Discrete element modelling of bedload transport

International audienceWe present a model for the description of bed load transport at the particle scale. The granular phase was modelled using discrete element method while the fluid phase was characterized by a fluid profile taken from the experiment. The coupling between the two phases was done considering only the effect of the fluid on the particle, through the drag force. The results of the model were compared to particular experimental results. A good agreement was obtained on the particle velocity and solid volume fraction in function of the depth considering the simplicity of the coupling

Bridging the gap between particle-scale forces and continuum modelling of size segregation: application to bedload transport

Gravity-driven size segregation is important in mountain streams where a wide range of grain sizes are transported as bedload. More particularly, vertical size segregation is a multi-scale process that originates in interactions at the scale of particles with important morphological consequences on the reach scale. To address this issue, a volume-averaged multi-phase flow model for immersed bidisperse granular flows was developed based on an interparticle segregation force (Guillard et al. 2016) and a granular Stokesian drag force (Tripathi and Khakhar 2013). An advection-diffusion model was derived from this model yielding parametrisations for the advection and diffusion coefficients based on the interparticle interactions. This approach makes it possible to bridge the gap between grain-scale physics and continuum modelling. Both models were successfully tested against existing Discrete Element Model (DEM) simulations of size segregation in bedload transport (Chassagne et al. 2020). Through a detailed investigation of the granular forces, it is demonstrated that the observed scaling of the advection and diffusion coefficients with the inertial number can be explained by the granular drag force dependency on the viscosity. The drag coefficient was shown to be linearly dependent on the small particle concentration. The scaling relationship of the segregation force with the friction coefficient is confirmed and additional non-trivial dependencies including the inertial number and small particle concentration are identified. Lastly, adding a size ratio dependency in the segregation force perfectly reproduces the DEM results for a large range of small particle concentrations and size-ratios

Revisiting slope influence in turbulent bedload transport: consequences for vertical flow structure and transport rate scaling

Gravity-driven turbulent bedload transport has been extensively studied over the past century in regard to its importance for Earth surface processes such as natural riverbed morphological evolution. In the present contribution, the influence of the longitudinal channel inclination angle on gravity-driven turbulent bedload transport is studied in an idealised framework considering steady and uniform flow conditions. From an analytical analysis based on the two-phase continuous equations, it is shown that : (i) the classical slope correction of the critical Shields number is based on an erroneous formulation of the buoyancy force, (ii) the influence of the slope is not restricted to the critical Shields number but affects the whole transport formula and (iii) pressure-driven and gravity-driven turbulent bedload transport are not equivalent from the slope influence standpoint. Analysing further the granular flow driving mechanisms, the longitudinal slope is shown to not only influence the fluid bed shear stress and the resistance of the granular bed, but also to affect the fluid flow inside the granular bed - responsible for the transition from bedload transport to debris flow. The relative influence of these coupled mechanisms allows us to understand the evolution of the vertical structure of the granular flow and to predict the transport rate scaling law as a function of a rescaled Shields number. The theoretical analysis is validated with coupled fluid-discrete element simulations of idealised gravity-driven turbulent bedload transport, performed over a wide range of Shields number values, density ratios and channel inclination angles. In particular, all the data are shown to collapse onto a master curve when considering the sediment transport rate as a function of the proposed rescaled Shields number

On granular rheology in bedload transport

The local granular phase rheology in bedload transport is investigated from discrete numerical simulations. The numerical model is based on a coupled Discrete Element Method with a 1D space-averaged fluid momentum balance. Using this model the averaged granular stress tensor profile can be computed from particle-particle interactions. In bed-load transport, the granular media exhibits quasi-static and dynamical behaviors. This physical situation can be used as a rheometer and the actual granular rheology can be deduced from a single simulation. Preliminary results suggests that the denser part of the flow, close to the static bed, is well described by a a μ(I)/Φ(I) rheology. Above this layer, the dense granular flow rheology fails to explain the observed shear and normal stresses, meaning that other mechanisms come into play

