Optimization of clamped beam geometry for fracture toughness testing of micron-scale samples

Fracture toughness measurements at the small scale have gained prominence over the years due to the continuing miniaturization of structural systems. Measurements carried out on bulk materials cannot be extrapolated to smaller length scales either due to the complexity of the microstructure or due to the size and geometric effect. Many new geometries have been proposed for fracture property measurements at small-length scales depending on the material behaviour and the type of device used in service. In situ testing provides the necessary environment to observe fracture at these length scales so as to determine the actual failure mechanism in these systems. In this paper, several improvements are incorporated to a previously proposed geometry of bending a doubly clamped beam for fracture toughness measurements. Both monotonic and cyclic loading conditions have been imposed on the beam to study R-curve and fatigue effects. In addition to the advantages that in situ SEM-based testing offers in such tests, FEM has been used as a simulation tool to replace cumbersome and expensive experiments to optimize the geometry. A description of all the improvements made to this specific geometry of clamped beam bending to make a variety of fracture property measurements is given in this paper.

Fault Tolerance on Large Scale Systems using Adaptive Process Replication

Exascale systems of the future are predicted to have mean time between failures (MTBF) of less than one hour. At such low MTBFs, employing periodic checkpointing alone will result in low efficiency because of the high number of application failures resulting in large amount of lost work due to rollbacks. In such scenarios, it is highly necessary to have proactive fault tolerance mechanisms that can help avoid significant number of failures. In this work, we have developed a mechanism for proactive fault tolerance using partial replication of a set of application processes. Our fault tolerance framework adaptively changes the set of replicated processes periodically based on failure predictions to avoid failures. We have developed an MPI prototype implementation, PAREP-MPI that allows changing the replica set. We have shown that our strategy involving adaptive process replication significantly outperforms existing mechanisms providing up to 20 percent improvement in application efficiency even for exascale systems.

Generalized Spatial Modulation in Large-Scale Multiuser MIMO Systems

Generalized spatial modulation (GSM) uses n(t) transmit antenna elements but fewer transmit radio frequency (RF) chains, n(rf). Spatial modulation (SM) and spatial multiplexing are special cases of GSM with n(rf) = 1 and n(rf) = n(t), respectively. In GSM, in addition to conveying information bits through n(rf) conventional modulation symbols (for example, QAM), the indices of the n(rf) active transmit antennas also convey information bits. In this paper, we investigate GSM for large-scale multiuser MIMO communications on the uplink. Our contributions in this paper include: 1) an average bit error probability (ABEP) analysis for maximum-likelihood detection in multiuser GSM-MIMO on the uplink, where we derive an upper bound on the ABEP, and 2) low-complexity algorithms for GSM-MIMO signal detection and channel estimation at the base station receiver based on message passing. The analytical upper bounds on the ABEP are found to be tight at moderate to high signal-to-noise ratios (SNR). The proposed receiver algorithms are found to scale very well in complexity while achieving near-optimal performance in large dimensions. Simulation results show that, for the same spectral efficiency, multiuser GSM-MIMO can outperform multiuser SM-MIMO as well as conventional multiuser MIMO, by about 2 to 9 dB at a bit error rate of 10(-3). Such SNR gains in GSM-MIMO compared to SM-MIMO and conventional MIMO can be attributed to the fact that, because of a larger number of spatial index bits, GSM-MIMO can use a lower-order QAM alphabet which is more power efficient.

Retrieval and Multi-scale Validation of Soil Moisture from Multi-temporal SAR Data in a Semi-Arid Tropical Region

The current study presents an algorithm to retrieve surface Soil Moisture (SM) from multi-temporal Synthetic Aperture Radar (SAR) data. The developed algorithm is based on the Cumulative Density Function (CDF) transformation of multi-temporal RADARSAT-2 backscatter coefficient (BC) to obtain relative SM values, and then converts relative SM values into absolute SM values using soil information. The algorithm is tested in a semi-arid tropical region in South India using 30 satellite images of RADARSAT-2, SMOS L2 SM products, and 1262 SM field measurements in 50 plots spanning over 4 years. The validation with the field data showed the ability of the developed algorithm to retrieve SM with RMSE ranging from 0.02 to 0.06 m(3)/m(3) for the majority of plots. Comparison with the SMOS SM showed a good temporal behaviour with RMSE of approximately 0.05 m(3)/m(3) and a correlation coefficient of approximately 0.9. The developed model is compared and found to be better than the change detection and delta index model. The approach does not require calibration of any parameter to obtain relative SM and hence can easily be extended to any region having time series of SAR data available.

