For the past several decades there have been many attempts to improve suspension performance due to its importance within vehicle dynamics. The suspension system main functions are to connect the chassis to the ground, and to isolate the chassis from the ground. To improve upon these two functions, large amounts of effort are focused on two elements that form the building blocks of the suspension system, stiffness and damping. With the advent of new technologies, such as variable dampers, and powerful microprocessors and sensors, suspension performance can be enhanced beyond the traditional capabilities of a passive suspension system. Recently, Yin et al. [1, 2] have developed a novel dual chamber pneumatic spring that can provide tunable stiffness characteristics, which is rare compared to the sea of tunable dampers. The purpose of this thesis is to develop a controller to take advantage of the novel pneumatic spring’s functionality with a tunable damper to improve vehicle dynamic performance. Since the pneumatic spring is a slow-acting element (i.e. low bandwidth), the typical control logic for semi-active suspension systems are not practical for this framework. Most semi-active controllers assume the use of fast-acting (i.e. high bandwidth) variable dampers within the suspension design. In this case, a lookup table controller is used to manage the stiffness and damping properties for a wide range of operating conditions. To determine the optimum stiffness and damping properties, optimization is employed. Four objective functions are used to quantify vehicle performance; ride comfort, rattle space (i.e. suspension deflection), handling (i.e. tire deflection), and undamped sprung mass natural frequency. The goal is to minimize the first three objectives, while maximizing the latter to avoid motion sickness starting from 1Hz and downward. However, these goals cannot be attained simultaneously, necessitating compromises between them. Using the optimization strength of genetic algorithms, a Pareto optima set can be generated to determine the compromises between objective functions that have been normalized. Using a trade-off study, the stiffness and damping properties can be selected from the Pareto optima set for suitability within an operating condition of the control logic. When implementing the lookup table controller, a practical method is employed to recognize the road profile as there is no direct method to determine road profile. To determine the road profile for the lookup table controller, the unsprung mass RMS acceleration and suspension state are utilized. To alleviate the inherent flip-flopping drawback of lookup table controllers, a temporal deadband is employed to eliminate the flip-flopping of the lookup table controller. Results from the semi-active suspension with tunable stiffness and damping show that vehicle performance, depending on road roughness and vehicle speed, can improve up to 18% over passive suspension systems. Since the controller does not constantly adjust the damping properties, cost and reliability may increase over traditional semi-active suspension systems. The flip-flopping drawback of lookup table controllers has been reduced through the use of a temporal deadband, however further enhancement is required to eliminate flip-flopping within the control logic. Looking forward, the novel semi-active suspension has great potential to improve vehicle dynamic performance especially for heavy vehicles that have large sprung mass variation, but to increase robustness the following should be considered: better road profile recognition, the elimination of flip-flopping between suspension states, and using state equations model of the pneumatic spring within the vehicle model for optimization and evaluation.

The thesis contributes to the body of knowledge in analyzing and optimizing inventories of multiple stocking locations in a supply chain system. Optimization model is developed for planning inventories with respect to the proposed inventory-pooling strategy. The model is solved under stochastic environment using a Hybrid Genetic Algorithm technique.

Evolvable Hardware is a technique derived from evolutionary computation applied to a hardware design. The term evolutionary computation involves similar steps as involved in the human evolution. It has been given names in accordance with the electronic technology like, Genetic Algorithm (GA), Evolutionary Strategy (ES) and Genetic Programming (GP). In evolutionary computing, a configured bit is considered as a human chromosome for a genetic algorithm, which has to be downloaded into hardware. Early evolvable hardware experiments were conducted in simulation and the only elite chromosome was downloaded to the hardware, which was labelled as Extrinsic Hardware. With the invent of Field Programmable Gate Arrays (FPGAs) and Reconfigurable Processing Units (RPUs), it is now possible for the implementation solutions to be fast enough to evaluate a real hardware circuit within an evolutionary computation framework; this is called an Intrinsic Evolvable Hardware. This research has been taken in continuation with project 'Evolvable Hardware' done at Manukau Institute of Technology (MIT). The project was able to manually evolve two simple electronic circuits of NAND and NOR gates in simulation. In relation to the project done at MIT this research focuses on the following: To automate the simulation by using In Circuit Debugging Emulators (IDEs), and to develop a strategy of configuring hardware like an FPGA without the use of their company supplied in circuit debugging emulators, so that the evolution of an intrinsic evolvable hardware could be controlled, and is hardware independent. As mentioned, the research conducted here was able to develop an evolvable hardware friendly Generic Structure which could be used for the development of evolvable hardware. The structure developed was hardware independent and was able to run on various FPGA hardware’s for the purpose of intrinsic evolution. The structure developed used few configuration bits as compared to current evolvable hardware designs.

