Probabilistic stress variation studies on composite single lap joint using Monte Carlo simulation

The work presented in this paper involves the stochastic finite element analysis of composite-epoxy adhesive lap joints using Monte Carlo simulation. A set of composite adhesive lap joints were prepared and loaded till failure to obtain their strength. The peel and shear strain in the bond line region at different levels of load were obtained using digital image correlation (DIC). The corresponding stresses were computed assuming a plane strain condition. The finite element model was verified by comparing the numerical and experimental stresses. The stresses exhibited a similar behavior and a good correlation was obtained. Further, the finite element model was used to perform the stochastic analysis using Monte Carlo simulation. The parameters influencing stress distribution were provided as a random input variable and the resulting probabilistic variation of maximum peel and shear stresses were studied. It was found that the adhesive modulus and bond line thickness had significant influence on the maximum stress variation. While the adherend thickness had a major influence, the effect of variation in longitudinal and shear modulus on the stresses was found to be little. (C) 2014 Elsevier Ltd. All rights reserved.

Matrix crack detection in spatially random composite structures using fractal dimension

Fractal dimension based damage detection method is studied for a composite structure with random material properties. A composite plate with localized matrix crack is considered. Matrix cracks are often seen as the initial damage mechanism in composites. Fractal dimension based method is applied to the static deformation curve of the structure to detect localized damage. Static deflection of a cantilevered composite plate under uniform loading is calculated using the finite element method. Composite material shows spatially varying random material properties because of complex manufacturing processes. Spatial variation of material property is represented as a two dimensional homogeneous Gaussian random field. Karhunen-Loeve (KL) expansion is used to generate a random field. The robustness of fractal dimension based damage detection methods is studied considering the composite plate with spatial variation in material properties.

Faster computation of the Karhunen-Loeve expansion using its domain independence property

The goal of this work is to reduce the cost of computing the coefficients in the Karhunen-Loeve (KL) expansion. The KL expansion serves as a useful and efficient tool for discretizing second-order stochastic processes with known covariance function. Its applications in engineering mechanics include discretizing random field models for elastic moduli, fluid properties, and structural response. The main computational cost of finding the coefficients of this expansion arises from numerically solving an integral eigenvalue problem with the covariance function as the integration kernel. Mathematically this is a homogeneous Fredholm equation of second type. One widely used method for solving this integral eigenvalue problem is to use finite element (FE) bases for discretizing the eigenfunctions, followed by a Galerkin projection. This method is computationally expensive. In the current work it is first shown that the shape of the physical domain in a random field does not affect the realizations of the field estimated using KL expansion, although the individual KL terms are affected. Based on this domain independence property, a numerical integration based scheme accompanied by a modification of the domain, is proposed. In addition to presenting mathematical arguments to establish the domain independence, numerical studies are also conducted to demonstrate and test the proposed method. Numerically it is demonstrated that compared to the Galerkin method the computational speed gain in the proposed method is of three to four orders of magnitude for a two dimensional example, and of one to two orders of magnitude for a three dimensional example, while retaining the same level of accuracy. It is also shown that for separable covariance kernels a further cost reduction of three to four orders of magnitude can be achieved. Both normal and lognormal fields are considered in the numerical studies. (c) 2014 Elsevier B.V. All rights reserved.

The Relationship Between Solar Coronal X-Ray Brightness and Active Region Magnetic Fields: A Study Using High-Resolution Hinode Observations

By using high-resolution observations of nearly co-temporal and co-spatial Solar Optical Telescope spectropolarimeter and X-Ray Telescope coronal X-ray data onboard Hinode, we revisit the problematic relationship between global magnetic quantities and coronal X-ray brightness. Co-aligned vector magnetogram and X-ray data were used for this study. The total X-ray brightness over active regions is well correlated with integrated magnetic quantities such as the total unsigned magnetic flux, the total unsigned vertical current, and the area-integrated square of the vertical and horizontal magnetic fields. On accounting for the inter-dependence of the magnetic quantities, we inferred that the total magnetic flux is the primary determinant of the observed integrated X-ray brightness. Our observations indicate that a stronger coronal X-ray flux is not related to a higher non-potentiality of active-region magnetic fields. The data even suggest a slightly negative correlation between X-ray brightness and a proxy of active-region non-potentiality. Although there are small numerical differences in the established correlations, the main conclusions are qualitatively consistent over two different X-ray filters, the Al-poly and Ti-poly filters, which confirms the strength of our conclusions and validate and extend earlier studies that used low-resolution data. We discuss the implications of our results and the constraints they set on theories of solar coronal heating.

