Directional control valves are widely used in hydraulic systems to control the flow direction and the flow rate. In order to design an actuator for such a valve a preliminary analysis of forces acting on the spool is necessary. The dominant axial force is the so called steady flow force, which is analysed within this study. For this purpose a 2/2-way spool valve with a sharp control edge was manufactured and investigated. CFD simulations were carried out to visualize the fluid flow inside the valve. The measured and simulated axial forces and pressure drops across the test valve are compared and show good qualitative correlation. However, the simulated values of axial forces are in average by 32 % lower compared with the measured ones. Therefore, the components of the axial force were scrutinized revealing a dominancy of the pressure force acting on ring areas in the spool chamber. Although CFD simulations are preferably used to save resources, the results of this study emphasise the importance of the experiments.

Darbe analizuojami laivo pasipriešinimo nustatymo būdai, metodai. Aprašomas praktiškai atliktas karinio laivo 5415 pasipriešinimo modelinis bandymas, bei pateikiami bandymo rezultatai. Naudojantis FLOW 3D simuliacine programa modeliuojamas virtualus laivo 5414 pasipriešinimo bandymas, bei pateikiami virtualaus bandymo rezultatai. Taikant daţnai naudojamus praktikoje apytikrius vandens pasipriešinimo skaičiavimo metodus vertinamas vandens pasipriešinimas laivo 5415 judėjimui. Palyginami apytikrių skaičiavimo metodų, bei realaus ir virtualaus pasipriešinimo eksperimentų rezultatai. Padaromos išvados, kaip tikslingai parinkti optimalų laivo eigumo preliminaraus vertinimo metodą laivo projektavimo metu. / The most used ship's resistance research techniques and methods were analyzed in current work. Were described war ship 5415 practical resistance modeling test and submitted test calculations. Using automation simulation program FLOW 3D were created a virtual ship resistance test and also submitted test calculations. Using approximate water resistance calculation methods was evaluated water resistance of the vessel 5415. Were compared the result of approximate resistance calculation method's, real and virtual resistance test experiment's. Were made conclusions, how to select the most optimal ship powering preliminary assessment method on the design stage.

Für jeden am Entwicklungsprozess Beteiligten ist es wichtig möglichst früh das Konzept zu verstehen und bewerten zu können. Die Anforderungen an eine Simulationssoftware hierfür sind die elegante Einbindung in die CAD Umgebung, die einfache Handhabung und natürlich die Verfügbarkeit einer genauen Lösung von Magnetik, Strömung, Festigkeit und Kopplungen. ANSYS AIM erfüllt genau diese Wünsche. ANSYS AIM basiert auf den validierten Solvern von ANSYS Mechanical, ANSYS CFD und ANSYS Maxwell und bietet in einer einheitlichen Umgebung einen leichten und modernen Einstieg in die Multiphysicssimulation. Das ist der Schlüssel, um während der Konstruktion die Produkteigenschaften zu verstehen und optimieren zu können. Im Rahmen des Vortrages verschaffen wir uns einen Überblick über die Breite der Anwendungen: - Bewertung von Kühlkonzepten - Bestimmung des Druckabfalls in Armaturen - Festigkeitsbewertung in Baugruppen - Thermische Auslegung stromdurchflossener Bauteile - Elektromagnetische und thermische Beurteilung von Spulen http://www.cadfem.de/produkte/ansys/ansys-aim.html

Safe and reliable operation of nuclear power plants is the basic requirement for the utilization of nuclear energy since accidents can release radioactivity and with that cause irreversible damage to human beings. Reliability and safety of nuclear reactors are highly dependent on the stability of thermal hydraulic processes occurring in them. Nucleate boiling occurs in Pressurized Water Reactors (PWRs) and Boiling Water Reactors (BWRs) as well as in their passive safety systems during an accident. Passive safety systems are solely driven by thermal gradients and gravitational force removing residual heat from the reactor core independent of any external power supply in the case of accidents. Instability of flow boiling in these passive circuits can cause flow oscillations. These oscillations may induce insufficient local cooling and mechanical loads, which threatens the reactors’ safety. Analysis of boiling two-phase flow and associated heat and mass transfer requires an accurate modeling of flow regime transitions and prediction of boiling parameters such as void fraction, steam bubble sizes, heat transfer coefficient, etc. Flow boiling has been intensively investigated