Academic literature on the topic 'ANSYS Computational Fluid Dynamic'

Today many researchers are looking toward computational fluid dynamics (CFD) as a tool that can help doctors understand and predict the severity of aneurysms, but there has yet to be any conclusive proof of the accuracy or the ease of implementation of this CFD analysis. To help solve this issue, CFD simulations were conducted to compare these setup practices in order to find the most accurate and computationally efficient setup. These simulation comparisons were applied over two CFD group challenges from the CFD community whose goal was not only to assess modeling accuracy, but the analysis of clinical use and the hemodynamics of rupture as well. Methodology compared included mesh style and refinement, timestep comparison, steady and unsteady flow comparison as well as flow rate amplitude comparison, inlet flow profile conditions, and outlet boundary conditions. The ?Best Practice? setup gave good overall results compared with challenge participant and in-vitro data.

There is an ongoing interest in analyzing the flow characteristics of swimming fish. Biology has resulted in some very efficient motions and formulating these motions is of interest to engineers. One such theory was written by Dr. William Vorus and Dr. Brandon Taravella involving ideal efficiency. It is therefore interesting to test the calculations to see if it is possible to design a motion that can create thrust without necessarily creating vorticity. The computational fluid dynamics software of ANSYS Fluent was used to calculate the resulting flow field of the eel motion to compare with the theoretical values.

To make sure that a dam is safe it is important to have good knowledge about the energy dissipation in the spillway. Physical hydraulic model tests are reliable when investigating how the water flow behaves on its way through the spillway. The problem with physical model testing is that it is both expensive and time consuming, therefore computational fluid dynamics, CFD, is a more feasible option. This projects focuses on a spillway located in Sweden that Vattenfall R&D built a physical model of to simulate the water discharge and evaluate the energy dissipation in order to rebuild the actual spillway. The main purpose of this project is to evaluate if the physical hydraulic test results can be reproduced by using CFD, and obtain detailed results about the flow that could not be obtained by physical testing. There are several steps that need to be completed to create a CFD-model. The first step is to create a geometry, then the geometry needs to be meshed. After the meshing the boundary conditions need to be set and the different models, multiphase model and the viscous model, need to be defined. Next step is to set the operating conditions and decide which solution method that will be used. Then the simulation can be run and the results can get extracted. In this project two CFD simulations were performed. The first simulation was to be compared with the physical hydraulic model test results and the second CFD simulation was of the rebuilt spillway. The results proved that the physical model test results could be recreated by using CFD. It also gave a better understanding of how the energy dissipation was in the spillway and indicates that the reconstruction of the actual spillway was successful since the new spillway both had a higher water discharge capacity and better energy dissipation.

Microbubble drag reduction (MBDR) is an effective method to improve the efficiency of fluid systems. MBDR is a field that has been extensively studied in the past, and experimental values of up to 80% to 90% drag reduction have been obtained. The effectiveness and simplicity of MBDR makes it a viable method for real world applications, particularly in naval applications where it can reduce the drag between the surface of ships and the surrounding water. A two dimensional single phase model was created in ANSYS Fluent to effectively model the behavior of bubble laden flow over a flat plate. This model was used to analyze the effectiveness of MBDR based on the following factors: Reynolds number, types of gas injected, upstream flow velocity, upstream fluid type, density ratio, flow rate of injected gas, using air as the upstream injected fluid.

