682,778 research outputs found

    Rheology of Granular Materials: Dynamics in a Stress Landscape

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    We present a framework for analyzing the rheology of dense driven granular materials, based on a recent proposal of a stress-based ensemble. In this ensemble fluctuations in a granular system near jamming are controlled by a temperature-like parameter, the angoricity, which is conjugate to the stress of the system. In this paper, we develop a model for slowly driven granular materials based on the stress ensemble and the idea of a landscape in stress space. The idea of an activated process driven by the angoricity has been shown by Behringer et al (2008) to describe the logarithmic strengthening of granular materials. Just as in the Soft Glassy Rheology (SGR) picture, our model represents the evolution of a small patch of granular material (a mesoscopic region) in a stress-based trap landscape. The angoricity plays the role of the fluctuation temperature in SGR. We determine (a) the constitutive equation, (b) the yield stress, and (c) the distribution of stress dissipated during granular shearing experiments, and compare these predictions to experiments of Hartley & Behringer (2003).Comment: 17 pages, 4 figure

    Coalescence of Liquid Drops: Different Models Versus\ud Experiment

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    The process of coalescence of two identical liquid drops is simulated numerically in the framework of two essentially different mathematical models, and the results are compared with experimental data on the very early stages of the coalescence process reported recently. The first model tested is the ‘conventional’ one, where it is assumed that coalescence as the formation of a single body of fluid occurs by an instant appearance of a liquid bridge smoothly connecting the two drops, and the subsequent process is the evolution of this single body of fluid driven by capillary forces. The second model under investigation considers coalescence as a process where a section of the free surface becomes trapped between the bulk phases as the drops are pressed against each other, and it is the gradual disappearance of this ‘internal interface’ that leads to the formation of a single body of fluid and the conventional model taking over. Using the full numerical solution of the problem in the framework of each of the two models, we show that the recently reported electrical measurements probing the very early stages of the process are better described by the interface formation/disappearance model. New theory-guided experiments are suggested that would help to further elucidate the details of the coalescence phenomenon. As a by-product of our research, the range of validity of different ‘scaling laws’ advanced as approximate solutions to the problem formulated using the conventional model is\ud established

    Response properties in a model for granular matter

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    We investigate the response properties of granular media in the framework of the so-called {\em Random Tetris Model}. We monitor, for different driving procedures, several quantities: the evolution of the density and of the density profiles, the ageing properties through the two-times correlation functions and the two-times mean-square distance between the potential energies, the response function defined in terms of the difference in the potential energies of two replica driven in two slightly different ways. We focus in particular on the role played by the spatial inhomogeneities (structures) spontaneously emerging during the compaction process, the history of the sample and the driving procedure. It turns out that none of these ingredients can be neglected for the correct interpretation of the experimental or numerical data. We discuss the problem of the optimization of the compaction process and we comment on the validity of our results for the description of granular materials in a thermodynamic framework.Comment: 22 pages, 35 eps files (21 figures

    Machine learning based digital twin for dynamical systems with multiple time-scales

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    Digital twin technology has a huge potential for widespread applications in different industrial sectors such as infrastructure, aerospace, and automotive. However, practical adoptions of this technology have been slower, mainly due to a lack of application-specific details. Here we focus on a digital twin framework for linear single-degree-of-freedom structural dynamic systems evolving in two different operational time scales in addition to its intrinsic dynamic time-scale. Our approach strategically separates into two components – (a) a physics-based nominal model for data processing and response predictions, and (b) a data-driven machine learning model for the time-evolution of the system parameters. The physics-based nominal model is system-specific and selected based on the problem under consideration. On the other hand, the data-driven machine learning model is generic. For tracking the multi-timescale evolution of the system parameters, we propose to exploit a mixture of experts as the data-driven model. Within the mixture of experts model, Gaussian Process (GP) is used as the expert model. The primary idea is to let each expert track the evolution of the system parameters at a single time-scale. For learning the hyperparameters of the ‘mixture of experts using GP’, an efficient framework that exploits expectation-maximization and sequential Monte Carlo sampler is used. Performance of the digital twin is illustrated on a multi-timescale dynamical system with stiffness and/or mass variations. The digital twin is found to be robust and yields reasonably accurate results. One exciting feature of the proposed digital twin is its capability to provide reasonable predictions at future time-steps. Aspects related to the data quality and data quantity are also investigated