through experiments, one-dimensional codes, and Computational Fluid Dynamics (CFD) methods. Costly hardware and no accessibility to all locations in complex geometries restrict the experimental investigation of flow boiling. Since one-dimensional codes such as ATHLET, RELAP and TRACE are ”lumped parameter” codes, they are unable to simulate complex flow boiling transition patterns. In the last decades, with the development of supercomputers, CFD has been considered as a useful tool to model heat and mass transfer occurring in flow boiling regimes. In many industrial applications and system designs, CFD codes and particularly the Eulerian-Eulerian (E-E) two-fluid model are quickly replacing the experimental and analytical methods. However, the application of this approach for flow boiling modelling poses a challenge for the development of bubble dynamics and wall boiling models to predict heat and mass transfer at the heating wall as well as phase-change mechanism. Many empirical and mechanistic models have been proposed for bubble dynamics modelling. Nevertheless, the validity of these models for only a narrow range of operating conditions and their uncertainties limit their applicability and consequently presently necessitate us to calibrate them for a given boundary condition via calibration factors. For that reason, the first aim of this thesis is the development of a bubble dynamics model for subcooled boiling flow, which needs no calibration factor to predict the bubble growth and detachment. This mechanistic model is formulated based on the force balance approach, physics of a single nucleated bubble and several well-developed models to cover the whole bubble life cycle including formation, growth and departure. This model considers dynamic inclination angle and contact angles between the bubble and the heating wall as well as the contribution of microlayer evaporation, thermal diffusion and condensation around the bubble cap. Validation against four experimental flow boiling data sets was conducted with no case-dependent recalibration and yielded good agreement. The second goal is the implementation of the developed bubble dynamics model in the E-E two-fluid model as a sub-model to improve the accuracy of boiling flow simulation and reduce the case dependency. This implementation requires an extension of the nucleation site activation and wall heat-partitioning models. The bubble dynamics and heat-partitioning models were coupled with the Population Balance Model (PBM) to handle bubble interactions and predict the Bubble Size Distribution (BSD). In addition, the contribution of bubble sliding to wall heat transfer, which has been rarely considered in other modelling approaches, is considered. Validation for model implementation in the E-E two-fluid model was made with ten experimental cases including R12 and R134a flow boiling in a pipe and an annulus. These test cases cover a wide range of operating parameters such as wall heat flux, fluid velocity, subcooling temperature and pressure. The validated parameters were the bubble diameter, void fraction, bubble velocity, Interfacial Area Density (IAD), bubble passing frequency, liquid and wall temperatures. Two-phase flow morphologies for an upward flow in a vertical heating pipe may change from bubbly to slug, plug, and annular flow. Since these flow patterns have a great impact on the heat and mass transfer rates, an accurate prediction of them is critical. The aim of this thesis is the implementation of the developed bubble dynamics and heat-partitioning models in the recently developed GENeralized TwO-Phase flow (GENTOP) framework for the modelling of these flow patterns transition as well. An adopted wall heat-partitioning model for high void fractions is presented and for a generic test case, flow boiling regimes of water in a vertical heating pipe were modelled using ANSYS CFX 18.2. Moreover, the impacts of wall superheat, subcooling temperature and fluid velocity on the flow boiling transition patterns and the effects of these patterns on the wall heat transfer coefficient were evaluated.:Nomenclature xi 1 Introduction 1 1.1 Background and motivation . . . . . . . . . . . . . . . . . . . . . . . 1 1.2 Objectives . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8 1.3 Outline of the thesis . . . . . . . . . . . . . . . . . . . . . . . . . . . 9 2 State-of-the-art in modelling of subcooled flow boiling 11 2.1 Physics of boiling . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12 2.2 Bubble growth modelling . . . . . . . . . . . . . . . . . . . . . . . . 15 2.3 CFD simulation of boiling flows . . . . . . . . . . . . . . . . . . . . . 