Inverse Geometry Design of Radiative Enclosures Using Particle Swarm Optimization Algorithms

Three different Particle Swarm Optimization (PSO) algorithms—standard PSO, stochastic PSO (SPSO) and differential evolution PSO (DEPSO)—are applied to solve the inverse geometry design problems of radiative enclosures. The design purpose is to satisfy a uniform distribution of radiative heat flux on the designed surface. The design surface is discretized into a series of control points, the PSO algorithms are used to optimize the locations of these points and the Akima cubic interpolation is utilized to approximate the changing boundary shape. The retrieval results show that PSO algorithms can be successfully applied to solve inverse geometry design problems and SPSO achieves the best performance on computational time. The influences of the number of control points and the radiative properties of the media on the retrieval geometry design results are also investigated

Optimization of the hyperthermia treatment of a skin tumor containing nanoparticles

This paper deals with the optimization of the hyperthermia treatment of skin cancer, with gold nanoshells loaded in the tumor. The physical problem involves a one-dimensional bioheat transfer problem, coupled to a radiation problem for the laser propagation within a multi-layered medium that includes several tissues. The corresponding bioheat transfer problem is governed by Pennes' equation, while the laser radiation propagation in the tissues is modelled with the diffusion δ-P1 approximation. The solution of the direct problem was obtained by finite volumes and verified with an analytic solution, as well as with the Matlab function pdepe. The thermal decomposition in the tissues was modelled with an Arrhenius equation, while the objective function was given by a quadratic form involving the difference between the predicted and the desired spatial variation of the thermal damage at a specific final time. Both the Levenberg-Marquardt and the Particle Swarm methods were implemented and provided similar results for the two design variables of interest in this work: the volume fraction of nanoparticles within the tumor and the laser power, by considering a fixed duration of 10 minutes for the treatment. The results obtained in this work also show that more than one treatment session is required for the total eradication of the tumor

Magnetocardiography in unshielded environment based on optical magnetometry and adaptive noise cancellation

This thesis proposes and demonstrates the concept of a magnetocardiographic system employing an array of optically-pumped quantum magnetometers and an adaptive noise cancellation for heart magnetic field measurement within a magnetically-unshielded environment. Optically-pumped quantum magnetometers are based on the use of the atomic-spin-dependent optical properties of an atomic medium. An Mxconfiguration- based optically-pumped quantum magnetometer employing two sensing cells containing caesium vapour is theoretically described and experimentally developed, and the dependence of its sensitivity and frequency bandwidth upon the light power and the alkali vapour temperature is experimentally demonstrated. Furthermore, the capability of the developed magnetometer of measuring very weak magnetic fields is experimentally demonstrated in a magnetically-unshielded environment. The adaptive noise canceller is based on standard Least-Mean-Squares (LMS) algorithms and on two heuristic optimization techniques, namely, Genetic Algorithms (GA) and Particle Swarm Optimization (PSO). The use of these algorithms is investigated for suppressing the power line generated 50Hz interference and recovering of the weak magnetic heart signals from a much higher electromagnetic environmental noise. Experimental results show that all the algorithms can extract a weak heart signal from a much-stronger magnetic noise, detect the P, QRS, and T heart features and highly suppress the common power line noise component at 50 Hz. Moreover, adaptive noise cancellation based on heuristic algorithms is shown to be more efficient than adaptive noise canceller based on standard or normalised LMS algorithm in heart features detection

Signal processing with optical delay line filters for high bit rate transmission systems

