Scale Modelling of Soil Structure Interaction during Earthquakes Using a Programmed Series of Explosions during Centrifugation

Scale models of Nuclear Power plants were constructed to study soil structure interaction during Earthquakes. The centrifuge of the C.E.S.T.A. Center near Bordeaux, France, was used to simulate gravity at 100 g (length scale 1: 100) on a 1000 kg net weight of soil and structure. The Earthquake was simulated by a surface wave created by a programmed series of small explosions suitably modified so that the free field signals of horizontal and vertical accelerometers had spectra resembling those of real Earthquakes according to similitude laws. The problem of echoes and suitability of a confined structure was studied without models of structures. In tests including models of structures movements and stresses in the soil and in the structure were measured using transducers of acceleration displacement pressure and deformation. The overall stability was studied

Mechanical identification of layer-specific properties of mouse carotid arteries using 3D-DIC and a hyperelastic anisotropic constitutive model

The role of mechanics is known to be of primary order in many arterial diseases; however, determining mechanical properties of arteries remains a challenge. This paper discusses the identifiability of the passive mechanical properties of a mouse carotid artery, taking into account the orientation of collagen fibres in the medial and adventitial layers. On the basis of 3D digital image correlation measurements of the surface strain during an inflation/extension test, an inverse identification method is set up. It involves a 3D finite element mechanical model of the mechanical test and an optimisation algorithm. A two-layer constitutive model derived from the Holzapfel model is used, with five and then seven parameters. The five-parameter model is successfully identified providing layer-specific fibre angles. The seven-parameter model is over parameterised, yet it is shown that additional data from a simple tension test make the identification of refined layer-specific data reliable.Comment: PB-CMBBE-15.pd

Optimization of Piezoelectric Electrical Generators Powered by Random Vibrations

This paper compares the performances of a vibrationpowered electrical generators using PZT piezoelectric ceramic associated to two different power conditioning circuits. A new approach of the piezoelectric power conversion based on a nonlinear voltage processing is presented and implemented with a particular power conditioning circuit topology. Theoretical predictions and experimental results show that the nonlinear processing technique may increase the power harvested by a factor up to 4 compared to the Standard optimization technique. Properties of this new technique are analyzed in particular in the case of broadband, random vibrations, and compared to those of the Standard interface.Comment: Submitted on behalf of TIMA Editions (http://irevues.inist.fr/tima-editions

Vibration stabilization for a cantilever magnet prototype at the subnanometer scale

In the future linear colliders, the size of the beams is in the nanometer range, which requires stabilization of the final magnets before the interaction point. In order to guarantee the desired luminosity, an absolute displacement lower than 1/3 of the beam size, above a few hertz, has to be obtained. This paper describes an adapted instrumentation, the developed feedback loops dedicated to the active compensation and an adapted modelling able to simulate the behaviour of the structure. The obtained results at the subnanometer scale at the free end of a cantilever magnet prototype with a combination of the developed active compensation method and a commercial active isolation system are described

Exploring NMR ensembles of calcium binding proteins: Perspectives to design inhibitors of protein-protein interactions

<p>Abstract</p> <p>Background</p> <p>Disrupting protein-protein interactions by small organic molecules is nowadays a promising strategy employed to block protein targets involved in different pathologies. However, structural changes occurring at the binding interfaces make difficult drug discovery processes using structure-based drug design/virtual screening approaches. Here we focused on two homologous calcium binding proteins, calmodulin and human centrin 2, involved in different cellular functions via protein-protein interactions, and known to undergo important conformational changes upon ligand binding.</p> <p>Results</p> <p>In order to find suitable protein conformations of calmodulin and centrin for further structure-based drug design/virtual screening, we performed <it>in silico </it>structural/energetic analysis and molecular docking of terphenyl (a mimicking alpha-helical molecule known to inhibit protein-protein interactions of calmodulin) into X-ray and NMR ensembles of calmodulin and centrin. We employed several scoring methods in order to find the best protein conformations. Our results show that docking on NMR structures of calmodulin and centrin can be very helpful to take into account conformational changes occurring at protein-protein interfaces.</p> <p>Conclusions</p> <p>NMR structures of protein-protein complexes nowadays available could efficiently be exploited for further structure-based drug design/virtual screening processes employed to design small molecule inhibitors of protein-protein interactions.</p