21 2.3.1 The Eulerian-Eulerian two-fluid model . . . . . . . . . . . . . 21 2.3.2 The Population Balance Model (PBM) . . . . . . . . . . . . . 22 2.3.3 Governing equations of the two-fluid model . . . . . . . . . . 25 2.3.4 Closure models for adiabatic bubbly flow . . . . . . . . . . . . 28 2.3.5 Phase transfer models . . . . . . . . . . . . . . . . . . . . . . 37 2.3.6 The Rensselaer Polytechnic Institute (RPI) wall boiling model 37 2.4 Flow boiling transition patterns in vertical pipes . . . . . . . . . . . . 42 2.5 The GENeralized TwO-Phase flow (GENTOP) concept . . . . . . . . . 45 2.5.1 Treatment of the continuous gas . . . . . . . . . . . . . . . . 46 2.5.2 The Algebraic Interfacial Area Density (AIAD) model . . . . . 46 2.6 Interfacial transfers of continuous gas . . . . . . . . . . . . . . . . . 47 2.6.1 Drag and lift forces . . . . . . . . . . . . . . . . . . . . . . . . 48 2.6.2 Cluster and surface tension forces . . . . . . . . . . . . . . . . 49 2.6.3 Complete coalescence . . . . . . . . . . . . . . . . . . . . . . 50 2.6.4 Entrainment modelling . . . . . . . . . . . . . . . . . . . . . . 51 2.6.5 Turbulence modelling . . . . . . . . . . . . . . . . . . . . . . 51 2.7 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 52 3 An improved bubble dynamics model for flow boiling 55 3.1 Modelling of the bubble formation . . . . . . . . . . . . . . . . . . . 55 3.1.1 Bubble growth rate . . . . . . . . . . . . . . . . . . . . . . . . 57 3.1.2 Force balance . . . . . . . . . . . . . . . . . . . . . . . . . . . 60 ix 3.1.3 Detachment criteria . . . . . . . . . . . . . . . . . . . . . . . 63 3.1.4 Wall heat flux model . . . . . . . . . . . . . . . . . . . . . . . 69 3.1.5 Heat transfer in the heating wall . . . . . . . . . . . . . . . . 70 3.2 Results and discussions . . . . . . . . . . . . . . . . . . . . . . . . . . 72 3.2.1 Discretization dependency study . . . . . . . . . . . . . . . . 72 3.2.2 Model validation . . . . . . . . . . . . . . . . . . . . . . . . . 72 3.2.3 Sensitivity analysis . . . . . . . . . . . . . . . . . . . . . . . . 79 3.3 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 84 4 An improved wall heat-partitioning model 85 4.1 The cavity group activation model . . . . . . . . . . . . . . . . . . . . 85 4.1.1 Bubble sliding length and influence area . . . . . . . . . . . . 88 4.1.2 Model implementation in the Eulerian-Eulerian framework . . 89 4.2 Results and discussions . . . . . . . . . . . . . . . . . . . . . . . . . . 90 4.2.1 DEBORA experiments . . . . . . . . . . . . . . . . . . . . . . 90 4.2.2 Subcooled flow boiling of R134a in an annulus . . . . . . . . 102 4.3 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 114 5 Modelling of flow boiling patterns in vertical pipes 115 5.1 Adopted wall heat-partitioning model for high void fractions . . . . . 115 5.2 Results and discussions . . . . . . . . . . . . . . . . . . . . . . . . . . 118 5.2.1 Effect of wall superheat on the flow boiling transition patterns 118 5.2.2 Effect of flow morphologies on the wall heat transfer coefficient124 5.2.3 Comparison of GENTOP and Eulerian-Eulerian two-fluid models . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 125 5.2.4 Effect of subcooling on the flow boiling transition patterns . . 129 5.2.5 Effect of inlet fluid velocity on the flow boiling transition patterns . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 131 5.3 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 132 6 Conclusions and outlook 133 6.1 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 133 6.2 Outlook . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 136 References 137 Declaration 155

This diploma thesis deals with the development of methods for evaluating retention features of green roofs. For the purpose of this thesis, a rainfall simulator was designed and various types of precipitation were examined. The thesis is divided into two main parts: a theoretical part and a practical part. In the theoretical part, the importance of water retention on green roofs is discussed. In addition, a physical theory related to this topic is included and various rainfall simulators used for scientific experiments in the Czech Republic and abroad are described. The practical part deals with the measurement of droplet size and rainfall simulator design. In this part, the process of measuring the flow and the intensity of rainfall by using scales, flow meter and rain gauge is described. For this purpose, a datalogger was developed by the Faculty of Eletrical Engineering in Brno. Finally, the results are sumarized and recommendations on how to conduct the research in the future are provided.