In den letzten Jahrzehnten ist das globale Kommunikationssystem in einem immer größerem Maße ein integraler Bestandteil des täglichen Lebens geworden. Optische Kommunikationssysteme sind die technologische Basis für diese Entwicklung. Nur Fasern können die riesige benötigte Bandbreite bereitstellen. Während für die ersten optischen Übertragungssysteme die Faser als "flacher" Kanal betrachtet werden konnte, machen Wellenlängenmultiplex und steigende Übertragungsraten die Einbeziehung von immer mehr physikalischen Effekten notwendig. Bei einer Erhöhung der Kanaldatenrate auf 40 Gbit/s und mehr ist die statische Kompensation von chromatischer Dispersion nicht mehr ausreichend. Die intrinsische Toleranz der Modulationsformate gegenüber Dispersion nimmt quadratisch mit der Symbolrate ab. Daher können beispielsweise durch Umwelteinflüsse hervorgerufene Dispersionsschwankungen die Dispersionstoleranz der Modulationsformate überschreiten. Dies macht eine adaptive Dispersionskompensation notwendig, was gleichzeitig auch Dispersionsmonitoring erfordert, um den adaptiven Kompensator steuern zu können. Vorhandene Links können mit Restdispersionskompensatoren ausgestattet werden, um sie für Hochgeschwindigkeitsübertragungen zu ertüchtigen. Optische Kompensationstechniken sind unabhängig von der Kanaldatenrate. Daher wird eine Erhöhung der Datenrate problemlos unterstützt. Optische Kompensatoren können WDM-fähig gebaut werden, um mehrere Kanäle auf einmal zu entzerren. Das Buch beschäftigt sich mit optischen Delay-Line-Filtern als eine Klasse von optischen Kompensatoren. Die Filtersynthese von solchen Delay-Line-Filtern wird behandelt. Der Zusammenhang zwischen optischen Filtern und digitalen FIR-Filtern mit komplexen Koeffizienten im Zusammenhang mit kohärenter Detektion wird aufgezeigt. Iterative und analytische Methoden, die die Koeffizienten für dispersions- und dispersions-slope-kompensierende Filter produzieren, werden untersucht. Genauso wichtig wie die Kompensation von Dispersion ist die Schätzung der Dispersion eines Signals. Mit Delay-Line-Filtern können die Restseitenbänder eines Signals genutzt werden, um die Dispersion zu messen. Alternativ kann nichtlineare Detektion angewandt werden, um die Pulsverbreiterung, die hauptsächlich von der Dispersion herrührt, zu schätzen. Mit gemeinsamer Dispersionskompensation und Dispersionsmonitoring können Dispersionskompensatoren auf die Signalverzerrungen eingestellt werden. Spezielle Eigenschaften der Filter zusammen mit der analytischen Beschreibung können genutzt werden, um schnelle und zuverlässige Steueralgorithmen zur Filtereinstellung bereitzustellen. Schließlich wurden Prototypen derartiger faseroptischen Kompensatoren von chromatischer Dispersion und Dispersions-Slope hergestellt und charakterisiert. Die Einheiten und ihr Systemverhalten wird gezeigt und diskutiert.Over the course of the past decades, the global communication system has become a central part of people's everyday lives. Optical communication systems are the technological basis for this development. Only fibers can provide the huge bandwidth that is required. Where the fiber could be regarded as a flat channel for the first optical transmission systems wavelength multiplexing and increasing line rates made it necessary to take more and more physical effects into account. When the line rates are increased to 40 Gbit/s and higher static chromatic dispersion compensation is not enough. The modulation format's intrinsic tolerance for dispersion decreases quadratically with the symbol rate. Thus, environmentally induced chromatic dispersion fluctuations may exceed the dispersion tolerance of the modulation formats. This makes an adaptive dispersion compensation necessary implying also the need for a monitoring scheme to steer the adaptive compensator. Legacy links that are CD-compensated by DCFs can be upgraded with residual dispersion compensators to make them ready for high speed transmission. Optical compensation is independent from the line rate. Hence, increasing the data rates is inherently supported. Optical compensators can be built WDM ready compensating multiple channels at once. The book deals with optical delay line filters as one class of optical compensators. The filter synthesis of such delay line filters is addressed. The connection between optical filters and digital FIR filters with complex coefficients that are used in conjunction with coherent detection could be shown. Iterative and analytical methods that produce the coefficients for dispersion (and also dispersion slope) compensating filters are researched. As important as the compensation of dispersion is the estimation of the dispersion of a signal. Using delay line filters, the vestigial sidebands of a signal can be used to measure the dispersion. Alternatively, nonlinear detection can be used to estimate the pulse broadening which is caused mainly by dispersion. With dispersion compensation and dispersion monitoring, dispersion compensators can be adapted to the signal's impairment. Special properties of the filter in conjunction with an analytical description can be used to provide a fast and reliable control algorithm for setting the filter to a given dispersion and centering it on a signal. Finally, prototypes of such fiber optic chromatic dispersion and dispersion slope compensation filters were manufactured and characterized. The device and system characterization of the prototypes is presented and discussed