This study raises some issues for training pilots to fly forced landings and examines the impact that these issues may have on the design of simulators for such training. It focuses on flight trajectories that a pilot of a single-engine general aviation aircraft should fly after engine failure and how pilots can be better simulator trained for this forced landing manoeuvre. A sensitivity study on the effects of errors and an investigation on the effect of tolerances in the aerodynamic parameters as prescribed in the Manual of Criteria for the Qualification of Flight Simulators have on the performance of flight simulators used for pilot training was carried out. It uses a simplified analytical model for the Beech Bonanza model E33A aircraft and a vertical atmospheric turbulence based on the MIL-F-8785C specifications. It was found that the effect of the tolerances is highly sensitive on the nature of the manoeuvre flown and that in some cases, negative transfe r of training may be induced by the tolerances. A forced landing trajectory optimisation was carried out using Genetic Algorithm. The forced landing manoeuvre analyses with pre-selected touchdown locations and pre-selected final headings were carried out for an engine failure at 650 ft AGL for bank angles varying from banking left at 45° to banking right at 45°, and with an aircraft's speed varying from 75.6 mph to 208 mph, corresponding to 5% above airplane's stall speed and airplane's maximum speed respectively. The results show that certain pre-selected touchdown locations are more susceptible to horizontal wind. The results for the forced landing manoeuvre with a pre-selected location show minimal distance error while the quality of the results for the forced landing manoeuvre with a pre-selected location and a final heading show that the results depend on the end constraints. For certain pre-selected touchdown locations and final headings, the airplane may either touchdown very close to the pre-selected touchdown location but with greater final h eading error from the pre-selected final heading or touchdown with minimal final heading error from the pre-selected final heading but further away from the pre-selected touchdown location. Analyses for an obstacle avoidance forced landing manoeuvre were also carried out where an obstacle was intentionally placed in the flight path as found by the GA program developed for without obstacle. The methodology developed successfully found flight paths that will avoid the obstacle and touchdown near the pre-selected location. In some cases, there exist more than one ensemble grouping of flight paths. The distance error depends on both the pre-selected touchdown location and where the obstacle was placed. The distance error tends to increase with the addition of a specific final heading requirement for an obstacle avoidance forced landing manoeuvre. As with the case without specific final heading requirement, there is a trade off between touching down nearer to the pre-selected location and touching down with a smaller final heading error.

