694 research outputs found

    Polymer extrusion: setting the operating conditions and defining the screw geometry

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    Multi-objective ant colony optimization for the twin-screw configuration problem

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    The Twin-Screw Configuration Problem (TSCP) consists in identifying the best location of a set of available screw elements along a screw shaft. Due to its combinatorial nature, it can be seen as a sequencing problem. In addition, different conflicting objectives may have to be considered when defining a screw configuration and, thus, it is usually tackled as a multi-objective optimization problem. In this research, a multi-objective ant colony optimization (MOACO) algorithm was adapted to deal with the TSCP. The influence of different parameters of the MOACO algorithm was studied and its performance was compared with that of a previously proposed multi-objective evolutionary algorithm and a two-phase local search algorithm. The experimental results showed that MOACO algorithms have a significant potential for solving the TSCP.This work has been supported by the Portuguese Fundacao para a Ciencia e Tecnologia under PhD grant SFRH/BD/21921/2005. Thomas Stutzle acknowledges support of the Belgian F.R.S-FNRS of which he is a research associate, the E-SWARM project, funded by an ERC Advanced Grant, and by the Meta-X project, funded by the Scientific Research Directorate of the French Community of Belgium

    Modelling the Interfacial Flow of Two Immiscible Liquids in Mixing Processes

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    This paper presents an interface tracking method for modelling the flow of immiscible metallic liquids in mixing processes. The methodology can provide an insight into mixing processes for studying the fundamental morphology development mechanisms for immiscible interfaces. The volume-of-fluid (VOF) method is adopted in the present study, following a review of various modelling approaches for immiscible fluid systems. The VOF method employed here utilises the piecewise linear for interface construction scheme as well as the continuum surface force algorithm for surface force modelling. A model coupling numerical and experimental data is established. The main flow features in the mixing process are investigated. It is observed that the mixing of immiscible metallic liquids is strongly influenced by the viscosity of the system, shear forces and turbulence. The numerical results show good qualitative agreement with experimental results, and are useful for optimisating the design of mixing casting processes

    Designing screws for polymer compounding in twin-screw extruders

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    Tese de doutoramento em Ciência e Engenharia de Polímeros e CompósitosConsidering its modular construction, co-rotating twin screw extruders can be easily adapted to work with polymeric systems with more stringent specifications. However, their geometrical flexibility makes the performance of these machines strongly dependent on the screw configuration. Therefore, the definition of the adequate screw geometry to use in a specific polymer system is an important process requirement which is currently achieved empirically or using a trial-and-error basis. The aim of this work is to develop an automatic optimization methodology able to define the best screw geometry/configuration to use in a specific compounding/reactive extrusion operation, reducing both cost and time. This constitutes an optimization problem where a set of different screw elements are to be sequentially positioned along the screw in order to maximize the extruder performance. For that, a global modeling program considering the most important physical, thermal and rheological phenomena developing along the axis of an intermeshing co-rotating twin screw extruder was initially developed. The accuracy and sensitivity of the software to changes in the input parameters was tested for different operating conditions and screw configurations using a laboratorial Leistritz LSM 30.34 extruder. Then, this modeling software was integrated into an optimization methodology in order to be possible solving the Twin Screw Configuration Problem. Multi-objective versions of local search algorithms (Two Phase Local Search and Pareto Local Search) and Ant Colony Optimization algorithms were implemented and adapted to deal with the combinatorial, discrete and multi-objective nature of the problem. Their performance was studied making use of the hypervolume indicator and Empirical Attainment Function, and compared with the Reduced Pareto Search Genetic Algorithm (RPSGA) previously developed and applied to this problem. In order to improve the quality of the results and/or to decrease the computational cost required by the optimization methodology, different hybrid algorithms were tested. The approaches developed considers the use of local search procedures (TPLS and PLS algorithms) into population based metaheuristics, as MOACO and MOEA algorithms. Finally, the optimization methodology developed was applied to the optimization of a starch cationization reaction. Several starch cationization case studies, involving different screw elements screw lengths and conflicting objectives, were tested in order to validate this technique and to prove the potential of this automatic optimization methodology.Devido à sua construção modular, as extrusoras de duplo-fuso co-rotativas podem ser facilmente adaptadas a sistemas poliméricos que requerem especificações mais rigorosas. No entanto, esta flexibilidade geométrica torna o seu desempenho fortemente dependente da configuração do parafuso. Por isso, a tarefa de definir a melhor configuração do parafuso para usar num determinado sistema polimérico é um requisito importante do processo que é actualmente realizada empiricamente ou utilizando um processo de tentativa erro. O objectivo principal deste trabalho é desenvolver uma metodologia automática de optimização que seja capaz de definir a melhor configuração/geometria do parafuso a usar num determinado sistema de extrusão, reduzindo custos e tempo. Este problema é um problema de optimização, onde os vários elementos do parafuso têm que ser sequencialmente posicionados ao longo do eixo do parafuso de forma a maximizar o desempenho da extrusora. Para isso, foi inicialmente desenvolvido um programa de modelação que considera os mais importantes fenómenos físicos, térmicos e reológicos que ocorrem ao longo da extrusora de duplo fuso co-rotativa. De forma a testar a precisão e a sensibilidade do software às alterações dos parâmetros, diversas condições operativas e configurações de parafuso foram testadas tendo como base uma extrusora laboratorial Leistritz LSM 30.34. Seguidamente, este software de modelação foi integrado numa metodologia de optimização com vista à resolução do problema de configuração da extrusora de duplo-fuso. Para lidar com a natureza combinatorial, discreta e multi-objectiva do problema em estudo, foram adaptadas e implementadas versões multi-objectivas de algoritmos de procura local (Two-Phase Local Search and Pareto Local Search) e Ant Colony Optimization. O desempenho dos diversos algoritmos foi estudado usando o hipervolume e as Empirical Attainment Functions. Os resultados foram comparados com os resultados obtidos com o algoritmo genético Reduced Pareto Search Genetic Algorithm (RPSGA) desenvolvido e aplicado anteriormente a este problema. Com o objectivo de melhorar a qualidade dos resultados e/ou diminuir o esforço computacional exigido pela metodologia de optimização, foram testadas diversas hibridizações. Os algoritmos híbridos desenvolvidos consideram a integração de algoritmos de procura local (TPLS e PLS) noutras metheuristicas, como MOACO e MOEA. Por fim, a metodologia de optimização desenvolvida neste trabalho foi testada na optimização de uma reacção de cationização do amido. Para validar esta técnica e provar o seu potencial, foram realizados vários estudos envolvendo diferentes elementos e comprimentos de parafusos, bem como, a optimização de objectivos em conflito

