Minimum weight design of fiber-reinforced laminated composite structures with maximum stress and Tsai-Wu failure criteria

In this article, a minimum weight design of carbon/epoxy laminates is carried out using genetic algorithms. New failure envelopes have been developed by the combination of two commonly used phenomenological failure criteria, namely Maximum Stress (MS) and Tsai-Wu (TW) are used to obtain the minimum weight of the laminate. These failure envelopes are the most conservative failure envelope (MCFE) and the least conservative failure envelope (LCFE). Uniaxial and biaxial loading conditions are considered for the study and the differences in the optimal weight of the laminate are compared for the MCFE and LCFE. The MCFE can be used for design of critical load-carrying composites, while the LCFE could be used for the design of composite structures where weight reduction is much more important than safety such as unmanned air vehicles.

The Reproducing Kernel DMS-FEM: 3D Shape Functions and Applications to Linear Solid Mechanics

We propose a family of 3D versions of a smooth finite element method (Sunilkumar and Roy 2010), wherein the globally smooth shape functions are derivable through the condition of polynomial reproduction with the tetrahedral B-splines (DMS-splines) or tensor-product forms of triangular B-splines and ID NURBS bases acting as the kernel functions. While the domain decomposition is accomplished through tetrahedral or triangular prism elements, an additional requirement here is an appropriate generation of knotclouds around the element vertices or corners. The possibility of sensitive dependence of numerical solutions to the placements of knotclouds is largely arrested by enforcing the condition of polynomial reproduction whilst deriving the shape functions. Nevertheless, given the higher complexity in forming the knotclouds for tetrahedral elements especially when higher demand is placed on the order of continuity of the shape functions across inter-element boundaries, we presently emphasize an exploration of the triangular prism based formulation in the context of several benchmark problems of interest in linear solid mechanics. In the absence of a more rigorous study on the convergence analyses, the numerical exercise, reported herein, helps establish the method as one of remarkable accuracy and robust performance against numerical ill-conditioning (such as locking of different kinds) vis-a-vis the conventional FEM.

Variable Sparsity Kernel Learning

This paper(1) presents novel algorithms and applications for a particular class of mixed-norm regularization based Multiple Kernel Learning (MKL) formulations. The formulations assume that the given kernels are grouped and employ l(1) norm regularization for promoting sparsity within RKHS norms of each group and l(s), s >= 2 norm regularization for promoting non-sparse combinations across groups. Various sparsity levels in combining the kernels can be achieved by varying the grouping of kernels-hence we name the formulations as Variable Sparsity Kernel Learning (VSKL) formulations. While previous attempts have a non-convex formulation, here we present a convex formulation which admits efficient Mirror-Descent (MD) based solving techniques. The proposed MD based algorithm optimizes over product of simplices and has a computational complexity of O (m(2)n(tot) log n(max)/epsilon(2)) where m is no. training data points, n(max), n(tot) are the maximum no. kernels in any group, total no. kernels respectively and epsilon is the error in approximating the objective. A detailed proof of convergence of the algorithm is also presented. Experimental results show that the VSKL formulations are well-suited for multi-modal learning tasks like object categorization. Results also show that the MD based algorithm outperforms state-of-the-art MKL solvers in terms of computational efficiency.

Repeated drop weight impacts and post-impact ILSS tests on glass-epoxy composite

E glass epoxy laminates of thicknesses in the range 2-5 mm were subjected to repeated impacts. For each thickness the number of hits to cause tup penetration was determined and the value of this number was higher the larger the thickness of the laminate tested. The C-scan, before and after impact, was done to obtain information regarding flaw distribution. Short beam shear test samples were made from locations at fixed distances from impact point and tested. The samples closer to the zone of impact showed lower strength values. Scanning fractography revealed shear deformation features for these samples and brittle fracture features for the region near the zone of impact.

Structural dependence of density in high molecular weight esters

The effect of molecular structure on density has been examined in high molecular weight esters (molecular weight 300-900), having varying degrees of branching. Densities were calculated from an empirical equation, which agrees well with the experimental values (error +/-1.5%), irrespective of branching. Since density is related to molecular packing and hence to the molecular rotation, in n-alkanes, the glass transition temperature (T(g)) and density both increase with molecular weight, and hence T(g) is directly related to the density. The esters exhibit a complex behavior. In linear esters the T(g) decreases with molecular weight which is explained from group contribution and molecular interactions. In the +-branched esters, however, T(g) decreases with molecular weight until the molecular weight reaches 600 and increases sharply thereafter. The Y-branched esters show an intermediate behavior. The dependence of T(g) on molecular weight has been explained from the segmental motion.

Robust Formulations for Handling Uncertainty in Kernel Matrices

We study the problem of uncertainty in the entries of the Kernel matrix, arising in SVM formulation. Using Chance Constraint Programming and a novel large deviation inequality we derive a formulation which is robust to such noise. The resulting formulation applies when the noise is Gaussian, or has finite support. The formulation in general is non-convex, but in several cases of interest it reduces to a convex program. The problem of uncertainty in kernel matrix is motivated from the real world problem of classifying proteins when the structures are provided with some uncertainty. The formulation derived here naturally incorporates such uncertainty in a principled manner leading to significant improvements over the state of the art. 1.

