Some physical properties of alkali borate tungstate glasses containing iron

A series of borotungstate glasses was prepared. The glass formation was confirmed by using X-ray diffraction measurements on the powder samples then measured using Mo¨ssbauer, differential thermal analysis (DTA), infra-red (IR) and d.c. conductivity. The iron in the alkali borate tungstate glass was found in the ferric state only. The introduction of tungsten to replace 25 mol % sodium tetraborate in the glass samples caused a little shift in the IR bands toward the lower frequency. The iron ions may act as a glass modifier whereas the tungsten ions may act as network former. The electrical conduction increased in the presence of tungsten due to the hopping mechanism between the two sites of tungsten (W⁵⁺, W⁶⁺).     

Generalized magneto-thermoviscoelastic plane waves under the effect of rotation without energy dissipation

A new model of the equations of generalized thermoviscoelasticity for a thermally, isotropic and electrically conducting half-space solid whose surface is subjected to a thermal shock is given. The formulation is applied to the generalized thermoelasticity based on the Green and Naghdi (GN) theory under the effect of rotation, where there is an initial magnetic field parallel to the plane boundary of the half-space. The medium is deformed because of thermal shock and due to the application of the magnetic field, it results in induced magnetic and electric fields in the medium. The normal mode analysis is used to obtain the expressions for the variables considered. The distributions of temperature, displacement, stress, induced magnetic and electric fields are represented graphically. Comparisons are made with the results predicted by the types II and III in the presence and absence of rotation.     

Analysis of phenols and nitrophenols in rainwater collected simultaneously on an urban and rural site in east of France

The behaviour of phenols and nitrophenols in the atmosphere is of concern for environmental research as these are known to be toxic to humans and wildlife. To increase the knowledge about these compounds, the concentrations of 20 phenols and nitrophenols in rainwater were studied in an urban (Strasbourg) and a rural (Erstein) site in Eastern France.The wet rain samples were collected on a weekly basis between January 2002 and July 2003, and analyzed for phenols and nitrophenols using SPME and gas chromatography coupled to mass spectrometry. The compounds were derivatized with MDBSTFA directly in the injection port of the gas chromatograph.Total concentrations ranged from 0 to 1383 µg L^− 1 in Strasbourg and from 0 to 1215 µg L^− 1 in Erstein. These concentrations are in the same range than those measured in other studies, but considerably higher than the concentrations measured for pesticides (about 10 times) and polycyclic aromatic hydrocarbons (about 1000 times) on the same sites and at the same period.Phenols, except for o-cresol, were generally less concentrated than nitrophenols. o-Cresol was one of the major compounds, probably due to its role as raw material in pesticide production. The concentrations of phenols and nitrophenols were found to vary with time. No seasonal trend was observed, but significant correlations with rainfall amount were identified.     

Efficient metaheuristics for pick and place robotic systems optimization

This paper deals with a pick and place robotic system design problem. The objective is to present an efficient method which is able to optimize the performances of the robotic system. By defining the suitable combination of scheduling rules, our method allows each robot to perform the assigned pick and place operations in real time in order to maximize the throughput rate. For that, we have developed different resolution methods which define the scheduling rule for each robot in order to seize the products from the first side of the system and to place them on the second side. We suggest three metaheuristics which are the ant colony optimization, the particle swarm optimization and the genetic algorithm. Then, we try to select the best algorithm which is able to get the best solutions with the lowest execution times. This is the main advantage of our methods compared to exact methods. This fact represents a great interest taking in consideration that our methods must respect a strong industrial constraint regarding the functioning of a real industrial robotic system. This constraint states that the answer time to manage the seizing strategies of the robots must be less than 1 second. Numerical results show that the different algorithms perform optimally for the tested instances in a reasonable computational time.     

Efficient bi-objective ant colony approach to minimize total tardiness and system unavailability for a parallel machine scheduling problem

In recent years, decision makers give more importance to the maintenance function, viewing its substantial contribution to business productivity. However, most literature on scheduling studies does not take into account maintenance planning when implementing production schedules. The achievement of production plan without taking into account maintenance activities increases the probability of machine breakdowns, and inversely, considering maintenance actions in production planning elongates the achievement dates of orders and affects deadlines. In this paper, we propose a bi-objective model to deal with production scheduling and maintenance planning problems simultaneously. The performance criteria considered for production and maintenance are, respectively, the total tardiness and the unavailability of the production system. The start times of preventive maintenance actions and their number are not fixed in advance but considered, with the execution dates of production tasks, as decisions variables of the problem. The solution of the integrated model is based on multi-objective ant colony optimization approach. The proposed algorithm (Pareto ant colony optimization) is compared, on the basis of several metrics, with well-known multi-objective genetic algorithms, namely NSGA-II and SPEA 2, and a hybrid particle swarm optimization algorithm. Interesting results are obtained via empirical study.     

Investigation on microwave absorption characteristics of ternary MWCNTs/CoFe2O4/FeCo nanocomposite coated with conductive PEDOT-Polyaniline Co-polymers

In this study, ternary MWCNTs/CoFe₂O₄/FeCo nanocomposite coated with conductive PEDOT-polyaniline (PA@MW/F/C) co-polymers were synthesized by microwave-assisted sol-gel followed in-situ polymerization methods. The phases, crystal structures, morphologies, magnetic and electromagnetic features of the as-prepared samples were identified via XRD, SEM, XPS, VSM, and VNA respectively. Absorption characteristics were investigated in the frequency (12–18 GHz) Ku band. XRD, VSM and SEM analysis confirmed the partial reduction process of CoFe₂O₄ and successfully decorated magneto-dielectric particles with co-polymers. By measuring electromagnetic features of the samples, it was found that coating magneto-dielectric particles with conductive co-polymers improved the permittivity and dielectric constant, accordingly affecting the impedance matching characteristic and attenuation constant performance. Moreover, exchange coupling behavior was found significant impacts on the microwave absorption properties. PA@MW/F/C coated nanocomposite revealed the maximum reflection loss of ?90 dB at 13.8 GHz with 4 GHz effective bandwidth and 1.5 mm thickness. Due to the enhanced interfacial polarization, impedance matching and exchange coupling effects of the as-prepared nanocomposite, it owns excellent microwave absorption properties, which can be applied as an absorber with distinguishing features (strong absorption, thin thickness, and broadest effective bandwidth).