Numerical simulation based on FEM/MLS coupling for solid mechanics

This paper presents the development of Meshless Methods based on the weighted least squares approximation (MLS) [1,3,14] to solve 2D mechanical problems. A particular construction support of weight functions involved in the construction of the MLS shape functions is elaborated. We propose a numerical simulation based on the coupling between the FEM and the MLS method. A Huerta et al. formulation is used to build the MLS shape function in the transition area FEM/MLS

Modélisation du comportement des biomasses bactériennes libres et fixées dans les réseaux de distribution d'eau potable

La prolifération bactérienne en réseaux de distribution d'eau potable est un souci majeur des distributeurs d'eau. La complexité des phénomènes impliqués dans la croissance bactérienne en réseaux nécessite une modélisation mathématique pour définir l'impact des différents paramètres de la qualité de l'eau et généraliser ces résultats à l'échelle du réseau de distribution. Une approche déterministe a été choisie pour développer cette modélisation prédictive de la croissance bactérienne dans les systèmes de distribution. Le modèle prend en compte : la croissance de fa biomasse libre et de la biomasse fixée, la consommation en nutriments exprimés par le CODB, l'action bactéricide du chlore sur la flore libre et la dore fixée, la déposition des bactéries en suspension et le détachement des bactéries fixées. Le modèle propose une approche originale pour la modélisation de l'action bactéricide du chlore. Par ailleurs, différentes formulations du détachement ont été testées algébriquement pour définir la modélisation la plus adaptée à notre système d'équations. Ce modèle a été couplé au logiciel de modélisation hydraulique IMCCOI.O développé par la SAFEGE. Utilisant les données hydrauliques et de géométrie générées par PICCOLO, le modèle prédit les numérations bactériennes en chaque noeud et sur chaque arc du réseau de distribution. Utilisant l'interface graphique de PICCOLO, le modèle permet une visualisation de l'évolution de la qualité bactérienne par cartographie. Des simulations ont été réalisées sur de nombreux réseaux présentant des tailles et des niveaux de complexité variables. Le modèle a été validé à partir de campagnes de prélèvements sur sites. Ce modèle permettant de simuler l'évolution de la qualité bactériologique à l'échelle du réseau est un outil unique pour le diagnostic et la gestion qualitative des systèmes de distribution d'eau potable.Of the many causes of distributed water quality deterioration, biological phenomena are undoubtedly the subject of the most study, and are also the most closely monitored because of short-term public health risks. Although high heterotrophic bacterial counts do not necessary constitute a health risk, they are the sign that a particular network is subject to biological disorders which can protect pathogenic species. What is more, the evolution of the bacterial biomass in the network also affects other aspects of distributed water quality, such as tastes and odours, the development macro-invertebrates, the appearance of colour and turbidity and the appearance of biocorrosion phenomena. Qualitative management of distribution networks is therefore to ensure that the quality of the product is kept as constant as possible up to the farthest points of the distribution. With this in mind, it is essential to understand, describe and model the various phenomena which lead to the evolution of water quality during distribution. Mathematical modelling is necessary in order to take ail parameters into account in view of the complexity of the different phenomena involved. A determinist type modelling was developed to predict bacterial variations (viable and total bacteria) during distribution. The model takes into account: - the fate of available nutrients consumed for the growth of suspended and fixed bacteria, - the influence of temperature on bacterial dynamics, - the natural mortality of bacteria by senescence and grazing, - the mortality resulting from the presence of chlorine disinfectant, with a differentiation between the action on free et fixed bacteria,- the impact of different forms of chlorine in water (HCIO/CIO-) dépending on pH on the mortality rate,- the deposition of suspended bacteria and the detachment of fixed bacteria,- the chlorine decay kinetics onder the influence of temperature, hydraulics and pipe materials.The modelling of the fixed biomass as a layer uniformly distributed over the pipe surface, expressed as an équivalent thickness of carbon, has been adopted. By this way, a differentiation between the mathematical expression of the free and that of the fixed biomass was made in the model. This mean it is possible to distinguish between phenomena depending on their locations: reactions in solution, réaction at the water/biofilm surface interface and within the biofiJm.This model proposes also an original approach for chlorine bactericidal action on suspended and fixed biomass. To model the action of chlorine on the fixed biomass and its stronger résistance compared with the free biomass, the diffusion of the chlorine through the boundary layer and the biofilm has been taken into account. This calculation of the average penetration depth of the chlorine front into the biofilm enables the identification of two layers: a chlorinated layer and a layer not attained by the chlorine which provides a material indication of the better resistance of the fixed biomass.As detachment is a key phenomenon in the modelling of bacterial dynamics in distribution Systems, the influence of different formulas of detachment kinetics on the mathematical expression of model variables were determined by soiving model equations.The model has been interfaced with PICCOLO software, the SAFEGE hydraulic calculation model. It is constructed by using hydraulic results previously generated by PICCOLO and a numerical scheme to predict bacterial count at each node and on each link of a network. Installed on a PC type computer, the model uses the graphic interface of PICCOLO and provides an effective and easy way to visualise on a computer screen water quality variations in the network, using a colour code for bacterial count, nutrient concentration and chlorine residual.The first model calibration was done using data from our pipe loop pilot under various operating conditions. The model has been also used to simulate a variety of distribution Systems of different sizes and levels of details and a validation of the model has been carried out by means of measurement campaigns on different distribution Systems.Animating and visualising variations of bacteria counts in distribution system is an unique approach to study the changes in water quality. This tool is helpful to propose strategies for the management of distribution Systems and treatment plants and define the different zones of bacterial regrowth in relation with hydraulic conditions

