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

Studies on Powder Compaction and Wire Extrusion of Pure Metals and Metal/CNT Nano Composites

The goal of this dissertation is to fabricate wires made of Cu/CNT and Al/CNT composites with good mechanical strength and super thermal/electrical conductivities using powder compaction and wire extrusion manufacturing processes. Powder compaction was studied using both test and simulation. Cold compaction, hot compaction and vibration assisted (cold) compaction tests were conducted to achieve different density ratios. Hot compaction tests improved about 6% compared with cold compaction under the same compression pressure. Although the relative density ratio does not obviously improve at vibration assisted (cold) compaction, the strength of the specimens made under vibration loading is much better than those of cold compaction. Additionally, finite element models with well calibrated Drucker Prager Cap (DPC) material constitutive model were built in Abaqus/Standard to simulate powder compaction processes. The results of finite element model have excellent correlations with test results up to the tested range, and finite element models can further predict the loading conditions required in order to achieve the higher density ratios of the materials. Two exponential formulas for predicting density ratio were obtained by combining the test data and the simulation results. A new analytical solution was first time developed to predict the axial pressure versus the density ratio for powder compaction according to DPC material model. The results between analytical solution and simulation model have an excellent match. Extrusion method was adopted to produce wires of aluminum (Al), copper (Cu) and copper/carbon nanotubes (Cu/CNTs) composites. A new analytical solution was developed to predict magnitude of extrusion force, where friction effects between die and sample were considered. The analytical solution achieved a much better result than the classical slip line theory and other existing analytical solutions. Extensive finite element (FE) models were built to validate the analytical solution under different extrusion conditions. FE simulation cases were run for different die angles (including 30°, 45° and 60°) and different extrusion area ratios (including 16:1 and 4:1). The comparison results showed a good match between analytical solutions and finite element models. Both Eulerian and Lagrangian methods were set up and compared in finite element models in order to predict the extrusion force during the extrusion process. Four wire extrusion tests of metals and metal/CNTs composites were successfully conducted under elevated temperatures ranging from 300°C to 703°C. Test results further validated the accuracy of the analytical solution

Integrated feedstock optimisation for multi-product polymer production

Thesis (PhD)--Stellenbosch University, 2022.ENGLISH ABSTRACT: A chemical complex can have multiple value chains, some of which may span across geographical locations. Decisions regarding the distribution of feedstock and intermediate feedstock to different production units can occur at different time intervals. This is highlighted as two problems, a feedstock distribution problem and an intermediate feedstock distribution problem. Unexpected events can cause an imbalanced value chain which requires timely decision-making to mitigate further adverse consequences. Scheduling methods can provide decision support during such events. The purpose of this research study is to develop an integrated decision support system which handles the two problems as a single problem and maximises profit in the value chain for hourly and daily decision-making. A high-level DSS architecture is presented that incorporates metaheuristic algorithms to generate production schedules for distribution of feedstock through the value chain. The solution evaluation process contains a balancing period to enable the application of metaheuristics to this type of problem and a novel encoding scheme is proposed for the hourly interval problem. It was found that metaheuristics algorithms can be used for this problem and integrated into the proposed decision support system.AFRIKAANSE OPSOMMING: ’n Chemiese kompleks kan verskeie waardekettings hê, waarvan sommige oor geografiese gebiede strek. Besluite rakende die verspreiding van grondstowwe en intermediêre grondstowwe na verskillende produksie-eenhede kan op verskillende tydsintervalle plaasvind. Dit word uitgelig as twee probleme: ’n probleem met die verspreiding van grondstowwe en ’n intermediêre grondstowwe verspreidingsprobleem. Onverwagte gebeure kan ’n ongebalanseerde waardeketting veroorsaak wat tydige besluitneming benodig om verdere gevolge te versag. Beplanningsmetodes kan ondersteuning bied tydens sulke geleenthede. Die doel van hierdie navorsingstudie was om ’n geïntegreerde stelsel vir besluitnemingsondersteuning oor die twee probleme as een probleem te ontwikkel, wat wins in die waardeketting vir uurlikse en daaglikse besluitneming maksimeer. ’n Hoëvlak DSS-argitektuur word aangebied met metaheuristieke om produksieskedules vir verspreidingstowwe deur die waardeketting te genereer. Die oplossingsevalueringsproses bevat ’n balanseerperiode om die metaheuristiek op hierdie tipe probleme toe te pas, en ’n nuwe koderingskema word voorgestel vir die uurlikse intervalprobleem. Die gevolgtrekking word gemaak dat metaheuristieke vir hierdie probleem gebruik kan word en ge¨ıntegreer kan word in die voorgestelde ondersteuningsstelsel vir besluitneming.Doctora

