Logistic optimization in tourism networks

55th European Regional Science Association Congress, Lisbon, Portugal (25-28 August 2015).

Otimização de estruturas de destilação azeotrópica com recurso a planeamento experimental

Trabalho Final de Mestrado para obtenção do grau de Mestre em Engenharia Química e Biológica

Optimization of Cu(II) biosorption onto ascophyllum nodosum by factorial design methodology

A Box–Behnken factorial design coupled with surface response methodology was used to evaluate the effects of temperature, pH and initial concentration in the Cu(II) sorption process onto the marine macroalgae Ascophyllum nodosum. The effect of the operating variables on metal uptake capacitywas studied in a batch system and a mathematical model showing the influence of each variable and their interactions was obtained. Study ranges were 10–40ºC for temperature, 3.0–5.0 for pH and 50–150mgL−1 for initial Cu(II) concentration. Within these ranges, the biosorption capacity is slightly dependent on temperature but markedly increases with pH and initial concentration of Cu(II). The uptake capacities predicted by the model are in good agreement with the experimental values. Maximum biosorption capacity of Cu(II) by A. nodosum is 70mgg−1 and corresponds to the following values of those variables: temperature = 40ºC, pH= 5.0 and initial Cu(II) concentration = 150mgL−1.

Application-specific modified particle swarm optimization for energy resource scheduling considering vehicle-to-grid

This paper presents a modified Particle Swarm Optimization (PSO) methodology to solve the problem of energy resources management with high penetration of distributed generation and Electric Vehicles (EVs) with gridable capability (V2G). The objective of the day-ahead scheduling problem in this work is to minimize operation costs, namely energy costs, regarding he management of these resources in the smart grid context. The modifications applied to the PSO aimed to improve its adequacy to solve the mentioned problem. The proposed Application Specific Modified Particle Swarm Optimization (ASMPSO) includes an intelligent mechanism to adjust velocity limits during the search process, as well as self-parameterization of PSO parameters making it more user-independent. It presents better robustness and convergence characteristics compared with the tested PSO variants as well as better constraint handling. This enables its use for addressing real world large-scale problems in much shorter times than the deterministic methods, providing system operators with adequate decision support and achieving efficient resource scheduling, even when a significant number of alternative scenarios should be considered. The paper includes two realistic case studies with different penetration of gridable vehicles (1000 and 2000). The proposed methodology is about 2600 times faster than Mixed-Integer Non-Linear Programming (MINLP) reference technique, reducing the time required from 25 h to 36 s for the scenario with 2000 vehicles, with about one percent of difference in the objective function cost value.

Control of baker’s yeast fermentation: PID and fuzzy algorithms

A MATLAB/SIMULINK-based simulator was employed for studies concerning the control of baker’s yeast fed-batch fermentation. Four control algorithms were implemented and compared: the classical PID control, two discrete versions- modified velocity and position algorithms, and a fuzzy law. The simulation package was seen to be an efficient tool for the simulation and tests of control strategies of the nonlinear process.

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.

Industry energy optimization: A case study in a biodiesel production site

This paper presents a case study of heat exchanger network (HEN) retrofit with the objective to reduce the utilities consumption in a biodiesel production process. Pinch analysis studies allow determining the minimum duty utilities as well the maximum of heat recovery. The existence of heat exchangers for heat recovery already running in the process causes a serious restriction for the implementation of grassroot HEN design based on pinch studies. Maintaining the existing HEN, a set of alternatives with additional heat exchangers was created and analysed using some industrial advice and selection criteria. The final proposed solution allows to increase the actual 18 % of recovery heat of the all heating needs of the process to 23 %, with an estimated annual saving in hot utility of 35 k(sic)/y.

An optimization approach for the job shop scheduling problem

This paper presents an optimization approach for the job shop scheduling problem (JSSP). The JSSP is a difficult problem in combinatorial optimization for which extensive investigation has been devoted to the development of efficient algorithms. The proposed approach is based on a genetic algorithm technique. The scheduling rules such as SPT and MWKR are integrated into the process of genetic evolution. The chromosome representation of the problem is based on random keys. The schedules are constructed using a priority rule in which the priorities and delay times of the operations are defined by the genetic algorithm. Schedules are constructed using a procedure that generates parameterized active schedules. After a schedule is obtained a local search heuristic is applied to improve the solution. The approach is tested on a set of standard instances taken from the literature and compared with other approaches. The computation results validate the effectiveness of the proposed approach.

Saving energy in the GFRP pultrusion process

This study addresses to the optimization of pultrusion manufacturing process from the energy-consumption point of view. The die heating system of external platen heaters commonly used in the pultrusion machines is one of the components that contribute the most to the high consumption of energy of pultrusion process. Hence, instead of the conventional multi-planar heaters, a new internal die heating system that leads to minor heat losses is proposed. The effect of the number and relative position of the embedded heaters along the die is also analysed towards the setting up of the optimum arrangement that minimizes both the energy rate and consumption. Simulation and optimization processes were greatly supported by Finite Element Analysis (FEA) and calibrated with basis on the temperature profile computed through thermography imaging techniques. The main outputs of this study allow to conclude that the use of embedded cylindrical resistances instead of external planar heaters leads to drastic reductions of both the power consumption and the warm-up periods of the die heating system. For the analysed die tool and process, savings on energy consumption up to 60% and warm-up period stages less than an half hour were attained with the new internal heating system. The improvements achieved allow reducing the power requirements on pultrusion process, and thus minimize industrial costs and contribute to a more sustainable pultrusion manufacturing industry.

