Search results for: S. Raissi

Authors: R. Eslami Farsani, S. Raissi, A. Shokuhfar, A. Sedghi

Abstract:

In this investigation, types of commercial and special polyacrylonitrile (PAN) fibers contain sodium 2-methyl-2- acrylamidopropane sulfonate (SAMPS) and itaconic acid (IA) comonomers were studied by fourier transform infrared (FT-IR) spectroscopy. The study of FT-IR spectra of PAN fibers samples with different comonomers shows that during stabilization of PAN fibers, the peaks related to C≡N bonds and CH2 are reduced sharply. These reductions are related to cyclization of nitrile groups and stabilization procedure. This reduction in PAN fibers contain IA comonomer is very intense in comparison with PAN fibers contain SAMPS comonomer. This fact indicates the cycling and stabilization for sample contain IA comonomer have been conducted more completely. Therefore the carbon fibers produced from this material have higher tensile strength due to suitable stabilization.

Keywords: PAN Fibers, Stabilization, Carbon Fibers, FT-IR.

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Authors: Khadija Raissi, Bechir Ben Gouissem

Abstract:

In this paper, we perform the investigation of some routing protocols in Vehicular Ad-Hoc Network (VANET) context. Indeed, we study the efficiency of protocols like Dynamic Source Routing (DSR), Ad hoc On-demand Distance Vector Routing (AODV), Destination Sequenced Distance Vector (DSDV), Optimized Link State Routing convention (OLSR) and Vehicular Multi-hop algorithm for Stable Clustering (VMASC) in terms of packet delivery ratio (PDR) and throughput. The performance evaluation and comparison between the studied protocols shows that the VMASC is the best protocols regarding fast data transmission and link stability in VANETs. The validation of all results is done by the NS3 simulator.

Keywords: VANET, smart city, AODV, OLSR, DSR, OLSR, VMASC, routing protocols, NS3.

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Authors: S. Raissi, R- Eslami Farsani

Abstract:

In recent years, response surface methodology (RSM) has brought many attentions of many quality engineers in different industries. Most of the published literature on robust design methodology is basically concerned with optimization of a single response or quality characteristic which is often most critical to consumers. For most products, however, quality is multidimensional, so it is common to observe multiple responses in an experimental situation. Through this paper interested person will be familiarize with this methodology via surveying of the most cited technical papers. It is believed that the proposed procedure in this study can resolve a complex parameter design problem with more than two responses. It can be applied to those areas where there are large data sets and a number of responses are to be optimized simultaneously. In addition, the proposed procedure is relatively simple and can be implemented easily by using ready-made standard statistical packages.

Keywords: Multi-Response Surface Methodology (MRSM), Design of Experiments (DOE), Process modeling, Quality improvement; Robust Design.

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Authors: S. Raissi

Abstract:

Response surface methodology (RSM) is a very efficient tool to provide a good practical insight into developing new process and optimizing them. This methodology could help engineers to raise a mathematical model to represent the behavior of system as a convincing function of process parameters. Through this paper the sequential nature of the RSM surveyed for process engineers and its relationship to design of experiments (DOE), regression analysis and robust design reviewed. The proposed four-step procedure in two different phases could help system analyst to resolve the parameter design problem involving responses. In order to check accuracy of the designed model, residual analysis and prediction error sum of squares (PRESS) described. It is believed that the proposed procedure in this study can resolve a complex parameter design problem with one or more responses. It can be applied to those areas where there are large data sets and a number of responses are to be optimized simultaneously. In addition, the proposed procedure is relatively simple and can be implemented easily by using ready-made standard statistical packages.

Keywords: Response Surface Methodology (RSM), Design of Experiments (DOE), Process modeling, Process setting, Process optimization.

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