A computational method for quasi-static fracture

A direct method for solving quasi-static, mixed-mode fracture problems is presented. The element-free Galerkin method is used in order to allow for crack growth without remeshing. An expression for the normalized, critical traction is derived in terms of the fracture resistance (R-curve) and a crack-dependent function. Sample problems demonstrate the capability of this method to accurately compute the post-peak equilibrium paths for structures with growing cracks.     

An efficient approach to converting three-dimensional image data into highly accurate computational models

Image-based meshing is opening up exciting new possibilities for the application of computational continuum mechanics methods (finite-element and computational fluid dynamics) to a wide range of biomechanical and biomedical problems that were previously intractable owing to the difficulty in obtaining suitably realistic models. Innovative surface and volume mesh generation techniques have recently been developed, which convert three-dimensional imaging data, as obtained from magnetic resonance imaging, computed tomography, micro-CT and ultrasound, for example, directly into meshes suitable for use in physics-based simulations. These techniques have several key advantages, including the ability to robustly generate meshes for topologies of arbitrary complexity (such as bioscaffolds or composite micro-architectures) and with any number of constituent materials (multi-part modelling), providing meshes in which the geometric accuracy of mesh domains is only dependent on the image accuracy (image-based accuracy) and the ability for certain problems to model material inhomogeneity by assigning the properties based on image signal strength. Commonly used mesh generation techniques will be compared with the proposed enhanced volumetric marching cubes (EVoMaCs) approach and some issues specific to simulations based on three-dimensional image data will be discussed. A number of case studies will be presented to illustrate how these techniques can be used effectively across a wide range of problems from characterization of micro-scaffolds through to head impact modelling.     

A computational method for frictional contact problem using finite element method

Using the finite element method a numerical procedure is developed for the solution of the two-dimensional frictional contact problems with Coulomb's law of friction. The formulation for this procedure is reduced to a complementarity problem. The contact region is separated into stick and slip regions and the contact stress can be solved systematically by applying the solution technique of the complementarity problem. Several examples are given to demonstrate the validity of the present formulation.     

A simple background elimination method for Raman spectra

In this paper, we consider a new background elimination method for Raman spectra. The proposed method is based on peak detection, smoothing, and interpolation. Since the background is usually slowly varying with respect to wavelength, we could estimate the background by eliminating significant peaks. For this purpose, we seek the peaks by inspecting the smoothed derivative of a given spectrum. After clipping out the corresponding peak regions, we estimate the background by applying a modified linear interpolation. Then the background is eliminated from the measured Raman spectrum by simple subtraction. The experimental results showed that the proposed method gave satisfactory results for real Raman spectra as well as synthetic data. As the proposed method requires no prior knowledge of spectrum, we expect that the method could be applied to other spectral data as well.     

A computational method to differentiate normal individuals,osteoarthritis and rheumatoid arthritis patients using serum biomarkers

The objective of this study was to develop a method for categorizing normal individuals (normal, n = 100) as well as patients with osteoarthritis (OA, n = 100), and rheumatoid arthritis (RA, n = 100) based on a panel of inflammatory cytokines expressed in serum samples. Two panels of inflammatory proteins were used as training sets in the construction of two separate artificial neural networks (ANNs). The first training set consisted of all proteins (38 in total) and the second consisted of only the significantly different proteins expressed (12 in total) between at least two patient groups. Both ANNs obtained high levels of sensitivity and specificity, with the first and second ANN each diagnosing 100% of test set patients correctly. These results were then verified by re-investigating the entire dataset using a decision tree algorithm. We show that ANNs can be used for the accurate differentiation between serum samples of patients with OA, a diagnosed RA patient comparator cohort and normal/control cohort. Using neural network and systems biology approaches to manage large datasets derived from high-throughput proteomics should be further explored and considered for diagnosing diseases with complex pathologies.     