    Optimization of polymer processing: a review (Part I - Extrusion)

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    Given the global economic and societal importance of the polymer industry, the continuous search for improvements in the various processing techniques is of practical primordial importance. This review evaluates the application of optimization methodologies to the main polymer processing operations. The most important characteristics related to the usage of optimization techniques, such as the nature of the objective function, the type of optimization algorithm, the modelling approach used to evaluate the solutions, and the parameters to optimize, are discussed. The aim is to identify the most important features of an optimization system for polymer processing problems and define the best procedure for each particular practical situation. For this purpose, the state of the art of the optimization methodologies usually employed is first presented, followed by an extensive review of the literature dealing with the major processing techniques, the discussion being completed by considering both the characteristics identified and the available optimization methodologies. This first part of the review focuses on extrusion, namely single and twin-screw extruders, extrusion dies, and calibrators. It is concluded that there is a set of methodologies that can be confidently applied in polymer processing with a very good performance and without the need of demanding computation requirements.This research was funded by NAWA-Narodowa Agencja Wymiany Akademickiej, under grant PPN/ULM/2020/1/00125 and European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie Grant Agreement No 734205–H2020-MSCA-RISE-2016. The authors also acknowledge the funding by FEDER funds through the COMPETE 2020 Programme and National Funds through FCT (Portuguese Foundation for Science and Technology) under the projects UID-B/05256/2020, UID-P/05256/2020

    ROM-Based Stochastic Optimization for a Continuous Manufacturing Process

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    This paper proposes a model-based optimization method for the production of automotive seals in an extrusion process. The high production throughput, coupled with quality constraints and the inherent uncertainty of the process, encourages the search for operating conditions that minimize nonconformities. The main uncertainties arise from the process variability and from the raw material itself. The proposed method, based on Bayesian optimization, takes these factors into account and obtains a robust set of process parameters. Due to the high computational cost and complexity of performing detailed simulations, a reduced order model is used to address the optimization. The proposal has been evaluated in a virtual environment where it is shown that the performance of the solution found minimizes the effects of process uncertainties.Comment: 7 pages, 8 figure

    Application of Machine Learning Tools for the Improvement of Reactive Extrusion Simulation

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    The purpose of this paper is to combine a classical 1D twin-screw extrusion model with machine learning techniques to obtain accurate predictions of a complex system despite few data. Systems involving reactive polyethylene oligomer dispersed in situ in a polypropylene matrix by reactive twin-screw extrusion are studied for this purpose. The twin-screw extrusion simulation software LUDOVIC is used and machine learning techniques dealing with low data limit are used as a correction of the simulation.This research was funded by the French ANR through the DataBEST project

    Engineering for a changing world: 60th Ilmenau Scientific Colloquium, Technische Universität Ilmenau, September 04-08, 2023 : programme

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    In 2023, the Ilmenau Scientific Colloquium is once more organised by the Department of Mechanical Engineering. The title of this year’s conference “Engineering for a Changing World” refers to limited natural resources of our planet, to massive changes in cooperation between continents, countries, institutions and people – enabled by the increased implementation of information technology as the probably most dominant driver in many fields. The Colloquium, supplemented by workshops, is characterised but not limited to the following topics: – Precision engineering and measurement technology Nanofabrication – Industry 4.0 and digitalisation in mechanical engineering – Mechatronics, biomechatronics and mechanism technology – Systems engineering – Productive teaming - Human-machine collaboration in the production environment The topics are oriented on key strategic aspects of research and teaching in Mechanical Engineering at our university
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