Vertically aligned carbon nanotube‐based composite: Elaboration and monitoring of the nanotubes alignment

We present the different elaboration steps of a composite formed of carbon nanotubes (CNT) carpet embedded in an epoxy polymer. Detailed characterization at each step of the elaboration process is performed. The good alignment of CNT in as‐grown carpets is kept all along the elaboration process of the composite, as it is measured at both macro and microscopic scales by X‐ray scattering. We also ensured by X‐ray fluorescence measurements that the iron‐based catalyst particles used for the synthesis were removed from the carpet after a high temperature post‐annealing treatment. These measurements give valuable information for further applications involving unidirectional nanotube composites and membranes, where CNT alignment is a key parameter. © 2013 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2014 , 131, 39730.     

Model‐based control addition to prescribe DFIG wind turbine fast frequency response

This paper investigates the physical capability of double‐fed induction generator (DFIG) wind turbines for inertial support of frequency response. Frequency stability is modeled using the DFIG electromechanical and generator controller dynamics, and a destabilizing effect is demonstrated in low‐inertia systems. To improve response, a synchronous reference frame DFIG controller is proposed that acts by following low‐frequency grid dynamics and adds a fast acting proportional plus integral (PI)‐controlled frequency‐responsive component to existing qd current commands. The proposed controller is derived in a straightforward manner using only the DFIG dynamic equations and is designed using pole/zero placement techniques. Laboratory experiments using a micro‐scale DFIG wind turbine with hub‐emulating flywheel prove better capability for transient frequency regulation even under extreme load change. The result is a DFIG controller that balances the appearance of transients in electrical and mechanical systems. Value is achieved in providing immediate continuous inertial response to support load change. The proposed frequency response can improve the use of existing physical inertia from wind turbines.     

Nitrogen transformations and retention in planted and artificially aerated constructed wetlands

Nitrogen (N) processing in constructed wetlands (CWs) is often variable, and the contribution to N loss and retention by various pathways (nitrification/denitrification, plant uptake and sediment storage) remains unclear. We studied the seasonal variation of the effects of artificial aeration and three different macrophyte species (Phragmites australis, Typha angustifolia and Phalaris arundinacea) on N processing (removal rates, transformations and export) using experimental CW mesocosms. Removal of total nitrogen (TN) was higher in summer and in planted and aerated units, with the highest mean removal in units planted with T. angustifolia. Export of ammonium (NH₄⁺), a proxy for nitrification limitation, was higher in winter, and in unplanted and non-aerated units. Planted and aerated units had the highest export of oxidized nitrogen (NO_y), a proxy for reduced denitrification. Redox potential, evapotranspiration (ETP) rates and hydraulic retention times (HRT) were all predictors of TN, NH₄⁺ and NO_y export, and significantly affected by plants. Denitrification was the main N sink in most treatments accounting for 47-62% of TN removal, while sediment storage was dominant in unplanted non-aerated units and units planted with P. arundinacea. Plant uptake accounted for less than 20% of the removal. Uncertainties about the long-term fate of the N stored in sediments suggest that the fraction attributed to denitrification losses could be underestimated in this study.     

Pictures worth a thousand tiles,a geometrical programming language for self-assembly

We present a novel way to design self-assembling systems using a notion of signal (or ray) akin to what is used in analyzing the behaviour of cellular automata. This allows purely geometrical constructions, with a smaller specification and easier analysis. We show how to design a system of signals for a given set of shapes, and how to transform these signals into a set of tiles which self-assemble into the desired shapes.     

Rate of evolution of the specific surface area of surface snow layers

The snowpack can impact atmospheric chemistry by exchanging adsorbed or dissolved gases with the atmosphere. Modeling this impact requires the knowledge of the specific surface area (SSA) of snow and its variations with time. We have therefore measured the evolution of the SSA of eight recent surface snow layers in the Arctic and the French Alps, using CH4 adsorption at liquid nitrogen temperature (77 K). The SSA of fresh snow layers was found to decrease with time, from initial values in the range 613-1540 cm2/g to values as low as 257 cm2/g after 6 days. This is explained by snow metamorphism, which causes modifications in crystal shapes, here essentially crystal rounding and the disappearance of microstructures. A parametrization of the rate of SSA decrease is proposed. We fit the SSA decrease to an exponential law and find that the time constant alpha(exp) (day(-1)) depends on temperature according to alpha(exp) = 76.6 exp (-1708/7), with Tin kelvin. Our parametrization predicts that the SSA of a snow layer evolving at -40 degrees C will decrease by a factor of 2 after 14 days, while a similar decrease at -1 degrees C will only require 5 days. Wind was found to increase the rate of SSA decrease, but insufficient data did not allow a parametrization of this effect.     

HDM: A Client/Server/Engine Architecture for Real-Time Web Usage Mining

The behavior of the users of a website may change so quickly that it becomes a real challenge to attempt to make predictions according to the frequent patterns coming from the analysis of an access log file. In order to reduce the obsolescence of behavioral patterns as much as possible, the ideal method would provide frequent patterns in real time, making the result immediately available. In this paper, we propose a method for finding frequent behavioral patterns in real time, whatever the number of connected users. Considering how fast frequent behavior patterns may have changed since the time the access log file was analyzed, this result thus provides completely appropriate navigation schemata for predicting user behavior. Based on a distributed heuristic, our method also tackles and provides answers to several problems within the framework of data mining: the discovery of interesting zones (a large number of frequent patterns concentrated over a period of time, or super-frequent patterns), discovering very long sequential patterns and interactive data mining (on-the-fly modification of the minimum support).