Research has shown that mixing in cross-junctions in water distribution systems is far from perfect, and that the entering fluids bifurcate from each other rather than mix. The purpose of this thesis is to study the behaviour of two fluids entering a cross-junction in a water distribution system. In this context, experimental tests and numerical simulations are performed in order to produce and test the mixing at cross-junctions. This study focuses on cross-junctions with equal pipe diameters, with flows that can vary from laminar to turbulent. The fluids are pure water and tracer. Different tracer materials with various flow configurations were tested experimentally and numerically. Firstly, an experimental study of mixing in cross-junctions was performed at the TZW: DVGW-Technologiezentrum Wasser (German Water Center) in Dresden. This experimental study pro-vides an overview of the parameters that can affect the mixing in cross-junctions, and is used to validate the numerical simulations. Different numerical approaches for modelling the mixing in cross-junctions are presented. The simulations use an existing commercial CFD code, ANSYS CFX 19.1, and are also extensively validated using experimental and numerical results from other researchers. In ANSYS CFX there are several models that can be used to simulate the mixing of two fluids. In this study both fluids are considered to be isothermal incompressible and without phase change. Two mixing models are tested: the additional variable model and the multi-component model. The three-dimensional models use RANS turbulence models and LES simulations. The parameters of the numerical setup were investigated carefully in order to study their effect on the results. Furthermore, the effect of changing the turbulent Schmidt number in the RANS simulations was extensively studied, and the results are compared with the experimental results. The accuracy of using Large eddy simulation to simulate mixing in cross junction is also tested, taking into consideration the required mesh resolution and the turbulence in the initial bound-ary conditions. This work presents an applicable numerical approach to simulate the fluid behaviours in cross-junctions. Using this approach, the effect of different parameters is tested, such as: Reynolds number, pipe diameter, mixing time, diffusivity and density difference. The results produced using the numerical approach revealed that one of the main parameters that affect the mixing is the density difference. It has a great effect on the outgoing concentration in cross-junctions, and the mixing behaviour changes when the tracer material and the flow regime are changed. The used approach will help to investigate the effect of various flow parameters on the mixing in cross-junctions. Based on the data set of this study, an empirical conceptual model for mixing in cross-junction is also presented using multiple regression, and there is potential for this model to be further developed in combination with experimental and numerical studies.:Abstract Kurzfassung Nomenclature List of Figures List of Tables 1 Introduction and Literature Review 1.1 Introduction 1.2 Literature Review 1.2.1 Transport in water distribution system 1.2.2 Mixing in pipe junctions 1.3 Research problems 1.4 Research methodology and objectives 2 Theoretical Background 2.1 Basic equations and terms in pipe hydraulic 2.1.1 Conservation of mass (the equation of continuity) 2.1.2 Conservation of momentum (the Navier-Stokes equations) 2.1.3 Contaminant transport (transport equation) 2.1.4 Reynolds number 2.1.5 Flow development in pipes 2.1.6 Velocity distribution in pipe flows 2.1.7 Definition of concentration and mass fraction 2.1.8 Viscosity 2.2 Turbulence and modeling 2.2.1 Spatial discretization methods 2.2.2 Turbulence models 2.2.3 Direct numerical simulation (DNS) 2.2.4 Reynolds averaged Navier-Stokes Equations (RANS) 2.2.5 Large eddy simulation 2.3 Modeling of mixing in ANSYS CFX 2.3.1 Additional variable 2.3.2 Multi-component flow model 2.3.3 Two-phase flow model 2.4 Mixing in cross-junctions (available models) 2.4.1 Complete mixing model 2.4.2 Bulk advective mixing model (BAM) 2.4.3 BAM-Wrap mixing model 2.4.4 Shao mixing model 3 Experimental Study 3.1 Introduction 3.2 