Séminaire

Séminaire Du 10 juin 2024 au 14 juin 2024

Saint-Martin-d'Hères - Domaine universitaire

The sodium salt of carboxymethylcellulose (NaCMC) is a water-soluble derivative of cellulose, which is broadly used for industrial applications such as food, pharmaceuticals, paints, etc., and serves as a thickener and water retention. The properties of NaCMC can be exquisitely tuned via their degree of substitution (DS), which corresponds to the average number of carboxymethyl groups per repeating glucose unit and varies between 0 and 3. Highly substituted polymers, i.e., for DS >1, are hydrophilic and disperse easily in water, yielding rheological features typical of polyelectrolyte solutions. In contrast, weakly substituted polymers, i.e., for DS<0.9, contain hydrophobic regions, which favor interchain aggregation and the formation of so-called ``fringed micelles'' yielding thixotropic and even gel-like properties at high enough concentrations. Here we show that gelation of NaCMC solution can be induced by lowering the pH, which decreases the charge density along the CMC chain and promotes the formation of multichain aggregates.

• En savoir plus sur Thibaut Divoux

Séminaire Équipe Géomécanique Le 14 juin 2024

Saint-Martin-d'Hères - Domaine universitaire

The lecture focuses on the use of advanced centrifuge modeling to enhance the understanding of offshore structures behavior. The example chosen is the torpedo pile used to anchor FPSO platforms in marine clay soils in deep water environment. The presentation compares the performance of vertical and inclined torpedo anchors, as well as torpedo clusters with varying spacing. The results of vertical pullout tests are also compared with API recommendations.

• En savoir plus sur Márcio de Souza Soares de Almeida

Séminaire Du 10 juin 2024 au 14 juin 2024

Saint-Martin-d'Hères - Domaine universitaire

The lecture focuses on the use of advanced physical modeling to enhance the understanding of offshore structure behavior. The example chosen is the monopile foundations for wind farms. The results of monotonic loading tests are presented and measured p-y curves are compared with API recommendations. In addition, the results of 100.000 cyclic loading tests are shown, with emphasis on the variation of stiffness and natural frequency with the number of cycles.

• En savoir plus sur Maria Cascão Ferreira de Almeida

Séminaire Le 2 février 2024

Charged polymers or polyelectrolytes (PEs) are ubiquitous. The conformations
of highly charged PEs are influenced by a combination of factors, including
long-range electrostatic interactions, solvent quality, temperature, counterion
valency, and dielect ric constant of the solvent. In this seminar, we will discuss
the impact of attractive neutral crowders on the conformations of a single,
similarly charged PE in the presence of oppositely charged counterions. Us-
ing extensive molecular dynamics simulations utilizing generic coarse-grained
bead–spring models, we identify three distinct phases: (1) the CCI phase
(Charged Collapsed due to Intra-polymer interactions), which corresponds to a
collapsed state primarily driven by the condensation of counterions; (2) the CE
phase (Charged Extended), characterized by an extended conformation of the
polymer due to repulsive electrostatic interactions within the PE; and (3) the
CCB phase (Charged Collapsed due to Bridging interactions), representing a
secondary collapsed state primarily induced by the presence of attractive bridg-
ing crowders, with a substantial number of crowders located within the col-
lapsed conformation. By identifying the phase transitions among these phases,
we obtain the phase diagram in the PE charge density and polymer–crowder
interaction phase space for monovalent, divalent, and trivalent counterions. Our simulations reveal that the interaction with
crowders can induce collapse, despite the presence of strong repulsive electrostatic interactions, and can replace condensed coun-
terions to facilitate a direct transition from the CCI and CE phases to the CCB phase.

• En savoir plus sur Kamal Tripathi

Séminaire Équipe Géomécanique Le 8 décembre 2023

Bio-cementation soil improvement methods are alternatives to invasive, carbon-intensive stabilisation techniques. These methods, which include microbially induced carbonate precipitation (MICP) and enzyme induced carbonate precipitation (EICP), use biogeochemical processes to drive carbonate precipitation and cement soil grains, thereby improving the material mechanical performance. Sands treated by bio-cementation methods typically exhibit an improvement in strength and stiffness, yet often with variable magnitudes, even at equal calcium carbonate contents. The variation in the mechanical performance of bio-cemented sands impedes the practical applications of MICP/ EICP, while it is poorly understood. In this presentation, we are going to understand the mechanical behaviour of bio-cemented sands, particularly the uncertainty or variation of the mechanical performance, from the microscopic point of view by using the discrete element method (DEM).

• En savoir plus sur Zhang Aoxi

Séminaire Équipe CoMHet Le 19 janvier 2024

Molecular dynamics simulations are ubiquitous in materials science, from drug discovery to design of advanced structural nanocomposites. Owing to the high-resolution of these simulations taking place at the atomic scale, predictions give access to data often complementary to experiments; be it characterisation of the nanostructure or even sophisticated instrumentation. I will begin the talk introducing the fundamentals of setting up molecular models and dynamics simulations to investigate the mechanics of materials. I will illustrate these aspects focusing on the collagen, the structural protein of choice in the human body and more largely the animal kingdom. I will present our recent investigations on the influence of hydration on the assembly of collagen microfibrils and the complex water dynamics within, trying to draw conclusions on the mechanical properties of the biopolymer.