    Low temperature dynamics of kinks on Ising interfaces

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    The anisotropic motion of an interface driven by its intrinsic curvature or by an external field is investigated in the context of the kinetic Ising model in both two and three dimensions. We derive in two dimensions (2d) a continuum evolution equation for the density of kinks by a time-dependent and nonlocal mapping to the asymmetric exclusion process. Whereas kinks execute random walks biased by the external field and pile up vertically on the physical 2d lattice, then execute hard-core biased random walks on a transformed 1d lattice. Their density obeys a nonlinear diffusion equation which can be transformed into the standard expression for the interface velocity v = M[(gamma + gamma'')kappa + H]$, where M, gamma + gamma'', and kappa are the interface mobility, stiffness, and curvature, respectively. In 3d, we obtain the velocity of a curved interface near the orientation from an analysis of the self-similar evolution of 2d shrinking terraces. We show that this velocity is consistent with the one predicted from the 3d tensorial generalization of the law for anisotropic curvature-driven motion. In this generalization, both the interface stiffness tensor and the curvature tensor are singular at the orientation. However, their product, which determines the interface velocity, is smooth. In addition, we illustrate how this kink-based kinetic description provides a useful framework for studying more complex situations by modeling the effect of immobile dilute impurities.Comment: 11 pages, 10 figure

    Influence of attractive van der Waals interactions on the optimal excitations in thermocapillary-driven spreading

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    Recent investigations of microfluidic flows have focused on manipulating the motion of very thin liquid films by modulating the surface tension through an applied streamwise temperature gradient. The extent to which the choice of contact line model affects the flow and stability of such thermocapillary-driven films is not completely understood. Regardless of the contact line model used, the linearized disturbance operator corresponding to the evolution of the film height is non-normal, and a generalized non-modal stability analysis is required. Surprisingly, early predictions of frontal instability that stemmed from conventional modal analysis of thermocapillary flow on a flat, infinite precursor film showed excellent agreement with experiment. Within the more rigorous framework provided by a generalized stability analysis, this work investigates the transient dynamics and amplification of optimal disturbances subject to a finite precursor film generated by attractive van der Waals forces. Convergence of the disturbance growth rates and perturbed shapes to the asymptotic solutions obtained by conventional linear stability analysis occurs early in the spreading process. In addition, the level of transient disturbance amplification is minimal. The equations governing thermocapillary-driven spreading exhibit a small degree of non-normality, which explains the source of agreement between modal theory and experiment. The more rigorous generalized stability analysis presented here, however, affords critical insight into the types of disturbances leading to maximum unstable growth and the exact influence of the contact line model used

    SPLEMMA: A Generic Framework for Controlled-Evolution of Software Product Lines

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    International audienceManaging in a generic way the evolution process of feature- oriented Software Product Lines (SPLs) is complex due to the number of elements that are impacted and the heterogeneity of the SPLs regarding artifacts used to define them. Existing work presents specific approaches to manage the evolution of SPLs in terms of such artifacts, i.e., assets, feature models and relation definitions. Moreover stakeholders do not necessarily master all the knowledge of the SPL making its evolution difficult and error-prone without a proper tool support. In order to deal with these issues, we introduce SPLEmma, a generic framework that follows a Model Driven Engineering approach to capture the evolution of a SPL independently of the kind of assets, technologies or feature models used for the product derivation. Authorized changes are described by the SPL maintainer and captured in a model used to generate tools that guide the evolution process and preserve the consistency of the whole SPL. We report on the application of our approach on two SPLs: YourCast for digital signage systems, and SALOON, which enables generation of configurations for cloud providers

    Rationale in Semi-Structured Processes

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    Abstract. This paper argues that an explicit account of rationale is essential for the effective management and evolution of semi-structured processes. Our approach is based on a view of semi-structured process models as unfinished products whose design is implicitly completed through their execution by process model users. The resulting refinements and modifications of the process models are instances of user-driven design innovation. Our framework shows how rationale can explain a user’s individual execution decisions, as a basis for process modelers to improve the original process specifications. We propose and illustrate a modeling approach using the FBS ontology
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