Valusenkan liukusulkimen säätöpiirin optimaalinen viritys

Tiivistelmä. Työn tavoitteena oli tutkia Outokummun Tornion tehtaan sulaton 2-linjan liukusulkimen säädön kehityspotentiaalia välialtaan painovaihtelujen minimoimiseksi. Välialtaan pienemmällä painohajonnalla haluttiin tehostaa kuonasulkeumien poistoa välialtaassa. Liukusulkimen säädön kehityksen yhteydessä tutkittiin myös mahdollisuutta vähentää liukusulkimen liikekertoja kulumisen vähentämiseksi. Tämän lisäksi tarkasteltiin muita mahdollisia välialtaan painovaihteluihin vaikuttavia tekijöitä. Työn alussa käytiin läpi terässulaton 2 linjan toimintaa ja tarkempaan tarkasteluun otettiin senkka-aseman, välialtaan ja liukusulkimen toiminta. Työssä tarkasteltiin aiempia samaan aihepiiriin liittyviä tutkimuksia ja niissä tehtyjä havaintoja, joista saatiin apua tässä työssä esiteltyihin parannusehdotuksiin. Työn teoriaosuudessa käytiin läpi mallinnusta, yleistä säätöpiireihin liittyvää teoriaa ja tässä työssä käytetyn Smith-prediktorin toimintaa. Kokeellisessa osuudessa tehtaalta saatua prosessidataa analysoitiin, minkä avulla luotiin kuva olemassa olevan prosessin käyttäytymisestä ja siihen liittyvän automaatiojärjestelmän toiminnasta. Tämän pohjalta kehitettiin useampi simulointimalli ja vaihtoehtoinen säätöratkaisu käyttäen Smith-prediktoria välialtaan painon ohjauksessa. Luoduilla simulointimalleilla simuloitiin ensisijaisesti välialtaan painoa, mutta myös liukusulkimen liikkeitä. Simulointien perusteella vaihtoehtoisella säädinratkaisulla saataisiin vähennettyä välialtaan painovaihteluja. Liukusulkimen liikekertoja saatiin simuloinneissa vähennettyä kasvattamalla sen minimiliikettä ilman, että välialtaan painovaihtelu olisi kasvanut. Liukusulkimen toiminnasta kuitenkin havaittiin, että sen nykyinen liike ei vastannut säätimen asettamia asetusarvoja halutulla tavalla, joten sen mekaaninen toimivuus on syytä varmistaa ennen mahdollisia muutoksia automaatiojärjestelmään. Simulointien osalta tulokset ovat suuntaa antavia ja prosessikokeisiin ei työssä ollut mahdollisuutta tulosten todentamiseksi.Optimal tuning of the ladle slide gate control system. Abstract. In this thesis, the aim was to study development potential of the slide gate control in order to minimize tundish weight variations at Outokumpu steel factory in Tornio. With smaller tundish weight variation,the desire was to improve removal of slag occlusions in the tundish. Possibility to reduce slide gate movements was also studied to reduce slide gate wear. In addition, other possible factors affecting tundish weight variations were studied. First the smelter production line 2 manufacturing process was introduced and then ladle station, tundish and slide gate operations were more closely looked at. Previous studies and their findings about the subject were examined which helped in this thesis when making suggestions for the improvements. Theory about modelling and control systems and how they link to this study were presented on the theory part of this thesis as well as the working principle of Smith predictor was explained. Process data was acquired from the factory for analysis which helped studying the behavior and the automation system of the process. This served as a basis for creating multiple simulation models and an alternative control system using Smith predictor to control tundish weight. Simulation models were used primarily to simulate tundish weight,but they were also used to simulate movement of the slide gate. Based on simulation results,the alternative control system provided decrease in tundish weight variation. Reduction of slide gate movements was achieved by increasing minimum movement of the slide gate without increasing tundish weight variation. It was also noticed that slide gate movement was not corresponding to the values set by the controller in the current system, which would require attention before any other implementations to the automation system. The results concerning simulations in this thesis are only indicative and there was no opportunity for process experiments to confirm these results