Mobility of bidisperse mixtures during bedload transport

The flow of segregated bidisperse assemblies of particles is of major importance for geophysical flows and bedload transport in particular. In the present paper, the mobility of strictly bidisperse segregated particle beds is studied with a coupled fluid discrete element method (DEM). Large particles are initially placed above small ones in a three-dimensional domain inclined at a slope of 10%. A gravity-driven water free surface flow induces a downslope shear-driven granular flow of the erodible bed. It is observed that, for the same water flow conditions, the bedload transport rate is higher in the bidisperse configuration than in the monodisperse one. Depending on the Shields number and on the depth of the interface between small and large particles, different transport phenomenologies are observed, ranging from no influence of the small particles to small particles reaching the bed surface due to diffusive remixing. In cases where the small particles hardly mix with the overlying large particles and for the range of studied size ratios (r < 4), it is shown that the increased mobility is not a bottom roughness effect, that would be due to the reduction of roughness of the underlying small particles, but a granular flow effect. This effect is analyzed within the framework of the mu(I) rheology, modeling the stress to strain rate relation for dense granular flows. It is demonstrated that the buried small particles are more mobile than larger particles and play the role of a "conveyor belt" for the large particles at the surface. Based on rheological arguments, a simple predictive model is proposed for the additional transport in the bidisperse case. It reproduces quantitatively the DEM results for a large range of Shields numbers and for size ratios smaller than 4. The results of the model are used to identify four different transport regimes of bidisperse mixtures, depending on the mechanism responsible for the mobility of the small particles. A phenomenological map is proposed for bidisperse bedload transport and, more generally, for any granular flow on an erodible bed

Cooperative Metaheuristics for Exploring Proteomic Data

Most combinatorial optimization problems cannotbe solved exactly. A class of methods, calledmetaheuristics, has proved its efficiency togive good approximated solutions in areasonable time. Cooperative metaheuristics area sub-set of metaheuristics, which implies aparallel exploration of the search space byseveral entities with information exchangebetween them. The importance of informationexchange in the optimization process is relatedto the building block hypothesis ofevolutionary algorithms, which is based onthese two questions: what is the pertinentinformation of a given potential solution andhow this information can be shared? Aclassification of cooperative metaheuristicsmethods depending on the nature of cooperationinvolved is presented and the specificproperties of each class, as well as a way tocombine them, is discussed. Severalimprovements in the field of metaheuristics arealso given. In particular, a method to regulatethe use of classical genetic operators and todefine new more pertinent ones is proposed,taking advantage of a building block structuredrepresentation of the explored space. Ahierarchical approach resting on multiplelevels of cooperative metaheuristics is finallypresented, leading to the definition of acomplete concerted cooperation strategy. Someapplications of these concepts to difficultproteomics problems, including automaticprotein identification, biological motifinference and multiple sequence alignment arepresented. For each application, an innovativemethod based on the cooperation concept isgiven and compared with classical approaches.In the protein identification problem, a firstlevel of cooperation using swarm intelligenceis applied to the comparison of massspectrometric data with biological sequencedatabase, followed by a genetic programmingmethod to discover an optimal scoring function.The multiple sequence alignment problem isdecomposed in three steps involving severalevolutionary processes to infer different kindof biological motifs and a concertedcooperation strategy to build the sequencealignment according to their motif conten

Solid-state carbon-13 NMR and computational characterization of the N719 ruthenium sensitizer adsorbed on TiO2 nanoparticles

The ruthenium-containing sensitizing dye N719 grafted on TiO2 nanoparticles was investigated by solidstate NMR. The carbon resonances are assigned by means of 13C cross-polarized dipolar dephasing experiments. DFT calculations of the carbon magnetic shielding tensors accurately describe the changes in chemical shifts observed upon grafting onto a titania surface via one or two carboxylic functions in the plane defined by the two isothiocyanate group

Trust-Aware Peer Sampling: Performance and Privacy Tradeoffs

International audienceThe ability to identify people that share one's own interests is one of the most interesting promises of the Web 2.0 driving user-centric applications such as recommendation systems or collaborative marketplaces. To be truly useful, however, information about other users also needs to be associated with some notion of trust. Consider a user wishing to sell a concert ticket. Not only must she find someone who is interested in the concert, but she must also make sure she can trust this person to pay for it. This paper addresses the need for trust in user-centric applications by propos- ing two novel distributed protocols that combine interest-based connections be- tween users with explicit links obtained from social networks à-la Facebook. Both protocols build trusted multi-hop paths between users in an explicit so- cial network supporting the creation of semantic overlays backed up by social trust. The first protocol, TAPS2 , extends our previous work on TAPS (Trust- Aware Peer Sampling), by improving the ability to locate trusted nodes. Yet, it remains vulnerable to attackers wishing to learn about trust values between ar- bitrary pairs of users. The second protocol, PTAPS (Private TAPS ), improves TAPS2 with provable privacy guarantees by preventing users from revealing their friendship links to users that are more than two hops away in the social network. In addition to proving this privacy property, we evaluate the per- formance of our protocols through event-based simulations, showing significant improvements over the state of the art