Generalized interval vector spaces and interval optimization

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Optimal control strategy for fed-batch enzymatic hydrolysis of lignocellulosic biomass based on epidemic modeling

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Estudo da dinâmica de populações utilizando a técnica de polinômios de colocação

Pós-graduação em Engenharia Elétrica - FEB

Solving the multiobjective environmental/economic dispatch problem using weighted sum and ε-constraint strategies and a predictor-corrector primal-dual interior point method

This paper proposes a technique for solving the multiobjective environmental/economic dispatch problem using the weighted sum and ε-constraint strategies, which transform the problem into a set of single-objective problems. In the first strategy, the objective function is a weighted sum of the environmental and economic objective functions. The second strategy considers one of the objective functions: in this case, the environmental function, as a problem constraint, bounded above by a constant. A specific predictor-corrector primal-dual interior point method which uses the modified log barrier is proposed for solving the set of single-objective problems generated by such strategies. The purpose of the modified barrier approach is to solve the problem with relaxation of its original feasible region, enabling the method to be initialized with unfeasible points. The tests involving the proposed solution technique indicate i) the efficiency of the proposed method with respect to the initialization with unfeasible points, and ii) its ability to find a set of efficient solutions for the multiobjective environmental/economic dispatch problem.

Design of laminated piezocomposite shell transducers with arbitrary fiber orientation using topology optimization approach

Sensor and actuator based on laminated piezocomposite shells have shown increasing demand in the field of smart structures. The distribution of piezoelectric material within material layers affects the performance of these structures; therefore, its amount, shape, size, placement, and polarization should be simultaneously considered in an optimization problem. In addition, previous works suggest the concept of laminated piezocomposite structure that includes fiber-reinforced composite layer can increase the performance of these piezoelectric transducers; however, the design optimization of these devices has not been fully explored yet. Thus, this work aims the development of a methodology using topology optimization techniques for static design of laminated piezocomposite shell structures by considering the optimization of piezoelectric material and polarization distributions together with the optimization of the fiber angle of the composite orthotropic layers, which is free to assume different values along the same composite layer. The finite element model is based on the laminated piezoelectric shell theory, using the degenerate three-dimensional solid approach and first-order shell theory kinematics that accounts for the transverse shear deformation and rotary inertia effects. The topology optimization formulation is implemented by combining the piezoelectric material with penalization and polarization model and the discrete material optimization, where the design variables describe the amount of piezoelectric material and polarization sign at each finite element, with the fiber angles, respectively. Three different objective functions are formulated for the design of actuators, sensors, and energy harvesters. Results of laminated piezocomposite shell transducers are presented to illustrate the method. Copyright (C) 2012 John Wiley & Sons, Ltd.

Multiobjective engineering design optimization problems: a sensitivity analysis approach

This paper proposes two new approaches for the sensitivity analysis of multiobjective design optimization problems whose performance functions are highly susceptible to small variations in the design variables and/or design environment parameters. In both methods, the less sensitive design alternatives are preferred over others during the multiobjective optimization process. While taking the first approach, the designer chooses the design variable and/or parameter that causes uncertainties. The designer then associates a robustness index with each design alternative and adds each index as an objective function in the optimization problem. For the second approach, the designer must know, a priori, the interval of variation in the design variables or in the design environment parameters, because the designer will be accepting the interval of variation in the objective functions. The second method does not require any law of probability distribution of uncontrollable variations. Finally, the authors give two illustrative examples to highlight the contributions of the paper.

Algoritmos evolutivos e modelo HP para predição de estruturas de proteínas

Predição de estruturas de proteínas (PSP) é um problema computacionalmente complexo. Modelos simplificados da molécula proteica (como o Modelo HP) e o uso de Algoritmos Evolutivos (AEs) estão entre as principais técnicas investigadas para PSP. Entretanto, a avaliação de uma estrutura representada pelo Modelo HP considera apenas o número de contatos hidrofóbicos, não possibilitando distinguir entre estruturas com o mesmo número de contatos hidrofóbicos. Neste trabalho, é apresentada uma nova formulação multiobjetivo para PSP em Modelo HP. Duas métricas são avaliadas: o número de contatos hidrofóbicos e a distância entre os aminoácidos hidrofóbicos, as quais são tratados pelo AE Multiobjetivo em Tabelas (AEMT). O algoritmo mostrou-se rápido e robusto.

