Correlation of microstructure and creep behaviour of MRI230D Mg alloy developed by two different casting technologies

The relationship between the as-cast microstructure and creep behaviour of the heat-resistant MRI230D Mg alloy produced by two different casting technologies is investigated. The alloy in both ingot-casting (IC) and high pressure die-casting (HPDC) conditions consists of alpha-Mg, 06 ((Mg,AI)(2)Ca), Al-Mn and Sn-Mg-Ca rich phases. However, the HPDC alloy resulted in relatively finer grain size and higher volume fraction of finer, denser network of eutectic C36 phase in the as-cast microstructure as compared to that of the IC alloy. The superior creep resistance exhibited by the HPDC alloy at all the stress levels and temperatures employed in the present investigation was attributed to the more effective dispersion strengthening effect caused by the presence of finer and denser network of the C36 phase. The increased amount of the eutectic C36 phase was the only change observed in the microstructures of both alloys following creep tests. (C) 2015 Elsevier B.V. All rights reserved.

Correlation between band propagation property and the nature of serrations in the Portevin-Le Chatelier effect

We investigate the correlation between the band propagation property and the nature and amplitude of serrations in the Portevin-Le Chatelier effect within the framework of the Ananthakrishna model. Several significant results emerge. First, we find that spatial and temporal correlations continuously increase with strain rate from type C to type A bands. Consequently, the nature of the bands also changes continuously from type C to A bands, and so do the changes in the associated serrations. Second, even the smallest extent of propagation induces small amplitude serrations. The spatial extent of band propagation is directly correlated with the duration of small amplitude serrations, a result that is consistent with recent experiments. This correspondence allows one to estimate the spatial extent of band propagation by just measuring the temporal stretch of small amplitude serrations. Therefore, this should be of practical value when only stress versus strain is recorded. Third, the average stress drop magnitude of the small amplitude serrations induced by the propagating bands remains small and nearly constant with strain rate. As a consequence, the fully propagating type A bands are in a state of criticality. We rationalize the increasing levels of spatial and temporal correlations found with increasing strain rates. Lastly, the model also predicts several band morphologies seen in experiments including the Luders-like propagating band. (C) 2015 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved.

Experimental determination and theoretical correlation for the solubilities of dicarboxylic acid esters in supercritical carbon dioxide

The synthesis of high molecular weight esters such as bis (2-ethylhexyl) sebacate is of significance for its use as a lubricant. This ester is synthesized by the transesterification of dimethyl sebacate with 2-ethylhexanol. Therefore, the solubilities of bis (2-ethylhexyl) sebacate and dimethyl sebacate were determined at 308-328 K at pressures of 10-18 MPa in supercritical carbon dioxide. The solubility of dimethyl sebacate was always higher than bis (2-ethylhexyl) sebacate at a given temperature and pressure. The Mendez-Teja model was used to verify the self-consistency of data. Further, a new semi-empirical model with three parameters was developed using the solution theory coupled with Wilson activity coefficient. This model was used to correlate the experimental data of this work and solubilities of many high molecular weight esters reported in the literature. (C) 2015 Elsevier B.V. All rights reserved.

Estimation of Aboveground Phytomass of Plantations Using Digital Photogrammetry and High Resolution Remote Sensing Data

The study follows an approach to estimate phytomass using recent techniques of remote sensing and digital photogrammetry. It involved tree inventory of forest plantations in Bhakra forest range of Nainital district. Panchromatic stereo dataset of Cartosat-1 was evaluated for mean stand height retrieval. Texture analysis and tree-tops detection analyses were done on Quick-Bird PAN data. The composite texture image of mean, variance and contrast with a 5x5 pixel window was found best to separate tree crowns for assessment of crown areas. Tree tops count obtained by local maxima filtering was found to be 83.4 % efficient with an RMSE+/-13 for 35 sample plots. The predicted phytomass ranged from 27.01 to 35.08 t/ha in the case of Eucalyptus sp. while in the case of Tectona grandis from 26.52 to 156 t/ha. The correlation between observed and predicted phytomass in Eucalyptus sp. was 0.468 with an RMSE of 5.12. However, the phytomass predicted in Tectona grandis was fairly strong with R-2=0.65 and RMSE of 9.89 as there was no undergrowth and the crowns were clearly visible. Results of the study show the potential of Cartosat-1 derived DSM and Quick-Bird texture image for the estimation of stand height, stem diameter, tree count and phytomass of important timber species.

Correlation Between Decay Rate and Amplitude of Solar Cycles as Revealed from Observations and Dynamo Theory

Using different proxies of solar activity, we have studied the following features of the solar cycle: i) The linear correlation between the amplitude of cycle and its decay rate, ii) the linear correlation between the amplitude of cycle and the decay rate of cycle , and iii) the anti-correlation between the amplitude of cycle and the period of cycle . Features ii) and iii) are very useful because they provide precursors for future cycles. We have reproduced these features using a flux-transport dynamo model with stochastic fluctuations in the Babcock-Leighton effect and in the meridional circulation. Only when we introduce fluctuations in meridional circulation, are we able to reproduce different observed features of the solar cycle. We discuss the possible reasons for these correlations.