Robust Adaptive Control of the Mold Level in the Continuous Casting Process Using Multiple Models

Abstract-In the continuous casting of steel, mold level control is fundamental for obtaining high productivity and high quality. Using conventional methods, it is difficult to achieve both stability and performance robustness because of different classes of disturbances and parameters uncertainties in the process. This paper presents a multi-model adaptive control architecture based on the so-called RMMAC methodology. With the help of precise definition of robust performance requirements, the number of models, estimators and controllers are merely derived. More importantly, the combination of robust non-adaptive mixed-µ synthesis and stochastic hypothesis testing concepts enables controller performances prediction as well as online monitoring process parameters which could be used by operators to take corrective actions. The generated signals are likewise useful for understanding the physical phenomena in the process

[Research activities in applied mathematics, fluid mechanics, and computer science]

This report summarizes research conducted at the Institute for Computer Applications in Science and Engineering in applied mathematics, fluid mechanics, and computer science during the period April 1, 1995 through September 30, 1995

Numerical simulation of bubbles and drops in complex geometries by using dynamic meshes

CFD techniques are important tools for the study of multiphase flows, because most of the physical phenomena of these flows often happen on space and time scales where experimental methodologies are impossible in practice. Notwithstanding, numerical approaches are limited by the computational power of the present computers. In this sense, small improvements in the efficiency of the simulations can make the difference between an approachable problem and an unapproachable one. The proposal of this doctoral thesis is focused on developing numerical algorithms to optimize the simulations of multiphase solvers based on single fluids formulations, applied on three-dimensional unstructured meshes, in the context of a finite-volume discretization. In particular, the methods developed in the context of this PhD thesis use a conservative level set technique to deal with the multiphase domain. The work has been organized in five chapters and four appendices. The first chapter constitutes an introduction to the multiphase flows and the different approaches used to study them. The core work of the of this PhD thesis is explained throughout chapters two, three, and four. In those chapters, the improvements performed on the multiphase DNS techniques are addressed in detail, providing results comparisons and discussions on the obtained outcomes. After developing the main ideas of the thesis, a final concluding chapter is presented, summarizing the main findings of this research, and pointing out some future work. Finally, the appendices includes some material that can be useful to understand in depth some specific parts of the thesis but, conversely, they are not essential to follow the main thread. As said before, the core work of this thesis is presented throughout chapters two, three and four. In chapter two, four domain optimization methods are formulated and tested. By using these techniques, small domains can be used in rising bubble simulations, thus saving computational resources. These methods have been implemented in a conservative level set framework. Some of these methods require the use of open boundaries. Therefore, a careful treatment of both inflow and outflow boundaries has been carried out. This includes the development of a new outflow boundary condition as a variation of the classical convective outflow. At this point, a study about the sizing of the computational domain has been conducted, paying special attention to the placement of the inflow and outflow boundaries. Additionally, once the methods are formulated, several validation cases are run to discuss the applicability and robustness of each method. The third chapter present a physical study of a challenging problem: the Taylor bubble. By using the most promising technique from those presented in the previous chapter (i.e. the moving mesh method), the problem of an elongated bubble rising in stagnant liquid is addressed here. A transient study on the velocity field of the problem is provided. Moreover, the study also includes sensitivity analyses with respect to the initial shape of the bubble, the initial volume of the bubble, the flow regime and the inclination of the channel. Chapter number four presents an extension of the developed