Effects of uncertainties in positioning of PIV plane on validation of CFD results of a high-head Francis turbine model

The use of Computational Fluid Dynamics (CFD) for the design of modern hydraulic turbines has increased and matured significantly the last decades. More recently, CFD is also used to understand how to safely widen the hydraulic turbine operating ranges, and to avoid hazardous conditions during transient operation. The accuracy of such CFD results relies on validation with experimental data. There are many uncertainties in both numerical and experimental studies of flow in hydraulic turbines. The present work is focusing on the effects of the uncertainties in the positioning of the experimental Particle Image Velocimetry (PIV) plane on the validation of CFD results of the high-head Francis-99 turbine model. A transient shutdown sequence is considered, where the available experimental and numerical data are considered accurate according to a conventional thorough validation procedure. A part of that validation procedure is the comparison of spatially and temporally varying velocity profiles along three lines of the experimental PIV plane. The positioning of this PIV plane is here considered uncertain, using three translational and three rotational stochastic parameters with uniform probability distribution functions. The validated CFD results are used to extract the data that depends on these uncertainties, while this is not possible for the experimental data. The polynomial chaos expansion method is employed for the Uncertainty Quantification (UQ) study while Sobol’ indices are utilized for the Sensitivity Analysis (SA). The UQ can be used to show how the considered uncertainties impact the extracted components of the velocity field, and the sensitivity analysis reveals the relative contribution of each uncertain parameter on the quantity of interest. For this particular Francis-99 case it is shown that the so-called horizontal velocity component is most sensitive to the plane-normal positioning of the PIV plane. This is also the velocity component where all the numerical results found in the literature differ most from the experimental results. It is also shown that the probability distribution function of the numerical horizontal velocity is covered by the experimental standard deviation bounds, which means that it is quantified that the numerical and experimental results are similar within the range of the uncertainties

Shape optimisation of the sharp-heeled Kaplan draft tube: Performance evaluation using Computational Fluid Dynamics

A methodology to assess the performance of an elbow-type draft tube is outlined. This was achieved using Computational Fluid Dynamics (CFD) to evaluate the pressure recovery and mechanical energylosses along a draft tube design, while using open-source and commercial software to parameterise and regenerate the geometry and CFD grid. An initial validation study of the elbow-type draft tube is carriedout, focusing on the grid-regeneration methodology, steady-state assumption, and turbulence modelling approach for evaluating the design’s efficiency. The Grid Convergence Index (GCI) technique was used to assess the uncertainty of the pressure recovery to the grid resolution. It was found that estimating the pressure recovery through area-weighted averaging significantly reduced the uncertainty due to the grid. Simultaneously, it was found that this uncertainty fluctuated with the local cross-sectional area along the geometry. Subsequently, a study of the inflow cone and outer-heel designs on the flowfield and pressure recovery was carried out. Catmull-Rom splines were used to parameterise these components, so as torecreate a number of proposed designs from the literature. GCI analysis is also applied to these designs,demonstrating the robustness of the grid-regeneration methodology

Recuperação de energia em sistemas de abastecimento de água com recurso a hidroturbinas

