Bayesian methodology for reliability model acceptance

This paper develops a methodology to assess the reliability computation model validity using the concept of Bayesian hypothesis testing, by comparing the model prediction and experimental observation, when there is only one computational model available to evaluate system behavior. Time-independent and time-dependent problems are investigated, with consideration of both cases: with and without statistical uncertainty in the model. The case of time-independent failure probability prediction with no statistical uncertainty is a straightforward application of Bayesian hypothesis testing. However, for the life prediction (time-dependent reliability) problem, a new methodology is developed in this paper to make the same Bayesian hypothesis testing concept applicable. With the existence of statistical uncertainty in the model, in addition to the application of a predictor estimator of the Bayes factor, the uncertainty in the Bayes factor is explicitly quantified through treating it as a random variable and calculating the probability that it exceeds a specified value. The developed method provides a rational criterion to decision-makers for the acceptance or rejection of the computational model.     

Image-based automated potato tuber shape evaluation

Potato tuber length to width (L/W) ratio is an indicator of shape phenotype, which is an important quality trait assessed in breeding and variety development. The standard method of measurement using calipers is labor intensive and time consuming. In this study, an image acquisition system was integrated with an automated potato sizer to capture video data of tubers during sorting for estimation of L/W ratios. An algorithm was developed to segment and estimate the L/W ratios from the video frame in an accurate and high-throughput manner. Line profile was used to determine the tuber position in the frame. The minimal bounding rectangle of each tuber was computed to estimate length and width of the tubers. The imaging conditions (light, imaging distance, and speed) were optimized using fresh market potato tubers (43 samples). Finally, the algorithm was tested with eight sets of field samples of tubers of cultivars Bondi and Alturas (about 709–1273 samples/set). Optimization results indicated that L/W measurement accuracy was higher than 95% for the fresh market potato tubers, with no significant effect of tested imaging conditions. There was also a significant correlation between ground-truth caliper measurements and image-based data (Pearson’s correlation coefficient: 0.84–0.99, p?<?0.01). The accuracies of L/W estimations for field samples of Bondi and Alturas tubers ranged from 76 to 100%. The lower accuracies are likely attributed to differences in sample size. Nevertheless, the method is applicable for rapid and accurate estimation of L/W ratio for a large set of samples .     

Chemical vapor infiltration of additively manufactured preforms: Pore-resolved simulations and experimental validation

The densification of additively manufactured porous preforms by chemical vapor infiltration (CVI) is studied using pore-resolved simulations and experiments. Experimentally, 3D printed silicon carbide (SiC) preforms are subject to CVI synthesis using methyltrichlorosilane (MTS) precursor to obtain high purity SiC/SiC composites. Optical images of the cross sections of the processed preforms are analyzed to obtain the spatial porosity distribution. The numerical method is based on a level set formulation to capture the spatial distribution and time evolution of the pore scale microstructural characteristics. The coupled transport and kinetic effects are represented using a dimensionless Thiele modulus. Simulations are initialized using representative synthetic preform geometries comprising of packed particles based on the size distribution of the powder used for 3D printing. The simulation results are validated against the experimental observations in terms of total density and the distribution of residual porosity. The densification characteristics, porosity classification, concentration profiles, and structure functions are analyzed as functions of processing temperature and Thiele modulus.     

Low Cycle Fatigue Behavior of 316LN Stainless Steel Alloyed with Varying Nitrogen Content. Part I: Cyclic Deformation Behavior

In this study, the influence of cyclic strain amplitude on the evolution of cyclic stress–strain response and the associated cyclic deformation mechanisms in 316LN stainless steel with varying nitrogen content (0.07 to 0.22 wt pct) is reported in the temperature range 773 K to 873 K (500 °C to 600 °C). Two mechanisms, namely dynamic strain aging and secondary cyclic hardening, are found to strongly influence the cyclic stress response. Deformation substructures associated with both the mechanisms showed planar mode of deformation. These mechanisms are observed to be operative over certain combinations of temperature and strain amplitude. For strain amplitudes >0.6 pct, wavy or mixed mode of deformation is noticed to suppress both the mechanisms. Cyclic stress–strain curves revealed both single and dual-slope behavior depending on the test temperature. Increase in nitrogen content is found to increase the tendency toward planar mode of deformation, while increase in strain amplitude leads to transition from planar slip bands to dislocation cell/wall structure formation, irrespective of the nitrogen content in 316LN stainless steel.     

