Damage limit states of reinforced concrete beams subjected to incremental cyclic loading using relaxation ratio analysis of AE parameters

This paper presents an experimental study on damage assessment of reinforced concrete (RC) beams subjected to incremental cyclic loading. During testing acoustic emissions (AEs) were recorded. The analysis of the AE released was carried out by using parameters relaxation ratio, load ratio and calm ratio. Digital image correlation (DIC) technique and tracking with available MATLAB program were used to measure the displacement and surface strains in concrete. Earlier researchers classified the damage in RC beams using Kaiser effect, crack mouth opening displacement and proposed a standard. In general (or in practical situations), multiple cracks occur in reinforced concrete beams. In the present study damage assessment in RC beams was studied according to different limit states specified by the code of practice IS-456:2000 and AE technique. Based on the two ratios namely load ratio and calm ratio and when the deflection reached approximately 85% of the maximum allowable deflection it was observed that the RC beams were heavily damaged. The combination of AE and DIC techniques has the potential to provide the state of damage in RC structures.

Indentation size effect and shear transformation zone size in a bulk metallic glass in two different structural states

The existence of an indentation size effect (ISE) in the onset of yield in a Zr-based bulk metallic glass (BMG) is investigated by employing spherical-tip nanoindentation experiments. Statistically significant data on the load at which the first pop-in in the displacement occurs were obtained for three different tip radii and in two different structural states (as-cast and structurally relaxed) of the BMG. Hertzian contact mechanics were employed to convert the pop-in loads to the maximum shear stress underneath the indenter. Results establish the existence of an ISE in the BMG of both structural states, with shear yield stress increasing with decreasing tip radius. Structural relaxation was found to increase the yield stress and decrease the variability in the data, indicating ``structural homogenization'' with annealing. Statistical analysis of the data was employed to estimate the shear transformation zone (STZ) size. Results of this analysis indicate an STZ size of similar to 25 atoms, which increases to similar to 34 atoms upon annealing. These observations are discussed in terms of internal structure changes that occur during structural relaxation and their interaction with the stressed volumes in spherical indentation of a metallic glass. (C) 2012 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved.

Selective excitation and detection of maximum quantum coherence of a group of scalar coupled protons in chiral molecules: an NMR experiment for enantiodiscrimination

The H-1 NMR spectroscopic discrimination of enantiomers in the solution state and the measurement of enantiomeric composition is most often hindered due to either very small chemical shift differences between the discriminated peaks or severe overlap of transitions from other chemically non-equivalent protons. In addition the use of chiral auxiliaries such as, crown ether and chiral lanthanide shift reagent may often cause enormous line broadening or give little degree of discrimination beyond the crown ether substrate ratio, hampering the discrimination. In circumventing such problems we are proposing the utilization of the difference in the additive values of all the chemical shifts of a scalar coupled spin system. The excitation and detection of appropriate highest quantum coherence yields the measurable difference in the frequencies between two transitions, one pertaining to each enantiomer in the maximum quantum dimension permitting their discrimination and the F-2 cross section at each of these frequencies yields an enantiopure spectrum. The advantage of the utility of the proposed method is demonstrated on several chiral compounds where the conventional one dimensional H-1 NMR spectra fail to differentiate the enantiomers.

Nonlinear dynamic analysis of dragonfly inspired piezoelectrically driven flapping and pitching wing

The nonlinear equations for coupled elastic flapping-twisting motion of a dragonfly in- spired smart flapping wing are used for a flapping wing actuated from the root by a PZT unimorph in the piezofan configuration. Excitation by the piezoelectric harmonic force generates only the flap bending motion, which in turn, induces the elastic twist motion due to interaction between flexural and torsional vibrations modes. An unsteady aerodynamic model is used to obtain the aerodynamic forces. Numerical simulations are performed using a wing whose size is the same as the dragonfly Sympetrum Frequens wing. It is found that the value of average lift reaches to its maximum when the smart flapping wing is excited at a frequency closer to the natural frequency in torsion. Moreover, consideration of the elastic twisting of flapping wing leads to an increase in the lift force. It is also found that the flapping wing generates sufficient lift to support its own weight and carry a small pay- load. Therefore, the piezoelectrically actuated smart flapping wing based on the geometry of Sympetrum Frequens wing and undergoing flapping-twisting motions may be considered as a potential candidate for use in MAV applications.