Mestrado em Engenharia MecânicaIn the last century, the main source of hydroelectric power came from conventional dams and the energy produced by hydro turbines had a fast growing. New applications of turbines in hydro power even in micro-scale projects have emerged. Water supply systems are large energy consumers due to the large amount of energy needed for pumping the water from low to high heights. However, gravity fed subsystems generally presents excess of pressure, which is lost with pressure reducing valves. Therefore, energy can be recovered from locals of excessively high flow and pressure. Nevertheless, water networks are highly complex systems and the flow conditions change instantaneously throughout the network. The control of the pressure is the top priority of the system providers and energy should be converted along with keeping the pressure to a desired level. The application of turbines appeared as an alternative to produce energy, to reduce leakage reductions and to manage network pressure. This work aims to investigate the energy production in water supply systems using micro hydro turbines. To find the optimal location for the installation of micro hydro turbine in the network, a tool is developed using the hydraulic simulator EPANET for obtaining flow regimes of each pipe. Technical feasibility analysis is automatically computed for the selection of appropriate type turbine and the CFD program ANSYS is used to design and verify the hydraulic performance of the turbine. A financial analysis is performed and has showed that energy production in water supply systems using micro turbines is a profitable alternative and a renewable solution for the world’s growing energy needs.No século passado, a principal fonte de energia hidroelétrica provinha de barragens convencionais e a energia produzida pelas turbinas hidráulicas teve um crescimento rápido. Neste século, novas aplicações de turbinas geradoras de energia elétrica, mesmo em projetos de microescala, emergiram. Os sistemas de abastecimento de água são grandes consumidores de energia devido à grande quantidade de energia necessária para o bombeamento de água de baixas para elevadas alturas manométricas. No entanto, os subsistemas alimentados graviticamente apresentam geralmente excesso de pressão, que se perde com válvulas de redução de pressão. Portanto, a energia pode ser recuperada de locais de caudal e pressão excessivamente elevados. No entanto, as redes de água são sistemas altamente complexos cujas condições hidráulicas mudam instantaneamente em toda a rede. O controle da pressão é a principal prioridade dos fornecedores e a energia deve ser recuperada ao mesmo tempo que se mantém a pressão desejada. A aplicação de turbinas aparece como uma alternativa para produzir energia, reduzir fugas e gerir a pressão da rede. Este trabalho tem como objetivo investigar a produção de energia em sistemas de abastecimento de água usando microturbinas hidráulicas. Para encontrar a localização ideal para a instalação da microturbina hidráulicas na rede, desenvolve-se uma ferramenta que recorre ao simulador hidráulico EPANET para obter regimes de escoamento de cada conduta. A análise de viabilidade técnica é calculada automaticamente para a seleção da turbina adequada e o programa CFD ANSYS é usado para projetar e verificar o desempenho hidráulico da turbina. Uma análise financeira é realizada e mostra que a produção de energia em sistemas de abastecimento de água usando microturbinas é uma alternativa lucrativa e uma solução renovável para as crescentes necessidades energéticas do mundo

