Study of the Mechanical Properties of Fibers Extracted from Tunisian Agave americana L.

Agave americana L. fibers, the most abundant variety in Tunisia, have a quite important textile potential. This potential is demonstrated by studying the extraction of these fibers from leaves, their physical properties such us fineness or density and their mechanical behavior in tensile tests. In this work, results of a mechanical behavior study of fibers extracted from the Agave americana L. plant are presented. These results deal with the principal and mechanical characteristics of these fibers which are the strain at break, the elasticity modulus and the rupture facture. These results permitted to situate these fibers, compared to the other textile fibers, as materials that can be used in technical applications such as reinforcing composites or geotextile. In order to understand the mechanical properties of these fibers, a correlation study between the properties already cited and the fine structure was done. The obtained results showed that the mechanical properties of Agave americana L. fibers are closely related to the individual fibers deformations and to the natural matrix (lignin and gums) that are linked to these elementary fibers.     

Enhancing Emergency Messages Dissemination in Vehicular Networks Using Network Coding

Vehicular ad-hoc networks play an important role in providing safety on the road. Vehicles generate and exchange emergency and control messages to avoid dangerous situations. According to IEEE 1609.4 standard, all these messages share the same control channel interval even if the emergency messages are with a highest priority. Besides that, network’s characteristics, such as vehicle density and high mobility, would make the diffusion of emergency messages a challenging task. Especially with the absence of acknowledgements and retransmission. Network coding could be seen as a solution where a block of data packets could be sent on the same transmission process. Firstly, we analyze the messages’ dissemination, and we propose a thoroughly model for success probability according to the emergency messages’ generation probabilities. Further, we propose a new network coding access scheme. The emergency messages take the priority in the channel access and it could be retransmitted several times. Thus, the scheme deals with the emergency messages’ loss and latency. NS-3 simulations show that our model increases emergency messages’ reliability.

     

Effect of organic eutectic on nitrocellulose stability during artificial aging

ABSTRACT

Recently, the eutectic composition of organic binary mixtures MENA+DPA has been found to be an efficient stabilizer of nitrocellulose. However, the behavior of such new stabilizer must be further investigated, especially after a long period of storage of the energetic composition. In this study, the stabilizing effect of the eutectic MENA+DPA on NC stability during artificial aging (at 338.65 K for 120 days), compared to its pure components, has been investigated by conventional stability tests and kinetic modeling. According to Bergmann & Junk (T = 405.15 K) results and over the entire period of aging, the eutectic MENA+DPA exhibits the best stabilizing effect on NC. The vacuum stability test (T = 353.15, 363.15, 373.15, and 383.15 K) results revealed that the amount of the evolved gas of NC containing this eutectic composition is very close to that of DPA, known as the conventional stabilizer. Furthermore, the kinetic modeling on VST data, obtained at four isothermal temperatures, was performed by two different methodologies, viz, fitting and free models to determine the kinetic triplets, which have been subsequently used to predict the storage lifetime for the studied systems. It was found that the NC stabilized by the eutectic MENA+DPA presents the highest value of the activation energy and has the longest storage lifetime during the entire heating period corroborating the stability tests results and affirming the excellent stabilizing effect of this mixture with respect to its pure component even if a long storage period is expected.     

Improving the Throughput in Lightly Disturbed IEEE 802.11 DCF Saturated Network Using the Fragmentation Mechanism Under Basic Access Mode

Wireless Personal Communications - The IEEE 802.11 is the most dominating protocol in the wireless local area networks and in which, the fundamental mechanism to access the channel is called...     

MILD combustion of hydrogenated biogas under several operating conditions in an opposed jet configuration