method to simulate bubbles and drops evolving in complex geometries. The use of an immersed boundary method allows to deal with intricate geometries and to reproduce internal boundaries within an ALE framework. The resulting method is capable of dealing with full unstructured meshes. Different problems are studied here to assert the proposed formulation, both involving constricting and non-constricting geometries. In particular, the following problems are addressed: a 2D gravity-driven bubble interacting with a highly-inclined plane, a 2D gravity-driven Taylor bubble turning into a curved channel, the 3D passage of a drop through a periodically constricted channel, and the impingement of a 3D drop on a flat plate.La Mecánica de Fluidos Computacional (CFD) es una importante disciplina para el estudio de flujos multifase. Esto se debe a que, en este tipo de flujos, la mayor parte de los fenómenos físicos ocurren en escalas de tiempo y espacio imposibles de detectar mediante una metodología experimental. Sin embargo, los enfoques numéricos están limitados por la potencia de cálculo de los ordenadores actuales. En este sentido, pequeñas mejoras en la eficiencia de las simulaciones pueden marcar la diferencia entre un problema que puede resolverse mediante CFD o uno que no. En la presente tesis doctoral se propone el desarrollo de varios algoritmos numéricos para optimizar simulaciones de flujos multifase basadas en formulaciones "single fluids", aplicadas en mallas no estructuradas y tridimensionales, en el contexto de discretizaciones "finite-volume". El trabajo se ha organizado en cinco capítulos y cuatro apéndices. El primer capítulo constituye una introducción a los flujos multifase y a los distintos enfoques usados para estudiarlos. El trabajo nuclear de la presente tesis reside en los capítulos tres, cuatro y cinco. En dichos capítulos se presentan las mejoras realizadas en las técnicas de resolución de flujos multifase mediante una metodología "DNS", aportando comparaciones de resultados y discusiones críticas de los resultados obtenidos. Después de desarrollar las ideas centrales de la tesis, se presenta un capítulo final con las conclusiones destacadas de este trabajo, señalando posibles líneas de trabajo futuro. Finalmente, se incluyen varios apéndices con material complementario que puede ser útil para profundizar en algún aspecto concreto del desarrollo, pero que a su vez no es esencial para entender las ideas principales del texto. Como se explica anteriormente, el trabajo central de la tesis se ha desarrollado a lo largo de los capítulos dos, tres y cuatro. En el segundo capítulo se formulan y prueban cuatro métodos de optimización de dominios de cálculo. Mediante la utilización de estos métodos se hace posible usar dominios de cálculo pequeños en problemas de burbujas ascendentes, ahorrando así recursos computacionales. Algunos de estos métodos requieren el uso de fronteras abiertas, por lo que se propone un estudio detallado de las condiciones de contorno de entrada y salida. Esto incluye el desarrollo de una nueva condición tipo "outflow". A continuación se estudia en profundidad el dimensionamiento del dominio de cálculo, prestando una atención especial a la posición de las fronteras de entrada y de salida. Con todo esto, el capítulo se cierra con una comparativa del rendimiento de los distintos métodos propuestos en varios problemas de burbujas ascendentes. El tercer capítulo presenta un estudio físico de un problema clave: la burbuja de Taylor. Usando la técnica con mejor rendimiento del capítulo anterior (es decir, la técnica de malla móvil), se aborda el problema de una burbuja alargada moviéndose en un fluido en reposo. Se lleva a cabo un estudio transitorio de la velocidad del campo fluido. Además, se realizan varios estudios de sensibilidad con respecto a la forma inicial de la burbuja, su volumen inicial, el régimen de flujo y la inclinación del canal. Por último, en el cuarto capítulo se presenta una extensión del método desarrollado para simular gotas y burbujas evolucionando en geometrías complejas. El uso de un método "Immersed Boundary" permite tratar geometrías complejas y reproducir fronteras internas en métodos que utilicen mallas móviles. En este punto, se estudian diversos problemas para validar la formulación propuesta, tanto en geometrías constrictivas como en no constrictivas. En particular, se han resuelto los siguientes problemas: una burbuja 2D interaccionando con un plano inclinado, una burbuja de Taylor 2D girando en un tubo curvo, el ascenso de una gota 3D dentro de un canal corrugado, y el impacto de una gota 3D contra una plaformaPostprint (published version