Belief propagation for minimum weight many-to-one matchings in the random complete graph

In a complete bipartite graph with vertex sets of cardinalities n and n', assign random weights from exponential distribution with mean 1, independently to each edge. We show that, as n -> infinity, with n' = n/alpha] for any fixed alpha > 1, the minimum weight of many-to-one matchings converges to a constant (depending on alpha). Many-to-one matching arises as an optimization step in an algorithm for genome sequencing and as a measure of distance between finite sets. We prove that a belief propagation (BP) algorithm converges asymptotically to the optimal solution. We use the objective method of Aldous to prove our results. We build on previous works on minimum weight matching and minimum weight edge cover problems to extend the objective method and to further the applicability of belief propagation to random combinatorial optimization problems.

Giant actuation in bulk carbon nanotubes under coupled electric and magnetic fields

We report an enhanced actuation in bulk carbon nanotubes (CNTs) under coupled electric and magnetic fields, which is much higher than that evaluated in the presence of individual fields. Coupled electric and magnetic fields induce a directional actuation demonstrating a transformation from polarity independent to dependent actuation behavior of CNTs. Both qualitative and quantitative analyses are performed to understand this transformation in the bulk CNTs. Moreover, actuations along radial and axial directions of CNTs have also demonstrated a similar directional behavior.

Thermoelectric properties of Pb0.75-xMnxSn0.25Te alloys with variable manganese content

Lead tin telluride is one of the well-established thermoelectric materials in the temperature range 350-750 K. In the present study, Pb0.75-xMnxSn0.25Te1.00 alloys with variable manganese (Mn) content were prepared by solid state synthesis and the thermoelectric properties were studied. X-ray diffraction, (XRD) showed that the samples followed Vegard's law, indicating solid solution formation and substitution of Mn at the Pb site. Scanning Electron Microscopy (SEM) showed that the grain sizes varied from <1 mu m to more than 10 mu m and MnTe rich phase was present for higher Mn content. Seebeck coefficient, electrical resistivity and thermal conductivity were measured from room temperature to 720 K. At 300 K, large Seebeck values were obtained, possibly due to increased effective mass on Mn substitution and low carrier concentration of the samples. At higher temperatures, transition from n-type to p-type indicated the presence of thermally generated carriers. Temperature dependent electrical resistivity showed the transition from degenerate to non-degenerate behavior. For thermal conductivity, low values (similar to 1 W/m-K at 300 K) were obtained. At higher temperatures bipolar conduction was observed, in agreement with the Seebeck and resistivity data. Due to low power factor, the maximum thermoelectric figure of merit (zT) was limited to 0.23 at 329 K for the sample with lowest Mn content (x=0.03). (C) 2015 Elsevier Ltd. All rights reserved.

Prediction of Land Surface Temperature under Cloudy Conditions using Microwave Remote Sensing and ANN

Land surface temperature (LST) is an important variable in climate, hydrologic, ecological, biophysical and biochemical studies (Mildrexler et al., 2011). The most effective way to obtain LST measurements is through satellites. Presently, LST from moderate resolution imaging spectroradiometer (MODIS) sensor is applied in various fields due to its high spatial and temporal availability over the globe, but quite difficult to provide observations in cloudy conditions. This study evolves of prediction of LST under clear and cloudy conditions using microwave vegetation indices (MVIs), elevation, latitude, longitude and Julian day as inputs employing an artificial neural network (ANN) model. MVIs can be obtained even under cloudy condition, since microwave radiation has an ability to penetrate through clouds. In this study LST and MVIs data of the year 2010 for the Cauvery basin on a daily basis were obtained from MODIS and advanced microwave scanning radiometer (AMSR-E) sensors of aqua satellite respectively. Separate ANN models were trained and tested for the grid cells for which both LST and MVI were available. The performance of the models was evaluated based on standard evaluation measures. The best performing model was used to predict LST where MVIs were available. Results revealed that predictions of LST using ANN are in good agreement with the observed values. The ANN approach presented in this study promises to be useful for predicting LST using satellite observations even in cloudy conditions. (C) 2015 The Authors. Published by Elsevier B.V.