Evaluation of strength of component-laminates in strip-based mechanisms

This paper deals with the evaluation of the component-laminate load-carrying capacity, i.e., to calculate the loads that cause the failure of the individual layers and the component-laminate as a whole in four-bar mechanism. The component-laminate load-carrying capacity is evaluated using the Tsai-Wu-Hahn failure criterion for various lay-ups. The reserve factor of each ply in the component-laminate is calculated by using the maximum resultant force and the maximum resultant moment occurring at different time steps at the joints of the mechanism. Here, all component bars of the mechanism are made of fiber reinforced laminates and have thin rectangular cross-sections. They could, in general, be pre-twisted and/or possess initial curvature, either by design or by defect. They are linked to each other by means of revolute joints. We restrict ourselves to linear materials with small strains within each elastic body (strip-like beam). Each component of the mechanism is modeled as a beam based on geometrically non-linear 3-D elasticity theory. The component problems are thus split into 2-D analyses of reference beam cross-sections and non-linear 1-D analyses along the three beam reference curves. For the thin rectangular cross-sections considered here, the 2-D cross-sectional nonlinearity is also overwhelming. This can be perceived from the fact that such sections constitute a limiting case between thin-walled open and closed sections, thus inviting the non-linear phenomena observed in both. The strong elastic couplings of anisotropic composite laminates complicate the model further. However, a powerful mathematical tool called the Variational Asymptotic Method (VAM) not only enables such a dimensional reduction, but also provides asymptotically correct analytical solutions to the non-linear cross-sectional analysis. Such closed-form solutions are used here in conjunction with numerical techniques for the rest of the problem to predict more quickly and accurately than would otherwise be possible. Local 3-D stress, strain and displacement fields for representative sections in the component-bars are recovered, based on the stress resultants from the 1-D global beam analysis. A numerical example is presented which illustrates the failure of each component-laminate and the mechanism as a whole.

Horizontal pullout capacity of a group of two vertical plate anchors in clay

The horizontal pullout capacity of a group of two vertical strip plate anchors, placed along the same vertical plane, in a fully cohesive soil has been computed by using the lower bound finite element limit analysis. The effect of spacing between the plate anchors on the magnitude of total group failure load (P-uT) has been evaluated. An increase of soil cohesion with depth has also been incorporated in the analysis. For a weightless medium, the total pullout resistance of the group becomes maximum corresponding to a certain optimum spacing between the anchor plates which has been found to vary generally between 0.5B and B; where B is the width of the anchor plate. As compared to a single plate anchor, the increase in the pullout resistance for a group of two anchors becomes greater at a higher embedment ratio. The effect of soil unit weight has also been analyzed. It is noted that the interference effect on the pullout resistance increases further with an increase in the unit weight of soil mass.

Maximum likelihood algorithms for joint estimation of synchronisation impairments and channel in multiple input multiple output-orthogonal frequency division multiplexing system

Maximum likelihood (ML) algorithms, for the joint estimation of synchronisation impairments and channel in multiple input multiple output-orthogonal frequency division multiplexing (MIMO-OFDM) system, are investigated in this work. A system model that takes into account the effects of carrier frequency offset, sampling frequency offset, symbol timing error and channel impulse response is formulated. Cramer-Rao lower bounds for the estimation of continuous parameters are derived, which show the coupling effect among different impairments and the significance of the joint estimation. The authors propose an ML algorithm for the estimation of synchronisation impairments and channel together, using the grid search method. To reduce the complexity of the joint grid search in the ML algorithm, a modified ML (MML) algorithm with multiple one-dimensional searches is also proposed. Further, a stage-wise ML (SML) algorithm using existing algorithms, which estimate less number of parameters, is also proposed. Performance of the estimation algorithms is studied through numerical simulations and it is found that the proposed ML and MML algorithms exhibit better performance than SML algorithm.

Learning from positive and unlabelled examples using maximum margin clustering

Learning from Positive and Unlabelled examples (LPU) has emerged as an important problem in data mining and information retrieval applications. Existing techniques are not ideally suited for real world scenarios where the datasets are linearly inseparable, as they either build linear classifiers or the non-linear classifiers fail to achieve the desired performance. In this work, we propose to extend maximum margin clustering ideas and present an iterative procedure to design a non-linear classifier for LPU. In particular, we build a least squares support vector classifier, suitable for handling this problem due to symmetry of its loss function. Further, we present techniques for appropriately initializing the labels of unlabelled examples and for enforcing the ratio of positive to negative examples while obtaining these labels. Experiments on real-world datasets demonstrate that the non-linear classifier designed using the proposed approach gives significantly better generalization performance than the existing relevant approaches for LPU.