Distributive thermometer: A new unary encoding for weightless neural networks

The binary encoding of real valued inputs is a crucial part of Weightless Neural Networks. The Linear Thermometer and its variations are the most prominent methods to determine binary encoding for input data but, as they make assumptions about the input distribution, the resulting encoding is sub-optimal and possibly wasteful when the assumption is incorrect. We propose a new thermometer approach that doesn’t require such assumptions. Our results show that it achieves similar or better accuracy when compared to a thermometer that correctly assumes the distribution, and accuracy gains up to 26.3% when other thermometer representations assume an unsound distribution.info:eu-repo/semantics/publishedVersio

LogicWiSARD: Memoryless synthesis of weightless neural networks

Weightless neural networks (WNNs) are an alternative pattern recognition technique where RAM nodes function as neurons. As both training and inference require mostly table lookups, few additions, and no multiplications, WNNs are suitable for high-performance and low-power embedded applications. This work introduces a novel approach to implement WiSARD, the leading WNN state-of-the-art architecture, completely eliminating memories and arithmetic circuits and utilizing only logic functions. The approach creates compressed minimized implementations by converting trained WNN nodes from lookup tables to logic functions. The proposed LogicWiSARD is implemented in FPGA and ASIC technologies to illustrate its suitability for edge inference. Experimental results show more than 80% reduction in energy consumption when the proposed LogicWiSARD model is compared with a multilayer perceptron network (MLP) of equivalent accuracy. Compared to previous work on FPGA implementations for WNNs, convolutional neural networks, and binary neural networks, the energy savings of LogicWiSARD range between 32.2% and 99.6%.info:eu-repo/semantics/acceptedVersio

Pruning weightless neural networks

Weightless neural networks (WNNs) are a type of machine learning model which perform prediction using lookup tables (LUTs) instead of arithmetic operations. Recent advancements in WNNs have reduced model sizes and improved accuracies, reducing the gap in accuracy with deep neural networks (DNNs). Modern DNNs leverage “pruning” techniques to reduce model size, but this has not previously been explored for WNNs. We propose a WNN pruning strategy based on identifying and culling the LUTs which contribute least to overall model accuracy. We demonstrate an average 40% reduction in model size with at most 1% reduction in accuracy.info:eu-repo/semantics/publishedVersio

Managing Learner’s Affective States in Intelligent Tutoring Systems

Abstract. Recent works in Computer Science, Neurosciences, Education, and Psychology have shown that emotions play an important role in learning. Learner’s cognitive ability depends on his emotions. We will point out the role of emotions in learning, distinguishing the different types and models of emotions which have been considered until now. We will address an important issue con-cerning the different means to detect emotions and introduce recent approaches to measure brain activity using Electroencephalograms (EEG). Knowing the influ-ence of emotional events on learning it becomes important to induce specific emo-tions so that the learner can be in a more adequate state for better learning or memorization. To this end, we will introduce the main components of an emotion-ally intelligent tutoring system able to recognize, interpret and influence learner’s emotions. We will talk about specific virtual agents that can influence learner’s emotions to motivate and encourage him and involve a more cooperative work, particularly in narrative learning environments. Pushing further this paradigm, we will present the advantages and perspectives of subliminal learning which inter

The Diffuse Approximation: a derivative tool dedicated to full-field measurements

This study proposes a filtering tool based on the diffuse approximation, in order to reconstruct strain fields from full-field displacement measurements. The question of the filtering of the noise is adressed and an alternative approach based on space-time filtering is proposed. The methods are then applied to the detection of early damage detection on a tensile test on an interlock composite