Specificity of the ModA11, ModA12 and ModD1 epigenetic regulator N-6-adenine DNA methyltransferases of Neisseria meningitidis

Phase variation (random ON/OFF switching) of gene expression is a common feature of host-adapted pathogenic bacteria. Phase variably expressed N-6-adenine DNA methyltransferases (Mod) alter global methylation patterns resulting in changes in gene expression. These systems constitute phase variable regulons called phasevarions. Neisseria meningitidis phasevarions regulate genes including virulence factors and vaccine candidates, and alter phenotypes including antibiotic resistance. The target site recognized by these Type III N-6-adenine DNA methyltransferases is not known. Single molecule, real-time (SMRT) methylome analysis was used to identify the recognition site for three key N. meningitidis methyltransferases: ModA11 (exemplified by M.NmeMC58I) (5'-CGY(m6)AG-3'), ModA12 (exemplified by M.Nme77I, M.Nme18I and M.Nme579II) (5'-AC(m6)ACC-3') and ModD1 (exemplified by M.Nme579I) (5'-CC(m6)AGC-3'). Restriction inhibition assays and mutagenesis confirmed the SMRT methylome analysis. The ModA11 site is complex and atypical and is dependent on the type of pyrimidine at the central position, in combination with the bases flanking the core recognition sequence 5'-CGY(m6)AG-3'. The observed efficiency of methylation in the modA11 strain (MC58) genome ranged from 4.6% at 5'-GCGC(m6)AGG-3' sites, to 100% at 5'-ACGT(m6)AGG-3' sites. Analysis of the distribution of modified sites in the respective genomes shows many cases of association with intergenic regions of genes with altered expression due to phasevarion switching.

Novel anti IGFBP2 single chain variable fragment inhibits glioma cell migration and invasion

Insulin like growth factor binding protein 2 (IGFBP2) is highly up regulated in glioblastoma (GBM) tissues and has been one of the prognostic indicators. There are compelling evidences suggesting important roles for IGFBP2 in glioma cell proliferation, migration and invasion. Extracellular IGFBP2 through its carboxy terminal arginine glycine aspartate (RGD) motif can bind to cell surface alpha 5 beta 1 integrins and activate pathways downstream to integrin signaling. This IGFBP2 activated integrin signaling is known to play a crucial role in IGFBP2 mediated invasion of glioma cells. Hence a molecular inhibitor of carboxy terminal domain of IGFBP2 which can inhibit IGFBP2-cell surface interaction is of great therapeutic importance. In an attempt to develop molecular inhibitors of IGFBP2, we screened single chain variable fragment (scFv) phage display libraries, Tomlinson I (Library size 1.47 x 10(8)) and Tomlinson J (Library size 1.37 x 10(8)) using human recombinant IGFBP2. After screening we obtained three IGFBP2 specific binders out of which one scFv B7J showed better binding to IGFBP2 at its carboxy terminal domain, blocked IGFBP2-cell surface association, reduced activity of matrix metalloprotease 2 in the conditioned medium of glioma cells and inhibited IGFBP2 induced migration and invasion of glioma cells. We demonstrate for the first time that in vitro inhibition of extracellular IGFBP2 activity by using human scFv results in significant reduction of glioma cell migration and invasion. Therefore, the inhibition of IGFBP2 can serve as a potential therapeutic strategy in the management of GBM.