[pt] O objetivo desta dissertação é desenvolver um método de solução baseado em Algoritmos Genéticos (GAs) aliado a um Sistema Baseado em Regras para encontrar e otimizar as soluções geradas para o problema de programação da produção de Óleos Combustíveis e Asfalto na REVAP (Refinaria do Vale do Paraíba). A refinaria é uma planta multiproduto, com dois estágios de máquinas em série - um misturador e um conjunto de tanques, com restrição de recursos e operando em regime contínuo. Foram desenvolvidos neste trabalho dois modelos baseados em algoritmos genéticos que são utilizados para encontrar a seqüência e os tamanhos dos lotes de produção dos produtos finais. O primeiro modelo proposto utiliza uma representação direta da programação da produção em que o horizonte de programação é dividido em intervalos discretos de um hora. O segundo modelo proposto utiliza uma representação indireta que é decodificada para formar a programação da produção. O Sistema Baseado em Regras é utilizado na escolha dos tanques que recebem a produção e os tanques que atendem à demanda dos diversos centros consumidores existentes. Um novo operador de mutação - Mutação por Vizinhança - foi proposto para minimizar o número de trocas operacionais na produção. Uma técnica para agregação de múltiplos objetivos, baseado no Método de Minimização de Energia, também foi incorporado aos Algoritmos Genéticos. Os resultados obtidos confirmam que os Algoritmos Genéticos propostos, associados com o Método de Minimização de Energia e a Mutação por Vizinhança, são capazes de resolver o problema de programação da produção, otimizando os objetivos operacionais da refinaria. / [en] The purpose of this dissertation is to develop a method, based on Genetics Algorithms and Rule Base Systems, to optimize the production scheduling of fuel oil and asphalt area in a petroleum refinery. The refinery is a multi- product plant, with two machine stages - one mixer and a set of tanks - with no setup time and with resource constrains in continuous operation. Two genetic algorithms models were developed to establish the sequence and the lot- size of all production shares. The first model proposed has a direct representation of the production scheduling which the time interval of scheduling is shared in one hour discrete intervals. The second model proposed has a indirect representation that need to be decoded in order to make the real production scheduling. The Rule Base Systems were developed to choice the tanks that receive the production and the tanks that provide the demand of the several consumer centers. A special mutation operator - Neighborhood Mutation - was proposed to minimize the number of changes in the production. A Multi-objective Fitness Evaluation technique, based on a Energy Minimization Method, was also incorporated to the Genetic Algorithm models. The results obtained confirm that the proposed Genetic Algorithm models, associated with the Multi- objective Energy Minimization Method and the Neighborhood Mutation, are able to solve the scheduling problem, optimizing the refinery operational objectives. / [es] El objetivo de esta disertación es desarrollar un método de solución utilizando Algoritmos Genéticos (GAs) aliado a un Sistema Basado en Reglas para encontrar y optimizar las soluciones generadas para el problema de programación de la producción de Aceites Combustibles y Asfalto en la REVAP (Refinería del Valle de Paraíba). La refinería es una planta multiproducto, con dos estados de máquinas en serie - un mezclador y un conjunto de tanques, con restricción de recursos y operando en régimen contínuo. En este trabajo se desarrollaron dos modelos basados en algoritmos genéticos que son utilizados para encontrar la secuencia y los tamaños de los lotes de producción de los productos finales. El primer modelo propuesto utiliza una representación directa de la programación de la producción en la cuál el horizonte de programación se divide en intervalos discretos de un hora. El segundo modelo, utiliza una representación indirecta que es decodificada para formar la programación de la producción. EL Sistema Basado en Reglas se utiliza en la selección de los tanques que reciben la producción y los tanques que atienden a la demanda de los diversos centros consumidores. Un nuevo operador de mutación - Mutación por Vecindad - fue propuesto para minimizar el número de cambios operacionales en la producción. le fue incorporado a los Algoritmos Genéticos una técnica para la agregación de múltiples objetivos, basado en el Método de Minimización de Energía. Los resultados obtenidos confirman que los Algoritmos Genéticos propuestos, asociados al Método de Minimización de Energía y la Mutación por Vecindad, son capazes de resolver el problema de programación de la producción, optimizando los objetivos operacionales de la refinería.

