Intergranular Oxidation of Nickel-Base Alloys: Potentialities of Focused Ion Beam Tomography

Oxidation of Metals - The present work focuses on the intergranular oxidation of Alloy 600 and its weld material Alloy 82 after exposure in simulated primary water at 340–360 °C...     

Experimental and numerical study of a modified ASTM C633 adhesion test for strongly-bonded coatings

When coatings are strongly bonded to their substrates it is often difficult to measure the adhesion values. The proposed method, which is suggested naming “silver print test”, consists in covering the central part of the samples with a thin layer of silver paint, before coating. The process used for testing this new method was the Air plasma spraying (APS), and the materials used were alumina coatings on C35 steel substrates, previously pre-oxidized in CO₂. The silver painted area was composed of small grains that did not oxidize but that significantly sintered during the APS process. The silver layer reduced the surface where the coating was linked to the substrate, which allowed its debonding, using the classical adhesion test ASTM C633-13, while the direct use of this test (without silver painting) led to ruptures inside the glue used in this test. The numerical modelling, based on the finite element method with the ABAQUS software, provided results in good agreement with the experimental measurements. This concordance validated the used method and allowed accessing to the values of adherence when the experimental test ASTM C633-13 failed, because of ruptures in the glue. After standardization, the “silver print test” might be used for other kinds of deposition methods, such as PVD, CVD, PECVD.     

A two-pronged approach for springback variability assessment using sparse polynomial chaos expansion and multi-level simulations

In this study, we show that stochastic analysis of metal forming process requires both a high precision and low cost numerical models in order to take into account very small perturbations on inputs (physical as well as process parameters) and to allow for numerous repeated analysis in a reasonable time. To this end, an original semi-analytical model dedicated to plain strain deep drawing based on a Bending-Under-Tension numerical model (B-U-T model) is used to accurately predict the influence of small random perturbations around a nominal solution estimated with a full scale Finite Element Model (FEM). We introduce a custom sparse variant of the Polynomial Chaos Expansion (PCE) to model the propagation of uncertainties through this model at low computational cost. Next, we apply this methodology to the deep drawing process of U-shaped metal sheet considering up to 8 random variables.     

Perceptions of the health and convenience characteristics of fresh and dried fruits

Dried fruits consumption has not received much research attention, although these foods are associated with potential health benefits. Therefore, the aim of this study was to compare fresh fruits and dried fruits on measures of health, convenience and consumer feelings.An on-line questionnaire that measured consumers' perceptions of the health benefits and convenience characteristics and their feelings about the consumption of both fresh fruits (apples and plums) and dried fruits (e.g., raisins, dates, and apricots) was completed by 693 respondents (Polish, French, and Dutch).Generally, fresh fruits were perceived to be healthier and less convenient than dried fruits. Consumers also reported more positive feelings about the consumption of fresh fruits compared to dried fruits. The more that the respondents were willing to sacrifice for their health, the more positively they rated the health aspects of both fresh and dried fruits, as well as several perceptions of convenience of both fresh and dried fruits. Health preoccupation was unrelated to most of the convenience perceptions and was associated with lower scores on several perceptions of healthiness. Recommendations for the consumer-oriented development of dried fruits are also provided.     

Imbalanced classification in sparse and large behaviour datasets

Recent years have witnessed a growing number of publications dealing with the imbalanced learning issue. While a plethora of techniques have been investigated on traditional low-dimensional data, little is known on the effect thereof on behaviour data. This kind of data reflects fine-grained behaviours of individuals or organisations and is characterized by sparseness and very large dimensions. In this article, we investigate the effects of several over-and undersampling, cost-sensitive learning and boosting techniques on the problem of learning from imbalanced behaviour data. Oversampling techniques show a good overall performance and do not seem to suffer from overfitting as traditional studies report. A variety of undersampling approaches are investigated as well and show the performance degrading effect of instances showing odd behaviour. Furthermore, the boosting process indicates that the regularization parameter in the SVM formulation acts as a weakness indicator and that a combination of weak learners can often achieve better generalization than a single strong learner. Finally, the EasyEnsemble technique is presented as the method outperforming all others. By randomly sampling several balanced subsets, feeding them to a boosting process and subsequently combining their hypotheses, a classifier is obtained that achieves noise/outlier reduction effects and simultaneously explores the majority class space efficiently. Furthermore, the method is very fast since it is parallelizable and each subset is only twice as large as the minority class size.     

Effect of wobbling mass modeling on joint dynamics during human movements with impacts

In automated mechanical transmissions, engaging sleeve with clutch gear causes the switches of mechanical coupling modes of engaging-related parts, and impacts may happen to make the part speeds have discrete transitions during the engaging. The two characters make the engaging process exhibit both continuity and discreteness. The aim of the paper is to develop a high-fidelity model to capture the trajectories of the parts in the transmission. We treat the engaging as a two-phase process—sleeve first interacting with synchro ring and then with clutch gear. The part movements under a certain constraint are governed by multibody dynamics, and the speed jumps caused by impacts are described using the Poisson coefficient of restitution. To couple the continuous evolutions and discrete transitions of the states, a hybrid automaton model is developed. This model allows for the characteristic analysis of the engaging process with multiple interaction cases between the engaging-related parts, and it is validated by bench tests. The effects of two key factors—the relative tooth position of sleeve and clutch gear and the shifting force—on engaging duration and impact are studied through numerical simulations.     

Change detection in coral reef communities using Ikonos satellite sensor imagery and historic aerial photographs

For decades, aerial photographs have been the only source of very high spatial resolution data for coral reef researchers. With the launch of the Ikonos satellite in 1999, imagery with a 4 m spatial resolution in multispectral mode can now be combined with historical aerial photographs for change detection. We demonstrate this potential by combining two aerial photographs (1981 and 1992) and an Ikonos image (2000) to detect change in the coral reef communities for Carysfort Reef, Florida, USA. The results show a loss of 'coral-dominated' bottom from 52% (1981) to 16% (1992) to finally 6% (2000), a trend similar to in situ observations.