Djillali Mahi

A MEMS-based solid propellant microthruster array for space and military applications

Since combustion is an easy way to achieve large quantities of energy from a small volume, we developed a MEMS based solid propellant microthruster array for small spacecraft and micro-air-vehicle applications. A thruster is composed of a fuel chamber layer, a top-side igniter with a micromachined nozzle in the same silicon layer. Layers are assembled by adhesive bonding to give final MEMS array. The thrust force is generated by the combustion of propellant stored in a few millimeter cube chamber. The micro-igniter is a polysilicon resistor deposited on a low stress SiO2/SiNx thin membrane to ensure a good heat transfer to the propellant and thus a low electric power consumption. A large range of thrust force is obtained simply by varying chamber and nozzle geometry parameters in one step of Deep Reactive Ion Etching (DRIE). Experimental tests of ignition and combustion employing home made (DB+x% BP) propellant composed of a Double-Base and Black-Powder. A temperature of 250 therefore degrees C, enough to propellant initiation, is reached for 40 mW of electric power. A combustion rate of about 3.4 mm/s is measured for DB+20% BP propellant and thrust ranges between 0.1 and 3,5 mN are obtained for BP ratio between 10% and 30% using a microthruster of 100 mu m of throat wide.

Electrical and optical analysis of the electric discharge, energized by AC voltage, on polluted insulating surface

This paper presents some results serving in modeling of flashover of polluted insulators, and also in the validity test of extension mechanisms of discharge. A flashover has been established on a laboratory model simulating a polluted insulator and has been read electrical and optical parameters in different points of the discharge path. Inspired by the previous works, optical results shown weak light intensity of the discharge comparable to streamers; these streamers could be used as forerunners of discharges that end to a flashover. This subject, besides its scientific relevance, is likely to have economic effects in the field of electrical energy distribution networks equipment.

Neural networks and fuzzy logic approaches to predict mechanical properties of XLPE insulation cables under thermal aging

The widespread use of cross-linked polyethylene (XLPE) as insulation in the manufacturing of medium- and high-voltage cables may be attributed to its outstanding mechanical and electrical properties. However, it is well known that degradation under service conditions is the major problem in the use of XLPE as cable insulation. Laboratory investigations of the insulations aging are time-consuming and cost-effective. To avoid such costs, we have developed two models which are based on artificial neural networks (ANNs) and fuzzy logic (FL) to predict the insulation properties under thermal aging. The proposed ANN is a supervised one based on radial basis function Gaussian and trained by random optimization method algorithm. The FL model is based on the use of fuzzy inference system. Both models are used to predict the mechanical properties of thermally aged XLPE. The obtained results are evaluated and compared to the experimental data in depth by using many statistical parameters. It is concluded that both models give practically the same prediction quality. In particular, they have ability to reproduce the nonlinear behavior of the insulation properties under thermal aging within acceptable error. Furthermore, our ANN and FL models can be used in the generalization phase where the prediction of the future state (not reached experimentally) of the insulation is made possible. Additionally, costs and time could be reduced.

Structural and electronic properties of doped oligothiophenes in the presence of p‑toluenesulfonate acids

We investigate the geometric and electronic structure of singly oxidized oligothiophenes in the presence of the counterion named p-toluenesulfonate acid (p-TSA) by performing ab initio density functional theory calculations using Becke-Half-and-Half-Lee-Yang-and-Parr hybrid functional on chains of up to 12 thiophene rings. Different possibilities of positioning the counterion along the conjugated chain are studied. The calculations indicate that the side orientation is the most stable structure of pTh/p-TSA complex. Further, the influence of the counterion on the charge distribution and structural geometry of charged oligothiophenes is also investigated. In the last part of the work, the solid-state packing effects are considered by studying the stacking of two conjugated chains in the presence of two counterions. Our results are consistent with several experimental observations on similar conjugated polymers.

Application of the analytical arc parameters on the dynamic modeling of HVDC flashover of polluted insulators

This paper presents a dynamic model of dc pollution flashover using analytical relationship of arc parameter (A and N). The model takes account the physical and electrical characteristics of the discharge and the pollution layer. Using the impedance criterion for the discharge propagation and the energy balance criterion for estimating the displacement, we simulate the dynamic behavior of current, discharge temperature and discharge resistance. The results of calculation are close to the experimental ones.

