When attempting to build mesoscale geometric models of woven reinforcements in composites based on X-ray microtomography data, we frequently run into ambiguous situations due to noise, particularly in contact zones between fiber tows, resulting in inadmissible cross-sectional shapes. We propose here a custom-built shape-manifold approach based on kernel PCA, k-means classification and Diffuse Approximation to identify, “repair” such badly segmented shapes in the feature space, and finally recover admissible shapes in the original space.
Accepted:
Published online:
Anna Madra 1; Piotr Breitkopf 2; Balaji Raghavan 3; François Trochu 4
@article{CRMECA_2018__346_7_532_0, author = {Anna Madra and Piotr Breitkopf and Balaji Raghavan and Fran\c{c}ois Trochu}, title = {Diffuse manifold learning of the geometry of woven reinforcements in composites}, journal = {Comptes Rendus. M\'ecanique}, pages = {532--538}, publisher = {Elsevier}, volume = {346}, number = {7}, year = {2018}, doi = {10.1016/j.crme.2018.04.008}, language = {en}, }
TY - JOUR AU - Anna Madra AU - Piotr Breitkopf AU - Balaji Raghavan AU - François Trochu TI - Diffuse manifold learning of the geometry of woven reinforcements in composites JO - Comptes Rendus. Mécanique PY - 2018 SP - 532 EP - 538 VL - 346 IS - 7 PB - Elsevier DO - 10.1016/j.crme.2018.04.008 LA - en ID - CRMECA_2018__346_7_532_0 ER -
%0 Journal Article %A Anna Madra %A Piotr Breitkopf %A Balaji Raghavan %A François Trochu %T Diffuse manifold learning of the geometry of woven reinforcements in composites %J Comptes Rendus. Mécanique %D 2018 %P 532-538 %V 346 %N 7 %I Elsevier %R 10.1016/j.crme.2018.04.008 %G en %F CRMECA_2018__346_7_532_0
Anna Madra; Piotr Breitkopf; Balaji Raghavan; François Trochu. Diffuse manifold learning of the geometry of woven reinforcements in composites. Comptes Rendus. Mécanique, Volume 346 (2018) no. 7, pp. 532-538. doi : 10.1016/j.crme.2018.04.008. https://comptes-rendus.academie-sciences.fr/mecanique/articles/10.1016/j.crme.2018.04.008/
[1] Stochastic characterisation methodology for 3-D textiles based on micro-tomography, Compos. Struct., Volume 173 (2017), pp. 44-52 | DOI
[2] Quantification of the internal structure and automatic generation of voxel models of textile composites from X-ray computed tomography data, Composites, Part A, Appl. Sci. Manuf., Volume 69 (2015), pp. 150-158 | DOI
[3] Image-based model reconstruction and meshing of woven reinforcements in composites, Int. J. Numer. Methods Eng., Volume 112 (2017) no. 9, pp. 1235-1252 | DOI
[4] An efficient k-means clustering algorithm: analysis and implementation, IEEE Trans. Pattern Anal. Mach. Intell., Volume 24 (2002) no. 7, pp. 881-892 | arXiv | DOI
[5] kPCA-based parametric solutions within the PGD framework, Arch. Comput. Methods Eng., Volume 25 (2018) no. 1, pp. 69-86 | DOI
[6] Level Set Methods and Dynamic Implicit Surfaces, Springer, New York, 2003
[7] On lines and planes of closest fit to systems of points in space, Philos. Mag., Volume 2 (1901) no. 6, pp. 559-572
[8] A bi-level meta-modeling approach for structural optimization using modified pod bases and diffuse approximation, Comput. Struct., Volume 127 (2013), pp. 19-28 | DOI
[9] Nonlinear component analysis as a kernel eigenvalue problem, Neural Comput., Volume 10 (1998), pp. 1299-1319
[10] Numerical material representation using proper orthogonal decomposition and diffuse approximation, Appl. Comput. Math., Volume 224 (2013), pp. 450-462 | DOI
[11] Generalizing the finite element method: diffuse approximation and diffuse elements, Comput. Mech., Volume 10 (1992), pp. 307-318
[12] Explicit form and efficient computation of MLS shape functions and their derivatives, Int. J. Numer. Methods Eng., Volume 48 (2000) no. 3, pp. 451-466 | DOI
[13] Towards simultaneous reduction of both input and output spaces for interactive simulation-based structural design, Comput. Methods Appl. Mech. Eng., Volume 265 (2013), pp. 174-185 | DOI
[14] Implicit constraint handling for shape optimisation with pod-morphing, Eur. J. Comput. Mech., Volume 21 (2012) no. 3–6, pp. 325-336 | DOI
[15] An objective meta-modeling approach for indentation-based material characterization, Mech. Mater., Volume 107 (2017), pp. 31-44 | DOI
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