A growing interest in distributed systems of small satellites has recently emerged due to their ability to perform a variety of new mission types, increasing technical capability, and reduced time and cost for development. However, the lack of available and dedicated small launch services currently restricts the establishment of these systems in orbit. Secondary payload launch opportunities and alternative deployment strategies can address the issue of access-to-orbit and support the delivery of the constellation to the correct orbit configuration following launch. Of these deployment strategies, the method of indirect plane separation, which utilises the natural precession of Earth orbits, is particularly applicable to the deployment of small satellite constellations due to the potential to significantly reduce propulsive requirements, albeit at the cost of increased deployment time. A review of satellite constellation design revealed that existing methods and tools are not suitable for the analysis of small satellite constellations and are not equipped to investigate alternative deployment strategies, despite the potential benefits of improved access-to-orbit, reduced system complexity, and reduced cost. To address the identified gaps in the design process, a methodology in which the analysis of small satellite constellation deployment is integrated into the system design framework is presented in this thesis. The corresponding system design-space is subsequently explored using a numerical optimisation method, which aids the identification of effective system designs and promotes the understanding of relationships between the design variables and output objectives. The primary objectives of this methodology are to ensure that the different opportunities for deployment of small satellite constellations are thoroughly examined during the design process and to support the development of improved mission and system designs. The presented methodology is demonstrated using a reduced order framework comprised of an analysis for the deployment of small satellite constellations, preliminary vehicle and propulsion system sizing processes, and system cost estimating relationships. Using this simplified mission design framework, the design space-exploration of three small satellite constellation mission case-studies is performed by application of a multiobjective genetic algorithm. Objectives of time-to-deploy, system mass, and system cost are used to direct the optimisation process and search for the most effective solutions in the system design-space. In order to perform the analysis of constellation deployment by the process of indirect plane separation, a simulation method using a semi-analytical propagation technique and time-varying atmospheric density model was developed and verified by comparison to the actual deployment of the FORMOSAT-3/COSMIC mission. The results of the case-studies presented illustrate the ability of the developed methodology to support the design process for satellite constellations and enable the identification of promising and improved system architectures for further development. Moreover, through the enumeration and quantification of the system design-space and tradespace, the methodology is shown to support the identification of relationships and trends between the design variables and selected output objectives, increasing the knowledge available to the system design team during the design process.

Airships provide an eco-friendly and cost-effective means to suit sustained airborne operations. Smaller autonomous airships are highly susceptible to adverse atmospheric conditions owing to their under-actuated, underpowered and bulky size relative to other types of unmanned aerial vehicles (UAVs). To mitigate these limitations, careful considerations of the size and shape must be made at the design stage. This research presents a methodology for obtaining an optimized shape of a semi-rigid airship. Rapid descent of the LTA ship is achieved by means of a moving gondola attached to a rigid keel mounted under the helium envelope from the bow to the mid-section of the hull. The study entails the application of a robust hybrid genetic algorithm (HGA) for the multi-disciplinary design and optimization of an airship capable of rapid descent, with lower drag and optimum surface area. A comprehensive sensitivity analysis was also performed on the basis of algorithmic parameters and atmospheric conditions. With the help of HGA, a semi-rigid airship capable of carrying a payload of 0.25 kg to 1.0 kg and capable of pitching at right angles is conceptually designed. The algorithm is also tested on commercially available vehicles to validate the results. In multi-objective optimization problems (MOOPs), the significance of different objectives is dependent on the user.

