A fretting crack initiation prediction taking into account the surface roughness and the crack nucleation process volume

This paper presents an experimental study of the fretting crack nucleation threshold, expressed in terms of loading conditions, with a cylinder/plane contact. The studied material is a damage tolerant aluminium alloy widely used in the aerospace application. Since in industrial problems, the surface quality is often variable, the impact of a unidirectional roughness is investigated via varying the roughness of the counter body in the fretting experiments. As expected, experimental results show a large effect of the contact roughness on the crack nucleation conditions. Rationalisation of the crack nucleation boundary independently of the studied roughnesses was successfully obtained by introducing the concept of effective contact area. This does show that the fretting crack nucleation of the studied material can be efficiently described by the local effective loadings inside the contact. Analytical prediction of the crack nucleation is presented with the Smith-Watson-Topper (SWT) parameter and size effect is also studied and discussed.Comment: 21 figure

A Smoothing Stochastic Phase Retrieval Algorithm for Solving Random Quadratic Systems

A novel Stochastic Smoothing Phase Retrieval (SSPR) algorithm is studied to reconstruct an unknown signal x ¿ ¿ n or Cn from a set of absolute square projections y k = |¿a k ; x¿| 2 . This inverse problem is known in the literature as Phase Retrieval (PR). Recent works have shown that the PR problem can be solved by optimizing a nonconvex and non-smooth cost function. Contrary to the recent truncated gradient descend methods developed to solve the PR problem (using truncation parameters to bypass the non-smoothness of the cost function), the proposed algorithm approximates the cost function of interest by a smooth function. Optimizing this smooth function involves a single equation per iteration, which leads to a simple scalable and fast method especially for large sample sizes. Extensive simulations suggest that SSPR requires a reduced number of measurements for recovering the signal x, when compared to recently developed stochastic algorithms. Our experiments also demonstrate that SSPR is robust to the presence of additive noise and has a speed of convergence comparable with that of state-of-the-art algorithms

Parallel computation of entries of A-1

In this paper, we are concerned about computing in parallel several entries of the inverse of a large sparse matrix. We assume that the matrix has already been factorized by a direct method and that the factors are distributed. Entries are efficiently computed by exploiting sparsity of the right-hand sides and the solution vectors in the triangular solution phase. We demonstrate that in this setting, parallelism and computational efficiency are two contrasting objectives. We develop an efficient approach and show its efficacy by runs using the MUMPS code that implements a parallel multifrontal method

Seismicity triggered by fluid injection–induced aseismic slip

Anthropogenic fluid injections are known to induce earthquakes. The mechanisms involved are poorly understood, and our ability to assess the seismic hazard associated with geothermal energy or unconventional hydrocarbon production remains limited. We directly measure fault slip and seismicity induced by fluid injection into a natural fault. We observe highly dilatant and slow [~4 micrometers per second (µm/s)] aseismic slip associated with a 20-fold increase of permeability, which transitions to faster slip (~10 µm/s) associated with reduced dilatancy and micro-earthquakes. Most aseismic slip occurs within the fluid-pressurized zone and obeys a rate-strengthening friction law µ = 0.67 + 0.045ln (v/v_0) with v_0 = 0.1 µm/s. Fluid injection primarily triggers aseismic slip in this experiment, with micro-earthquakes being an indirect effect mediated by aseismic creep

Simulation par éléments finis de la déformation de polycristaux à partir d'images de tomographie par contraste de diffraction

National audienceLa tomographie par contraste de diffraction donne accès à la forme, l'orientation et l'état de déformation élastique des grains dans des volumes polycristallins pouvant contenir à l'heure actuelle jusqu'à mille grains. La combinaison de cette technique avec la méthode des éléments finis est particuliè- rement prometteuse pour analyser le rôle de la cristallographie locale sur les mécanismes de déformation et de dégradation dans des matériaux polycristallins. Dans ce travail, un échantillon polycristallin de titane est imagé en 3D puis maillé et sa déformation de traction est calculée par éléments finis.See http://hal.archives-ouvertes.fr/docs/00/59/29/18/ANNEX/r_974AO844.pd

Modeling 1D distributed-memory dense kernels for an asynchronous multifrontal sparse solver