Device for converting linear displacements into electric pulses

Translated from Izmeritel'naya Tekhnika, No. 4, p. 14, April, 1993.     

A general rotation averaging method for granular materials

In order to study the rotational behavior of granular materials, rotation averaging methods are required. Most of the existing rotation averaging methods are only for 2D cases and limited by the shape, position and size of the averaging volumes. Hence, a general rotation averaging method is proposed in this paper. Our approach is simple yet works for both 2D and 3D cases with very little restriction. The performance of this method is shown by both hypothetical examples and DEM simulations of plane strain tests with different boundary conditions.     

A novel computational method for solving Troesch's problem with high-sensitivity parameter

Troesch's problem is a nonlinear boundary value problem arising in the confinement of a plasma column by radiation pressure, and also in the theory of gas porous electrodes. It is well known that finding numerical solutions to this problem is challenging, especially when the sensitivity parameter is large. In this article, we present an efficient and accurate numerical method for solving Troesch's problem. The method presented in this work is capable of computing the solution, even for extremely high-sensitivity parameter. The method is based on the the Newton–Raphson–Kantorovich approximation method in function space combined with the standard finite difference method. Although, available numerical solvers fail to provide accurate numerical solutions when the sensitivity parameter λ becomes large (λ exceeds 100) [1–5], the method proposed here is able to provide accurate numerical solutions for extremely large values of this sensitivity parameter, up to λ = 500. Numerical experiments are provided to show the accuracy of the method compared to existing solvers, as well as its capability to compute the solution for high values of the sensitivity parameter λ.     

A new multiscale computational method for elasto-plastic analysis of heterogeneous materials

A new multiscale computational method is developed for the elasto-plastic analysis of heterogeneous continuum materials with both periodic and random microstructures. In the method, the multiscale base functions which can efficiently capture the small-scale features of elements are constructed numerically and employed to establish the relationship between the macroscopic and microscopic variables. Thus, the detailed microscopic stress fields within the elements can be obtained easily. For the construction of the numerical base functions, several different kinds of boundary conditions are introduced and their influences are investigated. In this context, a two-scale computational modeling with successive iteration scheme is proposed. The new method could be implemented conveniently and adopted to the general problems without scale separation and periodicity assumptions. Extensive numerical experiments are carried out and the results are compared with the direct FEM. It is shown that the method developed provides excellent precision of the nonlinear response for the heterogeneous materials. Moreover, the computational cost is reduced dramatically.     

A computational method for optimal structural design II: Continuous problems

A method for solving structural design problems that allows a continuous distribution of material along structural elements is presented. The method is an extension of the generalized steepest descent method presented in Reference 1. Inequality constraints on design variables, displacement, natural frequency, and buckling are explicitly treated and a minimum weight cost function is employed. A steepest descent method for boundary-value state equations is developed and a computational algorithm is given. Several example problems in minimum weight structural design are solved and compared with results obtained by discretization techniques.     

A general approach for transferring hydrophobic nanocrystals into water

Hydrophobic inorganic nanocrystals have been transferred from organic solvent to aqueous solution through a robust and general ligand exchange procedure. Polyelectrolytes such as poly(acrylic acid) and poly(allylamine) are used to replace the original hydrophobic ligands on the surface of nanocrystals at an elevated temperature in a glycol solvent and eventually render the nanocrystals highly water soluble. The physical properties of the nanocrystals, such as superparamagnetism, photocatalytic activity, and photoluminescence, are maintained or improved after ligand exchange.     