Submitted by Maria Medeiros (maria.dilva1@ufcg.edu.br) on 2018-09-13T12:13:14Z No. of bitstreams: 1 LUCIANO MEDEIROS DE SOUZA - TESE (PPGEP) 2008.pdf: 1622133 bytes, checksum: e718708aa81aa024dab3ad2700717546 (MD5) / Made available in DSpace on 2018-09-13T12:13:14Z (GMT). No. of bitstreams: 1 LUCIANO MEDEIROS DE SOUZA - TESE (PPGEP) 2008.pdf: 1622133 bytes, checksum: e718708aa81aa024dab3ad2700717546 (MD5) Previous issue date: 2008-05-30 / Capes / No processo de produção de soda cáustica, umas das etapas é o resfriamento da solução de hidróxido de sódio. O resfriamento da solução de hidróxido de sódio é feito em uma série de tanques que utilizam água gelada e água de torre de resfriamento para reduzir a temperatura da solução até um valor especificado. Cada tanque é dotado de agitador e serpentina de resfriamento. A água usada para resfriamento escoa no interior das serpentinas em contracorrente. Nos primeiros tanques usa-se água da torre de resfriamento e nos últimos tanques água gelada. Um dos grandes problemas dos processos industriais é a incrustação formada nos equipamentos. No sistema de resfriamento de soda cáustica, incrustações se formam devido à cristalização de sais em torno da serpentina diminuindo o coeficiente global de transferência de calor. Um modelo assintótico em função do tempo para incrustações nos tanques foi ajustado para determinar o melhor momento da limpeza do tanque. Otimizar a limpeza dos tanques em relação ao período de tempo e a escolha do tanque é e minimizar o número de limpezas periódicas são os objetivos deste trabalho. A função objetivo é calculada pelo programa baseado num modelo para a simulação deste sistema de resfriamento com modelo de incrustação assintótica desenvolvido anteriormente para este projeto e integrado a outros subprogramas desenvolvidos em MATLAB que utilizam os algoritmos genéticos para escolherem as melhores soluções para o sistema. A partir dos algoritmos genéticos determinaram-se alguns ótimos locais analisando os valores da temperatura da solução no último tanque e o número de limpezas por dia, assim como efeitos na carga térmica e na diferença de temperatura entre a água de resfriamento e a solução. Com o uso dos algoritmos genéticos está sendo possível encontrar padrões ótimos de limpeza para os tanques. / In the process of caustic soda production, one of the stages is the cooling of the sodium hydroxide solution. The cooling of the sodium hydroxide solution is made in a series of tanks that use frozen water and water of cooling tower to reduce the temperature of the solution until the specified value. Each tank is endowed with agitator and coil of cooling. The cooling water flows in the interior of the coils in countercurrent. The water of cooling tower is used in the first tanks, where as the frozen in the last tanks. One of the great problems of the industrial processes is the fouling formed in the equipment. In the system of caustic soda water cooling of the BRASKEM, fouling if they form due to crystallization of leave around the coil diminishing the global coefficient transference heat. An asymptotic model in function of the time for fouling in the tanks it was adjusted to determine optimum moment where the tank must be clean. To optimize the cleaning of the tanks in relation to the period of time and the choice of the tank is and to minimize the number of periodic cleanings they are the objectives of this work. The objective function is calculated by the program based on a model for the simulation of this system of cooling with developed previously for this project and integrated model of asymptotic fouling function to other subprograms developed in MATLAB that use the genetic algorithms to choose the best solutions for the system. From the genetic algorithms some excellent places had been determined analyzing the values of the temperature of the solution in the last tank and the number of cleaning per day, as well as effect in the thermal load and the difference of temperature enters the water of cooling and the solution. With the use of the genetic algorithms it is being possible to find optimum cleaning schedule for the tanks.

[pt] A energia é assunto estratégico para a grande maioria dos países e indústrias no mundo. O consumo atual energético é de 138,32 TWh por ano e é previsto um aumento de 44% até o ano de 2030 o que demonstra um mercado em expansão. Porém, a sociedade atual exige soluções energéticas que causem o menor impacto ambiental possível, colocando em dúvida o uso das fontes de energia utilizadas atualmente. O uso da energia solar é uma alternativa para auxiliar no atendimento da futura demanda de energia. O seu principal entrave é o custo de produção de energia ser superior as fontes de energia atuais, principalmente o petróleo. Contudo nos últimos 10 anos foi verificado um crescimento exponencial na quantidade de módulos fotovoltaicos instalados em todo mundo. Nesse trabalho é realizado um estudo sobre célula solares com poços quânticos. O uso de poços quânticos já foi apontado como ferramenta para aumentar a eficiência de células fotovoltaicas. O objetivo é descrever uma metodologia baseada em algoritmos genéticos para projeto e análise desse tipo de dispositivo e estabelecer diretivas para se construir uma célula otimizada utilizando esta tecnologia. Os resultados obtidos estão de acordo com dados experimentais, demonstram a capacidade dos poços quânticos em aumentar a eficiência de uma célula e fornecem uma ferramenta tecnológica que espera-se contribuir para o desenvolvimento do país no setor energético. / [en] The energy is a strategical issue for the great majority of the countries and industries in the world. The current world energy consumption is of 138,32 TWh per year and is foreseen an increase of 44% until the year of 2030 which demonstrates a market in expansion. However, the society demands energy solutions that cause as least ambient impact as possible, putting in doubt the use of the current technologies of power plants. The utilization of solar energy is an alternative to assist in the attendance of the future demand of energy. Its main impediment is the superior cost of energy production in comparison with the current power plants, mainly the oil based ones. However in last the 10 years an exponential growth in the amount of installed photovoltaics modules worldwide was verified. In this work a study on solar cell with quantum wells is carried through. The use of quantum wells already was pointed as tool to increase the efficiency of photovoltaics cells. The objective is to describe a methodology based on genetic algorithms for project and analysis of this type of device and to establish directive to construct an optimized cell using this technology. The results are in accordance with experimental data, that demonstrates the capacity of the quantum wells in increasing the efficiency of a cell and supply a technological tool that expects to contribute for the development of the country in the energy sector.