MILD combustion of biogas takes its importance firstly from the combustion process that diminishes significantly fuel consumption and reduces emissions and secondly from the use of biogas which is a renewable fuel. In this paper, the influence of several operating conditions (namely biogas composition, hydrogen enrichment and oxidizer dilution) is studied on flame structure and emissions. The investigation is conducted in MILD regime with a special focus on chemical effects of CO₂ in the oxidizer. Opposed jet diffusion combustion configuration is adopted. The combustion kinetics is described by the Gri 3.0 mechanism and the Chemkin code is used to solve the problem.It is found that oxygen reduction has a significant effect on flame temperature and emissions while less sensitivity corresponds to hydrogen enrichment in MILD combustion regime. Temperature and species are considerably reduced by oxygen decrease in the oxidizer and augmented by hydrogen addition to the fuel. The maximum values of temperature and species are not influenced by the composition of the biogas in MILD regime. Blending biogas with hydrogen can be used to sustain MILD combustion at very low oxygen concentration in the fuel.In MILD combustion regime, the chemical effect of CO₂ in the oxidizer stream reduces considerably the flame temperature and species production, except CO which is enhanced. For high amounts of CO₂ in the oxidizer, the chemical effect of CO₂ becomes negligible.     

Improving the performance for task assignment in distributed server systems by partitioning the large tasks

Task Assignment in distributed server systems focuses on the policy that assigns the tasks reached these systems in order to improve the response time. These tasks, generally, have the property that there is a tiny fraction (about 3%) of the large tasks that makes half (50%) of the total load. However, this property creates additional problems: the large tasks make the load difficult to balance among the servers, and the small tasks will be delayed by the large ones when they are in the same queue. In this paper, we propose a new policy for the Web clusters that we call Partitioning Large Tasks (PLT) and which deals with these problems mostly under a high traffic demand and a high variability of task sizes. PLT partitions each large task into fragments and assigns them to be processed in a parallel way and completing at the same time to improve the mean response time, and separates the small tasks from the large tasks to avoid being delayed. Performance tests show a significantly improvement in performance of PLT over the existing task assignment policies.     

Localization Optimization in WSNs Using Meta-Heuristics Optimization Algorithms: A Survey

In Wireless Sensor Networks, node localization is one of the most important system parameters. Determining the exact position of nodes in these networks is one of vital and tedious tasks. This paper presents a review of the most localization methods which optimize the localization error. It provides a new taxonomy of techniques used in this field, including Mobile Anchor, Machine Learning, Matematical Models and Meta-heuristics. In this later, we survey its different algorithms such as Genetic Algorithm, Particle Swarm optimization, Ant Colony Optimization, BAT optimization algorithm, Firefly Optimization Algorithm, Flower Pollination Algorithm, Grey Wolf Optimization algorithm, Artificial Bees Colony Optimization Algorithm, Fish Swarm Optimization Algorithm and others. Further, the comparison between these metaheuristics algorithms based localization optimization is done. Finally, a comprehensive discussion of the performance parameters such as accuracy, convergence rate, energy consumption and the number of localized nodes is given.

     

Effect of the addition of H2 and H2O on the polluting species in a counter-flow diffusion flame of biogas in flameless regime

Biogas is obtained by fermentation of biomass, it is a renewable fuel and practically CO₂ neutral, offers a significant advantage compared to other fuels for its low carbon/hydrogen ratio (1 atom of carbon and 4 hydrogen atoms). Thus, the level of CO₂ emissions from biogas is lower than that of the other fuels. Biogas is a biodegradable and renewable fuel; its benefits are conjugated especially in a flameless combustion process that significantly reduces fuel consumption and polluting emissions. In this paper, we study the effects of the dilution of a mixture of the biogas BG75 (75% CH₄ and 25% CO₂) – hydrogen by a volume of water vapor ranging from 10% to 50%. The configuration of an opposed jet flame is used with a constant strain rate of 120 s^?1. The chemical kinetics is described by the Gri3.0 mechanism. It has been found that the combustion structure is very sensitive to the various parameters.     

Three-dimensional mathematical modeling of dispersed two-phase flow using class method of population balance in bubble columns

Computational fluid dynamics (CFD) simulations of bubble columns have received recently much attention and several multiphase models have been developed, tested, and validated through comparison with experimental data. In this work, we propose a model for two-phase flows at high phase fractions. The inter-phase forces (drag, lift and virtual mass) with different closure terms are used and coupled with a classes method (CM) for population balance. This in order to predict bubble’s size distribution in the column which results of break-up and coalescence of bubbles. Since these mechanisms result greatly of turbulence, a dispersed k– turbulent model is used.The results are compared to experimental data available from the literature using a mean bubble diameter approach and CM approach and the appropriate formulations for inter-phase forces in order to predict the flow are highlighted.The above models are implemented using the open source package OpenFoam.