亚格子过滤双流体模型的网格依赖性

基于双流体方程和颗粒动力学理论的计算模型被广泛应用于流化床的气固两相流数值计算,高精度网格是其准确计算流动的必要条件。一些经典的微尺度阻力模型,其网格尺度决定其模拟结果的精度。亚格子过滤双流体模型是一种有效的适用于粗糙网格的计算模型,其包含的气固相间作用力和颗粒相应力本构方程是在高精度网格条件下,以微尺度双流体方程和颗粒动力学理论计算得到的气固流场为基础,对计算结果进行小尺度过滤后得出。使用亚格子过滤双流体模型替换基于颗粒动力学理论的双流体模型,针对同一物理问题,在不同网格尺度下进行了数值计算,结果表明此计算模型相比经典阻力模型具有较好的网格无关特性,并且和实验结果较为一致。同时也对颗粒动力学理论与之相结合进行了尝试,即仅使用亚格子过滤阻力模型,颗粒相应力仍然使用颗粒动力学模型,其计算结果的网格无关性及与实验值的吻合程度优于经典模型。     

Influence of Secondary Cyclic Hardening on the Low Cycle Fatigue Behavior of Nitrogen Alloyed 316LN Stainless Steel

In this article, the occurrence of secondary cyclic hardening (SCH) and its effect on high-temperature cyclic deformation and fatigue life of 316LN Stainless steel are presented. SCH is found to result from planar slip mode of deformation and enhance the degree of hardening over and above that resulted from dynamic strain aging. The occurrence of SCH is strongly governed by the applied strain amplitude, test temperature, and the nitrogen content in the 316LN SS. Under certain test conditions, SCH is noticed to decrease the low cycle fatigue life with the increasing nitrogen content.     

Efficacy of La3+ entrapped chitosan bio‐polymeric matrix for the recovery of oil from oil‐in‐water emulsion

On the basis of the present study, the details of the recovery of cutting oil from oil‐in‐water emulsion using the modified forms of biopolymer chitosan viz., chitosan beads (CB), carboxylated chitosan beads (CCB), and lanthanum incorporated carboxylated chitosan beads (La‐CCB). Various oil sorption experiments were conducted using an extractive gravimetric method by optimizing various parameters such as contact time, pH, sorbent dosage, and initial oil concentration for maximum sorption. It was found that the oil removal percentage was comparatively less in the case of CB and CCB when compared with La‐CCB, which showed 85% of oil removal at acidic condition. The obtained adsorption equilibrium data was explained with Freundlich, Langmuir, D–R, and Tempkin isotherms to find the best fit for the sorption process. Thermodynamic parameters such as ΔG⁰, ΔH⁰, and ΔS⁰ were calculated in order to understand the nature of sorption process. The surface morphology and sorption of oil on the beads were confirmed by FTIR, SEM with EDAX, XRD, TGA, and DSC analysis. This work provides a potential platform for the expansion of oil removal technology. © 2015 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2016 , 133, 43218.     

Online 3-D tracking of suspension living cells imaged with phase-contrast microscopy

Neural stem cells/neural progenitors (NSCs/NPs) are cells that give rise to the main cell types of the nervous system: oligodendrocytes, neurons, and astrocytes. Studying NSCs/NPs with time-lapse microscopy is critical to the understanding of the biology of these cells. However, NSCs/NPs are very sensitive to phototoxic damage, and therefore, fluorescent dyes cannot be used to follow these cells. Also, since in most of NSC/NP-related experiments, a large number of cells neesd to be monitored. Consequently, the acquisition of a huge amount of images is required. An additional difficulty is related to our original suspension living, tracking objective, behavior much closer to the natural, in vivo, way of development of the cells. Indeed, unlike adherent cells, suspension cells float freely in a liquid solution, thus, making their dynamics very different from that of adherent cells. As a result, existing visual tracking algorithms that have primarily been developed to track adherent cells are no longer adequate to tackle living cells in suspension. This paper presents a novel automated 3-D visual tracking of suspension living cells for time-lapse image acquisition using phase-contrast microscopy. This new tracking method can potentially strongly impact on current 3-D video microscopy methods, paving the way for innovative analysis of NSCs/NPs and as a result, on the study of neurodegenerative diseases.     

Characterization of volatile organic compounds in human leukocyte antigen heterologous expression systems: a cell's "chemical odor fingerprint"

The major histocompatibility complex (MHC), or human leukocyte antigen (HLA) gene‐coding region in humans, plays a significant role in infectious disease response, autoimmunity, and cellular recognition. This super locus is essential in mate selection and kin recognition because of the organism‐specific odor which can be perceived by other individuals. However, how the unique MHC genetic combination of an organism correlates with generation of the organism‐specific odor is not well understood. In the present work, we have shown that human B‐cells produce a set of volatile organic compounds (VOCs) that can be measured by GC‐MS. More importantly, our results show that specific HLA alleles are related to production of selected VOCs, and that this leads to a cell‐specific odor “fingerprint”. We used a C1R HLA class I A and B locus negative cell line, along with C1R cell lines that were stably transfected with specific A and B alleles. Our work demonstrates for the first time that HLA alleles can directly influence production of specific odor compounds at the cellular level. Given that the resulting odor fingerprint depends on expression of specific HLA sequences, it may yield information on unique human scent profiles, composition of exhaled breath, as well as immune response states in future studies.