299 research outputs found
Appel nullité. Ordonnance du président du Tribunal de commerce refusant de procéder à la désignation d'un arbitre, Excès de pouvoir, Délai pour agir, Droit commun (non), Délai prévu en matière de contredit
No full textInternational audience(Cass. 2e civ., Bull. civ. II, n° 20, p. 13 ; Rev. arb. 1998. 113, note A. Hory, Consorts Bailly c/ Sté Ets H. Binetruy
Damage prediction for 3D woven composite structural features
No full text3D woven composites are becoming increasingly popular for use in structural applications. For effective use in design, predictive analysis tools are required to estimate stiffness and strength. The Domain Superposition Technique (DST) has been developed to allow prediction of 3D woven mechanical properties using models of reduced size compared to standard finite element analysis. This allows geometries of greater size than standard unit cell dimensions to be analysed. In particular, methods for including failure mechanisms in the analysis have been developed, thus allowing predictions of strength for structural features manufactured from 3D woven composites to be performed.</p
Yukawa textures with an anomalous horizontal abelian symmetry
No full textThe observed hierarchy of quark and lepton masses and mixings may be obtained by adding an abelian family symmetry to the Minimal Supersymmetric Model and coupling quarks and leptons to an electroweak singlet scalar field. In a large class of such models, this symmetry suffers from anomalies which must be compensated by the Green-Schwarz mechanism; this in turn fixes the electroweak mixing angle to be sin{sup 2}{theta}{sub W} = 3/8 at the string scale, without any assumed GUT structure. The analysis is extended to two distinct generalizations of the Standard Model: neutrino masses and mixings and R-parity violating interactions. (author). 31 refs., 2 tabs
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Supersymmetry Breaking and Weakly Vs. Strongly Coupled String Theory
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Automated generation of labeled synthetic training data for machine learning based segmentation of 3D-woven composites
No full textA novel pipeline for the generation of synthetic tomograms of woven composite materials, to be used for training of machine learning based segmentation algorithms is presented. The pipeline is completely based on open source software and heavily utilizes the graphical processing unit for fast data generation. The proposed method generates a surface mesh of the woven geometry, scans it, reconstructs the scan, and generates a voxel labeling of the generated tomogram. It is demonstrated that the method can generate images that show good agreement with experimentally produced x-ray computed tomography images of a 3D-woven carbon fiber reinforced polymer composite
Compressive failure predictions for carbon fiber-reinforced composites: A comparative study between imaging modalities
No full textWe compare compressive strength predictions for carbon fiber-reinforced composites based on different imaging modalities. We use X-ray computed tomography and optical microscopy for acquiring 3D and 2D images, respectively. Based on the acquired images, the fiber orientation distribution is estimated and used as input for 2D and 3D finite element models of both imaging modalities. Subsequently, the four model predictions are compared with experimental data to quantify their capabilities in terms of stiffness and strength. All models predict compressive failure associated with kink band formation near areas with a high degree of fiber misalignment. The 3D models predict a stiffness within one standard deviation of the experimental results but with significantly higher strength. We argue that the strength prediction shows a potential, as the measured strength is limited by load introduction failure. The 2D models predict a stiffness 4-7% higher than the 3D models. The strength predictions are similar to the measured strengths but 32-48% lower than the prediction based on 3D X-ray μCT. The discrepancy between strength predictions shows that a simple 2D approach is too limited for the investigated composite and that 3D models based on more advanced imaging modalities are required to accurately predict compressive failure
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