Optimization of Aluminium Profiles Production Planning

Dissertação de Mestrado Métodos de Apoio à Decisão EmpresarialNo atual ambiente empresarial, a crescente competitividade impulsiona as empresas a implementar estratégias de otimização para assegurar ou melhorar a sua posição no mercado. Nesse sentido é crucial tomar as melhores decisões do ponto de vista do planeamento da produção. A produção de perfis de alumínio apresenta vários desafios ao responsável da produção. Este trabalho aborda um caso real de uma empresa do setor metalúrgico, cuja área de negocio é o desenvolvimento e produção de perfis de alumínio para aplicação em diversas áreas, como obras de engenharia, arquitetura e industria em geral. O objetivo é minimizar o desperdício ocorrido na produção, designado de sucata, através da minimização dos tempos de preparação, que ocorrem quando a matriz é trocada, respeitando os prazos de entrega do produto e garantindo a qualidade. Este estudo de caso centra-se num problema de sequenciamento de flow shop que envolve tempos de preparação dependentes da sequência decorrentes da necessidade de alterar as ferramentas usadas no processo de extrusão de alumínio. Um modelo de programação inteira mista é desenvolvido e implementado para responder ao desafio da empresa. O problema será formulado na linguagem de modelagem AMPL e seria usado o solver Gurobi para resolver instâncias reais extraídas dos dados providenciados pela empresa. Os resultados obtidos com o modelo desenvolvido são comparados com a regra de despacho FIFO, em termos da soma dos tempos de preparação (e consequentemente do número de trocas de matrizes), bem como o cumprimento do prazo de entrega. Além disso, embora o procedimento atual da empresa não seja conhecido, os resultados obtidos são comparados com a média de trocas de matriz obtidas a partir dos dados históricos de produção fornecidos pela empresa. Conclui-se que, utilizando as soluções obtidas com o modelo desenvolvido, a quantidade de sucata gerada durante o processo de produção _e minimizada, uma vez que, o modelo garante a minimização da soma dos tempos de preparação e minimiza o número de vezes que ocorrem trocas de matriz.In the current business world, the increasing competitiveness forces companies to adopt optimization strategies to ensure or improve their market position. It is crucial to take the best decisions from the production planning point of view. The production of aluminium pro les poses several challenges to the production manager. This work addresses a real case of a company that operates in the aluminium market, whose core business is the development and production of aluminium pro les for application in several areas, such as, engineering, architecture and industry works in general. The aim is to minimize production waste, commonly known as scrap, through minimization of setup times, that occur when the die is changed, while respecting product delivery times and maintaining quality. This case study focuses on a scheduling ow shop problem involving sequence-dependent setup times arising from the need to change the tools used in the process of aluminium extrusion. A mixed integer programming model is developed and implemented for answering the company's challenge. The problem is formulated the AMPL modeling language and the Gurobi solver is used to solve real instances extracted from data provided by the company. The results obtained with the developed model are compared to the dispatching rule FIFO, in terms the sum of the setup times (and consequently the number of exchanges of dies), as well as the ful llment of the deadline. Furthermore, although the company's current procedure is not known, the results obtained are compared with the average of die changes obtained from the historical production data provided by the company. It is observed that by using the solutions obtained with the developed model, the quantity of scrap that is generated during the production process is minimized, since the model guarantees the minimization of the sum of the setup times, therefore minimizes the number of times there are die changes.N/

