Stem cell mechanical behaviour modelling: substrate’s curvature influence during adhesion

Recent experiments hint that adherent cells are sensitive to their substrate curvature. It is already well known that cells behaviour can be regulated by the mechanical properties of their environment. However, no mechanisms have been established regarding the influence of cell-scale curvature of the substrate. Using a numerical cell model, based on tensegrity structures theory and the non-smooth contact dynamics method, we propose to investigate the mechanical state of adherent cells on concave and convex hemispheres. Our mechanical cell model features a geometrical description of intracellular components, including the cell membrane, the focal adhesions, the cytoskeleton filament networks, the stress fibres, the microtubules, the nucleus membrane and the nucleoskeleton. The cell model has enabled us to analyse the evolution of the mechanical behaviour of intracellular components with varying curvature radii and with the removal of part of these components. We have observed the influence of the convexity of the substrate on the cell shape, the cytoskeletal force networks as well as on the nucleus strains. The more convex the substrate, the more tensed the stress fibres and the cell membrane, the more compressed the cytosol and the microtubules, leading to a stiffer cell. Furthermore, the more concave the substrate, the more stable and rounder the nucleus. These findings achieved using a verified virtual testing methodology, in particular regarding the nucleus stability, might be of significant importance with respect to the division and differentiation of mesenchymal stem cells. These results can also bring some hindsights on cell migration on curved substrates

Large-Scale Molecular Dynamics Elucidates the Mechanics of Reinforcement in Graphene-Based Composites

Using very large-scale classical molecular dynamics we examine the mechanics of nano-reinforcement of graphene-based nanocomposites. Our simulations show that significant quantities of large, defect-free and predominantly flat graphene flakes are required for successful enhancement of materials properties in excellent agreement with experimental and proposed continuum shear-lag theories. The critical length for enhancement is approximately 500nm and 300nm for graphene and GO respectively. The reduction of Young's modulus in GO results in a much smaller enhancement of the composite's Young's modulus. The simulations reveal that the flakes should be aligned and planar for optimal reinforcement. Undulations substantially degrade the enhancement of materials properties

Comportement mécanique des matériaux quasi-fragiles sous sollicitations cycliques : de l’expérimentation numérique au calcul de structures.

Macroscopic mechanical behavior models are developed for their light computational costs, allowing the simulation of large structural elements, and the precise description of mechanical phenomena observed by the material at lower scales. Such constitutive models are here developed in the seismic solicitation framework, therefore implying cyclic alternate loadings at the material scale, and applied to civil engineering buildings, often made of concrete, or more generally of quasi-brittle materials. To date, macroscopic models applicable to structural computations, while representing the cyclic mechanical behavior are rare. In consequence of the intricacy of the fracture processes to homogenize, macroscopic constitutive models either do not present sufficient robustness or miss on important phenomena. One of the limitations to the resolution of this issue is the lack of experimental data. Indeed, because of the complexity of the experiments to set up, few results on alternate cyclic tests on concrete are available in the literature.A virtual testing approach has therefore been established on a microscopic model of the material, able to provide results needed to the formulation and the calibration of a macroscopic model. In the microscopic model, the material is considered as structure itself, it is developed so as to only necessitate a reduced amount of results from controlled experimental tests, in order to be used. The microscopic model, a lattice discrete element model, has been developed on the basis of an existing lattice model and extended to the simulation of multi-axial and cyclic loadings. The microscopic model has then been validated as a virtual testing tool and used to establish equations of the macroscopic model, on the basis of damage and plasticity theories. The consistency of the proposed constitutive relation, embedding progressive unilateral effect, has been achieved using non-linear elasticity. The macroscopic model has finally been calibrated, entirely with the microscopic model, and employed to simulate the response of a reinforced concrete wall under alternate shear loading. This simulation has served to showcase the numerical robustness of the proposed model, as well as the significant contribution of the uni-axial alternate behavior of concrete to the structural damping of such structures.Les modèles de comportement mécanique, dits macroscopiques, sont développés à la fois pour leur légèreté, permettant le calcul d’éléments structuraux pouvant atteindre d’importantes dimensions, et pour leur finesse de représentation des phénomènes mécaniques observés par le matériau à des échelles plus fines. Le développement de tels modèles est ici effectué dans le cadre de la sollicitation sismique, donc des chargements cycliques alternés, appliquée à des ouvrages en matériaux quasi-fragiles, et plus précisément en béton. À ce jour, les modèles macroscopiques, effectivement applicables au calcul de structures, et représentatifs du comportement cyclique du béton sont encore rares. En conséquence de la complexité du problème de fissuration à homogénéiser, les modèles macroscopiques existants affichent une robustesse limitée ou ne permettent pas de reproduire l’ensemble des phénomènes mécaniques observés par le matériau. Une des barrières à la résolution de ces deux problématiques est le manque de données expérimentales relatives aux phénomènes à modéliser. En effet, en cause de la difficulté technique de les réaliser, peu de résultats d’essais cycliques alternés sur du béton sont disponibles dans la littérature.
Une démarche d’expérimentation numérique a donc été élaborée sur la base d’un modèle fin du matériau, dit microscopique, capable de fournir les résultats nécessaires à la formulation et à l’identification d’un modèle macroscopique. Dans le modèle microscopique le matériau est considéré comme une structure à part entière, il a été développé afin de ne nécessiter qu’une quantité réduite de résultats d’essais, maîtrisés, pour être mis en oeuvre. Le modèle microscopique, un modèle particulaire lattice, a été développé sur la base d’un modèle lattice existant, enrichi pour être en mesure de simuler le comportement des matériaux quasi-fragiles sous chargements multi-axiaux et cycliques. Le modèle microscopique a alors été validé en tant qu’outil d’expérimentation numérique, et exploité afin d’établir les équations constitutives du modèle macroscopique fondées sur les théories de l’endommagement et de la plasticité. La régularité de la relation de comportement proposée, intégrant un effet unilatéral progressif, a notamment été garantie par l’utilisation d’un modèle d’élasticité non-linéaire. Le modèle macroscopique a finalement été calibré, entièrement, à l’aide du modèle microscopique, et mis à l’oeuvre dans la simulation de la réponse d’un voile en béton armé soumis à un chargement de cisaillement cyclique alterné. Cette simulation a permis de mettre en avant la robustesse numérique du modèle développé, ainsi que la contribution significative du comportement uni-axial cyclique alterné du béton à l’amortissement de telles structures