Description of the model network 3.3 Results and discussion 3.3.1 Turbulent flow experiments 3.3.2 Laminar flow experiments 3.3.3 The interpolation of the experimental results 3.4 Conclusion 4 3D Numerical Study using ANSYS CFX 4.1 Introduction to ANSYS CFX 4.1.1 Model setup in ANSYS CFX 4.1.2 Modeling of mixing in cross-junctions 4.2 Additional variable model 4.2.1 Application of Reynolds averaged Navier-Stokes simulation 4.2.2 Sensitivity analysis of URANS simulations 4.2.3 Application of the large eddy simulation 4.2.4 Summary 4.3 Multi-component flow model 4.3.1 Setup of the multi-component simulation model 4.3.2 Results and discussion 4.4 Summary 5 Mixing Model for Cross junction 5.1 Introduction 5.2 Parameter sensitivity Analysis 5.2.1 The influence of changing the Reynolds number 5.2.2 The influence of changing the pipe diameter 5.2.3 The influence of the inflow and outflow ratios 5.2.4 The influence of changing the tracer properties 5.2.5 The influence of the pipe roughness 5.3 Conceptual model for mixing in cross junction 6 Summary 7 Outlook References APPENDIX A APPENDIX B<br>Frühere Forschungsergebnisse haben gezeigt, dass das Vermischen von gelösten Substanzen in Rohrkreuzen in Wasserversorgungssystemen alles andere als perfekt ist und wenn zwei Flüssigleiten in einem Rohrkreuz eintreten, trennen sie sich eher voneinander anstatt sich zu vermischen. Das Ziel dieser Forschungsarbeit ist es, das Verhalten von zwei Flüssigkeiten in einem Rohrkreuz zu untersuchen. In diesem Zusammenhang werden experimentelle Unter-suchungen und numerische Strömungssimulationen durchgeführt, um das Vermischen an Kreuzungspunkten in Wasserversorgungssystemen zu untersuchen. Diese Arbeit konzentriert sich auf Rohrkreuzen mit gleichen Rohrdurchmessern in Strömungen, die von laminar bis turbulent variieren können. Verschiedene Eigenschaften der Flüssigkeiten mit verschiedenen Strömungskonfigurationen wurden experimentell und numerisch getestet. Zunächst wurden im TZW (DVGW-Technologiezentrum Wasser) die experimentellen Untersuchungen zum Mi-schen in Rohrkreuzungen durchgeführt. Die durchgeführten experimentellen Untersuchungen bieten einen Überblick über die Parameter, die das Mischverhältnis in Kreuzungspunkten be-einflussen können, und werden zur Validierung der numerischen Simulationen verwendet. Verschiedene numerische Ansätze zur Modellierung des Vermischens in Rohrkreuzen werden vorgestellt. Die 3D-numerische Strömungssimulationen verwenden einen vorhandenen kommerziellen CFD-Code, ANSYS CFX 19.1, und werden auch anhand experimenteller und numerischer Ergebnisse anderer Forscher umfassend validiert. In ANSYS CFX gibt es mehre-re Modelle, mit denen das Vermischen von Flüssigkeiten simuliert werden kann. In dieser Arbeit werden beide Flüssigkeiten als isotherm, inkompressibel und ohne Phasenwechsel betrachtet. Es werden zwei Mischmodelle getestet: das Additional Variable Model und das Multi-component Model. Die 3D -Strömungsmodelle verwenden RANS-Turbulenzmodelle und LES-Simulationen. Die Parameter des numerischen Aufbaus wurden sorgfältig untersucht, um ihre Auswirkung auf die Ergebnisse zu untersuchen. Darüber hinaus wurde der Einfluss der Änderung der turbulenten Schmidt-Zahl in den RANS-Simulationen ausführlich untersucht und die Ergebnisse mit den experimentellen Ergebnissen verglichen. Die Genauigkeit der Ver-wendung einer Large-Eddy-Simulation zur Simulation des Vermischens in Rohrkreuz wird ebenfalls getestet, wobei die erforderliche Netzauflösung und die Turbulenzen in den An-fangs- und Randbedingungen berücksichtigt werden. Diese Arbeit präsentiert einen anwend-baren numerischen Ansatz zur Simulation des Fließverhaltens in Rohrkreuzen. Mit diesem Ansatz wird die Wirkung verschiedener Parameter getestet, z. B.: Reynolds-Zahl, Rohrdurch-messer, Vermischungszeit, Diffusivität und Dichteunterschied. Die mit den numerischen Mo-dellen erzielten Ergebnisse zeigten, dass einer der Hauptparameter, die das Vermischen in Rohrkreuzen beeinflussen, der Dichteunterschied ist, welcher einen großen Einfluss auf die ausgehende Konzentration in Kreuzungen hat. Der verwendete numerische Ansatz wird dazu beitragen, die Auswirkung verschiedener Strömungsparameter auf das Vermischen in Rohr-kreuzen zu untersuchen. Basierend auf dem Datensatz