Aerospace Medicine and Biology: A continuing bibliography with indexes, supplement 237

A bibliography is given on the biological, physiological, psychological, and environmental effects to which man is subjected during and following simulated or actual flight in the Earth's atmosphere or in interplanetary space. References describing similar effects of biological organisms of lower order are also included. Such related topics as sanitary problems, pharmacology, toxicology, safety and survival, life support systems, exobiology, and personnel factors receive appropriate attention. In general, emphasis is placed on applied research, but references to fundamental studies and theoretical principles related to experimental development also qualify for inclusion

An immersed boundary method for particles and bubbles in magnetohydrodynamic flows

This thesis presents a numerical method for the phase-resolving simulation of rigid particles and deformable bubbles in viscous, magnetohydrodynamic flows. The presented approach features solid robustness and high numerical efficiency. The implementation is three-dimensional and fully parallel suiting the needs of modern high-performance computing. In addition to the steps towards magnetohydrodynamics, the thesis covers method development with respect to the immersed boundary method which can be summarized in simple words by From rigid spherical particles to deformable bubbles. The development comprises the extension of an existing immersed boundary method to non-spherical particles and very low particle-to-fluid density ratios. A detailed study is dedicated to the complex interaction of particle shape, wake and particle dynamics. Furthermore, the representation of deformable bubble shapes, i.e. the coupling of the bubble shape to the fluid loads, is accounted for. The topic of bubble interaction is surveyed including bubble collision and coalescence and a new coalescence model is introduced. The thesis contains applications of the method to simulations of the rise of a single bubble and a bubble chain in liquid metal with and without magnetic field highlighting the major effects of the field on the bubble dynamics and the flow field. The effect of bubble coalescence is quantified for two closely adjacent bubble chains. A framework for large-scale simulations with many bubbles is provided to study complex multiphase phenomena like bubble-turbulence interaction in an efficient manner

Control of Continuous Casting Process Based on Two-Dimensional Flow Field Measurements

Two-dimensional flow field measurement allows us to obtain detailed information about the processes inside the continuous casting mould. This is very important because the flow phenomena in the mould are complex, and they significantly affect the steel quality. For this reason, control based on two-dimensional flow monitoring has a great potential to achieve substantial improvement over the conventional continuous casting control. Two-dimensional flow field measurement provides large amounts of measurement data distributed within the whole cross-section of the mould. An experimental setup of the continuous casting process called Mini-LIMMCAST located in Helmholtz-Zentrum Dresden-Rossendorf (HZDR), Dresden, Germany, is used for this thesis. This thesis examines two alternatives of flow measurement sensors: Ultrasound Doppler Velocimetry (UDV) and Contactless Inductive Flow Tomography (CIFT). Both sensor variants can obtain information on the velocity profile in the mould. Two approaches were considered to create the process model needed for model-based control: a spatially discretized version of a model based on partial differential equations and computational fluid dynamics and a model obtained using system identification methods. In the end, system identification proved to be more fruitful for the aim of creating the model-based controller. Specific features of the flow were parametrized to obtain the needed controlled variables and outputs of identified models. These features are mainly related to the exiting jet angle and the meniscus velocity. The manipulated variables considered are electromagnetic brake current and stopper rod position. Model predictive control in several versions was used as the main control approach, and the results of simulation experiments demonstrate that the model predictive controller can control the flow and achieve the optimum flow structures in the mould using UDV. CIFT measurements can provide similar velocity profiles. However, further technical developments in the CIFT sensor signal processing, such as compensating for the effects of the strong and time-varying magnetic field of the electromagnetic brake on CIFT measurements, are necessary if this sensor is to be used for closed-loop control.Two-dimensional flow field measurement allows us to obtain detailed information about the processes inside the continuous casting mould. This is very important because the flow phenomena in the mould are complex, and they significantly affect the steel quality. For this reason, control based on two-dimensional flow monitoring has a great potential to achieve substantial improvement over the conventional continuous casting control. Two-dimensional flow field measurement provides large amounts of measurement data distributed within the whole cross-section of the mould. An experimental setup of the continuous casting process called Mini-LIMMCAST located in Helmholtz-Zentrum Dresden-Rossendorf (HZDR), Dresden, Germany, is used for this thesis. This thesis examines two alternatives of flow measurement sensors: Ultrasound Doppler Velocimetry (UDV) and Contactless Inductive Flow Tomography (CIFT). Both sensor variants can obtain information on the velocity profile in the mould. Two approaches were considered to create the process model needed for model-based control: a spatially discretized version of a model based on partial differential equations and computational fluid dynamics and a model obtained using system identification methods. In the end, system identification proved to be more fruitful for the aim of creating the model-based controller. Specific features of the flow were parametrized to obtain the needed controlled variables and outputs of identified models. These features are mainly related to the exiting jet angle and the meniscus velocity. The manipulated variables considered are electromagnetic brake current and stopper rod position. Model predictive control in several versions was used as the main control approach, and the results of simulation experiments demonstrate that the model predictive controller can control the flow and achieve the optimum flow structures in the mould using UDV. CIFT measurements can provide similar velocity profiles. However, further technical developments in the CIFT sensor signal processing, such as compensating for the effects of the strong and time-varying magnetic field of the electromagnetic brake on CIFT measurements, are necessary if this sensor is to be used for closed-loop control.