Seismic response of reduced-scale modular block and rigid faced reinforced walls through shaking table tests

This paper focuses on understanding the seismic response of geosynthetic reinforced retaining walls through shaking table tests on models of modular block and rigid faced reinforced retaining walls. Reduced-scale models of retaining walls reinforced with geogrid layers were constructed in a laminar box mounted on a uniaxial shaking table and subjected to various levels of sinusoidal base shaking. Models were instrumented with ultrasonic displacement sensors, earth pressure sensors and accelerometers. Effects of backfill density, number of reinforcement layers and reinforcement type on the performance of rigid faced and modular block walls were studied through different series of model tests. Performances of the walls were assessed in terms of face deformations, crest settlement and acceleration amplification at different elevations and compared. Modular block walls performed better than the rigid faced walls for the same level of base shaking because of the additional support derived by stacking the blocks with an offset. Type and quantity of reinforcement has significant effect on the seismic performance of both the types of walls. Displacements are more sensitive to relative density of the backfill and decrease with increasing relative density, the effect being more pronounced in case of unreinforced walls compared to the reinforced ones. Acceleration amplifications are not affected by the wall facing and inclusion of reinforcement. (C) 2015 Elsevier Ltd. All rights reserved.

HYDROMAGNETICS OF ADVECTIVE ACCRETION FLOWS AROUND BLACK HOLES: REMOVAL OF ANGULAR MOMENTUM BY LARGE-SCALE MAGNETIC STRESSES

We show that the removal of angular momentum is possible in the presence of large-scale magnetic stresses in geometrically thick, advective, sub-Keplerian accretion flows around black holes in steady state, in the complete absence of alpha-viscosity. The efficiency of such an angular momentum transfer could be equivalent to that of alpha-viscosity with alpha = 0.01-0.08. Nevertheless, the required field is well below its equipartition value, leading to a magnetically stable disk flow. This is essentially important in order to describe the hard spectral state of the sources when the flow is non/sub-Keplerian. We show in our simpler 1.5 dimensional, vertically averaged disk model that the larger the vertical-gradient of the azimuthal component of the magnetic field is, the stronger the rate of angular momentum transfer becomes, which in turn may lead to a faster rate of outflowing matter. Finding efficient angular momentum transfer in black hole disks via magnetic stresses alone, is very interesting when the generic origin of alpha-viscosity is still being explored.

Divide and Conquer: Efficient Large-Scale Structure from Motion Using Graph Partitioning

Despite significant advances in recent years, structure-from-motion (SfM) pipelines suffer from two important drawbacks. Apart from requiring significant computational power to solve the large-scale computations involved, such pipelines sometimes fail to correctly reconstruct when the accumulated error in incremental reconstruction is large or when the number of 3D to 2D correspondences are insufficient. In this paper we present a novel approach to mitigate the above-mentioned drawbacks. Using an image match graph based on matching features we partition the image data set into smaller sets or components which are reconstructed independently. Following such reconstructions we utilise the available epipolar relationships that connect images across components to correctly align the individual reconstructions in a global frame of reference. This results in both a significant speed up of at least one order of magnitude and also mitigates the problems of reconstruction failures with a marginal loss in accuracy. The effectiveness of our approach is demonstrated on some large-scale real world data sets.

COMPOSITE AND MULTI-SCALE COMPLIANT MECHANISMS FOR MANIPULATION AND MECHANICAL CHARACTERIZATION

In this paper, we integrate two or more compliant mechanisms to get enhanced functionality for manipulating and mechanically characterizing the grasped objects of varied size (cm to sub-mm), stiffness (1e5 to 10 N/m), and materials (cement to biological cells). The concepts of spring-lever (SL) model, stiffness maps, and non-dimensional kinetoelastostatic maps are used to design composite and multi-scale compliant mechanisms. Composite compliant mechanisms comprise two or more different mechanisms within a single elastic continuum while multi-scale ones possess the additional feature of substantial difference in the sizes of the mechanisms that are combined into one. We present three applications: (i) a composite compliant device to measure the failure load of the cement samples; (ii) a composite multi-scale compliant gripper to measure the bulk stiffness of zebrafish embryos; and (iii) a compliant gripper combined with a negative-stiffness element to reduce the overall stiffness. The prototypes of all three devices are made and tested. The cement sample needed a breaking force of 22.5 N; the zebrafish embryo is found to have bulk stiffness of about 10 N/m; and the stiffness of a compliant gripper was reduced by 99.8 % to 0.2 N/m.

A Voltage Space Vector Diagram Formed by Nineteen Concentric Dodecagons for Medium-Voltage Induction Motor Drive

In this paper, a multilevel dodecagonal voltage space vector structure with nineteen concentric dodecagons is proposed for the first time. This space vector structure is achieved by cascading two sets of asymmetric three-level inverters with isolated H-bridges on either side of an open-end winding induction motor. The dodecagonal structure is made possible by proper selection of dc link voltages and switching states of the inverters. The proposed scheme retains all the advantages of multilevel topologies as well as the advantages of dodecagonal voltage space vector structure. In addition to that, a generic and simple method for calculation of pulsewidth modulation timings using only sampled reference values (v(alpha) and v(beta)) is proposed. This enables the scheme to be used for any closed-loop application such as vector control. In addition, a new method of switching technique is proposed, which ensures minimum switching while eliminating the fifth-and seventh-order harmonics and suppressing the eleventh and thirteenth harmonics, eliminating the need for bulky filters. The motor phase voltage is a 24-stepped wave-form for the entire modulation range thereby reducing the number of switchings of the individual inverter modules. Experimental results for steady-state operation, transient operation, including start-up have been presented and the results of fast Fourier transform analysis is also presented for validating the proposed concept.