A new method of reconstructing spectra

A theoretical method is proposed for accurate reconstruction of the spectrum using bounded sets of discrete values of the spectrum intensities. The method is based on a well known measurement theorem from optics. This method was used to solve the corresponding integral equation to eliminate instrumental distortions and to accurately reconstruct the spectra using the appropriate discrete values. Institute of Applied Physics Problems, Armenian Academy of Sciences Pis’ma Zh. Tekh. Fiz. 24, 5–9 (July 26, 1998)     

On computational procedures for the force method

It is known that the matrix force method has certain advantages over the displacement method for a class of structural problems. It is also known that the force method, when carried out by the conventional Gauss-Jordan procedure, tends to fill in the problem data, making the method unattractive for large size, sparse problems. This poor fill-in property, however, is not necessarily inherent to the method, and the sparsity may be maintained if one uses what we call the Turn-Back LU Procedure. The purpose of this paper is two-fold. First, it is shown that there exist some close relationships between the force method and the least squares problem, and that many existing algebraic procedures to perform the force method can be regarded as applications/extensions of certain well-known matrix factorization schemes for the least squares problem. Secondly, it is demonstrated that these algebraic procedures for the force method can be unified form the matrix factorization viewpoint. Included in this unification is the Turn-Back LU Procedure, which was originally proposed by Topçu in his thesis.⁸ It is explained why this procedure tends to produce sparse and banded ‘self-stress’ and flexibility matrices with small band width. Some computational results are presented to demonstrate the superiority of the Turn-Back LU Procedure over the other schemes considered in this paper.     

A model-free, fully automated baseline-removal method for Raman spectra

We present here a fully automated spectral baseline-removal procedure. The method uses a large-window moving average to estimate the baseline; thus, it is a model-free approach with a peak-stripping method to remove spectral peaks. After processing, the baseline-corrected spectrum should yield a flat baseline and this endpoint can be verified with the χ(2)-statistic. The approach provides for multiple passes or iterations, based on a given χ(2)-statistic for convergence. If the baseline is acceptably flat given the χ(2)-statistic after the first pass at correction, the problem is solved. If not, the non-flat baseline (i.e., after the first effort or first pass at correction) should provide an indication of where the first pass caused too much or too little baseline to be subtracted. The second pass thus permits one to compensate for the errors incurred on the first pass. Thus, one can use a very large window so as to avoid affecting spectral peaks--even if the window is so large that the baseline is inaccurately removed--because baseline-correction errors can be assessed and compensated for on subsequent passes. We start with the largest possible window and gradually reduce it until acceptable baseline correction based on the χ(2) statistic is achieved. Results, obtained on both simulated and measured Raman data, are presented and discussed.     

A general method for assembling single colloidal particle lines

We have developed a general method for assembling colloidal particles into one-dimensional lines of single particle thickness. Well-spaced, parallel single particle lines can be readily deposited on a substrate from a dilute Langmuir-Blodgett particle monolayer via a stick-slip motion of the water-substrate contact line. The particle density within the lines is controllable by the particle concentration in the monolayer as well as the pulling speed of the substrate. Lines of a great variety of materials and sizes, ranging from a few nanometers to a few micrometers, have been demonstrated. Multiple depositions create complex patterns such as cross lines, even of different particles. The ability of placing nanoparticles into one-dimensional arrays enables the construction of higher hierarchical device structures. For example, using gold nanoparticle seeds, vertical single nanowire arrays of silicon can be grown replicating the pattern of single particle lines.     

A general method for producing bioaffinity MALDI probes.

A bioaffinity probe based on the idea of immobilizing avidin on the probe surface to extract biotinylated oligosaccharide is described. The probe is produced by taking advantage of the natural affinity of proteins for hydrophobic polymer films. The avidin is immobilized by simply drying the solution on a polymer film surface. This produces a bioaffinity probe that shows enhanced activity for biotin-labeled oligosaccharides. The probe is produced in a matter of minutes but is highly effective for concentrating biotinylated oligosaccharide on the surface. The best matrix for the analysis is DHB, and the best film for the probe is a polyester material commonly used for transparency film. The efficacy of the probe is illustrated with neutral and anionic oligosaccharides. Oligosaccharides derivatized with biotin are retained while those that are unlabeled are washed away. No trace of the unlabeled oligosaccharide is observed in the mass spectrum.