Multi-Fidelity Design Optimization of Francis Turbine Runner Blades

RÉSUMÉ Ce projet de thèse propose une méthodologie Multi-Fidelity Design Optimisation (MFDO) qui vise à améliorer l'efficacité du processus de conception en génie mécanique. Cette méthodologie a été développée pour résoudre les problèmes liés à la conception mécanique des roues de turbines hydrauliques. Cette méthode peut être utilisée dans d'autres processus d’optimisation d'ingénierie, surtout si les processus d'optimisation sont coûteux. L'approche MFDO divise le coût informatique entre deux phases, une basse fidélité et une haute-fidélité. Cette méthode permet d'intégrer les avantages des évaluations à basse fidélité et haute-fidélité, et pour équilibrer le coût et la précision requise par chaque niveau de fidélité. Alors que la phase de basse fidélité contient la boucle itérative d'optimisation, la phase haute-fidélité évalue les candidats de conceptions prometteuses et calibre l'optimisation basse fidélité. La nouvelle approche de MFDO propose un Territorial-Based Filtering Algorithm (TBFA) qui relie les deux niveaux de fidélité. Cette méthode traite le problème que l'objectif d'optimisation à basse fidélité est différent de celui de la phase à haute-fidélité. Ce problème est commun dans les optimisations de substitutions basées sur la physique (par exemple en utilisant une analyse d’écoulement non visqueux à la place des évaluations d’écoulement visqueux). En fait, la vraie fonction n’est pas évaluable dans la phase basse fidélité due à l'absence de la physique impliquée dans ces évaluations. Par conséquent, les solutions dominantes de l'optimisation basse fidélité ne sont pas nécessairement dominantes du point de vue du véritable objectif. Par conséquent, le TBFA a été développé pour sélectionner un nombre donné de candidats prometteurs, qui sont dominants dans leurs propres territoires et qui sont assez différents du point de vue géométrique. Tandis que les objectifs de la phase haute-fidélité ne peuvent être évalués directement dans la phase basse-fidélité, certains objectifs peuvent être sélectionnés par des concepteurs chevronnés parmi des caractéristiques de conception, qui sont évaluables et suffisamment bien prédites par les analyses de basse fidélité. Des concepteurs expérimentés sont habitués à associer des objectifs de bas niveau à des bonnes conceptions. Un grand nombre d'études de cas ont été réalisées dans ce projet pour évaluer les capacités de la méthodologie MFDO proposée. Pour couvrir les différents types de roues de turbines Francis, trois roues différentes ont été choisies. Chacune d'elles avait ses propres défis de conception, qui devaient être pris en charge. Par conséquent, différentes formulations de problèmes d'optimisation ont été étudiées pour trouver la plus appropriée pour chaque problème en main.----------ABSTRACT This PhD project proposes a Multi-Fidelity Design Optimization (MFDO) methodology that aims to improve the design process efficiency. This methodology has been developed to tackle hydraulic turbine runner design problems, but it can be employed in other engineering optimizations, which have costly computational design processes. The MFDO approach splits the computational burden between low- and high-fidelity phases to integrate benefits of low- and high-fidelity evaluations, and to balance the cost and accuracy required by each level of fidelity. While the low-fidelity phase contains the iterative optimization loop, the high-fidelity phase evaluates promising design candidates and calibrates the low-fidelity optimization. The new MFDO approach proposes a flexible Territorial-Based Filtering Algorithm (TBFA) that connects the two levels of fidelity. This methodology addresses the problem that the low-fidelity optimization objective is different from the one in the high-fidelity phase. This problem is common in physics-based surrogate optimizations (e.g. using inviscid flow analyses instead of viscous flow evaluations). In fact, the real objective function is not assessable in the low-fidelity phase due to the lack of physics involved in the low-fidelity evaluations. Therefore, the dominant solutions of the low-fidelity optimization are not necessarily dominant from the real objective perspective. Hence, the TBFA has been developed to select a given number of promising candidates, which are dominant in their own territories and geometrically different enough. While high-fidelity objectives cannot be directly evaluated in the low-fidelity phase, some targets can be set by experienced designers for a subset of the design characteristics, which are assessable and sufficiently well predicted by low-fidelity analyses. The designers are accustomed to informally map good low-level targets to overall satisfying designs. A large number of case studies were performed in this project to evaluate the proposed MFDO capabilities. To cover different types of Francis turbine runners, three different runners were chosen. Each of them had its own special design challenges, which needed to be taken care of. Therefore, variant optimization problem formulations were investigated to find the most suitable for each problem at hand. Those formulations involved different optimization configurations built up from proper choices of objective functions, constraints, design variables, and other optimization features such as local or global exploration budgets and their portions of the overall computational resources

Small-Scale Hydropower and Energy Recovery Interventions: Management, Optimization Processes and Hydraulic Machines Applications

Several topics in the small-scale hydropower sector are of great interest for pursuing the goal of a more sustainable relationship with the environment. The goal of this Special Issue entitled “Small-Scale Hydropower and Energy Recovery Interventions: Management, Optimization Processes and Hydraulic Machines Applications” was to collect the most important contributions from experts in this research field and to arouse interest in the scientific community towards a better understanding of what might be the main key aspects of the future hydropower sector. Indeed, the Guest Editors are confident that the Special Issue will have an important impact on the entire scientific community working in this research field that is currently facing important changes in paradigm to achieve the goal of net-zero emissions in both the energy and water sectors

Analysis of the Swirling Flow Downstream a Francis Turbine Runner

An experimental and theoretical investigation of the flow at the outlet of a Francis turbine runner is carried out in order to elucidate the causes of a sudden drop in the draft tube pressure recovery coefficient at a discharge near the best efficiency operating point. Laser Doppler anemometry velocity measurements were performed for both axial and circumferential velocity components at the runner outlet. A suitable analytical representation of the swirling flow has been developed taking the discharge coefficient as independent variable. It is found that the investigated mean swirling flow can be accurately represented as a superposition of three distinct vortices. An eigenvalue analysis of the linearized equation for steady, axisymmetric, and inviscid swirling flow reveals that the swirl reaches a critical state precisely (within 1.3%) at the discharge where the sudden variation in draft tube pressure recovery is observed. This is very useful for turbine design and optimization, where a suitable runner geometry should avoid such critical swirl configuration within the normal operating range

