Activity Reports

Overall objectives

Elan is a young research team of Inria and Laboratoire Jean Kuntzmann (UMR 5224), with an original positioning across Computer Graphics and Computational Mechanics. The team is focussed on the design of predictive, robust, efficient, and controllable numerical models for capturing the shape and motion of visually rich mechanical phenomena, such as the buckling of an elastic ribbon, the flowing of sand, or the entangling of large fiber assemblies. Target applications encompass the digital entertainment industry (e.g., feature film animation, special effects), as well as virtual prototyping for the mechanical engineering industry (e.g., aircraft manufacturing, cosmetology); though very different, these two application fields require predictive and scalable models for capturing complex mechanical phenomena at the macroscopic scale. An orthogonal objective is the improvement of our understanding of natural physical and biological processes involving slender structures and frictional contact, through active collaborations with soft matter physicists. To achieve its goals, the team strives to master as finely as possible the entire modeling pipeline, involving a pluridisciplinary combination of scientific skills across Mechanics and Physics, Applied Mathematics, and Computer Science.

Radar (from 2021)

Raweb (until 2020)

New results

Nonsmooth simulations of 3D Drucker-Prager granular flows and validation against experimental column collapses

In collaboration with Gauthier Rousseau (TU Wien, formerly post-doc in the team), Hugo Rousseau (INRAE) and Gilles Daviet (NVIDIA, formerly PhD student in the team), we have performed thorough comparisons between the predictions of our numerical solver Sand6 for granular flows 7.1.2, and collapse experiments conducted in a narrow channel (in collaboration with EPFL). We have shown that our nonsmooth simulator, which relies on a constant friction coefficient corresponding to the yield angle of a granular heap, is able to reproduce with high fidelity various experimental granular collapses over inclined erodible beds. Our results, obtained for two different granular materials and for various bed inclinations, suggest that a simple constant friction rheology choice remains reasonable for capturing a large variety of unsteady granular flows at low inertial number. Using the versatility of our numerical approach, we have further analysed the possible biases pertaining to laboratory-scale experiments, and shown that, in the case of granular collapses, accurate predictions could be performed as long as care was taken in measuring yield angle of the granular material appropriately. This study has been submitted for publication 15.

Randomly stacked open-cylindrical shells as a functional mechanical device

In collaboration with Tomohiko Sano (Keio University), we have studied the mechanical behaviour of open cylindrical shells, randomly stacked in 2D configurations. Using both numerical simulations (relying on our validated curvature-based fibre model with non-smooth frictional contact 7) and experiments, we have shown that despite the randomness of the configurations, the stacked shells exhibit robust macroscopic dissipative properties, involving complex interplay between elasticity and friction, which control the occurrence of snap-fit events at the micro-scale. Our results demonstrate that the rearrangement of flexible components could yield versatile but predictive mechanical responses, paving the way to new kinds of metamaterials. These results have been presented at the ESMC 2022 international conference 13 and submitted for publication  43.

Estimation of friction coefficients in cloth

Following our work on the estimation of friction between a cloth sample and a substrate, we have published, in collaboration with Haroon Rasheed (former PhD student of the team), Stefanie Wuhrer (EPI Morphéo), Jean-Sébastien Franco (EPI Morphéo) and Arnaud Lazarus (Sorbonne Université), the extension to cloth-to-cloth friction estimation in the journal IEEE PAMI 8. The method relies on a neural network trained only on simulated data (yielded by our cloth simulator Argus), after a careful validation of the simulator. From this trained network, we were able to predict on a real experiment both the material class of the cloth samples as well as the friction coefficient at the interplay, with a good level of prediction.

The latter paper, where we have evidenced the influence of the predictibility of the simulator on the accuracy of the network, also marked a turning point in our research interests, as now we consider the physical validation of numerical models as a major research axis in the Elan team.

Lateral Indentation of a Thin Elastic Film.

In collaboration with Enrique Cerda, Eugenio Hamm, from Universidad de Santiago de Chile, and Miguel Trejo from Universidad de Buenos Aires, we published a paper 9 where we present an experimental setup for testing thin-film materials by studying the lateral indentation of a narrow opening cut into a film, triggering a cascade of buckling events. We showed that the force response F is dominated by bending and stretching effects for small displacements and slowly varies with indenter displacement Fd2/5 , to finally reach a wrinkled state that results in a robust nonlinear asymptotic relation, Fd4 . We present experiments with films of various thicknesses and material properties, and numerical simulations to confirm our analysis defining an order parameter that accounts for the different response regimes observed in experiments and simulations.

Simulation of printed-on-fabric assemblies.

In collaboration with Mélina Skouras (EPI Anima), David Jourdan, Adrien Bousseau (EPI GraphDeco), and Etienne Vouga (University of Texas at Austin), we have published  10.

Printing-on-fabric is an affordable and practical method for creating self-actuated deployable surfaces: thin strips of plastic are deposited on top of a pre-stretched piece of fabric using a commodity 3D printer. We present a new simulation method to obtain the rest shape of such structures. To obtain meaningful results, we have to properly estimate the mechanical behaviour of both, the fabric we use and the printing plastic. We perform cyclic traction measurement in spandex, material used for our validation, in different directions to characterize its anisotropy and disipative properties. We also use the cantiliver experiment for studying the bending behavior and obtain coherent value with that from the traction test. Finally we perform traction test for the printing plastic. We validate our model by comparing the output of our simulations with physical realizations of printed patterns on spandex.

Frictional three-point bending test: disentangling the role of friction through real and numerical experiments

In collaboration with Joël Marthelot, Ignacio Andrade-Silva and Olivier Pouliquen (IUSTI, Aix Marseille Université), we have investigated the role of friction in the well-known three-point bending test, traditionally used to measure the bending modulus of slender structures. By performing experiments and numerical simulations, both compared to our new theoretical model, we have devised an efficient protocol to disentangle the respective roles of elasticity and friction in the force response of an indented rod lying on frictional supports, thereby allowing accurate and independent measurements of both the bending modulus and the friction coefficient of the considered material. This work has been presented at the ESMC 2022 international conference 12, and an article is in preparation.


The ELAN team is involved, since 2015, in the ERC Starting Grant GEM. Within this project, several national and international collaborations have been set up, among which:

  • Inria teams MORPHEO and IMAGINE
  • Institut Jean le Rond d’Alembert (Paris)
  • OLM Digital (Japan)

The team is also involved in a long-term partnership with the University of Minnesota (USA) and IIT Delhi (India), and in several industrial collaborations in the fields of mechanical engineering and the feature film industry.

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