Horizontal pullout resistance of a group of two vertical anchors in sand

The horizontal pullout capacity of a group of two vertical strip anchors placed along the same vertical plane in sand has been determined by using the upper bound finite elements limit analysis. The variation of the efficiency factor (xi (gamma) ) with changes in clear spacing (S) between the anchors has been established to evaluate the total group failure load for different values of (i) embedment ratio (H/B), (ii) soil internal friction angle (phi), and (iii) anchor-soil interface friction angle (delta). The total group failure load, for a given H/B, becomes always maximum corresponding to a certain optimal spacing (S-opt). The value of S-opt/B was found to lie in a range of 0.5-1.4. The maximum magnitude of xi (gamma) increases generally with increases in H/B, phi and delta.

Experimental analysis of composite single-lap joints using digital image correlation and comparison with theoretical models

The demand for energy efficient, low weight structures has boosted the use of composite structures assembled using increased quantities of structural adhesives. Bonded structures may be subjected to severe working environments such as high temperature and moisture due to which the adhesive gets degraded over a period of time. This reduces the strength of a joint and leads to premature failure. Measurement of strains in the adhesive bondline at any point of time during service may be beneficial as an assessment can be made on the integrity of a joint and necessary preventive actions may be taken before failure. This paper presents an experimental approach of measuring peel and shear strains in the adhesive bondline of composite single-lap joints using digital image correlation. Different sets of composite adhesive joints with varied bond quality were prepared and subjected to tensile load during which digital images were taken and processed using digital image correlation software. The measured peel strain at the joint edge showed a rapid increase with the initiation of a crack till failure of the joint. The measured strains were used to compute the corresponding stresses assuming a plane strain condition and the results were compared with stresses predicted using theoretical models, namely linear and nonlinear adhesive beam models. A similar trend in stress distribution was observed. Further comparison of peel and shear strains also exhibited similar trend for both healthy and degraded joints. Maximum peel stress failure criterion was used to predict the failure load of a composite adhesive joint and a comparison was made between predicted and actual failure loads. The predicted failure loads from theoretical models were found to be higher than the actual failure load for all the joints.

Role of melt convection on optimization of PCM-based heat sink under cyclic heat load

In this article, we study the thermal performance of phase-change material (PCM)-based heat sinks under cyclic heat load and subjected to melt convection. Plate fin type heat sinks made of aluminum and filled with PCM are considered in this study. The heat sink is heated from the bottom. For a prescribed value of heat flux, design of such a heat sink can be optimized with respect to its geometry, with the objective of minimizing the temperature rise during heating and ensuring complete solidification of PCM at the end of the cooling period for a given cycle. For given length and base plate thickness of a heat sink, a genetic algorithm (GA)-based optimization is carried out with respect to geometrical variables such as fin thickness, fin height, and the number of fins. The thermal performance of the heat sink for a given set of parameters is evaluated using an enthalpy-based heat transfer model, which provides the necessary data for the optimization algorithm. The effect of melt convection is studied by taking two cases, one without melt convection (conduction regime) and the other with convection. The results show that melt convection alters the results of geometrical optimization.

A Phase Transition for the Uniform Distribution in the Pattern Maximum Likelihood Problem

In this paper, we consider the setting of the pattern maximum likelihood (PML) problem studied by Orlitsky et al. We present a well-motivated heuristic algorithm for deciding the question of when the PML distribution of a given pattern is uniform. The algorithm is based on the concept of a ``uniform threshold''. This is a threshold at which the uniform distribution exhibits an interesting phase transition in the PML problem, going from being a local maximum to being a local minimum.

