Micromechanical modeling of the effect of elastic and plastic anisotropies on the mechanical behavior of β-Ti alloys

International audienceNear β-titanium alloys like Ti-5553 or Ti-1023 often exhibit bimodal phase constituents embedded in a retained β-phase matrix, which represents up to 40% of the volume. The highly elastic anisotropic β-phase may strongly influence the mechanical behavior of these alloys. The present work models the effect of the coupled role of β-phase elastic and plastic anisotropies on the local and overall responses of a fully β-phase polycrystalline aggregate like the Ti-17 alloy. The model is based on an advanced elasto-viscoplastic self-consistent (EVPSC) homogenization scheme solved by the "translated field" method together with an affine linearization of the viscoplastic flow rule. The effects of elastic anisotropy, crystallographic texture and grain morphology are theoretically studied during uniaxial tensile tests, tension-compression tests as well as multiaxial plastic yielding. First, it is shown that different sets of elastic constants taken from literature give rise to similar effective responses but to widely scattered incompatibility stresses. During uniaxial tensile loading, the highest local incompatibility stresses are achieved in oriented grains at the end of the elastic regime. Likewise, the effect of the β-grain morphology for realistic grain aspect ratios is seen to be weak on the overall behavior but strong on incompatibility stresses. In addition, the elastic anisotropy can have a significant influence on yield surfaces for β-forged textured polycrystals. Finally, the simulated Bauschinger stress monotonically increases with the elastic anisotropy coefficient for a random texture while it may be reduced in case of β-forged texture due to a competition between elastic and plastic sources of incompatibility stresses

Criteria for fast and selective α precipitation at β grain boundaries in Ti-alloys Consequence for in-service microstructures

International audienceThe potential for β grain boundaries (GBs) to give rise to large Widmanstätten colonies was determined through the observation of a large amount of precipitates at β GBs in a β-metastable titanium alloy using electron backscatter imaging and diffraction. The most critical boundaries are those which transform early and where a type of Variant Selection (VS) called double Burgers VS occurs. This mechanisms take place at 'special' β boundaries misoriented so that an α precipitate can be related to both grains through the Burgers relation. It was shown that the most critical GBs have a disorientation at an angle of less than 10° from 49.5°/<110> or 60°/<110>. A simulation study allowed those boundaries to be quantifed in crystallographic textures typical of industrial products. Those texture have then been discussed as a function of their potential to form large Widmanstätten colonies

Criteria for fast and selective α precipitation at β grain boundaries in Ti-alloys Consequence for in-service microstructures

International audienceThe potential for β grain boundaries (GBs) to give rise to large Widmanstätten colonies was determined through the observation of a large amount of precipitates at β GBs in a β-metastable titanium alloy using electron backscatter imaging and diffraction. The most critical boundaries are those which transform early and where a type of Variant Selection (VS) called double Burgers VS occurs. This mechanisms take place at 'special' β boundaries misoriented so that an α precipitate can be related to both grains through the Burgers relation. It was shown that the most critical GBs have a disorientation at an angle of less than 10° from 49.5°/ or 60°/. A simulation study allowed those boundaries to be quantifed in crystallographic textures typical of industrial products. Those texture have then been discussed as a function of their potential to form large Widmanstätten colonies

An ensemble learning approach for the classification of remote sensing scenes based on covariance pooling of CNN features

International audienceThis paper aims at presenting a novel ensemble learning approach based on the concept of covariance pooling of CNN features issued from a pretrained model. Starting from a supervised classification algorithm, named multilayer stacked covariance pooling (MSCP), which exploits simultaneously second order statistics and deep learning features, we propose an alternative strategy which employs an ensemble learning approach among the stacked convolutional feature maps. The aggregation of multiple learning algorithm decisions, produced by different stacked subsets, permits to obtain a better predictive classification performance. An application for the classification of large scale remote sensing images is next proposed. The experimental results, conducted on two challenging datasets, namely UC Merced and AID datasets, improve the classification accuracy while maintaining a low computation time. This confirms, besides the interest of exploiting second order statistics, the benefit of adopting an ensemble learning approach

Improvement in real time detection and selectivity of phthalocyanine gas sensors dedicated to oxidizing pollutants evaluation

International audienceA sensor microsystem prototype, using copper phthalocyanine thin film as sensitive layer, and dedicated to ozone evaluation, was developed. The methodology implemented is based on cyclic sensor recalibrations by thermal cleaning of the sensitive membrane, and on pollutant concentration quantification according to the kinetics of sensor response. Results of laboratory experiments for various NO2 and O3 concentrations, in the range of 10–200 ppb, illustrate the selectivity of CuPc sensors towards ozone, obtained by our methodology. We have shown that ozone selectivity is especially improved for short time of exposure (few minutes) and for phthalocyanine layer maintained at low temperature (80 °C). For optimal conditions, our microsystem exhibits a threshold lower than 10 ppb, a resolution lower than 10 ppb, and good reproducibility of measurements. Performances obtained in real urban atmosphere are satisfying to ensure real time evaluation of ozone during several days. Long-term stability and the detection of NO2 by associating chemical filters to our microsystem will be also discussed

