Crystal plasticity modeling of deformation and creep in polycrystalline Ti-6242

This paper develops an experimentally validated computational model based on crystal plasticity for the analysis of two-phase α/β Ti-6242 polycrystalline alloys. A rate-dependent elastic-crystal plasticity model is incorporated in this model to accommodate anisotropy in material behavior and tension-compression asymmetry inherent to this alloy. A combination of microtesting, orientation imaging microscopy, computational simulations, and minimization process, involving genetic algorithms, is implemented in this study for careful characterization and calibration of the material parameters. Size effects are considered in this analysis through a simple scaling process. A homogenized equivalent model of the primary α with transformed β colonies is developed for incorporation in the Ti-6242 FE model. The polycrystalline Ti-6242 computational model incorporates accurate phase volume fractions, as well as statistically equivalent orientation distributions to those observed in the orientation imaging microscopy scans. The effects of orientation, misorientations, and microtexture distributions are investigated through simulations by this computational model. The model is used to simulate constant strain rate and creep tests in compression and tension, and the results are compared with experiments. The effects of microstructure and creep-induced load-shedding on the localization of microstructural stresses and strains are studied for potential crack initiation criteria.     

Determination of 5-aminolaevulinic acid dehydratase activity in erythrocytes and porphobilinogen in urine by micellar electrokinetic capillary chromatography

A micellar electrokinetic capillary chromatographic (MECC) method has been developed and optimised for the separation of 5-aminolaevulinic acid (ALA) and porphobilinogen (PBG). The running buffer consisted of a mixture of 20 mM sodium phosphate and 20 mM sodium borate containing 50 mM sodium dodecyl sulphate (SDS) adjusted to pH 9.5 with 1 M NaOH. The running voltage and temperature were 20-25 kV and 30 degrees C, respectively. The MECC method for the analysis of PBG is fast and simple and is useful for the screening of PBG in the urine of patients suspected to have acute intermittent porphyria (AIP), and for the confirmation of lead exposure by measuring red-cell ALA-dehydratase (ALA-D) activity with ALA as the enzyme substrate.     

SWGMM: a semi-wrapped Gaussian mixture model for clustering of circular–linear data

Finite mixture models are widely used to perform model-based clustering of multivariate data sets. Most of the existing mixture models work with linear data; whereas, real-life applications may involve multivariate data having both circular and linear characteristics. No existing mixture models can accommodate such correlated circular–linear data. In this paper, we consider designing a mixture model for multivariate data having one circular variable. In order to construct a circular–linear joint distribution with proper inclusion of correlation terms, we use the semi-wrapped Gaussian distribution. Further, we construct a mixture model (termed SWGMM) of such joint distributions. This mixture model is capable of approximating the distribution of multi-modal circular–linear data. An unsupervised learning of the mixture parameters is proposed based on expectation maximization method. Clustering is performed using maximum a posteriori criterion. To evaluate the performance of SWGMM, we choose the task of color image segmentation in LCH space. We present comprehensive results and compare SWGMM with existing methods. Our study reveals that the proposed mixture model outperforms the other methods in most cases.     

Design and Uncertainty Evaluation of a Strain Measurement System

Strain measurement is very important in various industrial applications as well as different disciplines of science and technology for direct and indirect observations of certain parameters. Designing signal conditioning circuit is always a challenging and important task for satisfactory and reliable performance of a sensor as well as the system. The design and implementation details of a signal conditioning circuit of resistive sensor (strain gauge) for strain measurement are presented in this paper. Also the important aspects in designing a signal conditioning circuit for resistive sensor are presented and a novel method for the measurement of strain is discussed. Quarter bridge configuration with AC voltage excitation is used for the measurement along with the necessary circuitry to get a suitable and measurable output DC voltage. The measurement system is calibrated using a cantilever of stainless steel and the details of calibration are presented in the paper. The uncertainty associated with the measurement system is evaluated.     

EMERS: a tree matching–based performance evaluation of mathematical expression recognition systems

Performance evaluation of mathematical expression recognition systems is attempted. The proposed method assumes expressions (input as well as recognition output) are coded following MathML or T_EX/LaT_EX (which also gets converted into MathML) format. Since any MathML representation follows a tree structure, evaluation of performance has been modeled as a tree-matching problem. The tree corresponding to the expression generated by the recognizer is compared with the groundtruthed one by comparing the corresponding Euler strings. The changes required to convert the tree corresponding to the expression generated by the recognizer into the groundtruthed one are noted. The number of changes required to make such a conversion is basically the distance between the trees. This distance gives the performance measure for the system under testing. The proposed algorithm also pinpoints the positions of the changes in the output MathML file. Testing of the proposed evaluation method considers a set of example groundtruthed expressions and their corresponding recognized results produced by an expression recognition system.     

Analysis of Elevated Temperature Flow Behavior of 316LN Stainless Steel Under Compressive Loading

To understand the flow behavior of a newly developed austenitic stainless steel 316LN with 0.14 wt% nitrogen, isothermal compression tests have been carried out in the hot working domain. From the analysis of flow behavior, it is observed that the nitrogen enhanced steel, in its hot working domain exhibits strain and strain rate hardening with thermal softening. The flow behavior analysis also demonstrates the coupled effect of strain–temperature and strain rate temperature on the flow stress. To depict the flow behavior of the material, strain compensated Arrhenius (SCA) equation and Model D8A have been used. The SCA predicts the flow curves with an average absolute error of 9.27% and a correlation coefficient of 0.977, whereas the prediction by Model D8A gives the average absolute relative error as 10.86% with a correlation coefficient of 0.966. For high temperature and intermediate strain rate, both Model D8A and SCA equation depict the flow behavior of 316L (0.14)N SS with good correlation and generalization. However, at low temperature and high strain rate domain, both the models are unable to depict the behavior; this is attributed to the fact that the material shows two slope behaviors where the constants have been calculated assuming a linear relationship between stress and strain rate.