While being quite popular, molecular dynamics simulations have several limitations (force field precision, ergodicity). Among these, the spectrum of spatiotemporal scales integrated within a simulation is extremely limited. This is particularly problematic when mechanical properties are of interest, as these emerge from the combination of scales ranging from the nanoscale (chemistry) to the macroscale (processing, testing). Unlike real-life experiments, all scales cannot be resolved simultaneously using computer simulations. I will give an overview of the existing multiscale simulation strategies: from rather cheap hierarchical to expensive concurrent approaches. I will illustrate their applicability with examples from my past research on the fracture of concrete under seismic loading and the dynamic behaviour of impacted shells of epoxy-graphene nanocomposites.

• En savoir plus sur Maxime Vassaux

Séminaire Le 5 octobre 2023 Accurate models for the behaviour of materials are of fundamental importance in material science and mechanics. Traditionally, these models are derived from first principles (thermodynamics) and fine-tuned using heuristic/empirical methods to ensure calibration over experiments. However, heuristic constitutive modelling can fall short in describing the behaviour of complex materials that display path-dependent behaviours and possess multiple inherent scales, e.g. metamaterials, geomaterials, and biomaterials.
In recent years, the advent of Machine Learning, fuelled by a continuously increasing flow of data, has provided promising solutions to address the limitations of traditional constitutive modelling. Here, we present the Thermodynamics-based Artificial Neural Networks (Masi et al. 2021; Masi and Stefanou, 2022), which embed the fundamental laws of thermodynamics directly into their structure, thus ensure thermodynamically consistent predictions.

This talk mainly focuses on two major issues: (1) the non trivial identification of representative material state variables (Masi and Stefanou, 2023)—an essential ingredient in non-equilibrium thermodynamics—and (2) the shortcoming of ML in dealing with small data, i.e. limited and sparse material data sets (Masi and Einav, 2023). The capabilities of the methodology are demonstrated for the constitutive modelling of several complex, multiscale materials, displaying inelastic behaviour, path- and rate-dependency.
 

• F. Masi, I. Stefanou, P. Vannucci, V. Maffi-Berthier (2021). Thermodynamics-based Artificial Neural Networks for constitutive modeling. J Mech Phys Solids 147, 104277. doi: 10.1016/j.jmps.2020.104277.
• F. Masi, I. Stefanou (2022a). Multiscale modeling of inelastic materials with Thermodynamics-based Artificial Neural Networks (TANN), Comput Methods Appl Mech Eng 398, 115190. doi: 10.1016/j.cma.2022.115190.
• F. Masi, I. Stefanou (2023). Evolution TANN and the identification of internal variables and evolution
• equations in solid mechanics, J Mech Phys Solids 174, 105245. doi: 10.1016/j.jmps.2023.105245.
• F. Masi, I. Einav (2023). Neural differential constitutive equations for small data. Under preparation.

• En savoir plus sur Filippo Masi

Séminaire Équipe Géomécanique Le 4 mai 2023

Identifying governing equations from data and solving them to acquire spatio-temporal responses is desirable, yet highly challenging, for many practical problems. Machine learning (ML) has emerged as an alternative to influence knowledge discovery in complex geotechnical processes. To demonstrate feasibility, this study develops an ML-assisted data-driven approach to automatically recover Terzaghi’s consolidation theory from measured data and obtain the corresponding solutions. This process incorporates several algorithms including sparse regression and prior information based neural network (PiNet), transformed weak-form partial differential equations (PDEs) (to reduce sensitivity to noisy measurement), and Monte Carlo dropout to achieve a measure of prediction uncertainty. The results indicate that consolidation PDEs can be accurately extracted using the proposed approach which is also shown to be robust to noisy measurements. PDEs solved by PiNet are also shown to provide excellent agreement with actual results thus highlighting its potential for inverse analysis. The proposed approach is generic and provides an auxiliary method to verify heuristic interpretations of data or to directly identify patterns and obtain solutions without the need for expert intervention.

• En savoir plus sur Zhang Pin

Séminaire Le 27 avril 2023 L’objectif de cet exposé est de présenter quelques résultats sur la formalisation géométrique des milieux discrets. On s’attachera  à décrire la nature géométrique (ou intrinsèque) des objets intervenant dans l’écriture des lois de comportements des milieux discrets ainsi que de l’évolution incrémentale de tels milieux. Nous présenterons tout d’abord un aperçu historique des questions sous jacentes, aperçu qui  permettra de comprendre des motivations de ces développements. Ensuite selon le temps disponible nous avancerons dans la description géométrique des différents objets impliqués dans les lois et évolutions incrémentales: forces, déformations, taux de déformations, stabilité, élasticité, hyperélasticité, hypoélasticité, etc. 

• En savoir plus sur Jean Lerbet

Séminaire Le 23 février 2023

The mechanism with which cells measure the dimension of the organ in which they are embedded, and slow down their growth when the final size is reached, is a long-standing problem in developmental biology. Feedback loops between growth and mechanical stress are increasingly believed to be important. In this presentation, I will introduce the concept of morphoelasticity as a standard continuum framework for modelling growing elastic tissues and provide insight into the feedback loops between growth and stress by considering simple 1D and 2D examples, such as a spring growing against a passive medium. However, without additional variables, the classical morphoelasticity theory often leads to either a collapse or unbounded growth of the tissue and prohibits reaching a finite asymptotic size. To address this issue, I will show how to modify the classical setting by including an energetic cost associated with growth, leading to the physical effect of size control.

These ideas will be applied to a specific system of a multicellular spheroid growing against the pressure of a medium in which it is embedded. The present model provides a qualitatively correct residual stress profile and has a naturally emerging necrotic core, both of which have been established experimentally in multicellular spheroids, and could be a step towards a better understanding of the role of mechanics in growing biological tissues.

 

• En savoir plus sur Alexander Erlich