Systems comparison and regression trees

A method for non parametric modelling of dynamical systems was presented in a previous paper . This work intends to propose a new approach for addressing the problem of dynamical systems comparison and detection of abrupt changes . The algorithm that is presented here, relies upon both d-dimensionnal histogram and regression tree estimation, and the use of f-divergences . Illustrations on different non linear systems are provided .Nous proposons ici une application de la méthode de modélisation non linéaire non paramétrique de systèmes dynamiques, présentée dans un précédent article. L'approche proposée dans le cadre de ce travail repose sur une partition récursive de l'espace d'état du système, conduisant à un arbre de régression. Ce modèle fournit une estimation de l'histogramme d-dimensionnel de l'espace des états du système : nous montrons comment l'utilisation de distances ou de divergences entre lois de probabilité permet alors de quantifier les différences dynamiques entre systèmes. Cette approche est illustrée sur deux exemples : la détection de changements de modèles autorégressifs dans une série temporelle et la détection de la présence éventuelle d'un soliton de type « breather » susceptible d'apparaître dans le comportement d'une chaîne d'oscillateurs couplés soumis à un potentiel extérieur

Regression trees for non parametric modeling and time series prediction

We present a non-parametric approach to nonlinear modeling and prediction based on adaptive partitioning of the reconstructed phase space associated with the process . The partitioning method is implemented with a recursive tree-structured algorithm which successively refines the partition by binary splitting where the splitting threshold is determined by a penalized maximum entropy criterion. An analysis of the statistical behavior of the splitting rule suggests a criterion for determining the depth of the tree . The effectiveness of this method is illustrated through comparisons with classical approaches for nonlinear system analysis on the basis of reconstruction error and computational complexity . An important relation between our tree-structured model for the process and generalized non-linear thresholded AR model (ART) is established . We illustrate our method for cases where classical linear prediction is known to be rather ineffective : chaotic signals (measured at the output of a Chua-type electronic circuit), and second order ART signal .Nous présentons une approche non linéaire non paramétrique pour la modélisation et la prédiction de signaux, basée sur une méthode de partition récursive de l'espace des phases reconstruit, associé au système sur lequel le signal est prélevé. La partition de l'espace des phases est obtenue par un algorithme récursif de partition binaire. Les seuils de partition sont déterminés à l'aide d'un critère de maximum d'entropie. Une courte analyse statistique du comportement de ces seuils permet de définir un critère simple d'arrêt de la partition récursive. L'intérêt de cette méthode est illustré par la comparaison avec des méthodes classiques dans le cadre de l'analyse de systèmes non linéaires, ainsi que du point de vue du coût de calcul. Nous présentons un lien important entre cette méthode reposant sur une partition hiérarchique (en arbre) et les modèles non linéaires auto-régressifs à seuils (ART). Dans ce contexte, la méthode présentée est appliquée dans des cas pour lesquels les méthodes linéaires échouent en général : les signaux de chaos (séries expérimentales mesurées sur des circuits électroniques de type Chua), ainsi que sur des séries numériques ART d'ordre deux

Extracting non-linear integrate-and-fire models from experimental data using dynamic I–V curves

The dynamic I–V curve method was recently introduced for the efficient experimental generation of reduced neuron models. The method extracts the response properties of a neuron while it is subject to a naturalistic stimulus that mimics in vivo-like fluctuating synaptic drive. The resulting history-dependent, transmembrane current is then projected onto a one-dimensional current–voltage relation that provides the basis for a tractable non-linear integrate-and-fire model. An attractive feature of the method is that it can be used in spike-triggered mode to quantify the distinct patterns of post-spike refractoriness seen in different classes of cortical neuron. The method is first illustrated using a conductance-based model and is then applied experimentally to generate reduced models of cortical layer-5 pyramidal cells and interneurons, in injected-current and injected- conductance protocols. The resulting low-dimensional neuron models—of the refractory exponential integrate-and-fire type—provide highly accurate predictions for spike-times. The method therefore provides a useful tool for the construction of tractable models and rapid experimental classification of cortical neurons

Stabilization study at the sub-nanometer level at the interaction point of the future Compact Linear Collider

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