Chaos Firefly Algorithm With Self-Adaptation Mutation Mechanism for Solving Large-Scale Economic Dispatch With Valve-Point Effects and Multiple Fuel Options

This paper presents a new metaheuristic optimization algorithm, the firefly algorithm (FA), and an enhanced version of it, called chaos mutation FA (CMFA), for solving power economic dispatch problems while considering various power constraints, such as valve-point effects, ramp rate limits, prohibited operating zones, and multiple generator fuel options. The algorithm is enhanced by adding a new mutation strategy using self-adaptation parameter selection while replacing the parameters with fixed values. The proposed algorithm is also enhanced by a self-adaptation mechanism that avoids challenges associated with tuning the algorithm parameters directed against characteristics of the optimization problem to be solved. The effectiveness of the CMFA method to solve economic dispatch problems with high nonlinearities is demonstrated using five classic test power systems. The solutions obtained are compared with the results of the original algorithm and several methods of optimization proposed in the previous literature. The high performance of the CMFA algorithm is demonstrated by its ability to achieve search solution quality and reliability, which reflected in minimum total cost, convergence speed, and consistency

Genetic based optimisation of the design parameters for an array-on-device orbital motion wave energy converter

Optimisation of Wave Energy Converters (WECs) is a very important topic to obtain competitive devices in the energy market. Wave energy is a renewable resource that could contribute significantly to a future sustainable world. Research is on-going to reduce costs and increase the amount of energy captured. This work aims to optimise a WaveSub device made up of multiple floats in a line by investigating the influence of 6 different design parameters such as the number of floats. Here we show that a multi-float configuration of 6 floats is more competitive in terms of Levelised Cost Of Energy (LCOE) compared to a single float configuration with a LCOE reduction of around 21%. We demonstrate that multi-float configurations of this device reduce the LCOE especially because of the reduction of grid connection, installation, control and mooring costs. From the power capture perspective, optimized multi-float configurations still have similar capacity factors to the single float configuration. This research gives important indications for further development of the WECs from an optimisation perspective. These promising results show that more complex, optimized, multi-float configurations could be investigated in future

Particle Swarm Optimization

Particle swarm optimization (PSO) is a population based stochastic optimization technique influenced by the social behavior of bird flocking or fish schooling.PSO shares many similarities with evolutionary computation techniques such as Genetic Algorithms (GA). The system is initialized with a population of random solutions and searches for optima by updating generations. However, unlike GA, PSO has no evolution operators such as crossover and mutation. In PSO, the potential solutions, called particles, fly through the problem space by following the current optimum particles. This book represents the contributions of the top researchers in this field and will serve as a valuable tool for professionals in this interdisciplinary field

Kinetics and Mechanism of Metal Nanoparticle Growth via Optical Extinction Spectroscopy and Computational Modeling: The Curious Case of Colloidal Gold

An overarching computational framework unifying several optical theories to describe the temporal evolution of gold nanoparticles (GNPs) during a seeded growth process is presented. To achieve this, we used the inexpensive and widely available optical extinction spectroscopy, to obtain quantitative kinetic data. In situ spectra collected over a wide set of experimental conditions were regressed using the physical model, calculating light extinction by ensembles of GNPs during the growth process. This model provides temporal information on the size, shape, and concentration of the particles and any electromagnetic interactions between them. Consequently, we were able to describe the mechanism of GNP growth and divide the process into distinct genesis periods. We provide explanations for several longstanding mysteries, for example, the phenomena responsible for the purple-greyish hue during the early stages of GNP growth, the complex interactions between nucleation, growth, and aggregation events, and a clear distinction between agglomeration and electromagnetic interactions. The presented theoretical formalism has been developed in a generic fashion so that it can readily be adapted to other nanoparticulate formation scenarios such as the genesis of various metal nanoparticles.Comment: Main text and supplementary information (accompanying MATLAB codes available on the journal webpage