Evaluation of Guiding Device for Downstream Fish Migration with in-Field Particle Tracking Velocimetry and CFD

The performance of a fish guiding device located just upstream a hydropower plant is scrutinized. The device is designed to redirect surface orientated down-stream migrating fish (smolts) away from the turbines towards a spillway that act as a relatively safe fishway. Particles are added up-stream the device and the fraction particles going to the spillway is measured. A two-frame Particle Tracking Velocimetry algorithm is used to derive the velocity field of the water. The experimental results are compared to simulations with CFD. If the smolts move passively as the particles used in the study the guiding device works very well and some modifications may optimize its performance. In-field Particle Tracking Velocimetry is a suitable technique for the current case and the results compare well with numerical simulations

Analysis and Prevention of Vortex Breakdown in the Simplified Discharge Cone of a Francis Turbine

We perform a numerical analysis of the decelerated swirling flow into the discharge cone of a model Francis turbine operated at variable discharge and constant head, using an axisymmetric turbulent swirling flow model and a corresponding simplified computational domain. Inlet boundary conditions correspond to velocity and turbulent kinetic energy profiles measured downstream the Francis runner. Our numerical results are validated against experimental data on a survey section further downstream in the cone, showing that the Reynolds stress turbulence model with a quadratic pressure-strain term correctly captures the flow field. It is shown that the diffuser performance quickly deteriorates as the turbine discharge decreases, due to the occurrence and development of vortex breakdown, with a central quasistagnant region. We investigate a novel flow control technique, which uses a water jet injected from the runner crown tip along the axis. It is shown that the jet discharge can be optimized for minimum overall losses, while the vortex breakdown is eliminated. This flow control method is useful for mitigating the Francis turbine flow instabilities when operating at partial discharge

The Turgo impulse turbine:a CFD based approach to the design improvement with experimental validation