An Assessment of the Workforce and Occupations in the Highway, Street, and Bridge Construction Industries in Indiana

This project explores workforce and occupations within the highway, street, and bridge construction industries (NAICS 237310) in Indiana. There are five specific deliverable comprised of three data reports, one policy document, and a website. The first data report includes an assessment of the workforce based on the eight-part framework, which are industry, occupations, job postings, hard-to-fill jobs, Classification of Instructional Programs (CIP), GAP Analysis, compatibility, and automation. The report defines a cluster followed by a detailed analysis of the occupations, skills, job postings, etc., in the NAICS 237310 industry in Indiana. The report makes use of specialized labor market databases, such as the Economic Modeling Specialists International (EMSI), CHMURA JobsEQ, etc. The analysis is based only on the jobs covered under the unemployment insurance or the Quarterly Census of Employment and Wages (QCEW) data. The second data report analyzes jobs to jobs flows to and from the construction industry in Indiana, with a particular emphasis on the Great Recession, by utilizing the Bureau of Labor Statistics (BLS) data. The third data report looks into the equal employment opportunity or Section 1391 and 1392 data for Indiana and analyzes specific characteristics of that data. The policy report includes a set of recommendations for workforce development for INDOT and a summary of the three data reports. The key data on occupations within the NAICS 237310 are provided in an interactive website. The website provides a data dashboard for individual INDOT Districts. The policy document recommends steps for development of the highways, streets and bridges construction workforce in INDOT Districts

Encodage de matrices de covariance par les vecteurs de Fisher log-euclidien : application à la classification supervisée d'images satellitaires

National audienceThis paper introduces a new hybrid architecture based on Fisher vector encoding (VF) of the convolutional layer outputs of a neural network. The originality of this work is based on the exploitation of second-order statistics via the calculation of local covariance matrices. Considering the intrinsic properties of the Riemannian manifold of covariance matrices, we propose to use the log-euclidean metric in order to extend the concept of VF encoding: the log-euclidean Fisher vectors (LE VF). The proposed architecture is then evaluated on different remote sensing databases : the UC Merced Land Use Land Cover database, the AID database, as well as on two Pléiades datasets on maritime pine forests and oyster beds.Cet article présente une nouvelle architecture hybride basée sur l'encodage par vecteurs de Fisher (VF) des sorties des couches convolutives d'un réseau de neurones. L'originalité de ce travail repose sur l'exploitation des statistiques d'ordre deux via le calcul des matrices de covariance locales. Considérant les propriétés intrinsèques à la géométrie Riemannienne propre à l'espace des matrices de covariance, nous proposons d'utiliser la métrique log-euclidienne afin d'étendre le concept des VF pour l'encodage de matrices de covariance : les vecteurs de Fisher log-euclidiens (LE VF). L'architecture proposée est ensuite évaluée sur différentes bases de données de télédétection : la base UC Merced Land Use Land Cover, la base AID, ainsi que sur deux jeux de données Pléiades sur des forêts de pins maritimes et de parcs ostréicoles

Stress partitioning in a near-β Titanium alloy induced by elastic and plastic phase anisotropies: experimental and modeling

International audienceThe load transfer induced by the elas c and plas c phase anisotropies of a Ti-10V-2Fe-3Al tanium alloy is studied. The microstructure consists in α nodules embedded in elongated β grains. EBSD performed on the alloy shows no crystallographic texture neither for α nor β phase. Tensile tests along the elonga on direc on, at a strain rate of 2 x 10-3 s-1 give a yield stress of 830 MPa with 13% duc lity. Simula ons based on an advanced two-phase polycrystalline elasto-viscoplas c self-consistent (EVPSC) model predict that the β phase first plas fies with a sequen al onset of plas city star ng from oriented β grains, then and finally oriented β grains. This leads to a strong load transfer from the β grains to the α nodules whose average behavior remains elas c up to high stresses (~940 MPa). However, addi onal simula ons considering exclusively β grains of specific orienta on show that the behavior of α nodules is strongly dependent on the β texture in which they are embedded. Especially, in β grains, which plas fy the latest, the model predicts the onset of plas city in favorably orientated α nodules. Moreover, the orienta on spread within the β grains can modify the average plas c behavior of α phase. In future, these results will be compared to data obtained from in-situ High Energy XRD and SEM/EBSD experiments

The Action Constraints of an Object Increase Distance Estimation in Extrapersonal Space

This study investigated the role of action constraints related to an object as regards allocentric distance estimation in extrapersonal space. In two experiments conducted in both real and virtual environments, participants intending to push a trolley had to estimate its distance from a target situated in front of them. The trolley was either empty (i.e., light) or loaded with books (i.e., heavy). The results showed that the estimated distances were larger for the heavy trolley than for the light one, and that the actual distance between the participants and the trolley moderated this effect. This data suggests that the potential mobility of an object used as a reference affects distance estimation in extrapersonal space. According to embodied perception theories, our results show that people perceive space in terms of constraints related to their potential actions

BMC Nephrol

An amendment to this paper has been published and can be accessed via the original article