fitted. The three curve-fitting parameters are: an elastic threshold strain γe, up to which the elastic shear modulus is effectively constant at G0; a reference strain γr, defined as the shear strain at which the secant modulus has reduced to 0·5G0; and a curvature parameter a, which controls the rate of modulus reduction. The two characteristic strains γe and γr were found to vary with sand type (i.e. uniformity coefficient), soil state (i.e. void ratio, relative density) and mean effective stress. The new empirical expression for shear modulus reduction G/G0 is shown to make predictions that are accurate within a factor of 1·13 for one standard deviation of random error, as determined from 3860 data points. The initial elastic shear modulus, G0, should always be measured if possible, but a new empirical relation is shown to provide estimates within a factor of 1·6 for one standard deviation of random error, as determined from 379 tests. The new expressions for non-linear deformation are easy to apply in practice, and should be useful in the analysis of geotechnical structures under static loading.

Inhomogeneous soils and their effect on ground vibration due to underground railways

Ground vibration due to underground railways is a significant source of disturbance for people living or working near subways. Numerical models are commonly used to predict vibration levels; however, uncertainty inherent to these simulations must be understood to give confidence in the predictions. A semi-analytical approach is developed herein to investigate the effect of uncertainty in soil material properties on the surface vibration of layered halfspaces excited by an underground railway. The half-space is simulated using the thin-layer method coupled with the pipe-in-pipe (PiP) method for determining the load on the buried tunnel. The K-L expansion method is employed to smoothly vary the material properties throughout the soil by up to 10%. The simulation predicts a surface rms velocity variation of 5-10dB compared to a homogeneous, layered halfspace. These results suggest it may be prudent to include a 5dB error band on predicted vibration levels when simulating areas of varied material properties.

Mechanical response of carbon fiber composite sandwich panels with pyramidal truss cores

The combination of light carbon fiber reinforced polymer (CFRP) composite materials with structurally efficient sandwich panel designs offers novel opportunities for ultralight structures. Here, pyramidal truss sandwich cores with relative densities ρ̄ in the range 1-10% have been manufactured from carbon fiber reinforced polymer laminates by employing a snap-fitting method. The measured quasi-static shear strength varied between 0.8 and 7.5 MPa. Two failure modes were observed: (i) Euler buckling of the struts and (ii) delamination failure of the laminates. Micro-buckling failure of the struts was not observed in the experiments reported here while Euler buckling and delamination failures occurred for the low (ρ̄≤1%) and high (ρ̄>1%) relative density cores, respectively. Analytical models for the collapse of the composite cores by these failure modes are presented. Good agreement between the measurements and predictions based on the Euler buckling and delamination failure of the struts is observed while the micro-buckling analysis over-predicts the measurements. The CFRP pyramidal cores investigated here have a similar mechanical performance to CFRP honeycombs. Thus, for a range of multi-functional applications that require an "open-celled" architecture (e.g. so that cooling fluid can pass through a sandwich core), the CFRP pyramidal cores offer an attractive alternative to honeycombs. © 2012 Elsevier Ltd. All rights reserved.

Measurement of the elastic constants of nanometric films

Carbon coatings of thickness down to 2 nanometers are needed to increase the storage density in magnetic hard disks and reach the 100 Gbit/in2 target. Methods to measure the properties of these ultrathin hard films still have to be developed. We show that combining Surface Brillouin Scattering (SBS) andX-ray reflectivity measurements the elastic constants of such films are accessible. Tetrahedral amorphous carbofilms of thickness down to about 2 nm were deposited on Si by an S bend filtered cathodic vacuum arc, achieving a continuous coverage on large areas free of macroparticles. Film thickness and mass density are measured by X-ray reflectivity: densities above 3 g/cm3 are found, indicating a significant sp3 content. The dispersion relations of surface acoustic waves are measured by SBS. We show that for thicknesses above ∼4 nm these waves can be described by a continuum elastic model based on a single homogeneous equivalent film. The elastic constants can then be obtained by fitting the dispersion relations, computed for given film properties, to the measured dispersion relations. For thicknesses of 3 nm or less qualitative differences among films are well measurable, but quantitative results are less reliable. We have thus shown that we can grow and characterise nanometer size tetrahedral amorphous carbon film, which maintain their high density and peculiar mechanical properties down to around 4 nm thickness, satisfying the requirements set for the hard disk coating material.