Active thermography for the investigation of corrosion in steel surfaces

The present work aims at developing an experimental methodology for the analysis of corrosion phenomena of steel surfaces by means of Active Thermography (AT), in reflexion configuration (RC). The peculiarity of this AT approach consists in exciting by means of a laser source the sound surface of the specimens and acquiring the thermal signal on the same surface, instead of the corroded one: the thermal signal is then composed by the reflection of the thermal wave reflected by the corroded surface. This procedure aims at investigating internal corroded surfaces like in vessels, piping, carters etc. Thermal tests were performed in Step Heating and Lock-In conditions, by varying excitation parameters (power, time, number of pulse, ….) to improve the experimental set up. Surface thermal profiles were acquired by an IR thermocamera and means of salt spray testing; at set time intervals the specimens were investigated by means of AT. Each duration corresponded to a surface damage entity and to a variation in the thermal response. Thermal responses of corroded specimens were related to the corresponding corrosion level, referring to a reference specimen without corrosion. The entity of corrosion was also verified by a metallographic optical microscope to measure the thickness variation of the specimens

Meta-parametric design: Developing a computational approach for early stage collaborative practice

Computational design is the study of how programmable computers can be integrated into the process of design. It is not simply the use of pre-compiled computer aided design software that aims to replicate the drawing board, but rather the development of computer algorithms as an integral part of the design process. Programmable machines have begun to challenge traditional modes of thinking in architecture and engineering, placing further emphasis on process ahead of the final result. Just as Darwin and Wallace had to think beyond form and inquire into the development of biological organisms to understand evolution, so computational methods enable us to rethink how we approach the design process itself. The subject is broad and multidisciplinary, with influences from design, computer science, mathematics, biology and engineering. This thesis begins similarly wide in its scope, addressing both the technological aspects of computational design and its application on several case study projects in professional practice. By learning through participant observation in combination with secondary research, it is found that design teams can be most effective at the early stage of projects by engaging with the additional complexity this entails. At this concept stage, computational tools such as parametric models are found to have insufficient flexibility for wide design exploration. In response, an approach called Meta-Parametric Design is proposed, inspired by developments in genetic programming (GP). By moving to a higher level of abstraction as computational designers, a Meta-Parametric approach is able to adapt to changing constraints and requirements whilst maintaining an explicit record of process for collaborative working

Reinforcement Learning Approach for Autonomous UAV Navigation in 3D Space

In the last two decades, the rapid development of unmanned aerial vehicles (UAVs) resulted in their usage for a wide range of applications. Miniaturization and cost reduction of electrical components have led to their commercialization, and today they can be utilized for various tasks in an unknown environment. Finding the optimal path based on the start and target pose information is one of the most complex demands for any intelligent UAV system. As this problem requires a high level of adaptability and learning capability of the UAV, the framework based on reinforcement learning is proposed for the localization and navigation tasks. In this paper, Q-learning algorithm for the autonomous navigation of the UAV in 3D space is implemented. To test the proposed methodology for UAV intelligent control, the simulation is conducted in ROS-Gazebo environment. The obtained simulation results have shown that the UAV can reach the target pose autonomously in an efficient way

Reinforcement Learning Approach for Autonomous UAV Navigation in 3D Space

In the last two decades, the rapid development of unmanned aerial vehicles (UAVs) resulted in their usage for a wide range of applications. Miniaturization and cost reduction of electrical components have led to their commercialization, and today they can be utilized for various tasks in an unknown environment. Finding the optimal path based on the start and target pose information is one of the most complex demands for any intelligent UAV system. As this problem requires a high level of adaptability and learning capability of the UAV, the framework based on reinforcement learning is proposed for the localization and navigation tasks. In this paper, Q-learning algorithm for the autonomous navigation of the UAV in 3D space is implemented. To test the proposed methodology for UAV intelligent control, the simulation is conducted in ROS-Gazebo environment. The obtained simulation results have shown that the UAV can reach the target pose autonomously in an efficient way

EG-ICE 2021 Workshop on Intelligent Computing in Engineering

The 28th EG-ICE International Workshop 2021 brings together international experts working at the interface between advanced computing and modern engineering challenges. Many engineering tasks require open-world resolutions to support multi-actor collaboration, coping with approximate models, providing effective engineer-computer interaction, search in multi-dimensional solution spaces, accommodating uncertainty, including specialist domain knowledge, performing sensor-data interpretation and dealing with incomplete knowledge. While results from computer science provide much initial support for resolution, adaptation is unavoidable and most importantly, feedback from addressing engineering challenges drives fundamental computer-science research. Competence and knowledge transfer goes both ways