Repositório Colecção: Capítulos de Livros
https://hdl.handle.net/1822/3717
Capítulos de Livros2024-03-29T15:26:50ZExtrusion compounding of polyethylene with blowing agent
https://hdl.handle.net/1822/90274
Título: Extrusion compounding of polyethylene with blowing agent
Autor: Martins, Carla I.; Covas, J. A.; Ferreira, Tiago
Resumo: Cellular plastics are very attractive for the production of lightweight, structural and/or large
dimension parts, e.g., boats, floaters, decks, etc. For their production, polymers and chemical
blowing agents are either mixed or compounded prior to processing by injection or rotational
moulding. It is essential to ensure good dispersion of the blowing agent in the polymeric matrix,
and prevent its activation from occurring during compounding, i.e., an optimal processing
window must be used. The aim of this work is to produce medium density polyethylene with
Azodicarbonamide (MDPE/ADCA) masterbatches in pellet form for further processing by
rotational moulding. For that purpose, a set of experimental procedures was conducted to
evaluate the correct processing window without premature expansion during extrusion. Upon
melt compounding of the masterbatch in pellets of different sizes, foamed parts were produced
and characterized in terms of visual aspect, expansion ability and morphology.
<b>Tipo</b>: bookPart2024-03-28T14:35:31ZReliability and NDT methods
https://hdl.handle.net/1822/89749
Título: Reliability and NDT methods
Autor: Santos, Telmo G.; Oliveira, J. P.; Machado, Miguel A.; Inácio, Patrick L.; Duarte, Valdemar R.; Rodrigues, Tiago A.; Santos, Rui A.; Simão, Carlos; Carvalho, Marta; Martins, Ana; Nascimento, Micael; Novais, Susana; Ferreira, Marta S.; Pinto, João L.; Fernandes, Francisco B.; Camacho, Edgar; Viana, J. C.; Miranda, R. M.
Resumo: Composites are finding increased use in structural high demanding and high added value applications in advanced industries. A wide diversity exists in terms of matrix type, which can be either polymeric or metallic and type of reinforcements (ceramic, polymeric or metallic). Several technologies have been used to produce these composites; among them, additive manufacturing (AM) is currently being applied. In structural applications, the presence of defects due to fabrication is of major concern, since it affects the performance of a component with negative impact, which can affect, ultimately, human lives. Thus, the detection of defects is highly important, not only surface defects but also barely visible defects. This chapter describes the main types of defects expected in composites produced by AM. The fundamentals of different non-destructive testing (NDT) techniques are briefly discussed, as well as the state of the art of numerical simulation for several NDT techniques. A multiparametric and customized inspection system was developed based on the combination of innovative techniques in modelling and testing. Experimental validation with eddy currents, ultrasounds, X-ray and thermography is presented and analysed, as well as integration of distinctive techniques and 3D scanning characterization.
<b>Tipo</b>: bookPartReducing the number of objectives for many-objectives optimization: empirical analysis of a machine learning approach
https://hdl.handle.net/1822/87572
Título: Reducing the number of objectives for many-objectives optimization: empirical analysis of a machine learning approach
Autor: Gaspar-Cunha, A.; Costa, Paulo; Monaco, Francisco; Delbem, Alexandre
Editor: Gauger, Nicolas; Giannakoglou, Kyriakos; Papadrakakis, Manolis; Periaux, Jacques
Resumo: The practical need of solving real-world optimization problems is faced very often of dealing with many objectives, but from the beginning, a question arises: Are all the objectives really necessary? The answer to this question lies in the complex relations existing between the parameters of the process, i.e., not only between the objectives and the decision variables (DVs), but also between the DVs and DVs and between the objectives and objectives. Simultaneously, intense research is made to improve the performance of multi-objective population-based algorithms to deal with many objectives that, often, imply complex algorithms and time consuming computations with complex results that experts on the field of the problem might not understand and, as a consequence, did not accept and apply in practice. A straightforward alternative is to infer the complex relations between the process parameters with the aim of reducing the number of objectives. The use of Machine Learning (ML) methodologies for that can be very useful since it is someway demonstrated in the literature on the subject of reducing the number of objectives. In this work, ML is used to reduce the number of objectives and the results are assessed empirically using a real-world application.
<b>Tipo</b>: bookPart2023-12-18T10:44:37ZIdentifying correlations in understanding and solving many-objective optimisation problems
https://hdl.handle.net/1822/87570
Título: Identifying correlations in understanding and solving many-objective optimisation problems
Autor: Chugh, T.; Gaspar-Cunha, A.; Deutz, A. H.; Duro, J. A.; Oara, D. C.; Rahat, A.
Editor: Brockhoff, D.; Emmerich, M.; Naujoks, B.; Purshouse, R
Resumo: Optimisation problems involving multiple objectives are commonly found in real-world applications. The existence of conflicting objectives produces trade-offs where a solution can be better with respect to one objective but requires a compromise in the other objectives. In many real-world problems the relationship between objectives is unknown or uncertain, and it is common to find problems with non-conflicting objectives. Understanding these relationships has been proven useful in different ways. The search efficiency of a multi-objective optimisation algorithm can benefit if objectives that are not essential to describe the Pareto-optimal front are omitted during the search procedure. Analysts and decision makers might get a better understanding about exiting synergies between the objectives, in turn facilitating the decision-making process of identifying the best solution. One particular useful technique to capture the relationships between objective functions is to rely on correlation measures. This chapter explores the literature of finding correlations among objective functions in solving multi-objective optimisation problems. Particularly, we focus on innovization and objective reduction approaches. We explain different statistical correlation measures and also provide details of benchmark and real-world optimisation problems solved by exploiting the correlations. This chapter provides an insight in solving multi-objective optimisation problems by considering the correlation among objective functions.
<b>Tipo</b>: bookPart2023-12-18T10:07:16ZScalability of multi-objective evolutionary algorithms for solving real-world complex optimization problems
https://hdl.handle.net/1822/87569
Título: Scalability of multi-objective evolutionary algorithms for solving real-world complex optimization problems
Autor: Gaspar-Cunha, A.; Costa, Paulo; Monaco, Francisco; Delbem, Alexandre
Editor: Emmerich, M.; Deutz, A.; Wang. H.; Kononova, A.; Naujoks, B.; Li, K.; Miettinen, K.; Yevseyeva. I.
Resumo: The use Multi-Objective Evolutionary Algorithms (MOEAs) to solve real-world multi-objective optimization problems often finds a problem designated by the curse of dimensionality. This is mainly because the progression of the algorithm along successive generations is based on non-dominance relations that practically do not exist when the number of objectives is high. Also, the existence of many objectives makes the choice of a solution to the problem under study very difficult. Several methods have been proposed in the literature to reduce the number of objectives to use during the optimization process. In the present work, a methodology to reduce the number of objectives is proposed. This method is based on DAMICORE (DAta MIning of COde REpositories), a machine-learning algorithm proposed by the authors. A theoretical comparison with a similar machine learning approach is made, pointing out some advantages of using the proposed algorithm using a benchmark problem designated by DTLZ5. Also, a real problem is used to show the effectiveness of the methodology.
<b>Tipo</b>: conferencePaper2023-12-18T10:00:32Z