Gaussian Approximation Potential: an interatomic potential derived from first principles Quantum Mechanics

Simulation of materials at the atomistic level is an important tool in studying microscopic structure and processes. The atomic interactions necessary for the simulation are correctly described by Quantum Mechanics. However, the computational resources required to solve the quantum mechanical equations limits the use of Quantum Mechanics at most to a few hundreds of atoms and only to a small fraction of the available configurational space. This thesis presents the results of my research on the development of a new interatomic potential generation scheme, which we refer to as Gaussian Approximation Potentials. In our framework, the quantum mechanical potential energy surface is interpolated between a set of predetermined values at different points in atomic configurational space by a non-linear, non-parametric regression method, the Gaussian Process. To perform the fitting, we represent the atomic environments by the bispectrum, which is invariant to permutations of the atoms in the neighbourhood and to global rotations. The result is a general scheme, that allows one to generate interatomic potentials based on arbitrary quantum mechanical data. We built a series of Gaussian Approximation Potentials using data obtained from Density Functional Theory and tested the capabilities of the method. We showed that our models reproduce the quantum mechanical potential energy surface remarkably well for the group IV semiconductors, iron and gallium nitride. Our potentials, while maintaining quantum mechanical accuracy, are several orders of magnitude faster than Quantum Mechanical methods.

Learning based automatic face annotation for arbitrary poses and expressions from frontal images only

Statistical approaches for building non-rigid deformable models, such as the Active Appearance Model (AAM), have enjoyed great popularity in recent years, but typically require tedious manual annotation of training images. In this paper, a learning based approach for the automatic annotation of visually deformable objects from a single annotated frontal image is presented and demonstrated on the example of automatically annotating face images that can be used for building AAMs for fitting and tracking. This approach employs the idea of initially learning the correspondences between landmarks in a frontal image and a set of training images with a face in arbitrary poses. Using this learner, virtual images of unseen faces at any arbitrary pose for which the learner was trained can be reconstructed by predicting the new landmark locations and warping the texture from the frontal image. View-based AAMs are then built from the virtual images and used for automatically annotating unseen images, including images of different facial expressions, at any random pose within the maximum range spanned by the virtually reconstructed images. The approach is experimentally validated by automatically annotating face images from three different databases. © 2009 IEEE.

Electrical transport and percolation in magnetoresistive manganite / insulating oxide composites: case of La0.7Ca0.3MnO3 / Mn3O4

We report the results of electrical resistivity measurements carried out on well-sintered La0.7Ca0.3MnO3 / Mn3O4 composite samples with almost constant composition of the magnetoresistive manganite phase (La0.7Ca0.3MnO3). A percolation threshold (fc) occurs when the La0.7Ca0.3MnO3 volume fraction is ~ 0.19. The dependence of the electrical resistivity as a function of La0.7Ca0.3MnO3 volume fraction (fLCMO) can be described by percolation-like phenomenological equations. Fitting the conducting regime (fLCMO > fc) by the percolation power law returns a critical exponent t value of 2.0 +/- 0.2 at room temperature and 2.6 +/-0.2 at 5 K. The increase of t is ascribed to the influence of the grain boundaries on the electrical conduction process at low temperature.

Self-assembled multilayer graphene oxide membrane and carbon nanotubes synthesized using a rare form of natural graphite

The fabrication of flexible multilayer graphene oxide (GO) membrane and carbon nanotubes (CNTs) using a rare form of high-purity natural graphite, vein graphite, is reported for the first time. Graphite oxide is synthesized using vein graphite following Hummer's method. By facilitating functionalized graphene sheets in graphite oxide to self-assemble, a multilayer GO membrane is fabricated. Electric arc discharge is used to synthesis CNTs from vein graphite. Both multilayer GO membrane and CNTs are investigated using microscopy and spectroscopy experiments, i.e., scanning electron microscopy (SEM), atomic force microscopy (AFM), high-resolution transmission electron microscopy (HRTEM), Fourier transform infrared spectroscopy (FTIR), X-ray diffraction (XRD), thermogravimetric analysis (TGA), core level photoelectron spectroscopy, and C K-edge X-ray absorption spectroscopy (NEXAFS), to characterize their structural and topographical properties. Characterization of vein graphite using different techniques reveals that it has a large number of crystallites, hence the large number of graphene sheets per crystallite, preferentially oriented along the (002) plane. NEXAFS and core level spectra confirm that vein graphite is highly crystalline and pure. Fourier transform infrared (FT-IR) and C 1s core level spectra show that oxygen functionalities (-C-OH, -CO,-C-O-C-) are introduced into the basal plane of graphite following chemical oxidation. Carbon nanotubes are produced from vein graphite through arc discharge without the use of any catalyst. HRTEM confirm that multiwalled carbon nanotube (MWNTs) are produced with the presence of some structure in the central pipe. A small percentage of single-walled nanotubes (SWNTs) are also produced simultaneously with MWNTs. Spectroscopic and microscopic data are further discussed here with a view to using vein graphite as the source material for the synthesis of carbon nanomaterials. © 2013 American Chemical Society.