This work investigates the fluid flow in a cylindrical millilitre vial stirred by a magnetic stirred bar using Computational Fluid Dynamic (CFD). Stirred millilitre vials are used to study nucleation phenomena and crystallization as an outline of literature study of nucleation and crystallization phenomena and the role of stirring in this process. The baffle free vial was meshed with around 500,000 cells. To simulate the stirring a rotary frame and moving walls were used. Stirring speeds were between 100 and 1000 rpm where considered, correspondently to a stirrer Reynolds number between 260 and 2600. For stirring speeds bellow 500 rpm, simulations by both the both laminar flow model and the k-ε model where run, while above 500 rpm only k-ε was used. Results of the two models were very similar indicative the adequacy of k-ε to simulate the flow even at low Reynolds. The flow shows expected circulation pattern with upwards pumping close to side walls and downwards pumping in the centre of cylindrical vial. At 1000 rpm circulation patterns expands up to the top of the vial while at 300 rpm and lower the upper half of the vial is poorly mixed. The average turbulent energy of the flow is very low comparing with the squared stirrer tip speed and the power number decrees with Reynolds number, indicating that the flow is not fully turbulent.

In order to enhance accessibility to microgravity research, the design process for experiments on the ISS must be streamlined and accessible to all scientific disciplines, not just aerospace engineers. Thus, a general design and analysis toolbox with accompanying best practices manual for microgravity liquid containment is proposed. The work presented in this thesis improves the design process by introducing a modular liquid tank design which can be filled, drained, or act as a passive liquid-gas separation device. It can also be pressurized, and used for aerosol spray. This tank can be modified to meet the design requirements of various experimental setups and liquids. Furthermore, rough simulations of this tank are presented and available to the user for modification. The simulation and design methodology for other general cases is discussed as well. After reading this thesis, the user should have a basic understanding of how liquids behave in microgravity. She will be able to run simple simulations, design, build, test, and fly a liquid management device which has been modified to suit the requirements of her specific experiment. The general tank design can be manufactured using 3-D printing, traditional CNC milling, or a combination thereof. The design methodology and best practices presented here have been used to design tanks used in experiments on the International Space Station for Budweiser and Lambda Vision. Both tanks functioned nominally on orbit. While the specific data from these experiments cannot be presented due to proprietary restrictions, using this thesis as a design guide for new experiments should yield favorable results when applied to new tank designs. If the reader has any questions or would like an updated design process, the author’s preferred contact information can be found using the Orcid iD: 0000-0002-2617-2957 .

The subject of this final thesis is to process selected parts of the construction technological project for the apartment house Eden in Poprad. The thesis deals with the implementation of the rough construction of the building. The content of this thesis is a engineering report, site plan with estate road layout, time schedule and financial plan for the whole object, feasibility study of the main technological stages of the building, construction site equipment project with drawings of three main technological stages, design of major construction machinery and mechanisms, time schedule of the rough construction of the main building, balance of workers and main machines, item budget, technological regulation for the realization of monolithic floor slab, control and test plan for the realization of monolithic reinforced concrete structures. As another assignment, I process selected points of LEED certification, noise study and health and safety plan.

Wärmespeicher tragen bei optimierter Integration in Wärme- und Kälteversorgungsanlagen zur Einsparung von installierter Erzeugerleistung, Brennstoffeinsatz und Betriebskosten bei. Leider treten in Wärmespeichern oft noch beachtliche Verluste auf und das Potenzial zur Kosten- und Energieeinsparung wird nicht vollständig ausgeschöpft. Dabei spielen nicht nur Wärmeverluste an die Umgebung, sondern vor allem auch innere Verluste im Speicher eine Rolle. Schwerpunkte der vorliegenden Arbeit sind die Beschreibung der einzelnen Verluste an Wasserwärmespeichern, die Ermittlung ihrer Ausmaße abhängig von der konstruktiven Gestaltung und der Betriebsweise des Speichers sowie die Auswirkungen der Verluste auf einen vorgelagerten Wärmeerzeuger und den Einsatz von Primärenergie. Die Ergebnisse basieren auf umfangreichen Speichermodellierungen mit dem CFD-Code Fluent sowie experimentellen Untersuchungen an drei Testspeichern. Der quantitative Vergleich der Verluste für ausgewählte Beispiele zeigt bestehende Defizite sowie die Potenziale für die Verbesserung der Konstruktion neuer Wasserwärmespeicher auf. / If hot water storage tanks are optimally integrated in heat or cold supply systems, they contribute to a reduction of required capacity, fuel and operation costs. Unfortunately, even today remarkable heat losses and internal losses occur in hot water storage tanks. The potential for cost and energy reductions is not completely utilized yet. Here, not only heat losses to the ambience, but also internal losses play a decisive role. Main focus of the presented work is the description of the single losses at hot water storage tanks and the determination of the correlation between the losses, the tank design and the mode of operation. Furthermore the effects of the losses in the tank on the efficiency of different types of heat generators and the input of primary energy into the system have been examined. The results are based on extended numerical modeling with the CFD-code Fluent as well as experimental test with three storage tanks. The quantitative comparison of the losses for selected examples shows the current shortcomings but even the potential for an optimized hot water storage tank design.

