5 resultados para Surrogatebased optimization

em SAPIENTIA - Universidade do Algarve - Portugal


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The application of a supercritical Rankine cycle in combined cycles does not happen in today’s thermoelectric power stations. Nevertheless, the most recent development in gas turbines, that allows a high efficiency and high exhaust gases temperatures, and the improvement of high pressure and temperature alloys, makes this cycle possible. This study’s intent is to prove the viability of this combined cycle, since it can break the 60% efficiency barrier, which is the plafond in actual power stations. To attain this target, several configurations for this cycle have been simulated, optimized and analyzed [1]. The simulations were done with the computational program IPSEpro [2] and the optimizations were effectuated with software developed for the effect, using the DFP method [3]. In parallel with the optimization that claims the cycle’s efficiency maximization, an exergetic analysis was also made [4] to all the cycle components. In opposite to what happens in subcritical combined cycles, it was demonstrated that in supercritical combined cycles the higher efficiency takes place with a single steam pressure in the heat recovery steam generator (HRSG).

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Dissertação de Mestrado , Engenharia Biológica, Faculdade de Engenharia de Recursos Naturais, Universidade do Algarve, 2008

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Multilayer perceptrons (MLPs) (1) are the most common artificial neural networks employed in a large field of applications. In control and signal processing applications, MLPs are mainly used as nonlinear mapping approximators. The most common training algorithm used with MLPs is the error back-propagation (BP) alg. (1).

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Tese de doutoramento, Bioquimica, Faculdade de Ciências e Tecnologia, Universidade do Algarve, 2015

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Dissertação de Mestrado, Engenharia Informática, Faculdade de Ciências e Tecnologia, Universidade do Algarve, 2015