Made available in DSpace on 2014-12-17T14:08:32Z (GMT). No. of bitstreams: 1 RicardoWO.pdf: 3213751 bytes, checksum: 8d8983eff6f68357e2e660b4041a5b84 (MD5) Previous issue date: 2009-03-19 / Coordena??o de Aperfei?oamento de Pessoal de N?vel Superior / In the present study we elaborated algorithms by using concepts from percolation theory which analyze the connectivity conditions in geological models of petroleum reservoirs. From the petrophysical parameters such as permeability, porosity, transmittivity and others, which may be generated by any statistical process, it is possible to determine the portion of the model with more connected cells, what the interconnected wells are, and the critical path between injector and source wells. This allows to classify the reservoir according to the modeled petrophysical parameters. This also make it possible to determine the percentage of the reservoir to which each well is connected. Generally, the connected regions and the respective minima and/or maxima in the occurrence of the petrophysical parameters studied constitute a good manner to characterize a reservoir volumetrically. Therefore, the algorithms allow to optimize the positioning of wells, offering a preview of the general conditions of the given model s connectivity. The intent is not to evaluate geological models, but to show how to interpret the deposits, how their petrophysical characteristics are spatially distributed, and how the connections between the several parts of the system are resolved, showing their critical paths and backbones. The execution of these algorithms allows us to know the properties of the model s connectivity before the work on reservoir flux simulation is started / No presente estudo foram elaborados algoritmos, utilizando conceitos da teoria da percola??o, que analisam as condi??es de conectividade em modelos geol?gicos elaborados para reservat?rios de petr?leo. A partir de seus par?metros petrof?sicos, tais como: permeabilidade, porosidade, transmissibilidade e outros, gerados por qualquer processo estat?stico, ? poss?vel conhecer qual a por??o do modelo onde ocorre o maior n?mero de c?lulas conectadas, quais s?o os po?os que est?o conectados entre si e qual o caminho m?nimo entre injetores e produtores. Permitindo, assim, classificar o reservat?rio segundo os par?metros petrof?sicos modelados. Podendo determinar, tamb?m, qual a porcentagem do reservat?rio a que cada po?o est? conectado. De uma forma geral, as regi?es conectadas e os respectivos m?nimos e/ou m?ximos da ocorr?ncia dos par?metros petrof?sicos estudados, constituem uma boa forma de caracterizar volumetricamente um reservat?rio. Os algoritmos permitem, ent?o, otimizar o posicionamento de loca??es de po?os oferecendo uma vis?o antecipada das condi??es gerais da conectividade de um determinado modelo. A inten??o n?o ? avaliar modelos geol?gicos, mas mostrar como as jazidas s?o interpretadas, como suas caracter?sticas petrof?sicas se distribuem espacialmente e como as conex?es entre as diversas partes do sistema s?o resolvidas, mostrando seus caminhos cr?ticos e backbones . A execu??o desses algoritmos permite que as caracter?sticas relativas ? conectividade do modelo sejam conhecidas mesmo antes de se iniciar o trabalho de simula??o de fluxo do reservat?rio