The overall performance of a hydrogen storage system can be affected by various parameters, such as operation and design parameters, but also by the state of the hydrogen contained inside the storage tanks. In this work, a methodology is developed to evaluate the state of the hydrogen during the filling process and its impact on the overall system performance under variable operation conditions and design parameters. To approach as close as possible hydrogen as real gas, the thermodynamic properties of it are obtained from experimental thermodynamic tables. Based on those thermodynamic tables, a discrete database for each thermodynamic property is constructed. To minimize the error and achieve acceptable execution time, a searching method based on curve fitting techniques is developed to derive the thermodynamic properties from the discretized data. The evaluation of the hydrogen state is done based on a developed method that derives the pressure and temperature based on calculated thermodynamic properties during the filling process. The interaction between the contained hydrogen and tank during the filling process is taken into account during the methodology development. Furthermore, energy requirements for the compression system of the hydrogen storage system, including the cooling demand, are also included in the methodology. Based on the developed methodology, a transient model that can evaluate the hydrogen state condition, storage tank wall temperature condition, and energy requirement of the storage system is developed. Validation against experimental and simulation results for an actual filling event of a hydrogen storage tank is done, showing good agreement in the results. The model was used to simulate the performance of a hydrogen storage system, inspired in terms of layout by a real-world HRS storage system. The results showed that the total amount of filled hydrogen and the filling duration of the charging process are greatly affected by the compression and heat transfer phenomena occurring inside the tank. The storage tanks with lower volumes and higher operation pressure tend to be more affected by compression and heat transfer phenomena. Operation parameters such as inlet mass flow and inlet temperature, can have an impact on the system, both in terms of energy consumption and filling performance. Furthermore, based on the investigation of compression stages, the results showed that the number of stages can affect the compression ratio of each stage, resulting in lower or higher efficiency, which directly affects the energy consumption of the compression system. A parametric investigation of the upper operation pressures of the hydrogen tanks showed that the total amount of stored hydrogen is affected when the respective upper pressures vary. Last, it was shown that there is an optimal upper pressure level for each bank that can result in lower specific compression energy, indicating that the model could be used for optimization purposes.

No description available.

