On global Hessenberg based methods for solving Sylvester matrix equations

In the first part of this paper, we investigate the use of Hessenberg-based methods for solving the Sylvester matrix equation $AX+XB=C$. To achieve this goal, the Sylvester form of the global generalized Hessenberg process is presented. Using this process, different methods based on a Petrov–Galerkin or on a minimal norm condition are derived. In the second part, we focus on the SGl-CMRH method which is based on the Sylvester form of the Hessenberg process with pivoting strategy combined with a minimal norm condition. In order to accelerate the SGl-CMRH method, a preconditioned framework of this method is also considered. It includes both fixed and flexible variants of the SGl-CMRH method. Moreover, the connection between the flexible preconditioned SGl-CMRH method and the fixed one is studied and some upper bounds for the residual norm are obtained. In particular, application of the obtained theoretical results is investigated for the special case of solving linear systems of equations with several right-hand sides. Finally, some numerical experiments are given in order to evaluate the effectiveness of the proposed methods.     

Application of GA-Optimized ANNs to Predict the Water Content,CO2 and H2S Absorption Capacity of Diethanolamine (DEA) in Khangiran Gas Sweetening Plant

Theoretical Foundations of Chemical Engineering - In this work, with the aim of accurate prediction of water content, H2S and CO2 absorption capacity of diethanolamine (DEA) solvent in Khangiran...     

Bond graph modeling,design and experimental validation of a photovoltaic/fuel cell/ electrolyzer/battery hybrid power system

This work presents a complete bond graph modeling of a hybrid photovoltaic-fuel cell-electrolyzer-battery system. These are multi-physics models that will take into account the influence of temperature on the electrochemical parameters. A bond graph modeling of the electrical dynamics of each source will be introduced. The bond graph models were developed to highlight the multi-physics aspect describing the interaction between hydraulic, thermal, electrochemical, thermodynamic, and electrical fields. This will involve using the most generic modeling approach possible for managing the energy flows of the system while taking into account the viability of the system. Another point treated in this work is to propose. In this work, a new strategy for the power flow management of the studied system has been proposed. This strategy aims to improve the overall efficiency of the studied system by optimizing the decisions made when starting and stopping the fuel cell and the electrolyzer. It was verified that the simulation results of the proposed system, when compared to simulation results presented in the literature, that the hydrogen demand is increased by an average of 8%. The developed management algorithm allows reducing the fuel cell degradation by 87% and the electrolyzer degradation by 65%. As for the operating time of the electrolyzer, an increment of 65% was achieved, thus improving the quality of the produced hydrogen. The Fuel Cell's running time has been decreased by 59%. With the ambition to validate the models proposed and the associated commands, the development of this study gave rise to the creation of an experimental platform. Using this high-performance experimental platform, experimental tests were carried out and the results obtained are compared with those obtained by simulation under the same metrological conditions.     

Ballistic behavior of plain and reinforced concrete slabs under high velocity impact

This work presents a numerical simulation of ballistic penetration and high velocity impact behavior of plain and reinforced concrete slabs. In this paper, we focus on the comparison of the performance of the plain and reinforced concrete slabs of unconfined compressive strength 41 MPa under ballistic impact. The concrete slab has dimensions of 675 mm × 675 mm × 200 mm, and is meshed with 8-node hexahedron solid elements in the impact and outer zones. The ogive-nosed projectile is considered as rigid element that has a mass of 0.386 kg and a length of 152 mm. The applied velocities vary between 540 and 731 m/s. 6 mm of steel reinforcement bars were used in the reinforced concrete slabs. The constitutive material modeling of the concrete and steel reinforcement bars was performed using the Johnson-Holmquist-2 damage and the Johnson-Cook plasticity material models, respectively. The analysis was conducted using the commercial finite element package Abaqus/Explicit. Damage diameters and residual velocities obtained by the numerical model were compared with the experimental results and effect of steel reinforcement and projectile diameter were studies. The validation showed good agreement between the numerical and experimental results. The added steel reinforcements to the concrete samples were found efficient in terms of ballistic resistance comparing to the plain concrete sample.     

