A one-dimensional prescribed curvature equation modeling the corneal shape

We prove existence, uniqueness, and stability of solutions of the prescribed curvature problem (u'/root 1 + u'(2))' = au - b/root 1 + u'(2) in [0, 1], u'(0) = u(1) = 0, for any given a > 0 and b > 0. We also develop a linear monotone iterative scheme for approximating the solution. This equation has been proposed as a model of the corneal shape in the recent paper (Okrasinski and Plociniczak in Nonlinear Anal., Real World Appl. 13:1498-1505, 2012), where a simplified version obtained by partial linearization has been investigated.

Complex evolution of a multi-particle system

This paper studies a discrete dynamical system of interacting particles that evolve by interacting among them. The computational model is an abstraction of the natural world, and real systems can range from the huge cosmological scale down to the scale of biological cell, or even molecules. Different conditions for the system evolution are tested. The emerging patterns are analysed by means of fractal dimension and entropy measures. It is observed that the population of particles evolves towards geometrical objects with a fractal nature. Moreover, the time signature of the entropy can be interpreted at the light of complex dynamical systems.

Fractional order modelling of zero length column desorption response for adsorbents with variable particle sizes

This manuscript analyses the data generated by a Zero Length Column (ZLC) diffusion experimental set-up, for 1,3 Di-isopropyl benzene in a 100% alumina matrix with variable particle size. The time evolution of the phenomena resembles those of fractional order systems, namely those with a fast initial transient followed by long and slow tails. The experimental measurements are best fitted with the Harris model revealing a power law behavior.

Dynamical behaviour of multi-particle large-scale systems

Collective behaviours can be observed in both natural and man-made systems composed of a large number of elemental subsystems. Typically, each elemental subsystem has its own dynamics but, whenever interaction between individuals occurs, the individual behaviours tend to be relaxed, and collective behaviours emerge. In this paper, the collective behaviour of a large-scale system composed of several coupled elemental particles is analysed. The dynamics of the particles are governed by the same type of equations but having different parameter values and initial conditions. Coupling between particles is based on statistical feedback, which means that each particle is affected by the average behaviour of its neighbours. It is shown that the global system may unveil several types of collective behaviours, corresponding to partial synchronisation, characterised by the existence of several clusters of synchronised subsystems, and global synchronisation between particles, where all the elemental particles synchronise completely.

Task-based occupational exposure assessment and particle number concentration: two important data resources to perform risk assessment for occupational exposure to particles

Environment monitoring has an important role in occupational exposure assessment. However, due to several factors is done with insufficient frequency and normally don´t give the necessary information to choose the most adequate safety measures to avoid or control exposure. Identifying all the tasks developed in each workplace and conducting a task-based exposure assessment help to refine the exposure characterization and reduce assessment errors. A task-based assessment can provide also a better evaluation of exposure variability, instead of assessing personal exposures using continuous 8-hour time weighted average measurements. Health effects related with exposure to particles have mainly been investigated with mass-measuring instruments or gravimetric analysis. However, more recently, there are some studies that support that size distribution and particle number concentration may have advantages over particle mass concentration for assessing the health effects of airborne particles. Several exposure assessments were performed in different occupational settings (bakery, grill house, cork industry and horse stable) and were applied these two resources: task-based exposure assessment and particle number concentration by size. The results showed interesting results: task-based approach applied permitted to identify the tasks with higher exposure to the smaller particles (0.3 μm) in the different occupational settings. The data obtained allow more concrete and effective risk assessment and the identification of priorities for safety investments.