In recent years the steelmaking industry has been subjected to continuous attempts to improve its production route. The main goals has been to increase the competitiveness and to reduce the environmental impact. The development of predictive models has therefore been of crucial importance in order to achieve such optimization. Models are representations or idealizations of reality which can be used to investigate new process strategies without the need of intervention in the process itself. Together with the development of Industry 4.0, Machine Learning (ML) has turned out as a promising modeling approach for the steel industry. However, ML models are generally difficult to interpret, which makes it complicated to investigate if the model accurately represents reality. The present work explores the practical usefulness of applied ML models in the context of the secondary metallurgy processes in steelmaking. In particular, the application of interest is the prediction of the liquid steel temperature after the vacuum treatment step in the Vacuum Tank Degasser (VTD). The choice of the VTD process step is related to its emerging importance in the SSAB Oxelösund steel plant due to the planned future investment in an Electric Arc Furnace (EAF) based production line. The temperature is an important parameter of process control after the vacuum treatment since it directly influences the castability of the steel. Furthermore, there are not many available models which predict the temperature after the vacuum treatment step. The present thesis focuses first on giving a literature background of the statistical modeling approach, mainly addressing the ML approach, and the VTD process. Furthermore, it is reported the methodology behind the construction of the ML model for the application of interest and the results of the numerical experiments. All the statistical concepts used are explained in the literature section. By using the described methodologies, several findings originated from the resulting ML models predicting the temperature of the liquid steel after the vacuum treatment in the VTD.A high complexity of the model is not necessary in order to achieve a high predictive performance on the test data. On the other hand, the data quality is the most important factor to take into account when improving the predictive performance. Itis fundamental having an expertise in both metallurgy and machine learning in order to create a machine learning model that is both relevant and interpretable to domain experts. This knowledge is indeed fundamental for the selection of the input data and the machine learning model framework. Crucial information for the predictions result to be the heat status of the ladle as well as the stirring process time and the temperature benchmarks before and after the vacuum steps. However, to draw specific conclusions, a higher model predictive performance is needed. This can only be obtained upon a significant data quality improvement. / Stålindustrin har under de senaste åren ständigt förbättrat sin produktionsförmåga som i huvudsak har bidragit till ökad konkurrenskraft och minskad miljöpåverkan. Utvecklingen  av  prediktiva  modeller  har  under  denna  process  varit  av  avgörande betydelse för att uppnå dessa bedrifter. Modeller är representationer eller idealiseringar av verkligheten som kan användas för att utvärdera nya processtrategier utan att åberopa  ingrepp  i  själva  processen.    Detta  sparar  industrin  både  tid och pengar.   I takt  med  Industri  4.0  har  maskininlärning  blivit  uppmärksammad  som ett ytterligare modelleringsförfarande inom stålindustrin. Maskininlärningsmodeller är dock generellt svårtolkade, vilket gör det utmanande att undersöka om modellen representerar verkligheten. Detta arbete undersöker den praktiska användningen av maskininlärningsmodeller inom sekundärmetallurgin på  ett  svenskt  stålverk.    Tillämpningen  är  i  synnerhet av   intresse   för   att   kunna   förutspå   temperaturen   hos   det   flytande   stålet   efter vakuumbehandlingssteget  i  VTD-processen. Denna  process  valdes  eftersom den är av  stor  betydelse  för  framtida  ståltillverkning  hos  SSAB  i  Oxelösund. Detta är primärt  på  grund  utav  att  SSAB  kommer  att  investera  i  en ljusbågsugnsbaserad produktionslinje.   Temperaturen är en viktig processparameter eftersom den direkt påverkar   stålets   gjutbarhet. Utöver   detta   har   inga   omfattande   arbeten   gjorts gällande  att  förutspå  temperaturen  efter vakuumbehandlingssteget  med  hjälp av maskininlärningsmodeller. Arbetet presenterar först en litteraturbakgrund inom statistisk modellering med fokus på maskininlärning och VTD-processen.  Därefter redovisas metodiken som använts för att skapa  maskininlärningsmodellerna  som  ligger  till  grund  för  de  numeriska experimenten samt resultaten. Genom att använda de beskrivna metoderna härrörde flera fynd från de skapande maskininlärningsmodellerna. En hög grad av komplexitet är inte   nödvändig   för   att   uppnå   en   hög   prediktiv   förmåga   på   data   som   inte använts  för  att  anpassa  modellens  parametrar.   Å  andra  sidan  är  datakvalitén den viktigaste faktorn om man ämnar att förbättra den prediktiva förmågan hos modellen. Utöver  detta  är  det  av  yttersta  vikt  att  ha  kompetens  inom  både  metallurgi  och maskininlärning för att skapa en modell som är både relevant och tolkbar för experter inom  området  processmetallurgi. Ideligen  är  kunskap  inom  processmetallurgi grundläggande för val av indata och val av maskininlärningsalgoritm. Under analysen av maskininlärningsmodellerna upptäcktes det att skänkens värmestatus, omrörningstiden i processen, samt temperaturriktmärkena före och efter vakuumstegen var de mest avgörande variablerna för modellens prediktiva förmåga. För att kunna dra specifika slutsatser behöver modellen ha en högre prediktiv förmåga. Detta kan endast erhållas efter en betydande förbättring av datakvalitén.

This report details the work which has been done to redesign an older process control lab setup, in order for it to become fully modular and wirelessly controllable.The process control lab setup of interest was the quadruple water tank process. Asa proof of concept, a single prototype tank module of the quadruple tank setup wasto be redesigned, where this new design would use entirely modular and wirelesslycontrollable sensors and actuators. The design of these wireless devices was donefrom scratch, the end result was that a set of micro-controller based devices whichcommunicate over Xbee radios were manufactured. Control of this wireless tanksystem was achieved through a custom Simulink interface, said interface was alsocreated during this project. The finalized tank prototype system worked as intendedand it fulfilled all of the relevant system requirements regarding the sensor and actuator network design. There was originally a mechanical design component in thisproject which had to be left after the initial research stages due to time constraints,which concerned the construction of a new tank system. This prototype system wasa proof of concept, which proved the feasibility of building larger scale wirelesslycontrollable process control systems, such as the quadruple water tank process.

No description available.

No description available.