Ensembles Are Required to Handle Aleatoric and Parametric Uncertainty in Molecular Dynamics Simulation

Classical molecular dynamics is a computer simulation technique that is in widespread use across many areas of science, from physics and chemistry to materials, biology, and medicine. The method continues to attract criticism due its oft-reported lack of reproducibility which is in part due to a failure to submit it to reliable uncertainty quantification (UQ). Here we show that the uncertainty arises from a combination of (i) the input parameters and (ii) the intrinsic stochasticity of the method controlled by the random seeds. To illustrate the situation, we make a systematic UQ analysis of a widely used molecular dynamics code (NAMD), applied to estimate binding free energy of a ligand-bound to a protein. In particular, we replace the usually fixed input parameters with random variables, systematically distributed about their mean values, and study the resulting distribution of the simulation output. We also perform a sensitivity analysis, which reveals that, out of a total of 175 parameters, just six dominate the variance in the code output. Furthermore, we show that binding energy calculations dampen the input uncertainty, in the sense that the variation around the mean output free energy is less than the variation around the mean of the assumed input distributions, if the output is ensemble-averaged over the random seeds. Without such ensemble averaging, the predicted free energy is five times more uncertain. The distribution of the predicted properties is thus strongly dependent upon the random seed. Owing to this substantial uncertainty, robust statistical measures of uncertainty in molecular dynamics simulation require the use of ensembles in all contexts

Toward High Fidelity Materials Property Prediction from Multiscale Modeling and Simulation

The current approach to materials discovery and design remains dominated by experimental testing, frequently based on little more than trial and error. With the advent of ever more powerful computers, rapid, reliable, and reproducible computer simulations are beginning to represent a feasible alternative. As high performance computing reaches the exascale, exploiting the resources efficiently presents interesting challenges and opportunities. Multiscale modeling and simulation of materials are extremely promising candidates for exploiting these resources based on the assumption of a separation of scales in the architectures of nanomaterials. Examples of hierarchical and concurrent multiscale approaches are presented which benefit from the weak scaling of monolithic applications, thereby efficiently exploiting large scale computational resources. Several multiscale techniques, incorporating the electronic to the continuum scale, which can be applied to the efficient design of a range of nanocomposites, are discussed. Then the work on the development of a software toolkit designed to provide verification, validation, and uncertainty quantification to support actionable prediction from such calculations is discussed

Automated Variance-Based Sensitivity Analysis of a Heterogeneous Atomistic-Continuum System

A fully automated computational tool for the study of the uncertainty in a mathematical-computational model of a heterogeneous multi-scale atomistic-continuum coupling system is implemented and tested in this project. This tool can facilitate quantitative assessments of the model’s overall uncertainty for a given specific range of variables. The computational approach here is based on the polynomial chaos expansion using projection variance, a pseudo-spectral method. It also supports regression variance, a point collocation method with nested quadrature point where the random sampling method takes a dictionary of the names of the parameters which are manually defined to vary with corresponding distributions. The tool in conjunction with an existing platform for verification, validation, and uncertainty quantification offers a scientific simulation environment and data processing workflows that enables the execution of simulation and analysis tasks on a cluster or supercomputing platform with remote submission capabilities