In-situ X-ray diffraction studies during growth of Ni-Ti shape memory alloy films and their complementary ex-situ characterization

Shape Memory Alloy (SMA) Ni-Ti films have attracted much interest as functional and smart materials due to their unique properties. However, there are still important issues unresolved like formation of film texture and its control as well as substrate effects. Thus, the main challenge is not only the control of the microstructure, including stoichiometry and precipitates, but also the identification and control of the preferential orientation since it is a crucial factor in determining the shape memory behaviour. The aim of this PhD thesis is to study the optimisation of the deposition conditions of films of Ni-Ti in order to obtain the material fully crystallized at the end of the deposition, and to establish a clear relationship between the substrates and texture development. In order to achieve this objective, a two-magnetron sputter deposition chamber has been used allowing to heat and to apply a bias voltage to the substrate. It can be mounted into the six-circle diffractometer of the Rossendorf Beamline (ROBL) at the European Synchrotron Radiation Facility (ESRF), Grenoble, France, enabling an in-situ characterization by X-ray diffraction(XRD) of the films during their growth and annealing. The in-situ studies enable us to identify the different steps of the structural evolution during deposition with a set of parameters as well as to evaluate the effect of changing parameters on the structural characteristics of the deposited film. Besides the in-situ studies, other complementary ex-situ characterization techniques such as XRD at a laboratory source, Rutherford backscattering spectroscopy(RBS), Auger electron spectroscopy (AES), cross-sectional transmission electron microscopy (X-TEM), scanning electron microscopy (SEM), and electrical resistivity (ER) measurements during temperature cycling have been used for a fine structural characterization. In this study, mainly naturally and thermally oxidized Si(100) substrates, TiN buffer layers with different thicknesses (i.e. the TiN topmost layer crystallographic orientation is thickness dependent) and MgO(100) single crystals were used as substrates. The chosen experimental procedure led to a controlled composition and preferential orientation of the films. The type of substrate plays an important role for the texture of the sputtered Ni-Ti films and according to the ER results, the distinct crystallographic orientations of the Ni-Ti films influence their phase transformation characteristics.

Particle swarm optimization: dynamical analysis through fractional calculus

This chapter considers the particle swarm optimization algorithm as a system, whose dynamics is studied from the point of view of fractional calculus. In this study some initial swarm particles are randomly changed, for the system stimulation, and its response is compared with a non-perturbed reference response. The perturbation effect in the PSO evolution is observed in the perspective of the fitness time behaviour of the best particle. The dynamics is represented through the median of a sample of experiments, while adopting the Fourier analysis for describing the phenomena. The influence upon the global dynamics is also analyzed. Two main issues are reported: the PSO dynamics when the system is subjected to random perturbations, and its modelling with fractional order transfer functions.

Friction and wear in thrust ball bearings lubricated with biodegradable greases

Thrust ball bearings lubricated with several different types of grease, including three biodegradable low-toxicity greases, were tested in a modified four-ball machine in order to evaluate the bearing friction torque. At the end of each test, grease samples were obtained and analysed through ferrography, allowing the quantification and evaluation of the bearing wear. In order to compare the grease performance in terms of friction and wear, a correlation between the grease characteristics (base oil, bleed oil, thickener structure, and rheological parameters) and the experimental results was established.

On the use of particle swarm optimization to maximize bending stiffness of functionally graded structures

Functionally graded materials are a type of composite materials which are tailored to provide continuously varying properties, according to specific constituent's mixing distributions. These materials are known to provide superior thermal and mechanical performances when compared to the traditional laminated composites, because of this continuous properties variation characteristic, which enables among other advantages, smoother stresses distribution profiles. Therefore the growing trend on the use of these materials brings together the interest and the need for getting optimum configurations concerning to each specific application. In this work it is studied the use of particle swarm optimization technique for the maximization of a functionally graded sandwich beam bending stiffness. For this purpose, a set of case studies is analyzed, in order to enable to understand in a detailed way, how the different optimization parameters tuning can influence the whole process. It is also considered a re-initialization strategy, which is not a common approach in particle swarm optimization as far as it was possible to conclude from the published research works. As it will be shown, this strategy can provide good results and also present some advantages in some conditions. This work was developed and programmed on symbolic computation platform Maple 14. (C) 2013 Elsevier B.V. All rights reserved.