Development of heat sink device by using topology optimization

Small scale fluid flow systems have been studied for various applications, such as chemical reagent dosages and cooling devices of compact electronic components. This work proposes to present the complete cycle development of an optimized heat sink designed by using Topology Optimization Method (TOM) for best performance, including minimization of pressure drop in fluid flow and maximization of heat dissipation effects, aiming small scale applications. The TOM is applied to a domain, to obtain an optimized channel topology, according to a given multi-objective function that combines pressure drop minimization and heat transfer maximization. Stokes flow hypothesis is adopted. Moreover, both conduction and forced convection effects are included in the steady-state heat transfer model. The topology optimization procedure combines the Finite Element Method (to carry out the physical analysis) with Sequential Linear Programming (as the optimization algorithm). Two-dimensional topology optimization results of channel layouts obtained for a heat sink design are presented as example to illustrate the design methodology. 3D computational simulations and prototype manufacturing have been carried out to validate the proposed design methodology.

Paralelización del código de desenredo y suavizado de mallas de tetraedros "S.U.S Code"

Máster Universitario en Sistemas Inteligentes y Aplicaciones Numéricas en Ingeniería (SIANI)

Application of evolutionary algorithms and the boundary element method in the optimization of noise barrier profiles

[EN]This Ph.D. thesis presents a general, robust methodology that may cover any type of 2D acoustic optimization problem. A procedure involving the coupling of Boundary Elements (BE) and Evolutionary Algorithms is proposed for systematic geometric modifications of road barriers that lead to designs with ever-increasing screening performance. Numerical simulations involving single- and multi-objective optimizations of noise barriers of varied nature are included in this document. results disclosed justify the implementation of this methodology by leading to optimal solutions of previously defined topologies that, in general, greatly outperform the acoustic efficiency of classical, widely used barrier designs normally erected near roads.

Multiobjective genetic algorithms applied to heat transfer problems

In the present work, the multi-objective optimization by genetic algorithms is investigated and applied to heat transfer problems. Firstly, the work aims to compare different reproduction processes employed by genetic algorithms and two new promising processes are suggested. Secondly, in this work two heat transfer problems are studied under the multi-objective point of view. Specifically, the two cases studied are the wavy fins and the corrugated wall channel. Both these cases have already been studied by a single objective optimizer. Therefore, this work aims to extend the previous works in a more comprehensive study.

Calibrazione di modelli idrologici con algoritmi multiobiettivo

Traditional procedures for rainfall-runoff model calibration are generally based on the fit of the individual values of simulated and observed hydrographs. It is used here an alternative option that is carried out by matching, in the optimisation process, a set of statistics of the river flow. Such approach has the additional, significant advantage to allow also a straightforward regional calibration of the model parameters, based on the regionalisation of the selected statistics. The minimisation of the set of objective functions is carried out by using the AMALGAM algorithm, leading to the identification of behavioural parameter sets. The procedure is applied to a set of river basins located in central Italy: the basins are treated alternatively as gauged and ungauged and, as a term of comparison, the results obtained with a traditional time-domain calibration is also presented. The results show that a suitable choice of the statistics to be optimised leads to interesting results in real world case studies as far as the reproduction of the different flow regimes is concerned.