dieser Studie wird auch ein empiri-sches konzeptionelles Modell für das Vermischen in Rohrkreuz unter Verwendung multipler Regression vorgestellt. Dieses Modell kann in Kombination mit experimentellen und numeri-schen Studien weiterentwickelt werden.:Abstract Kurzfassung Nomenclature List of Figures List of Tables 1 Introduction and Literature Review 1.1 Introduction 1.2 Literature Review 1.2.1 Transport in water distribution system 1.2.2 Mixing in pipe junctions 1.3 Research problems 1.4 Research methodology and objectives 2 Theoretical Background 2.1 Basic equations and terms in pipe hydraulic 2.1.1 Conservation of mass (the equation of continuity) 2.1.2 Conservation of momentum (the Navier-Stokes equations) 2.1.3 Contaminant transport (transport equation) 2.1.4 Reynolds number 2.1.5 Flow development in pipes 2.1.6 Velocity distribution in pipe flows 2.1.7 Definition of concentration and mass fraction 2.1.8 Viscosity 2.2 Turbulence and modeling 2.2.1 Spatial discretization methods 2.2.2 Turbulence models 2.2.3 Direct numerical simulation (DNS) 2.2.4 Reynolds averaged Navier-Stokes Equations (RANS) 2.2.5 Large eddy simulation 2.3 Modeling of mixing in ANSYS CFX 2.3.1 Additional variable 2.3.2 Multi-component flow model 2.3.3 Two-phase flow model 2.4 Mixing in cross-junctions (available models) 2.4.1 Complete mixing model 2.4.2 Bulk advective mixing model (BAM) 2.4.3 BAM-Wrap mixing model 2.4.4 Shao mixing model 3 Experimental Study 3.1 Introduction 3.2 Description of the model network 3.3 Results and discussion 3.3.1 Turbulent flow experiments 3.3.2 Laminar flow experiments 3.3.3 The interpolation of the experimental results 3.4 Conclusion 4 3D Numerical Study using ANSYS CFX 4.1 Introduction to ANSYS CFX 4.1.1 Model setup in ANSYS CFX 4.1.2 Modeling of mixing in cross-junctions 4.2 Additional variable model 4.2.1 Application of Reynolds averaged Navier-Stokes simulation 4.2.2 Sensitivity analysis of URANS simulations 4.2.3 Application of the large eddy simulation 4.2.4 Summary 4.3 Multi-component flow model 4.3.1 Setup of the multi-component simulation model 4.3.2 Results and discussion 4.4 Summary 5 Mixing Model for Cross junction 5.1 Introduction 5.2 Parameter sensitivity Analysis 5.2.1 The influence of changing the Reynolds number 5.2.2 The influence of changing the pipe diameter 5.2.3 The influence of the inflow and outflow ratios 5.2.4 The influence of changing the tracer properties 5.2.5 The influence of the pipe roughness 5.3 Conceptual model for mixing in cross junction 6 Summary 7 Outlook References APPENDIX A APPENDIX B

Every computational fluid dynamics engineer deals with a never ending story – limitedcomputer resources. In computational fluid dynamics there is practically never enoughcomputer power. Limited computer resources lead to long calculation times which result inhigh costs and one of the main reasons is that large quantity of elements are needed in acomputational mesh in order to obtain accurate and reliable results.Although there exist established meshing approaches for the Siemens 4th generation DLEburner, mesh dependency has not been fully evaluated yet. The main goal of this work istherefore to better optimize accuracy versus cell count for this particular burner intended forsimulation of air/gas mixing where eddy-viscosity based turbulence models are employed.Ansys Fluent solver was used for all simulations in this work. For time effectivisationpurposes a 30° sector model of the burner was created and validated for the meshconvergence study. No steady state solutions were found for this case therefore timedependent simulations with time statistics sampling were employed. The mesh convergencestudy has shown that a coarse computational mesh in air casing of the burner does not affectflow conditions downstream where air/gas mixing process is taking place and that a majorpart of the combustion chamber is highly mesh independent. A large reduction of cell count inthose two parts is therefore allowed. On the other hand the RPL (Rich Pilot Lean) and thepilot burner turned out to be highly mesh density dependent. The RPL and the Pilot burnerneed to have significantly more refined mesh as it has been used so far with the establishedmeshing approaches. The mesh optimization has finally