DC-DC Converters Modelling Approach Using Spectral Decomposition Theorem

Abstract DC–DC converters are nonlinear systems that exhibit a complicated nonlinear phenomena, its modelling presents the basic step of its analysis and control. In this work, we propose a discrete modelling technique that allows an accurate description of the converter behaviour with a minimum of simplifying assumptions and validity hypothesis. The proposed method validation is achieved by means of simulation and a comparative study results.

Modeling flashover voltage (FOV) of polluted HV insulators using artificial neural networks (ANNs)

This paper attempts to apply artificial intelligent techniques in high voltage applications and especially to estimate the critical flashover voltage (FOV) for polluted insulators, using experimental measurements carried out in an insulator test station according to the IEC norm and a mathematical model based on the characteristics of the insulator: the diameter, the height, the creepage distance, the form factor and the equivalent salt deposit density and estimates the critical flashover voltage. Two types of artificial neural networks (ANNs) are designed to establish a nonlinear model between the above mentioned characteristics and the critical flashover voltage. The ANNs models, algorithms, and tools have been developed using the software package Matlab. The obtained results are promising and insure that artificial intelligent techniques can estimate the critical flashover voltage for new designed insulators with different operating conditions and constitute an indispensable models that can be used in field simulations of various parameters for polluted insulators. Further comparative analysis of the estimated results with the measured data collected from the site measurement amply demonstrate the effectiveness of the use of artificial intelligent techniques for modeling (ANNs) of FOV.

Electrostatic interference calculation from H-V power lines to aerial pipelines using hybrid PSO - CSM approach

The objective of the work presented in this paper was the study of the electrostatic interference induced by high-voltage power lines, on the aerial pipeline. The induced voltages can affect the operating personnel, pipeline associated equipment, cathodic protection systems. The calculation of the induced voltages is typically done for personnel safety reasons, in order to ensure that induced voltages are not hazardous to someone in contact with the pipeline. Quite often, mitigation is required to reduce these induced voltages to levels under the safe threshold, in this calculation, a combination of particle swarm optimization (PSO) and Charge Simulation Method (CSM) is proposed. PSO is a population-based stochastic optimization algorithm modeled after the simulation of the social behavior of bird flocks and animal hordes, the optimum allocations of the simulating charges can be obtained using PSO. The simulation results obtained were analyzed and compared with those obtained using the admittance technique.

Optimized Sliding Mode Control of DC-DC Boost Converter for Photovoltaic System

DC–DC converters are an important element in photovoltaic systems to attain desired level of energy and to shape it according to the demand. This paper proposes new optimized sliding mode controller (SMC) with fixed switching frequency for a boost converter to step up a fluctuating solar panel voltage to a higher constant DC voltage. Based on the converter functioning principle, a sliding mode controller (SMC) is proposed. Then, a method for SMC parameters selection using simplex and PSO techniques is given. The simplex method allows obtaining the admissible ranges for SMC parameters while taking into account practical considerations about the converter. Then, theses ranges will be used by the particle swarm optimization technique (PSO) to find optimal values for controller parameters.

New HVDC flashover of polluted insulators -dynamic modeling-

This study presents the improved flashover dynamic model based on both, impedance criterion for the discharge propagation and energy balance criterion for estimating the discharge displacement. One main contribution in this paper is that our model its enabling to predict the instantaneous changes of the discharge characteristic such as leakage current, discharge temperature, arc resistance and also the temporal evolution of their analytics parameters (A, N). To demonstrate the efficiency of the developed model we applied it for flat plat insulators model which are polluted only with NaCl. Taking advantage of the designed model, we originate to take into account the majority of physical and thermal discharge properties such as analytics parameters (we elsewhere presented) and a particular solution of Elenbaas-Heller equation that has been proposed by Frank-Kamenetski and the temperature parameter. Of particular interest, the previous parameter (i.e., temperature) which is the most preponderant factor in our model has not been treated above in the literature for dynamic model. Finally, the obtained computer simulations are in good agreement with the experimental results.