Resource-Aware Predictive Models in Cyber-Physical Systems

Cyber-Physical Systems (CPS) are composed of computing devices interacting with physical systems. Model-based design is a powerful methodology in CPS design in the implementation of control systems. For instance, Model Predictive Control (MPC) is typically implemented in CPS applications, e.g., in path tracking of autonomous vehicles. MPC deploys a model to estimate the behavior of the physical system at future time instants for a specific time horizon. Ordinary Differential Equations (ODE) are the most commonly used models to emulate the behavior of continuous-time (non-)linear dynamical systems. A complex physical model may comprise thousands of ODEs that pose scalability, performance and power consumption challenges. One approach to address these model complexity challenges are frameworks that automate the development of model-to-model transformation. In this dissertation, a state-based model with tunable parameters is proposed to operate as a reconfigurable predictive model of the physical system. Moreover, we propose a run-time switching algorithm that selects the best model using machine learning. We employed a metric that formulates the trade-off between the error and computational savings due to model reduction. Building statistical models are constrained to having expert knowledge and an actual understanding of the modeled phenomenon or process. Also, statistical models may not produce solutions that are as robust in a real-world context as factors outside the model, like disruptions would not be taken into account. Machine learning models have emerged as a solution to account for the dynamic behavior of the environment and automate intelligence acquisition and refinement. Neural networks are machine learning models, well-known to have the ability to learn linear and nonlinear relations between input and output variables without prior knowledge. However, the ability to efficiently exploit resource-hungry neural networks in embedded resource-bound settings is a major challenge.Here, we proposed Priority Neuron Network (PNN), a resource-aware neural networks model that can be reconfigured into smaller sub-networks at runtime. This approach enables a trade-off between the model's computation time and accuracy based on available resources. The PNN model is memory efficient since it stores only one set of parameters to account for various sub-network sizes. We propose a training algorithm that applies regularization techniques to constrain the activation value of neurons and assigns a priority to each one. We consider the neuron's ordinal number as our priority criteria in that the priority of the neuron is inversely proportional to its ordinal number in the layer. This imposes a relatively sorted order on the activation values. We conduct experiments to employ our PNN as the predictive model in a CPS application. We can see that not only our technique will resolve the memory overhead of DNN architectures but it also reduces the computation overhead for the training process substantially. The training time is a critical matter especially in embedded systems where many NN models are trained on the fly