Predicting the Bubble-Point Pressure and Formation-Volume-Factor of Worldwide Crude Oil Systems

This paper presents models for predicting the bubble-point pressure (P_b) and oil formation-volume-factor at bubble-point (B_ob) for crude oil samples collected from several regions around the world. The regions include major producing oil fields in North and South America, North Sea, South East Asia, Middle East, and Africa. The model was developed using artificial neural networks with 5200 experimentally obtained PVT data sets. This represents the largest data set ever collected to be used in developing P_b and B_ob models. An additional 234 PVT data sets were used to investigate the effectiveness of the neural network models to predict outputs from inputs that were not used during the training process. The network model is able to predict the bubble-point pressure and the oil formation-volume-factor as a function of the solution gas-oil ratio, the gas relative density, the oil specific gravity, and the reservoir temperature. In order to obtain a generalized accurate model, back propagation with momentum for error minimization was used. The accuracy of the models developed in this study was compared in details with several published correlations. This study shows that if artificial neural networks are successfully trained, they can be excellent reliable predictive tools to estimate crude oil properties better than available correlations. The network models can be easily incorporated into any reservoir simulators and/or production optimization software.     

Characterization of RF sputtered thin film potassium sodium niobate (KNN) with silicon and nickel electrodes

A low cost recipe for thin film deposition of Potassium Sodium Niobate, (Na,K)NbO₃ (KNN) is pursued. The use of expensive noble metals as electrodes was avoided and instead highly doped silicon was used for both the structural layer and the bottom electrode. Nickel was used for the top electrode. In order to evaluate the outcome, the films were studied in terms of stoichiometry, crystal structure and leakage current density. RF sputtering of thin films of KNN at room temperature was successfully done. Proper crystal structure (Perovskite structure) was achieved after post deposition annealing. Though the leakage current density exhibited high dependency on the polarity of the applied voltage, a leakage current density of 1 × 10⁻⁶ A/cm² at 100 kV/cm was measured. A stoichiometry study revealed that the relative ratio of the volatile elements (Na and K) in the samples was within the acceptable range, however, a total loss of about 25–33 % was observed.

     

Compensation schemes and performance analysis of jointly nonlinear amplifier and timing errors for CP-OFDM based cognitive radio networks

The principal objective of cognitive radio (CR) networks is to configure and share dynamically the spectrum resources in order to avoid user interference and congestion. This goal is limited by the effect of errors synchronization between primary and secondary users. In this paper, we study the impact of the asynchronism on the cyclic prefix-based orthogonal frequency division multiplexing modulation (CP-OFDM) including nonlinear HPA model. The considered system includes a reference primary user perfectly synchronized with its reference base station and Nsu interfering secondary users. We provide a new theoretical aspect of interference analysis in the context of the OFDM based CR network. Furthermore, on the basis of this analysis, we derive the accurate expression of bit error rate in the presence of a Rayleigh flat fading channel. Finally, to solve the problems of asynchronism and nonlinearity, a hybrid iterative method of compensation and parallel interference cancellation have been developed based on these two conditions.

     

A Sliding Mode Multiobserver Based on an Uncoupled Multimodel: An Application on a Transesterification Reaction

This paper concerns the design of robust sliding mode multiobserver for nonlinear systems. A discrete uncoupled multimodel structure is retained for the modeling of nonlinear systems. Unlike the classically used multimodel structures, the retained uncoupled multimodel is known by its flexibility of modeling, thus, the structures of the partial models are adapted to the complexity of the local models in each operating zone. Sufficient conditions are provided, in terms of linear matrix inequalities (LMIs), to ensure the asymptotic stability of the proposed sliding mode multiobserver. A convergence analysis is achieved to obtain the convergence radius. A numerical example and a real time application on a transesterification reactor are carried out to illustrate, once again, the performance of the proposed sliding mode multiobserver in terms of precision and rapidity of convergence.     

Sliding wear transition for the CW614 brass alloy

Dry sliding wear tests were performed on a CW614 brass alloy using a pin-on-ring configuration. Wear kinetics were measured within a load range of 20–80 N and sliding velocity ranging from 1 to 7 m/s. Chemical compositions, morphologies and microstructures of worn surfaces and wear debris were characterised by scanning electron microscope (SEM) and energy dispersive X-ray spectrometer (EDS). Two main wear regimes have been observed: severe wear and mild wear. The results of wear tests and metallographic investigations on worn surfaces have been summarised in a wear mechanism map. It was found that the wear transition is controlled by a critical temperature at the contact surface.     

An optimization strategy based on a metamodel applied for the prediction of the initial blank shape in a deep drawing process

The transformation of the sheet into a product without failure and excess of material in a deep drawing operation means that the initial blanks should be correctly designed. Therefore, the initial blank design is a critical step in deep drawing design procedure. Consequently, an easy approach for engineers in predicting the initial blank shape is necessary to reduce wastage in material and to overcome the large time consumed in the classical approaches. Thus, the aim of the present investigation is to propose an automatic procedure for the quick sheet metal forming optimization. In fact, a metamodel will be build based on artificial neural networks which will be coupled then with an optimization procedure in order to predict the initial blank shape in a rectangular cup deep drawing operation. The metamodel is built from the finite element simulations using ABAQUS commercial code. This procedure allows a significant reduce of the CPU time compared to classical optimization one. The results show that the desired shape is in good agreement with the one calculated using the optimized blank shape.     

A systematic design of emulators for multivariable non square and nonlinear systems

In this paper, multimodel and neural emulators are proposed for uncoupled multivariable nonlinear plants with unknown dynamics. The contributions of this paper are to extend the emulators to multivariable non square systems and to propose a systematic method to compute the multimodel synthesis parameters. The effectiveness of the proposed emulators is shown through two simulation examples. The obtained results are very satisfactory, they illustrate the performance of both emulators and show the advantages of the multimodel emulator relatively to the neural one.     

Almost Sure Practical Exponential Stability of Nonlinear Disturbed Stochastic Systems with Guaranteed Decay Rate

In this paper, we consider nonlinear stochastic differential equations driven by multiplicative noises and affected by exogenous disturbances. Sufficient conditions are investigated for almost sure practical exponential stability of the non trivial solutions of these equations. A lower bound of the decay rate of these solutions is guaranteed.     

Aqueous hydrazine borane N2H4BH3 and nickel-based catalyst: An effective couple for the release of hydrogen in near-ambient conditions

Nickel-based bimetallic catalysts were screened using the sodium borohydride NaBH₄ hydrolysis and the aqueous hydrazine borane N₂H₄BH₃ dehydrogenation. A total of 22 bimetallic catalysts were synthesized according to an easy process while focusing on metals like Fe, Co, Ni, Cu, Rh, Pd, Ag, Ir, Pt and Au. In the end, the bimetallic candidate Ni_87.5Pt_12.5 showed to be the most active and the most selective for the dehydrogenation of N₂H₄BH₃. At 70?°C, it is able to decompose N₂H₄BH₃ into 5.8 equivalents of H₂+N₂ in less than 12?min such as: N₂H₄BH₃?+?3H₂O?→?0.95 N₂?+?0.1 NH₃?+?B(OH)₃?+?4.85H₂. Durability and stability tests were also performed. In our conditions, Ni_87.5Pt_12.5 was found to suffer from small loss of performance because of an electronic evolution of the catalytic surface leading to modified sorption properties of the catalytic sites. Our main results are reported and discussed herein.