shown that at least as accurate resultsof air/gas mixing results may be obtained with 3x smaller cell count. Furthermore it has beenshown that significantly more accurate results may be obtained with 60% smaller cell count aswith the established meshing approaches.A short mesh study of the Siemens 3rd generation DLE burner in ignition stage of operationwas also performed in this work. This brief study has shown that the established meshingapproach for air/gas mixing purposes is sufficient for use with Ansys Fluent solver whilecertain differences were discovered when comparing the results obtained with Ansys Fluentagainst those obtained with Ansys CFX solver. Differences between Fluent and CFX solverwere briefly discussed in this work as identical simulation set up in both solvers producedslightly different results. Furthermore the obtained results suggest that Fluent solver is lessmesh dependent as CFX solver for this particular case.

Solar energy is one of a very few low-carbon energy technologies with the enormous potential to grow to a large scale. Currently, solar power is generated via the photovoltaic (PV) and concentrating solar power (CSP) technologies. The ability of CSPs to scale up renewable energy at the utility level, as well as to store energy for electrical power generation even under circumstances when the sun is not available (after sunset or on a cloudy day), makes this technology an attractive option for sustainable clean energy. The levelised electricity cost (LEC) of CSP with thermal storage was about 0.16-0.196 Euro/kWh in 2013 (Kost et al., 2013). However, lowering LEC and harvesting more solar energy from CSPs in future motivate researchers to work harder towards the optimisation of such plants. The situation tempts people and governments to invest more in this ultimate clean source of energy while shifting the energy consumption statistics of their societies from fossil fuels to solar energy. Usually, researchers just concentrate on the optimisation of technical aspects of CSP plants (thermal and/or optical optimisation). However, the technical optimisation of a plant while disregarding economic goals cannot produce a fruitful design and in some cases may lead to an increase in the expenses of the plant, which could result in an increase in the generated electrical power price. The study focused on a comprehensive optimisation of one of the main CSP technology types, the linear Fresnel collector (LFC). In the study, the entire LFC solar domain was considered in an optimisation process to maximise the harvested solar heat flux throughout an imaginary summer day (optical goal), and to minimise cavity receiver heat losses (thermal goal) as well as minimising the manufacturing cost of the plant (economic goal). To illustrate the optimisation process, an LFC was considered with 12 design parameters influencing three objectives, and a unique combination of the parameters was found, which optimised the performance. In this regard, different engineering tools and approaches were introduced in the study, e.g., for the calculation of thermal goals, Computational Fluid Dynamics (CFD) and view area approaches were suggested, and for tackling optical goals, CFD and Monte-Carlo based ray-tracing approaches were introduced. The applicability of the introduced methods for the optimisation process was discussed through case study simulations. The study showed that for the intensive optimisation process of an LFC plant, using the Monte Carlo-based ray-tracing as high fidelity approach for the optical optimisation objective, and view area as a low fidelity approach for the thermal optimisation objective, made more sense due to the saving in computational cost without sacrificing accuracy, in comparison with other combinations of the suggested approaches. The study approaches can be developed for the optimisation of other CSP technologies after some modification and manipulation. The techniques provide alternative options for future researchers to choose the best approach in tackling the optimisation of a CSP plant regarding the nature of optimisation, computational cost and accuracy of the process.<br>Thesis (PhD)--University of Pretoria, 2017.<br>Mechanical and Aeronautical Engineering<br>PhD<br>Unrestricted