To solve sparse systems of linear equations, multifrontal methods rely on dense partial LU decompositions of so-called frontal matrices; we consider a parallel asynchronous setting in which several frontal matrices can be factored simultaneously. In this context, to address performance and scalability issues of acyclic pipelined asynchronous factorization kernels, we study models to revisit properties of left and right-looking variants of partial $LU$ decompositions, study the use of several levels of blocking, before focusing on communication issues. The general purpose sparse solver MUMPS has been modified to implement the proposed algorithms and confirm the properties demonstrated by the models

The grain microstructure of polycrystalline materials as revealed by the combined use of synchrotron X-ray imaging and diffraction techniques

National audienceCombining the principles of x-ray imaging and diffraction techniques, it has recently become possible to map the 3D grain microstructure in a range of polycrystalline materials. Associating this 3D orientation mapping with conventional attenuation and/or phase contrast tomography yields a non-destructive characterization technique, enabling time-lapse observation of dynamic processes in the bulk of structural materials. The capabilities and limitations., as well as future perspectives of this new characterization approach will be discussed and illustrated on selected application examples

Characterization of polycrystalline materials by X-ray diffraction contrast tomography

National audienceSynchrotron based X-ray imaging and diffraction techniques offer interesting possibilities for characterizing the grain microstructure in a variety of polycrystalline mono-and multiphase materials. Direct visualization of the three-dimensional grain boundary network or of two-phase (duplex) grain structures by means of absorption and/or phase contrast techniques is possible, but restricted to specific material systems (Ludwig 2009b). However, conventional attenuation or phase contrast imaging techniques do not give access to the crystallographic orientation of the grains and additional diffraction measurements are required. On the other hand, three-dimensional X-ray diffraction methods like Differential Aperture X-ray Microscopy (DAXM, (Larson, 2002) or 3D X-ray Diffraction Microscopy (3DXRD) (Poulsen, 2004) can analyse the 3D grain structure and/or elastic strain tensors of individual grains in polycrystalline materials, but are blind to the microstructural features (inclusions, cracks and porosity) visible in attenuation and/or phase contrast imaging techniques . A recent extension of the 3DXRD methodology, termed X-ray diffraction contrast tomography (DCT) (Ludwig 2009a), combines the principles of 3DXRD and X-ray absorption tomography. With a single scan, DCT can provide simultaneous access to the grain shape, crystallographic orientation, full elastic strain tensor and the local attenuation coefficient distribution in three dimensions. The technique applies to a range of plastically undeformed, polycrystalline mono-phase materials, fulfilling some conditions on grain size and texture. The straightforward combination with in-situ microtomographic observations opens interesting new possibilities for the characterization of microstructure related damage and deformation mechanisms in these materials

Transcriptomic analysis of the exit from dormancy of Aspergillus fumigatus conidia

<p>Abstract</p> <p>Background</p> <p>Establishment of aspergillosis is depending upon the exit from dormancy and germination of the conidia of <it>Aspergillus fumigatus </it>in the lung. To gain an understanding of the molecular mechanisms underlying the early steps of conidial germination, we undertook a transcriptomic analysis using macroarrays constructed with PCR fragments from > 3,000 genes (around one third of the annotated <it>A</it>. <it>fumigatus </it>genome).</p> <p>Results</p> <p>Major results of this analysis are the following: (i) conidia stored pre-packaged mRNAs transcripts (27% of genes have transcripts in the resting conidia; (ii) incubation at 37°C in a nutritive medium induced up- and down-regulation of genes: 19% of the total number of genes deposited on the array were up-regulated whereas 22% of the genes with pre-packaged mRNA in the resting conidia were down-regulated; (iii) most modifications were seen during the first 30 min of germination whereas very little modification of gene expression occurred during the following hour; (iv) one-year old conidia and one-week old conidia behaved similarly at transcriptional level.</p> <p>Conclusion</p> <p>Transcriptomic data indicate that the exit from dormancy is associated with a shift from a fermentative metabolism to a respiratory metabolism as well as a trend toward immediate protein synthesis.</p

Robust memory-aware mappings for parallel multifrontal factorizations

International audienceWe study the memory scalability of the parallel multifrontal factorization of sparse matrices. In particular, we are interested in controlling the active memory specific to the multifrontal factorization. We illustrate why commonly used mapping strategies (e.g., the proportional mapping) cannot provide a high memory efficiency, which means that they tend to let the memory usage of the factorization grow when the number of processes increases. We propose “memory-aware” algorithms that aim at maximizing the granularity of parallelism while respecting memory constraints. These algorithms provide accurate memory estimates prior to the factorization and can significantly enhance the robustness of a multifrontal code. We illustrate our approach with experiments performed on large matrices