A Bacterial Foraging Optimization and Learning Automata Based Feature Selection for Motor Imagery EEG Classification

Selection of relevant features is an open problem in Brain-computer interfacing (BCI) research. Sometimes, features extracted from brain signals are high dimensional which in turn affects the accuracy of the classifier. Selection of the most relevant features improves the performance of the classifier and reduces the computational cost of the system. In this study, we have used a combination of Bacterial Foraging Optimization and Learning Automata to determine the best subset of features from a given motor imagery electroencephalography (EEG) based BCI dataset. Here, we have employed Discrete Wavelet Transform to obtain a high dimensional feature set and classified it by Distance Likelihood Ratio Test. Our proposed feature selector produced an accuracy of 80.291% in 216 seconds.

A comparison of the fine-scale structure of the diurnal cycle of tropical rain and lightning

In this study, the fine-scale structure of the diurnal variability of ground-based lightning is systematically compared with satellite-based rain. At the outset, it is shown that tropical variability of lightning exhibits a prominent diurnal mode, much like rain. A comparison of the geographical distribution of the timing of the diurnal maximum shows that there is very good agreement between the two observables over continental and coastal regions throughout the tropics. Following this global tropical comparison, we focus on two regions, Borneo and equatorial South America, both of which show the interplay between oceanward and landward propagations of the phase of the diurnal maximum. Over Borneo, both rain and lightning clearly show a climatological cycle of ``breathing in'' (afternoon to early morning) and ``breathing out'' (morning to early afternoon). Over the equatorial east coast of South America, landward propagation is noticed in rain and lightning from early afternoon to early morning. Along the Pacific coast of South America, both rain and lightning show oceanward propagation. Though qualitatively consistent, over both regions the propagation is seen to extend further in rainfall. Additionally, given that lightning highlights vigorous convection, the timing of its diurnal maximum often precedes that of rainfall in the convective life cycle. (C) 2015 Elsevier B.V. All rights reserved.

Small-Signal Stability Analysis of an Open-Loop Induction Motor Drive Including the Effect of Inverter Deadtime

This paper demonstrates light-load instability in a 100-kW open-loop induction motor drive on account of inverter deadtime. An improved small-signal model of an inverter-fed induction motor is proposed. This improved model is derived by linearizing the nonlinear dynamic equations of the motor, which include the inverter deadtime effect. Stability analysis is carried out on the 100-kW415-V three-phase induction motor considering no load. The analysis brings out the region of instability of this motor drive on the voltage versus frequency (V-f) plane. This region of light-load instability is found to expand with increase in inverter deadtime. Subharmonic oscillations of significant amplitude are observed in the steady-state simulated and measured current waveforms, at numerous operating points in the unstable region predicted, confirming the validity of the stability analysis. Furthermore, simulation and experimental results demonstrate that the proposed model is more accurate than an existing small-signal model in predicting the region of instability.

Theoretical and Experimental Evaluation of Pulsating Torque Produced by Induction Motor Drives Controlled With Advanced Bus-Clamping Pulsewidth Modulation

This paper investigates possible reduction of pulsating torque in open-loop and vector-controlled induction motor drives through deployment of certain advanced bus-clamping pulsewidth modulation (ABCPWM) method. Toward this goal, a simple and machine-independent method is proposed to analyze the torque harmonic spectrum of a voltage source inverter fed induction motor, operated with any real-time pulsewidth modulation (PWM) method. The analytically evaluated torque harmonic spectra, pertaining to conventional space vector PWM (CSVPWM), bus-clamping PWM (BCPWM), and ABCPWM, are validated through simulation and experimental results. Theoretical and experimental studies bring out the superiority of the ABCPWM in terms of torque harmonics over CSVPWM and BCPWM. The magnitude of the dominant torque harmonic with the ABCPWM scheme is shown to be significantly lower than that with CSVPWM, over a wide range of speed. The rms torque ripple (i.e., total rms value of all harmonic torques) is lower with ABCPWM than with BCPWM over the entire range of speed.

Sparse representation-based human detection: a scale-embedded dictionary approach

Human detection is a complex problem owing to the variable pose that they can adopt. Here, we address this problem in sparse representation framework with an overcomplete scale-embedded dictionary. Histogram of oriented gradient features extracted from the candidate image patches are sparsely represented by the dictionary that contain positive bases along with negative and trivial bases. The object is detected based on the proposed likelihood measure obtained from the distribution of these sparse coefficients. The likelihood is obtained as the ratio of contribution of positive bases to negative and trivial bases. The positive bases of the dictionary represent the object (human) at various scales. This enables us to detect the object at any scale in one shot and avoids multiple scanning at different scales. This significantly reduces the computational complexity of detection task. In addition to human detection, it also finds the scale at which the human is detected due to the scale-embedded structure of the dictionary.