694 research outputs found
Multi-objective ant colony optimization for the twin-screw configuration problem
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
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
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)
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
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
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Understanding matrix-assisted continuous co-crystallization using a data mining approach in Quality by Design (QbD)
YesThe present study demonstrates the application of decision tree algorithms to the co-crystallization process. Fifty four (54) batches of carbamazepine-salicylic acid co-crystals embedded in poly(ethylene oxide) were manufactured via hot melt extrusion and characterized by powder X-ray diffraction, differnetial scanning calorimetry, and near-infrared spectroscopy. This dataset was then applied in WEKA, which is an open-sourced machine learning software to study the effect of processing temperature, screw speed, screw configuration, and poly(ethylene oxide) concentration on the percentage of co-crystal conversion. The decision trees obtained provided statistically meaningful and easy-to-interpret rules, demonstrating the potential to use the method to make rational decisions during the development of co-crystallization processes.Commonwealth Scholarship Commission in the UK (ZMCS-2018-783) and Engineering and Physical Sciences Research Council (EPSRC EP/J003360/1 and EP/L027011/1
Application of Machine Learning Tools for the Improvement of Reactive Extrusion Simulation
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
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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