The estimation of the junction temperature (Tj) is very important factor for improving the reliability and efficiency of the power electronic converters. A new electro-thermal (ET) model of low voltage power MOSFET is described in this paper. The electro-thermal model allows fast estimation of the junction temperature, based on the transient thermal impedances (Zth) using the (RC) Foster thermal network model and total power losses. The parameters of the (RC) Foster thermal network model are extracted from the data provided by the manufacturer’s datasheet using particle swarm optimization (PSO) method. Moreover, a dc/dc Buck converter is also analyzed by simulation to evaluate the electro-thermal model. The simulation results indicate a good agreement between the proposed model and manufacturer’s data. Finally, the electro-thermal (ET) model simulation using this (RC) Foster thermal network model shows a reasonable accuracy for estimating the junction temperature in a Dc/Dc buck converter.

In the oil and gas industry, it is common to use gas liquefaction that allows storage and transport of large quantities of LNG and LPG. One of the main disadvantages of this storage mode is the BLEVE risk, which remains a major concern for risk decision-makers. In order to prevent the occurrence of this risk and reduce its impact, risk analysts often use quantitative risk analysis (QRA), which is based on the understanding and quantification of the accidental phenomena and their consequences (overpressure, thermal radiation, toxicity dose). QRA is a rigorous and advanced approach that requires reliable data in order to obtain a good estimate and control of risks. The main objective of this paper (Part II) is to integrate the Sedov-Taylor model developed in Part I into the QRA approach in order to evaluate BLEVE blast effect, and illustrate it with a case study on a pressurized LPG accumulator located in the MPP3-plant of SONATRACH company in the Hassi R’Mel gas field (the largest gas field in Algeria). A parametric analysis of the fuel mass, temperature at failure and rupture pressure is carried out to study their influence on the evolution of BLEVE overpressure. In addition, the evaluation of BLEVE thermal effect is performed in order to better realize an exhaustive QRA. Through this application, the results show the great relevance of the Sedov-Taylor model in the consequence analysis and also in the development of process safety recommendations.

Field observations and sedimentological analyses of alluvial terraces of the O. Gourzi (Batna, NE Algeria) lead us to consider sediments as dominated by clayey and silty-sandy fractions overlain by gravel and calcareous coarser fractions. Moderate CaO3 contents would have resulted from the dissolution of the nearby carbonate relieves. They are mainly composed of Maastrichtian limestones. The distribution of the mineral fraction led us to identify 07 levels including horizons of coarse fractions alternating with layers rich in sand and silt with a roughly constant clay fraction through the stratigraphic column. Kurtosis values, frequency histograms of a prokurtic type, rarily mesokurtic, mark a constant power mode for the transport agent. Classification indices indicate poorly- to moderately sorted material, indicating a turbiditic depositional environment. Quartz grain nature and morphoscopy refer to Miocene sandstones as a potential origin. The ferruginous coating is due to the initiating pedogenesis.

In this work, we present a comprehensive investigation of JL-GAA MOSFET including degradation-related ageing effects to study the nanoscale JL-GAA MOSFET reliability against the ageing phenomenon. A quantitative analysis of the device reliability behavior is carried out, in order to show the impact of the ageing effects on the device performance for digital applications. Moreover, the effect of the stress time on the device subthreshold behavior including the threshold voltage, DIBL and swing factor is elucidated, where the degradation related-ageing effects is represented by a new current generator in the opposite direction that describes the exponential degradation of the current as function of the stress time. Further, the role of introducing a high-k layer on the gate oxide in improving the JL-GAA MOSFET immunity against the degradation-related ageing effects is analyzed, where the proposed structure exhibits an excellent immunity against the ageing effects. In order to show the impact of the proposed approach on the nanoelectronic circuits designing, the developed model has been implemented to study the performance behavior of voltage amplifier circuit including degradation-related ageing effects. Therefore, the proposed approach can offer new insights regarding the investigation and simulation of the nanoelectronic circuits including the degradation-related ageing effects.

This paper presents a hybrid strategy combining compact analytical models of short channel Gate-All-Around Junctionless (GAAJ) MOSFET and metaheuristic-based approach for parameters optimization. The proposed GAAJ MOSFET design includes highly extension regions doping. The aim is to investigate the impact of this design on the RF and analog performances systematically and to show the immunity behavior against the short channel effects (SCEs) degradation. In this context, an analytical model via the meticulous solution of 2D Poisson equation, incorporating source/drain (S/D) extensions effect, has been developed and verified by comparing it with TCAD simulation results. A comparative evaluation between the proposed GAAJ MOSFET structure and the classical device in terms of RF/Analog performances is also investigated. The proposed design provides RF/Analog performances improvement. Furthermore, based on the presented analytical models, Genetic Algorithms (GA) optimization approach is used to optimize the design of S/D parameters. The optimized structure exhibits better performances, i.e., cut-off frequency and drive current are improved. Besides, it shows superior immunity behavior against the RF/Analog degradation due to the unwanted SCEs. The insights offered by the proposed paradigm will help to enlighten designer in future challenges facing the GAAJ MOSFET technology for high RF/analog applications.

In this paper a dynamic tracking control of mobile robot using neural network global fast sliding mode (NN-GFSM) is presented. The proposed strategy combines two control approaches, kinematic control and dynamic control. The laws of kinematic control are based on GFSM in order to determine the adequate velocities for the system stability in finite time. The dynamic controller combines two control techniques, the GFSM to stabilize the velocities errors, and a neural network controller in order to approximate a nonlinear function and to deal the disturbances. This dynamic controller allows the robots to follow the desired trajectory even in the presence of disturbances. The designed controller is dynamically simulated by using Matlab/ Simulink and the simulations results show the efficiency and robustness of the proposed control strategy.