A MOSFET-only wideband LNA exploiting thermal noise canceling and gain optimization

Dissertação apresentada na Faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa para a obtenção do grau de Mestre em Engenharia Electrotécnica e de Computadores

Time-domain optimization of amplifiers based on distributed genetic algorithms

Thesis presented in partial fulfillment of the requirements for the degree of Doctor of Philosophy in the subject of Electrical and Computer Engineering

Production optimization of rotavirus-like particles: a system biology approach

Dissertation presented to obtain a Ph.D. degree in Engineering and Technology Sciences, Systems Biology at the Instituto de Tecnologia Química e Biológica, Universidade Nova de Lisboa

Application-Specific Modified Particle Swarm Optimization for energy resource scheduling considering vehicle-to-grid

This paper presents a modified Particle Swarm Optimization (PSO) methodology to solve the problem of energy resources management with high penetration of distributed generation and Electric Vehicles (EVs) with gridable capability (V2G). The objective of the day-ahead scheduling problem in this work is to minimize operation costs, namely energy costs, regarding the management of these resources in the smart grid context. The modifications applied to the PSO aimed to improve its adequacy to solve the mentioned problem. The proposed Application Specific Modified Particle Swarm Optimization (ASMPSO) includes an intelligent mechanism to adjust velocity limits during the search process, as well as self-parameterization of PSO parameters making it more user-independent. It presents better robustness and convergence characteristics compared with the tested PSO variants as well as better constraint handling. This enables its use for addressing real world large-scale problems in much shorter times than the deterministic methods, providing system operators with adequate decision support and achieving efficient resource scheduling, even when a significant number of alternative scenarios should be considered. The paper includes two realistic case studies with different penetration of gridable vehicles (1000 and 2000). The proposed methodology is about 2600 times faster than Mixed-Integer Non-Linear Programming (MINLP) reference technique, reducing the time required from 25 h to 36 s for the scenario with 2000 vehicles, with about one percent of difference in the objective function cost value.

Modelling and optimization of the ion exchange membrane bioreactor for removal of anionic pollutants from drinking water streams

Dissertação para obtenção do Grau de Doutor em Engenharia Química, especialidade de Engenharia Bioquímica

Valorização da Drêche Cervejeira: Fermentação de Pentoses

O presente trabalho tem como objetivo a otimização da etapa de fermentação dos açúcares obtidos a partir da drêche cervejeira para produção do bioetanol através da utilização das leveduras Pichia stipitis NCYC 1541 e Kluyveromyces marxianus NCYC 2791 como agentes fermentativos. O meio de cultura usado para manter as culturas destas leveduras foi Yeast Extract Peptone Dextrose (YEPD). O principal propósito deste trabalho foi o de encontrar alternativas aos combustíveis fósseis, pautando-se por soluções inofensivas para o meio ambiente e sustentáveis. Assim, o trabalho está dividido em quatro etapas: 1) caraterização química e biológica da drêche; 2) pré-tratamento ácido e hidrólise enzimática para primeiramente quebrar as moléculas de lenhina que envolvem os polímeros de celulose e hemicelulose e em seguida romper as ligações poliméricas destas macromoléculas por ação enzimática e transforma-las em açúcares simples, respetivamente, obtendo-se então a glucose, a maltose, a xilose e a arabinose; e, por último, 3) otimização da etapa de fermentação da glucose, maltose e das pentoses que constitui a condição essencial para se chegar à síntese do bioetanol de um modo eficiente e sustentável e 4) a recuperação do bioetanol produzido por destilação fracionada. A quantificação dos açúcares libertados no processo foi feita recorrendo a análises por cromatografia líquida de alta eficiência (HPLC). Neste estudo foram identificados e quantificados cinco açúcares: Arabinose, Glucose, Maltose, Ribose e Xilose. Na etapa de pré-tratamento e hidrólise enzimática foram usados os ácidos clorídrico (HCl) e nítrico (HNO3) com a concentração de 1% (m/m), e as enzimas Glucanex 100g e Ultraflo L. Foram testadas seis condições de pré-tratamento e hidrólise enzimática, alterando os parâmetros tempo de contacto e razão enzimas/massa de drêche, respetivamente, e mantendo a temperatura (50 ºC), velocidade de agitação (75 rpm) e concentração dos ácidos (1% (m/m)). No processamento de 25 g de drêche seca com 0,5 g de Glucanex, 0,5 mL de Ultraflo e um tempo de reação de 60 minutos para as enzimas foi obtida uma eficiência de 15%, em hidrolisado com 6% da celulose. Realizou-se a fermentação do hidrolisado resultante do pré-tratamento ácido e hidrólise enzimática de drêche cervejeira e de meios sintéticos preparados com os açúcares puros, usando as duas estirpes selecionadas para este estudo: Pichia stipitis NCYC 1541 e Kluyveromyces marxianus NYCY 2791. As eficiências de fermentação dos açúcares nos meios sintéticos foram superiores a 80% para ambas as leveduras. No entanto, as eficiências de fermentação do hidrolisado da drêche foram de 45,10% pela Pichia stipitis e de 36,58 para Kluyveromyces marxianus, para um tempo de fermentação de 72 horas e à temperatura de 30 °C. O rendimento teórico em álcool no hidrolisado da drêche é de 0,27 g/g, três vezes maior do que o real (0,0856 g/g), para Pichia stipitis e de 0,19 g/g seis vezes maior do que o real (0,0308 g/g), para a Kluyveromyces marxianus.