Sviluppo di tecniche per la progettazione delle reti di monitoraggio della qualita' dell'aria

L’obiettivo del lavoro consiste nell’implementare una metodologia operativa volta alla progettazione di reti di monitoraggio e di campagne di misura della qualità dell’aria con l’utilizzo del laboratorio mobile, ottimizzando le posizioni dei dispositivi di campionamento rispetto a differenti obiettivi e criteri di scelta. La revisione e l’analisi degli approcci e delle indicazioni fornite dalla normativa di riferimento e dai diversi autori di lavori scientifici ha permesso di proporre un approccio metodologico costituito da due fasi operative principali, che è stato applicato ad un caso studio rappresentato dal territorio della provincia di Ravenna. La metodologia implementata prevede l’integrazione di numerosi strumenti di supporto alla valutazione dello stato di qualità dell’aria e degli effetti che gli inquinanti atmosferici possono generare su specifici recettori sensibili (popolazione residente, vegetazione, beni materiali). In particolare, la metodologia integra approcci di disaggregazione degli inventari delle emissioni attraverso l’utilizzo di variabili proxy, strumenti modellistici per la simulazione della dispersione degli inquinanti in atmosfera ed algoritmi di allocazione degli strumenti di monitoraggio attraverso la massimizzazione (o minimizzazione) di specifiche funzioni obiettivo. La procedura di allocazione sviluppata è stata automatizzata attraverso lo sviluppo di un software che, mediante un’interfaccia grafica di interrogazione, consente di identificare delle aree ottimali per realizzare le diverse campagne di monitoraggio

Optimal game theoretic distributed control methodologies in small scale power systems

This dissertation presents the competitive control methodologies for small-scale power system (SSPS). A SSPS is a collection of sources and loads that shares a common network which can be isolated during terrestrial disturbances. Micro-grids, naval ship electric power systems (NSEPS), aircraft power systems and telecommunication system power systems are typical examples of SSPS. The analysis and development of control systems for small-scale power systems (SSPS) lacks a defined slack bus. In addition, a change of a load or source will influence the real time system parameters of the system. Therefore, the control system should provide the required flexibility, to ensure operation as a single aggregated system. In most of the cases of a SSPS the sources and loads must be equipped with power electronic interfaces which can be modeled as a dynamic controllable quantity. The mathematical formulation of the micro-grid is carried out with the help of game theory, optimal control and fundamental theory of electrical power systems. Then the micro-grid can be viewed as a dynamical multi-objective optimization problem with nonlinear objectives and variables. Basically detailed analysis was done with optimal solutions with regards to start up transient modeling, bus selection modeling and level of communication within the micro-grids. In each approach a detail mathematical model is formed to observe the system response. The differential game theoretic approach was also used for modeling and optimization of startup transients. The startup transient controller was implemented with open loop, PI and feedback control methodologies. Then the hardware implementation was carried out to validate the theoretical results. The proposed game theoretic controller shows higher performances over traditional the PI controller during startup. In addition, the optimal transient surface is necessary while implementing the feedback controller for startup transient. Further, the experimental results are in agreement with the theoretical simulation. The bus selection and team communication was modeled with discrete and continuous game theory models. Although players have multiple choices, this controller is capable of choosing the optimum bus. Next the team communication structures are able to optimize the players’ Nash equilibrium point. All mathematical models are based on the local information of the load or source. As a result, these models are the keys to developing accurate distributed controllers.

Service Level Agreements-Driven Management of Distributed Applications in Cloud Computing Environments

Cloud Computing enables provisioning and distribution of highly scalable services in a reliable, on-demand and sustainable manner. However, objectives of managing enterprise distributed applications in cloud environments under Service Level Agreement (SLA) constraints lead to challenges for maintaining optimal resource control. Furthermore, conflicting objectives in management of cloud infrastructure and distributed applications might lead to violations of SLAs and inefficient use of hardware and software resources. This dissertation focusses on how SLAs can be used as an input to the cloud management system, increasing the efficiency of allocating resources, as well as that of infrastructure scaling. First, we present an extended SLA semantic model for modelling complex service-dependencies in distributed applications, and for enabling automated cloud infrastructure management operations. Second, we describe a multi-objective VM allocation algorithm for optimised resource allocation in infrastructure clouds. Third, we describe a method of discovering relations between the performance indicators of services belonging to distributed applications and then using these relations for building scaling rules that a CMS can use for automated management of VMs. Fourth, we introduce two novel VM-scaling algorithms, which optimally scale systems composed of VMs, based on given SLA performance constraints. All presented research works were implemented and tested using enterprise distributed applications.