State Transition Based Embedding in Cepstrum Domain for Audio Copyright Protection

In this paper, we propose a new state transition based embedding (STBE) technique for audio watermarking with high fidelity. Furthermore, we propose a new correlation based encoding (CBE) scheme for binary logo image in order to enhance the payload capacity. The result of CBE is also compared with standard run-length encoding (RLE) compression and Huffman schemes. Most of the watermarking algorithms are based on modulating selected transform domain feature of an audio segment in order to embed given watermark bit. In the proposed STBE method instead of modulating feature of each and every segment to embed data, our aim is to retain the default value of this feature for most of the segments. Thus, a high quality of watermarked audio is maintained. Here, the difference between the mean values (Mdiff) of insignificant complex cepstrum transform (CCT) coefficients of down-sampled subsets is selected as a robust feature for embedding. Mdiff values of the frames are changed only when certain conditions are met. Hence, almost 50% of the times, segments are not changed and still STBE can convey watermark information at receiver side. STBE also exhibits a partial restoration feature by which the watermarked audio can be restored partially after extraction of the watermark at detector side. The psychoacoustic model analysis showed that the noise-masking ratio (NMR) of our system is less than -10dB. As amplitude scaling in time domain does not affect selected insignificant CCT coefficients, strong invariance towards amplitude scaling attacks is also proved theoretically. Experimental results reveal that the proposed watermarking scheme maintains high audio quality and are simultaneously robust to general attacks like MP3 compression, amplitude scaling, additive noise, re-quantization, etc.

Synthetic image super resolution using FeatureMatch

In this paper, we propose a super resolution (SR) method for synthetic images using FeatureMatch. Existing state-of-the-art super resolution methods are learning based methods, where a pair of low-resolution and high-resolution dictionary pair are trained, and this trained pair is used to replace patches in low-resolution image with appropriate matching patches from the high-resolution dictionary. In this paper, we show that by using Approximate Nearest Neighbour Fields (ANNF), and a common source image, we can by-pass the learning phase, and use a single image for dictionary. Thus, reducing the dictionary from a collection obtained from hundreds of training images, to a single image. We show that by modifying the latest developments in ANNF computation, to suit super resolution, we can perform much faster and more accurate SR than existing techniques. To establish this claim we will compare our algorithm against various state-of-the-art algorithms, and show that we are able to achieve better and faster reconstruction without any training phase.

A Few Case Studies on the Correlation of Particle Network and Its Stability on the Ionic Conductivity of Solid-Liquid Composite Electrolytes

We discuss here the crucial role of the particle network and its stability on the long-range ion transport in solid liquid composite electrolytes. The solid liquid composite electrolytes chosen for the study here comprise nanometer sized silica (SiO2) particles having various surface chemical functionalities dispersed in nonaqueous lithium salt solutions, viz, lithium perchlorate (LiClO4) in two different polyethylene glycol based solvents. These systems constitute representative examples of an independent class of soft matter electrolytes known as ``soggy sand'' electrolytes, which have tremendous potential in diverse electrochemical devices. The oxide additive acts as a heterogeneous dopant creating free charge carriers and enhancing the local ion transport. For long-range transport, however, a stable spanning particle network is needed. Systematic experimental investigations here reveal that the spatial and time dependent characteristics of the particle network in the liquid solution are nontrivial. The network characteristics are predominantly determined by the chemical makeup of the electrolyte components and the chemical interactions between them. It is noteworthy that in this study the steady state macroscopic ionic conductivity and viscosity of the solid liquid composite electrolyte are observed to be greatly determined by the additive oxide surface chemical functionality, solvent chemical composition, and solvent dielectric constant.

Real-time maximum a-posteriori image reconstruction for fluorescence microscopy

Rapid reconstruction of multidimensional image is crucial for enabling real-time 3D fluorescence imaging. This becomes a key factor for imaging rapidly occurring events in the cellular environment. To facilitate real-time imaging, we have developed a graphics processing unit (GPU) based real-time maximum a-posteriori (MAP) image reconstruction system. The parallel processing capability of GPU device that consists of a large number of tiny processing cores and the adaptability of image reconstruction algorithm to parallel processing (that employ multiple independent computing modules called threads) results in high temporal resolution. Moreover, the proposed quadratic potential based MAP algorithm effectively deconvolves the images as well as suppresses the noise. The multi-node multi-threaded GPU and the Compute Unified Device Architecture (CUDA) efficiently execute the iterative image reconstruction algorithm that is similar to 200-fold faster (for large dataset) when compared to existing CPU based systems. (C) 2015 Author(s). All article content, except where otherwise noted, is licensed under a Creative Commons Attribution 3.0 Unported License.