An experimental study of forced convective heat transfer for fully developed Al 2 O 3 –water nanofluid in an annulus tube

Nanofluids have been known as practical materials to ameliorate heat transfer within diverse industrial systems. The current work presents an empirical study on forced convection effects of Al₂O₃–water nanofluid within an annulus tube. A laminar flow regime has been considered to perform the experiment in high Reynolds number range using several concentrations of nanofluid. Also, the boundary conditions include a constant uniform heat flux applied on the outer shell and an adiabatic condition to the inner tube. Nanofluid particle is visualized with transmission electron microscopy to figure out the nanofluid particles. Additionally, the pressure drop is obtained by measuring the inlet and outlet pressure with respect to the ambient condition. The experimental results showed that adding nanoparticles to the base fluid will increase the heat transfer coefficient (HTC) and average Nusselt number. In addition, by increasing viscosity effects at maximum Reynolds number of 1140 and increasing nanofluid concentration from 1% to 4% (maximum performance at 4%), HTC increases by 18%.     

Design and Implementation of a Flexible Manufacturing Control System Using Neural Network

Design and implementation of a sequential controller based on the concept of artificial neural networks for a flexible manufacturing system are presented. The recurrent neural network (RNN) type is used for such a purpose. Contrary to the programmable controller, an RNN-based sequential controller is based on a definite mathematical model rather than depending on experience and trial and error techniques. The proposed controller is also more flexible because it is not limited by the restrictions of the finite state automata theory. Adequate guidelines of how to construct an RNN-based sequential controller are presented. These guidelines are applied to different case studies. The proposed controller is tested by simulations and real-time experiments. These tests prove the successfulness of the proposed controller performances. Theoretical as well as experimental results are presented and discussed indicating that the proposed design procedure using Elman's RNN can be effective in designing a sequential controller for event-based type manufacturing systems. In addition, the simulation results assure the effectiveness of the proposed controller to outperform the effect of noisy inputs.     

Adaptive stabilization of a class of nonlinear systems using high-gain feedback

This note presents a high-gain feedback stabilizing control algorithm in which the high-gain parameter is adapted on-line. The algorithm is developed for a class of nonlinear systems which can be viewed as the nonlinear counterpart of uniform rank systems. The system can be unknown except for a number of vital pieces of information. For single-input single-output linear systems such information is usually required in the traditional adaptive control literature.     

Complex formation of montmorillonite clay with polymers. Part 2: The use of montmorillonite clay–vinyl monomer complex as a comonomer in the copolymerization reaction of styrene–acrylonitrile monomers

The bulk copolymerization of styrene–acrylonitrile monomers using styrene‐N⁺–montmorillonite complex as a comonomer in the polymerization was studied. The X‐ray diffraction (XRD) analysis showed that part of the styrene‐N⁺–montmorillonite complex remained non‐dispersed (immiscible) and the copolymer was excluded from the interlayer of the immiscible part of the clay. The successive chemical extraction process revealed that a reasonable amount of the styrene–acrylonitrile copolymer was directly attached to the styrene‐N⁺–montmorillonite complex and enveloped the clay. Highly exfoliated clay lamella and nanospheres (3–5 nm) were observed by transmission electron microscopy (TEM). The montmorillonite clay assume two different morphologies, immiscible and exfoliated, on the basis of the XRD and TEM data. A simple method of calculation of the ratio of the exfoliated/immiscible amounts of the clay indicated that the amount of the styrene‐N⁺–montmorillonite complex exfoliated into separate lamella was 40 % (w/w) of the amount of the clay samples containing 2 % of the (styrene‐N⁺–montmorillonite complex) clay. This amount of exfoliated clay decreases with the increase of the concentration of the clay. The presence of the styrene‐N⁺–montmorillonite clay in the copolymerization reaction had a minor effect on both the copolymer composition and the molecular weight. Modification of the clay with the derivatized styrene monomer can achieve a nanocomposite using a percentage no more than 4 % (w/w) of complex in the copolymer. Copyright © 2004 Society of Chemical Industry     

The development and application of a multiple wavelength illumination technique for the vision-based process monitoring of aero-structure riveting

Airframe riveting is a critical process that requires high levels of process monitoring and quality assurance due to the very high risk associated with the failure of such joints. This paper describes the development of the enabling technology developed for a machine vision-based process monitoring system. One of the key factors affecting the performance of a machine vision system is the quality of the lighting. In the application described in this paper the available lighting was severely limited by the confined space in which the system had to operate. The problem was also compounded by the reflective nature of the objects to be examined. The initial images obtained were not suitable for further processing due to the presence of significant shadows and specular reflections. A novel solution to this problem based on multiple wavelength illumination and signal processing is presented along with results from experimental trials of the approach.