The use of Computational Fluid Dynamics (CFD) has become a well-established approach in the analysis and optimisation of impulse hydro turbines. Recent studies have shown that modern CFD tools combined with faster computing processors can be used to accurately simulate the operation of impulse turbine runners and injectors in timescales suitable for design optimisation studies and which correlate well with experimental results. This work has however focussed mainly on Pelton turbines and the use of CFD in the analysis and optimisation of Turgo turbines is still in its infancy, with no studies showing a complete simulation of a Turgo runner capturing the torque on the inside and outside blade surfaces and producing a reliable extrapolation of the torque and power at a given operating point. Although there have been some studies carried out in the past where injector geometries (similar for both Pelton and Turgo turbines) have been modified to improve their performance, there has been no thorough investigation of the basic injector design parameters and the influence they have on the injector performance. The aim of this research is to use modern CFD tools to develop models which aid the better understanding of Turgo impulse turbine runners and injectors and facilitate the optimisation of existing designs. CFD is used to model and optimise both the injectors and the runner of a modern commercial Turgo impulse turbine and the accuracy of the models are verified by carrying out experimental tests on the original and optimised designs. The original designs together with experience in the operation of these turbines were provided by the industrial sponsors of this research Gilbert Gilkes and Gordon Ltd. The research described in this thesis can be split into five main parts: 1.Development of a numerical model to analyses the flow through the Turgo runner using modern CFD tools combined with a series of assumptions to reduce the computational time while still retaining the accuracy of the model. Using this model to optimise the design of the Turgo runner provided by Gilkes. 2.Development of a similar numerical model for a simplified 2D injector design to facilitate a study of the impact of the basic design parameters on the performance over a range of operating conditions. Applying these optimisations to the existing Gilkes design and taking the numerical analysis further by including the full injector geometry as well as the branch pipe and guide vanes. 3.Manufacture and experimental testing of the original and optimised Turgo runners. 4.Manufacture and experimental testing of the original and optimised injector designs. 5.Verification of the numerical models developed in 1.) and 2.) by comparison with the experimental results. The numerical model developed in 1.) includes several simplifying assumptions in order to reduce the computational time and produce models which could solve in reasonable timescales allowing many design variations to be analysed. As the runner simulations require a transient analysis of complex multi-phase free surface flow with a rotating frame of reference they are already computationally costly and efforts have to be made to reduce this computational cost if the models are to be effective for optimisation purposes. The runner model simplifications were the exclusion of any casing interactions by not modelling the casing and the use of a 2 blade model analysing only a single blade passage in order to reduce the size of the computational domain. Several modelling assumptions were also introduced and attempts are made to quantify the effects of these assumptions through unit tests. For discretisation of the domain two mesh sizes were used, a coarse mesh which slightly under predicts the efficiency but was suitable for comparing designs and a fine mesh which gave mesh independent results. The fine mesh took over 4 times longer to solve rendering it unfeasible for optimisation purposes and it was therefore used only at key points to verify the design changes made using the coarse mesh. The analysis and optimisation of the injectors carried out in 2.) use similar CFD tools as the runner analysis however the geometry (excluding the branch pipe and guide vanes) could be simplified into a 2D axisymmetric case operating at steady state conditions. This drastically reduces the solve time and allows the use of a mesh independent model and the analysis of hundreds of designs and operating conditions. Once the optimisations had been carried out, the design changes were verified by extending the model to analyse the 3D case with a straight pipe upstream of the injector and a 3D full case including the branch pipe and guide vanes. In 3.), following the optimisation of the runner in 1.), a Finite Element Analysis (FEA) of the runner was carried out to ensure the optimised runner had sufficient strength for operation at the highest heads recommended for a runner of this size. The design was strengthened based on the results of the FEA and CFD was carried out in conjunction with these changes to ensure minimal loss in hydraulic efficiency. The manufacturing process was also researched and Design for Manufacture and Assembly (DFMA) was applied to the strengthened design identifying two optimised designs (LE4 and LE1) which will be tested before and after additional dressing of the leading edges. Both optimised runner designs were manufactured and tested at the Laboratory of Hydraulic Machines, National Technical University of Athens (NTUA). Following the injector analysis and optimisations in 2.), the optimised injectors were manufactured for experimental testing using both the Pelton and the Turgo test rig at NTUA in 4.). As the design changes made were not critical to the strength of the injectors there was no need to carry out a FEA. The CFD model verification in Part 5.) looks initially at the full Turgo system in order to compare the absolute difference between the numerical efficiency and the experimental efficiency of the original Turgo runner at the best efficiency point. The mechanical losses of the test rig are estimated to determine the experimental hydraulic efficiency. The numerical hydraulic efficiency is then determined by calculating the losses upstream of the injector, using standard pipe flow equations and combing these with the losses through the injector, as well as the numerical efficiency of the runner by simulating the runner using the ‘real jet’ profile produced by the full injector simulations. The results showed the numerical model to be over-predicting the efficiency by 1.26%. The numerical difference in the performance of the two injectors is then compared to the experimental difference measured during testing. This is done by importing the ‘real jet’ profiles produced by the full 3D injector simulations into the LE1 runner simulation. This allows the difference in total efficiency between the injectors combined with the runner to be compared to the experimental differences which also includes the impact of the jet on the runner performance. The comparison between the injectors is less accurate as more uncertainties are introduced when combining these models and the differences are smaller however the CFD was able to predict the improvements to within 0.4%. Finally, the numerical differences between the runner designs and the experimental differences are compared showing that the runner model is able to predict differences in hydraulic efficiency to within 0.1%. This accuracy is largely down to that fact that many of the systematic experimental and modelling errors are cancelled out when comparing only the runners. The CFD model verification has shown that although the absolute performance of the Turgo system can be modelled numerically to within a good degree of accuracy, it requires combining injector and runner models as well as estimating additional losses in the pipework which can prove time consuming. However for design comparison and optimisations the CFD models have been shown to be far more accurate suggesting that this is where these numerical models are most useful