Global response sensitivity analysis using probability distance measures and generalization of Sobol's analysis

The study introduces two new alternatives for global response sensitivity analysis based on the application of the L-2-norm and Hellinger's metric for measuring distance between two probabilistic models. Both the procedures are shown to be capable of treating dependent non-Gaussian random variable models for the input variables. The sensitivity indices obtained based on the L2-norm involve second order moments of the response, and, when applied for the case of independent and identically distributed sequence of input random variables, it is shown to be related to the classical Sobol's response sensitivity indices. The analysis based on Hellinger's metric addresses variability across entire range or segments of the response probability density function. The measure is shown to be conceptually a more satisfying alternative to the Kullback-Leibler divergence based analysis which has been reported in the existing literature. Other issues addressed in the study cover Monte Carlo simulation based methods for computing the sensitivity indices and sensitivity analysis with respect to grouped variables. Illustrative examples consist of studies on global sensitivity analysis of natural frequencies of a random multi-degree of freedom system, response of a nonlinear frame, and safety margin associated with a nonlinear performance function. (C) 2015 Elsevier Ltd. All rights reserved.

Identification of dominant modes in random dynamical and aeroelastic systems

Identification of dominant modes is an important step in studying linearly vibrating systems, including flow-induced vibrations. In the presence of uncertainty, when some of the system parameters and the external excitation are modeled as random quantities, this step becomes more difficult. This work is aimed at giving a systematic treatment to this end. The ability to capture the time averaged kinetic energy is chosen as the primary criterion for selection of modes. Accordingly, a methodology is proposed based on the overlap of probability density functions (pdf) of the natural and excitation frequencies, proximity of the natural frequencies of the mean or baseline system, modal participation factor, and stochastic variation of mode shapes in terms of the modes of the baseline system - termed here as statistical modal overlapping. The probabilistic descriptors of the natural frequencies and mode shapes are found by solving a random eigenvalue problem. Three distinct vibration scenarios are considered: (i) undamped arid damped free vibrations of a bladed disk assembly, (ii) forced vibration of a building, and (iii) flutter of a bridge model. Through numerical studies, it is observed that the proposed methodology gives an accurate selection of modes. (C) 2015 Elsevier Ltd. All rights reserved.

Turbulent states and their transitions in mathematical models for ventricular tissue: The effects of random interstitial fibroblasts

We study the dynamical behaviors of two types of spiral-and scroll-wave turbulence states, respectively, in two-dimensional (2D) and three-dimensional (3D) mathematical models, of human, ventricular, myocyte cells that are attached to randomly distributed interstitial fibroblasts; these turbulence states are promoted by (a) the steep slope of the action-potential-duration-restitution (APDR) plot or (b) early afterdepolarizations (EADs). Our single-cell study shows that (1) the myocyte-fibroblast (MF) coupling G(j) and (2) the number N-f of fibroblasts in an MF unit lower the steepness of the APDR slope and eliminate the EAD behaviors of myocytes; we explore the pacing dependence of such EAD suppression. In our 2D simulations, we observe that a spiral-turbulence (ST) state evolves into a state with a single, rotating spiral (RS) if either (a) G(j) is large or (b) the maximum possible number of fibroblasts per myocyte N-f(max) is large. We also observe that the minimum value of G(j), for the transition from the ST to the RS state, decreases as N-f(max) increases. We find that, for the steep-APDR-induced ST state, once the MF coupling suppresses ST, the rotation period of a spiral in the RS state increases as (1) G(j) increases, with fixed N-f(max), and (2) N-f(max) increases, with fixed G(j). We obtain the boundary between ST and RS stability regions in the N-f(max)-G(j) plane. In particular, for low values of N-f(max), the value of G(j), at the ST-RS boundary, depends on the realization of the randomly distributed fibroblasts; this dependence decreases as N-f(max) increases. Our 3D studies show a similar transition from scroll-wave turbulence to a single, rotating, scroll-wave state because of the MF coupling. We examine the experimental implications of our study and propose that the suppression (a) of the steep slope of the APDR or (b) EADs can eliminate spiral-and scroll-wave turbulence in heterogeneous cardiac tissue, which has randomly distributed fibroblasts.