Describing the Flow Curve of Shear-Banding Fluids Through a Structural Minimal Model

Main characteristics of colloidal systems that develop fluid phases with different mechanical properties, namely shear-banding fluids, are briefly reviewed both from experimental and theoretical (modelling) point of view. A non-monotonic shear stress vs. shear rate constitutive relation is presented. This relation derives from a phenomenological model of a shear ratedependent viscosity describing structural changes and involves the possibility of multivalued shear rates under a given shear stress. In the case of a stress-dependent viscosity, the same model allows one to predict vorticity banding. Predictions of this model under controlled stress are discussed, namely occurrence of a kind of top- and bottom-jumping of the shear rate in response to stress increasing-decreasing. Applying this model to evaluation of the flow curve of such colloidal systems is performed. Particular emphasis is placed on the adequate computation of the shear rate function in cylindrical Couette cells in order to handle the corresponding flow curve which exhibits the well-known shear stress plateau. Indeed, as different fluid phases coexist in the flow domain, measured (torque vs. angular velocity) data cannot be directly converted into rheometric (shear stress vs. shear rate) functions. As the lacking non-local terms in the model prevents the direct determination of the stress-plateau, this value is included as an adjustable parameter. Thus model predictions satisfactorily match up experimental data of wormlike micellar solutions from the literature.Comment: 22 pages, 9 fi

On the Flow Curve of Colloids Presenting Shear-Induced Phase Transitions

This work deals with the evaluation of the flow curve of colloidal systems that develop fluid phases with different mechanical properties, namely shear-banding fluids. The problem involved is that, as different fluid phases coexist in the flow domain of the rheometric cell, measured data cannot be directly converted into rheometric functions. In order to handle this problem, a shear stress vs. shear rate constitutive relation is introduced to interpret the steady state flow curves. The relation derives from a phenomenological description of structural changes, and involves the possibility of multivalued shear rates under a given shear stress. Numerical predictions satisfactorily match up to experimental data of wormlike micellar solutions. A crucial aspect is the adequate computation of the shear rate function from raw data measured in the rheometric cell.Comment: 12 page

On the Viscosity of Concentrated Suspensions of Charged Colloids

This work is concerned with the theoretical estimation of the low-shear viscosity of concentrated suspensions of charged-stabilized latex particles. Calculations are based on the assumption that particles interacting through purely repulsive potentials behave as equivalent hard-spheres (HS), and suspension viscosity may be analyzed in the framework of HS systems. In order to predict numerically the HS radius, the pair potential due to double-layer interaction, as a function of particle concentration, was investigated by using Poisson-Boltzmann theory and the cell model. Calculations explain appropriately experimental data for a wide range of particle sizes, volume fractions and salt concentrations. The problem concerning the effective surface charge of latex particles is also discussed.Fil: Berli, Claudio Luis Alberto. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Desarrollo Tecnológico para la Industria Química. Universidad Nacional del Litoral. Instituto de Desarrollo Tecnológico para la Industria Química; ArgentinaFil: Deiber, Julio Alcides. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Desarrollo Tecnológico para la Industria Química. Universidad Nacional del Litoral. Instituto de Desarrollo Tecnológico para la Industria Química; ArgentinaFil: Quemada, Daniel. Universite Paris VII; Franci

Optimal investment and hedging under partial and inside information

This article concerns optimal investment and hedging for agents who must use trading strategies which are adapted to the filtration generated by asset prices, possibly augmented with some inside information related to the future evolution of an asset price. The price evolution and observations are taken to be continuous, so the partial (and, when applicable, inside) information scenario is characterised by asset price processes with an unknown drift parameter, which is to be filtered from price observations. We first give an exposition of filtering theory, leading to the Kalman-Bucy filter. We outline the dual approach to portfolio optimisation, which is then applied to the Merton optimal investment problem when the agent does not know the drift parameter of the underlying stock. This is taken to be a random variable with a Gaussian prior distribution, which is updated via the Kalman filter. This results in a model with a stochastic drift process adapted to the observation filtration, and which can be treated as a full information problem, and an explicit solution to the optimal investment problem is possible. We also consider the same problem when the agent has noisy knowledge at time $0$ of the terminal value of the Brownian motion driving the stock. Using techniques of enlargement of filtration to accommodate the insider's additional knowledge, followed by filtering the asset price drift, we are again able to obtain an explicit solution. Finally we treat an incomplete market hedging problem. A claim on a non-traded asset is hedged using a correlated traded asset. We summarise the full information case, then treat the partial information scenario in which the hedger is uncertain of the true values of the asset price drifts. After filtering, the resulting problem with random drifts is solved in the case that each asset's prior distribution has the same variance, resulting in analytic approximations for the optimal hedging strategy

An architecture for integrating learning object repository resources into web videoconference services

Reusing Learning Objects saves time and reduce development costs. Hence, achieving their interoperability in multiple contexts is essential when creating a Learning Object Repository. On the other hand, novel web videoconference services are available due to technological advancements. Several benefits can be gained by integrating Learning Objects into these services. For instance, they can allow sharing, co-viewing and synchronized co-browsing of these resources at the same time that provide real time communication. However, several efforts need to be undertaken to achieve the interoperability with these systems. In this paper, we propose a model to integrate the resources of the Learning Object Repositories into web videoconference services. The experience of applying this model in a real e-Learning scenario achieving interoperability with two different web videoconference services is also described

Avalanche behavior in yield stress fluids

We show that, above a critical stress, typical yield stress fluids (gels and clay suspensions) and soft glassy materials (colloidal glasses) start flowing abruptly and subsequently accelerate, leading to avalanches that are remarkably similar to those of granular materials. Rheometrical tests reveal that this is associated with a bifurcation in rheological behavior: for small stresses, the viscosity increases in time; the material eventually stops flowing. For slightly larger stresses the viscosity decreases continuously in time; the flow accelerates. Thus the viscosity jumps discontinuously to infinity at the critical stress. We propose a simple physical model capable of reproducing these effects.Philippe Coussot, Q. D. Nguyen, H.T. Huynh, and Daniel Bon

'Towards a Conceptual Framework for Innate Immunity'

Innate immunity now occupies a central role in immunology. However, artificial immune system models have largely been inspired by adaptive not innate immunity. This paper reviews the biological principles and properties of innate immunity and, adopting a conceptual framework, asks how these can be incorporated into artificial models. The aim is to outline a meta-framework for models of innate immunity