[pt] Com o crescimento da demanda de óleo, as empresas de petróleo têm sido forçadas a explorar novas reservas em águas cada vez mais profundas. Em função do alto custo das operações de exploração de petróleo, torna-se necessário o desenvolvimento de tecnologias capazes de aumentar a eficiência e reduzir os custos envolvidos. Neste contexto, a utilização de unidades flutuantes torna-se cada vez mais freqüente em águas profundas. O posicionamento das unidades flutuantes durante as operações de exploração de óleo é garantido pelas linhas de ancoragem, que são estruturas flexíveis compostas, geralmente, por trechos de aço, amarras e/ou cabos sintéticos. O presente trabalho apresenta o desenvolvimento de um Algoritmo Genético (AG) para solucionar o problema da disposição das linhas de ancoragem de unidades flutuantes utilizadas nas operações de exploração de petróleo. A distribuição das linhas de ancoragem é um dos fatores que influencia diretamente nos deslocamentos (offsets) sofridos pelas unidades flutuantes quando submetidas às ações ambientais, como ventos, ondas e correntes. Desta forma, o AG busca uma disposição ótima das linhas de ancoragem cujo objetivo final é a minimização dos deslocamentos da unidade flutuante. Os operadores básicos utilizados por este algoritmo são mutação, crossover e seleção. Neste trabalho, foi adotada a técnica steady-state, que só efetua a substituição de um ou dois indivíduos por geração. O cálculo da posição de equilíbrio estático da unidade flutuante é feito aplicando-se a equação da catenária para cada linha de ancoragem com o objetivo de se obterem as forças de restauração na unidade, e empregando-se um processo iterativo para calcular a sua posição final de equilíbrio. / [en] With the increasing demand for oil, oil companies have been forced to exploit new fields in deep waters. Due to the high cost of oil exploitation operations, the development of technologies capable of increasing efficiency and reducing costs is crucial. In this context, the use of floating units in deep waters has become more frequent. The positioning of the floating units during oil exploitation operations is done using mooring lines, which are flexible structures usually made of steel wire, steel chain and/or synthetic cables. This work presents the development of a Genetic Algorithm (GA) procedure to solve the problem of the mooring pattern of floating units used in oil exploitation operations. The distribution of mooring lines is one of the factors that directly influence the displacements (offsets) suffered by floating units when subjected to environmental conditions such as winds, waves and currents. Thus, the GA seeks an optimum distribution of the mooring lines whose final goal is to minimize the units´ displacements. The basic operators used in this algorithm are mutation, crossover and selection. In the present work, the steady- state GA has been implemented, which performs the substitution of only one or two individuals per generation. The computation of the floating unit´s static equilibrium position is accomplished by applying the catenary equilibrium equation to each mooring line in order to obtain the out-of-balance forces on the unit, and by using an iterative process to compute the final unit equilibrium position.