Evaluation of the accuracy of an impact load cell using lumped parameter modeling and analysis

The objective of the current study is to evaluate the fidelity of load cell reading during impact testing in a drop-weight impactor using lumped parameter modeling. For the most common configuration of a moving impactor-load cell system in which dynamic load is transferred from the impactor head to the load cell, a quantitative assessment is made of the possible discrepancy that can result in load cell response. A 3-DOF (degrees-of-freedom) LPM (lumped parameter model) is considered to represent a given impact testing set-up. In this model, a test specimen in the form of a steel hat section similar to front rails of cars is represented by a nonlinear spring while the load cell is assumed to behave in a linear manner due to its high stiffness. Assuming a given load-displacement response obtained in an actual test as the true behavior of the specimen, the numerical solution of the governing differential equations following an implicit time integration scheme is shown to yield an excellent reproduction of the mechanical behavior of the specimen thereby confirming the accuracy of the numerical approach. The spring representing the load cell, however,predicts a response that qualitatively matches the assumed load-displacement response of the test specimen with a perceptibly lower magnitude of load.

Generative Maximum Entropy Learning for Multiclass Classification

Maximum entropy approach to classification is very well studied in applied statistics and machine learning and almost all the methods that exists in literature are discriminative in nature. In this paper, we introduce a maximum entropy classification method with feature selection for large dimensional data such as text datasets that is generative in nature. To tackle the curse of dimensionality of large data sets, we employ conditional independence assumption (Naive Bayes) and we perform feature selection simultaneously, by enforcing a `maximum discrimination' between estimated class conditional densities. For two class problems, in the proposed method, we use Jeffreys (J) divergence to discriminate the class conditional densities. To extend our method to the multi-class case, we propose a completely new approach by considering a multi-distribution divergence: we replace Jeffreys divergence by Jensen-Shannon (JS) divergence to discriminate conditional densities of multiple classes. In order to reduce computational complexity, we employ a modified Jensen-Shannon divergence (JS(GM)), based on AM-GM inequality. We show that the resulting divergence is a natural generalization of Jeffreys divergence to a multiple distributions case. As far as the theoretical justifications are concerned we show that when one intends to select the best features in a generative maximum entropy approach, maximum discrimination using J-divergence emerges naturally in binary classification. Performance and comparative study of the proposed algorithms have been demonstrated on large dimensional text and gene expression datasets that show our methods scale up very well with large dimensional datasets.

Selection and thermodynamic analysis of a turbocharger for a producer gas-fuelled multi-cylinder engine

The current work addresses the use of producer gas, a bio-derived gaseous alternative fuel, in engines designed for natural gas, derived from diesel engine frames. Impact of the use of producer gas on the general engine performance with specific focus on turbo-charging is addressed. The operation of a particular engine frame with diesel, natural gas and producer gas indicates that the peak load achieved is highest with diesel fuel (in compression ignition mode) followed by natural gas and producer gas (both in spark ignite mode). Detailed analysis of the engine power de-rating on fuelling with natural gas and producer gas indicates that the change in compression ratio (migration from compression to spark ignited mode), difference in mixture calorific value and turbocharger mismatch are the primary contributing factors. The largest de-rating occurs due to turbocharger mismatch. Turbocharger selection and optimization is identified as the strategy to recover the non-thermodynamic power loss, identified as the recovery potential (the loss due to mixture calorific value and turbocharger mismatch) on operating the engine with a fuel different from the base fuel. A turbocharged after-cooled six cylinder, 5.9 l, 90 kWe (diesel rating) engine (12.2 bar BMEP) is available commercially as a naturally aspirated natural gas engine delivering a peak load of 44.0 kWe (6.0 bar BMEP). The engine delivers a load of 27.3 kWe with producer gas under naturally aspirated mode. On charge boosting the engine with a turbocharger similar in configuration to the diesel engine turbocharger, the peak load delivered with producer gas is 36 kWe (4.8 bar BMEP) indicating a de-rating of about 60% over the baseline diesel mode. Estimation of knock limited peak load for producer gas-fuelled operation on the engine frame using a Wiebe function-based zero-dimensional code indicates a knock limited peak load of 76 kWe, indicating the potential to recover about 40 kWe. As a part of the recovery strategy, optimizing the ignition timing for maximum brake torque based on both spark sweep tests and established combustion descriptors and engine-turbocharger matching for producer gas-fuelled operation resulted in a knock limited peak load of 72.8 kWe (9.9 bar BMEP) at a compressor pressure ratio of 2.30. The de-rating of about 17.0 kWe compared to diesel rating is attributed to the reduction in compression ratio. With load recovery, the specific biomass consumption reduces from 1.2 kg/kWh to 1.0 kg/kWh, an improvement of over 16% while the engine thermal efficiency increases from 28% to 32%. The thermodynamic analysis of the compressor and the turbine indicates an isentropic efficiency of 74.5% and 73%, respectively.