A Split-and-Merge Dictionary Learning Algorithm for Sparse Representation: Application to Image Denoising

In big data image/video analytics, we encounter the problem of learning an over-complete dictionary for sparse representation from a large training dataset, which cannot be processed at once because of storage and computational constraints. To tackle the problem of dictionary learning in such scenarios, we propose an algorithm that exploits the inherent clustered structure of the training data and make use of a divide-and-conquer approach. The fundamental idea behind the algorithm is to partition the training dataset into smaller clusters, and learn local dictionaries for each cluster. Subsequently, the local dictionaries are merged to form a global dictionary. Merging is done by solving another dictionary learning problem on the atoms of the locally trained dictionaries. This algorithm is referred to as the split-and-merge algorithm. We show that the proposed algorithm is efficient in its usage of memory and computational complexity, and performs on par with the standard learning strategy, which operates on the entire data at a time. As an application, we consider the problem of image denoising. We present a comparative analysis of our algorithm with the standard learning techniques that use the entire database at a time, in terms of training and denoising performance. We observe that the split-and-merge algorithm results in a remarkable reduction of training time, without significantly affecting the denoising performance.

A thermodynamic correlation between damage and fracture as applied to concrete fatigue

Fatigue damage in concrete is characterized by the simultaneous presence of micro and macrocracks. The theory of fracture mechanics conveniently handles the propagation of macrocracks, whereas damage mechanics precisely describes the state of microcracking. This paper provides a platform to correlate fracture mechanics and damage mechanics theories through an energy equivalence within a thermodynamic framework by equating the energy dissipated according to each theory. Through this correlation, damage corresponding to a given crack length could be obtained, and alternatively a discrete crack could be transformed into an equivalent damage zone. The results are validated using available experimental data on concrete fatigue including stiffness degradation and acoustic emission. (C) 2015 Elsevier Ltd. All rights reserved.

Digital image analysis around isotropic points for photoelastic pattern recognition

Fringe tracking and fringe order assignment have become the central topics of current research in digital photoelasticity. Isotropic points (IPs) appearing in low fringe order zones are often either overlooked or entirely missed in conventional as well as digital photoelasticity. We aim to highlight image processing for characterizing IPs in an isochromatic fringe field. By resorting to a global analytical solution of a circular disk, sensitivity of IPs to small changes in far-field loading on the disk is highlighted. A local theory supplements the global closed-form solutions of three-, four-, and six-point loading configurations of circular disk. The local theoretical concepts developed in this paper are demonstrated through digital image analysis of isochromatics in circular disks subjected to three-and four-point loads. (C) 2015 Society of Photo-Optical Instrumentation Engineers (SPIE)

A thermodynamic correlation between damage and fracture as applied to concrete fatigue

Fatigue damage in concrete is characterized by the simultaneous presence of micro and macrocracics. The theory of fracture mechanics conveniently handles the propagation of macrocracks, whereas damage mechanics precisely describes the state of microcracking. This paper provides a platform to correlate fracture mechanics and damage mechanics theories through an energy equivalence within a thermodynamic framework by equating the energy dissipated according to each theory. Through this correlation, damage corresponding to a given crack length could be obtained, and alternatively a discrete crack could be transformed into an equivalent damage zone. The results are validated using available experimental data on concrete fatigue including stiffness degradation and acoustic emission. (C) 2015 Elsevier Ltd. All rights reserved.

Crystal chemistry and photomechanical behavior of 3,4-dimethoxycinnamic acid: correlation between maximum yield in the solid-state topochemical reaction and cooperative molecular motion

A new monoclinic polymorph, form II (P2(1)/c, Z = 4), has been isolated for 3,4-dimethoxycinnamic acid (DMCA). Its solid-state 2 + 2 photoreaction to the corresponding alpha-truxillic acid is different from that of the first polymorph, the triclinic form I (P (1) over bar, Z = 4) that was reported in 1984. The crystal structures of the two forms are rather different. The two polymorphs also exhibit different photomechanical properties. Form I exhibits photosalient behavior but this effect is absent in form II. These properties can be explained on the basis of the crystal packing in the two forms. The nanoindentation technique is used to shed further insights into these structure-property relationships. A faster photoreaction in form I and a higher yield in form II are rationalized on the basis of the mechanical properties of the individual crystal forms. It is suggested that both Schmidt-type and Kaupp-type topochemistry are applicable for the solid-state trans-cinnamic acid photodimerization reaction. Form I of DMCA is more plastic and seems to react under Kaupp-type conditions with maximum molecular movements. Form II is more brittle, and its interlocked structure seems to favor Schmidt-type topochemistry with minimum molecular movement.