Friction and wear properties of MoAlB against Al2O3 and 100Cr6 steel counterparts

The present work investigates, for the first time, the dry sliding friction and wear behaviour of fully dense, predominantly single-phase MoAlB ceramics against alumina (Al₂O₃) and 100Cr6 steel counterparts. Against Al₂O₃, the friction coefficient (μ) increased with increasing load and the wear was highly dependent on the load applied. A transition from mild wear under 1 N and 4 N to severe wear at 10 N occurred. Scanning electron microscopy revealed that abrasion is the dominant wear mechanism. Against steel, μ decreased with increasing load and the wear rates were low, under all applied loads. The morphologies of the worn surfaces against steel were characterized by the appearance of a rippled layers. Atomic force microscopy and Raman spectroscopy were used to propose a possible formation mechanism of such patterns. X-ray photoelectron spectroscopy revealed the rippled surfaces to be composed of Fe₂O₃ and a mixture of MoO_x.     

Fitting stress relaxation experiments with fractional Zener model to predict high frequency moduli of polymeric acoustic foams

This paper presents a time domain method to determine viscoelastic properties of open-cell foams on a wide frequency range. This method is based on the adjustment of the stress–time relationship, obtained from relaxation tests on polymeric foams’ samples under static compression, with the four fractional derivatives Zener model. The experimental relaxation function, well described by the Mittag–Leffler function, allows for straightforward prediction of the frequency-dependence of complex modulus of polyurethane foams. To show the feasibility of this approach, complex shear moduli of the same foams were measured in the frequency range between 0.1 and 16 Hz and at different temperatures between ?20 °C and 20 °C. A curve was reconstructed on the reduced frequency range (0.1 Hz–1 MHz) using the time–temperature superposition principle. Very good agreement was obtained between experimental complex moduli values and the fractional Zener model predictions. The proposed time domain method may constitute an improved alternative to resonant and non-resonant techniques often used for dynamic characterization of polymers for the determination of viscoelastic moduli on a broad frequency range.     

Ethanol-sensing properties of potassium bromide/multi-walled carbon nanotube composites

The work reported in this paper is related to the fabrication and electrical characterization of multi-walled carbon nanotubes (MWNT)-based solid composites pellets with potential application as gas sensor at room temperature, using potassium bromide as supporting material. Results show an electrical conductivity of the composites as a function of the MWNT loading following a power law associated with a percolation phenomenon. A variation of the electrical resistance of the composites as a function of ethanol concentration in a nitrogen atmosphere has also been observed, allowing detection of ethanol from about hundred of ppm. It is also shown the existence of an optimal MWNT loading for which the composite reaches its best ethanol-sensing performances.     

VANET: A novel service for predicting and disseminating vehicle traffic information

The arrival of cloud computing technology promises innovative solutions to the problems inherent in existing vehicular ad hoc network (VANET) networks. Because of the highly dynamic nature of these networks in crowded conditions, some network performance improvements are needed to anticipate and disseminate reliable traffic information. Although several approaches have been proposed for the dissemination of data in the vehicular clouds, these approaches rely on the dissemination of data from conventional clouds to vehicles, or vice versa. However, anticipating and delivering data, in a proactive way, based on query message or an event driven has not been defined so far by these approaches. Therefore, in this paper, a VANET‐Cloud layer is proposed for traffic management and network performance improvements during congested conditions. For the traffic management, the proposed layer integrates the benefits of the connected sensor network (CSN) to collect traffic data and the cloud infrastructure to provide on‐demand and automatic cloud services. In this work, traffic services use a data exchange mechanism to propagate the predicted data using a fuzzy aggregation technique. In the evaluation phase, simulation results demonstrate the effectiveness of the proposed VANET‐Cloud layer to dramatically improve traffic safety and network performance as compared with recent works.     

A survey on personality-aware recommendation systems

With the emergence of personality computing as a new research field related to artificial intelligence and personality psychology, we have witnessed an unprecedented proliferation of personality-aware recommendation systems. Unlike conventional recommendation systems, these new systems solve traditional problems such as the cold start and data sparsity problems. This survey aims to study and systematically classify personality-aware recommendation systems. To the best of our knowledge, this survey is the first that focuses on personality-aware recommendation systems. We explore the different design choices of personality-aware recommendation systems, by comparing their personality modeling methods, as well as their recommendation techniques. Furthermore, we present the commonly used datasets and point out some of the challenges of personality-aware recommendation systems.

     

Use of Photothermally Generated Seebeck Voltage for Thermal Characterization of Thermoelectric Materials

A simple and accurate experimental procedure to measure simultaneously the thermal properties (conductivity, diffusivity, and effusivity) of thermoelectric (TE) materials using their Seebeck voltage is proposed. The technique is based on analysis of a periodically oscillating thermoelectric signal generated from a TE material when it is thermally excited using an intensity-modulated laser source. A self-normalization procedure is implemented in the presented method using TE signals generated by changing the laser heating from one side to another of the TE material. Experiments are done on a polyaniline carbon nanohybrid (6.6 wt.% carbon nanotubes), yielding a thermal conductivity of 1.106 ± 0.001 W/m-K. The results are compared with the results from photothermal infrared radiometry experiments.     

Two-dimensional modeling of electrochemical and transport phenomena in the porous structures of a PEMFC

A two-dimensional CFD model of PEM fuel cell is developed by taking into account the electrochemical, mass and heat transfer phenomena occurring in all of its regions simultaneously. The catalyst layers and membrane are each considered as distinct regions with finite thickness and calculated properties such as permeability, local protonic conductivity, and local dissolved water diffusion. This finite thickness model enables to model accurately the protonic current in these regions with higher accuracy than using an infinitesimal interface. In addition, this model takes into account the effect of osmotic drag in the membrane and catalyst layers. General boundary conditions are implemented in a way taking into consideration any given species concentration at the fuel cell inlet, such as water vapor which is a very important parameter in determining the efficiency of fuel cells. Other operating parameters such as temperature, pressure and porosity of the porous structure are also investigated to characterize their effect on the fuel cell efficiency.