TiB2 nanostructured coating for GFRP injection moulds

In the injection moulding of polypropylene reinforced with hard glass fibres, die materials are commonly subjected to severe abrasive wear. In order to improve its wear resistance, an unbalanced magnetron sputtering PVD compositional monolayered coating has been produced. The film was composed by a nanostructured TiB2 monolayer. Microstructure characterization and thickness evaluation were conducted by scanning electron microscopy (SEM). Film topography and roughness were accessed by SEM and Atomic Force Microscopy (AFM). The phase analyse was investigated by X-ray diffraction (XRD), using Cu Kalpha radiation. Scratch tests were conducted in order to study the film adhesion to the substrate. Load-Displacement curves (nanoindentation analysis) allowed measuring the film hardness and Young's modulus. A ball-cratering tribometer was used to determine the micro-abrasion laboratorial wear resistance, under different tests conditions, using SiC particles in distilled water slurry. At the end of these tests, the worn surfaces were analyzed by SEM and Energy Dispersive X-ray Spectroscopy (EDS) in order to compare these results with some other coatings already tested in the same conditions. To test the practical wear resistance, 135000 injection cycles were done in a plastic injection industrial mould. Coated samples were put on the plastic feed canal, after a turbulent zone. In these tests, a 30% (wt) glass fibres reinforced polypropylene was used. Worn sample surfaces were analyzed by SEM after 45.000 and 90.000 cycles. Image analyses were made in order to evaluate the damage increases and to observe the wear mechanisms involved.

Particle swarm optimization with fractional-order velocity

This paper proposes a novel method for controlling the convergence rate of a particle swarm optimization algorithm using fractional calculus (FC) concepts. The optimization is tested for several well-known functions and the relationship between the fractional order velocity and the convergence of the algorithm is observed. The FC demonstrates a potential for interpreting evolution of the algorithm and to control its convergence.

A one-dimensional prescribed curvature equation modeling the corneal shape.

We prove existence, uniqueness, and stability of solutions of the prescribed curvature problem (u'/root 1 + u'(2))' = au - b/root 1 + u'(2) in [0, 1], u'(0) = u(1) = 0, for any given a > 0 and b > 0. We also develop a linear monotone iterative scheme for approximating the solution. This equation has been proposed as a model of the corneal shape in the recent paper (Okrasinski and Plociniczak in Nonlinear Anal., Real World Appl. 13:1498-1505, 2012), where a simplified version obtained by partial linearization has been investigated.

Particle swarm design of digital circuits

Swarm Intelligence (SI) is the property of a system whereby the collective behaviors of (unsophisticated) agents interacting locally with their environment cause coherent functional global patterns to emerge. Particle swarm optimization (PSO) is a form of SI, and a population-based search algorithm that is initialized with a population of random solutions, called particles. These particles are flying through hyperspace and have two essential reasoning capabilities: their memory of their own best position and knowledge of the swarm's best position. In a PSO scheme each particle flies through the search space with a velocity that is adjusted dynamically according with its historical behavior. Therefore, the particles have a tendency to fly towards the best search area along the search process. This work proposes a PSO based algorithm for logic circuit synthesis. The results show the statistical characteristics of this algorithm with respect to number of generations required to achieve the solutions. It is also presented a comparison with other two Evolutionary Algorithms, namely Genetic and Memetic Algorithms.

Modified particle swarm optimization for day-ahead distributed energy resources scheduling including vehicle-to-grid

Mestrado em Engenharia Electrotécnica – Sistemas Eléctricos de Energia

Modified Particle Swarm Optimization Applied to Integrated Demand Response and DG Resources Scheduling

The elastic behavior of the demand consumption jointly used with other available resources such as distributed generation (DG) can play a crucial role for the success of smart grids. The intensive use of Distributed Energy Resources (DER) and the technical and contractual constraints result in large-scale non linear optimization problems that require computational intelligence methods to be solved. This paper proposes a Particle Swarm Optimization (PSO) based methodology to support the minimization of the operation costs of a virtual power player that manages the resources in a distribution network and the network itself. Resources include the DER available in the considered time period and the energy that can be bought from external energy suppliers. Network constraints are considered. The proposed approach uses Gaussian mutation of the strategic parameters and contextual self-parameterization of the maximum and minimum particle velocities. The case study considers a real 937 bus distribution network, with 20310 consumers and 548 distributed generators. The obtained solutions are compared with a deterministic approach and with PSO without mutation and Evolutionary PSO, both using self-parameterization.