Effect of solvent on the ultrasonic degradation of poly(vinyl acetate)

The ultrasonic degradation of poly(vinyl acetate) was carried out in six different solvents and two mixtures of solvents. The evolution of molecular weight distribution (MWD) with time was determined with gel permeation chromatography. The observed MWDs were analyzed by continuous distribution kinetics. A stoichiometric kernel that accounts for preferential mid-point breakage of the polymer chains was used. The degradation rate coefficient of the polymer in each solvent was determined from the model. The variations of rate coefficients were correlated with vapor pressure of the solvent, the Flory–Huggins polymer–solvent interaction parameter and the kinematic viscosity of the solution. A lower saturation vapor pressure resulted in higher degradation rates of the polymer. The degradation rate increased with increasing kinematic viscosity.

Thermal Weight Functions and Stress Intensity Factors for Bonded Dissimilar Media Using Body Analogy

In this study, an analytical method is presented for the computation of thermal weight functions in two dimensional bi-material elastic bodies containing a crack at the interface and subjected to thermal loads using body analogy method. The thermal weight functions are derived for two problems of infinite bonded dissimilar media, one with a semi-infinite crack and the other with a finite crack along the interface. The derived thermal weight functions are shown to reduce to the already known expressions of thermal weight functions available in the literature for the respective homogeneous elastic body. Using these thermal weight functions, the stress intensity factors are computed for the above interface crack problems when subjected to an instantaneous heat source.

Control of Molecular Weight and Polydispersity of Hyperbranched Polymers Using a Reactive B(3) Core: A Single-Step Route to Orthogonally Functionalizable Hyperbranched Polymers

Molecular weight and polydispersity are two structural features of hyperbranched polymers that are difficult to control because of the statistical nature of the step-growth polycondensation of AB(2) type monomers; the statistical growth also causes the polydispersity index to increase with percent conversion (or molecular weight). We demonstrate that using controlled amounts of a specifically designed B(3) core, containing B-type functionality that are more reactive than those present in the AB(2) monomer, both the molecular weight and the polydispersity can be readily controlled; the PDI was shown to improve with increasing mole-fraction of the B(3) core while the polymer molecular weight showed an expected decrease. Incorporation of a ``clickable'' propargyl group in the B(3) core unit permitted the generation of a core-functionalizable hyperbranched polymer. Importantly, this clickable core, in combination with a recently developed AB(2) monomer, wherein the B-type groups are allyl ethers and A is an hydroxyl group, led to the generation of a hyperbranched polymer carrying orthogonally functionalizable core and peripheral groups, via a single-step melt polycondensation. Selective functionalization of the core and periphery using two different types of chromophores was achieved, and the occurrence of fluorescence resonance energy transfer (FRET) between the donor and acceptor chromophores was demonstrated.

Control of Molecular Weight and Polydispersity of Hyperbranched Polymers Using a Reactive B(3) Core: A Single-Step Route to Orthogonally Functionalizable Hyperbranched Polymers

Molecular weight and polydispersity are two structural features of hyperbranched polymers that are difficult to control because of the statistical nature of the step-growth polycondensation of AB(2) type monomers; the statistical growth also causes the polydispersity index to increase with percent conversion (or molecular weight). We demonstrate that using controlled amounts of a specifically designed B(3) core, containing B-type functionality that are more reactive than those present in the AB(2) monomer, both the molecular weight and the polydispersity can be readily controlled; the PDI was shown to improve with increasing mole-fraction of the B(3) core while the polymer molecular weight showed an expected decrease. Incorporation of a ``clickable'' propargyl group in the B(3) core unit permitted the generation of a core-functionalizable hyperbranched polymer. Importantly, this clickable core, in combination with a recently developed AB(2) monomer, wherein the B-type groups are allyl ethers and A is an hydroxyl group, led to the generation of a hyperbranched polymer carrying orthogonally functionalizable core and peripheral groups, via a single-step melt polycondensation. Selective functionalization of the core and periphery using two different types of chromophores was achieved, and the occurrence of fluorescence resonance energy transfer (FRET) between the donor and acceptor chromophores was demonstrated.

Constant weight codes based on ideals of commutative rings

We present a construction of constant weight codes based on the prime ideals of a Noetherian commutative ring. The coding scheme is based on the uniqueness of the primary decomposition of ideals in Noetherian rings. The source alphabet consists of a set of radical ideals constructed from a chosen subset of the prime spectrum of the ring. The distance function between two radical ideals is taken to be the Hamming metric based on the symmetric distance between sets. As an application we construct codes for random networks employing SAF routing.

Evaluation of 2D image reconstruction using fan-beam FBP algorithm with no backprojection weight from WLP completed truncated projection data

This paper presents the image reconstruction using the fan-beam filtered backprojection (FBP) algorithm with no backprojection weight from windowed linear prediction (WLP) completed truncated projection data. The image reconstruction from truncated projections aims to reconstruct the object accurately from the available limited projection data. Due to the incomplete projection data, the reconstructed image contains truncation artifacts which extends into the region of interest (ROI) making the reconstructed image unsuitable for further use. Data completion techniques have been shown to be effective in such situations. We use windowed linear prediction technique for projection completion and then use the fan-beam FBP algorithm with no backprojection weight for the 2-D image reconstruction. We evaluate the quality of the reconstructed image using fan-beam FBP algorithm with no backprojection weight after WLP completion.