Investigation of the Performance of a Staggered Configuration of Tidal Turbines Using CFD

This is the final version of the article. Available from Elsevier via the DOI in this record.This paper investigates the influence of wake interaction and blockage on the performance of individual turbines in a staggered configuration in a tidal stream farm using the CFD based Immersed Body Force turbine modelling method. The inflow condition to each turbine is unknown in advance making it difficult to apply the correct loading to individual devices. In such cases, it is necessary to establish an appropriate range of operating points by varying the loading or body forces in order to understand the influence of wake interaction and blockage on the performance of the individual devices. The performance of the downstream turbines was heavily affected by the wake interaction from the upstream turbines, though there were accelerated regions within the farm which could be potentially used to increase the overall power extraction from the farm. Laterally closely packed turbines can improve the performance of those turbines due to the blockage effect, but this could also affect the performance of downstream turbines. Thus balancing both the effect of blockage and wake interaction continues to be a huge challenge for optimising the performance of devices in a tidal stream farm.This study is funded by EPSRC, project number EP/J010138/1, under the Supergen Marine research program

Near-wall modelling in Eulerian–Eulerian simulations

This is the author accepted manuscript. The final version is available from Elsevier via the DOI in this recordThe near-wall region in turbulent Eulerian–Eulerian (E–E) simulations has hitherto received little to no attention. A standard approach to modelling this region is through the employment of single-phase wall-functions in the fluid-phase and it is unclear whether such an approach is capable of capturing the turbulent fluid-particle interaction in the near-wall region. In order to both investigate and alleviate E–E models reliance on single-phase wall-functions we propose an E–E elliptic relaxation model to account for the near-wall non-homogeneity which arises in wall-bounded flows. The proposed model is derived within an E–E framework and enables the full resolution of the boundary layer and arbitrary wall sensitivity. The model is then compared against the conventional kf−εf turbulence model with standard single-phase wall-functions. Additionally, the modelling is compared against a low-Re number turbulence model. The elliptic relaxation model is implemented within the open-source CFD toolbox OpenFOAM, applied to a vertical downward-facing channel and validated against the benchmark experimental data of Kulick et al. [1]. Model results show marked improvements over the conventional turbulence model across mean flow and turbulence statistics predictions. The use of conventional single-phase wall functions were shown to negatively impede on the prediction of the velocity covariance coupling term and as a result the particle fluctuation energy. Moreover, this also lead to an underestimation of the near-wall volume fraction accumulation. Finally, the elliptic relaxation model, E-E model and accompanying validation cases are made open-source.University of Exete

Fully-coupled pressure-based two-fluid solver for the solution of turbulent fluid-particle systems

This is the author accepted manuscript. The final version is available from Elsevier via the DOI in this recordA fully-coupled pressure-based two-fluid solver for the solution of turbulent fluid-particle flows is presented. The numerical framework details several crucial aspects: implicit treatment of the phase-velocity-pressure coupling, the implicit treatment of inter-phase momentum transfer and finally the solution algorithm. The two-fluid solver is implemented within the open source tool-box foam-extend which is a community driven fork of OpenFOAM. The coupled solver is verified against a standard segregated implementation of the two-fluid solution algorithm and validated against benchmark experimental data. The coupled solver shows marked improvements in convergence, stability and solution time. The coupled implementation is capable of solving to a tolerance that is six orders of magnitude smaller in residual error and 1.7 times quicker than the segregated solver. Additionally, the sequentially solved system of phase-energies experienced performance improvements when solved in conjunction with the coupled solver

Reynolds-Averaged Two-Fluid Model prediction of moderately dilute fluid-particle flow over a backward-facing step

This is the author accepted manuscript. The final version is available from Elsevier via the DOI in this record In this work a Reynolds-Averaged Two-Fluid fully coupled model (RA-TFM) for modelling of turbulent fluid-particle flow is implemented in OpenFOAM and applied to a vertically orientated backward-facing step. Three particle classes with varying mass loadings (10–40%) and different Stokes number are investigated. Details of the implementation and solution procedure are provided with special attention given to challenging terms. The prediction of mean flow statistics are in good agreement with the data from literature and show a distinct improvement over current model predictions. This improvement was due to the separation of the particle turbulent kinetic energy kp, and the granular temperature Θp, in which the large scale correlated motion and small scale uncorrelated motion are governed by separate transport equations. For each case simulated in this work, turbulence attenuation was accurately predicted, a finding that is attributed to separate coupling terms in both transport equations of kp and εp

CFD characterization of flow regimes inside open cell foam substrates

This is the author accepted manuscript. The final version is available from the publisher via the DOI in this record.In this work a combination of micro-CT, image-based modeling and CFD has been applied to investigate the pressure drop in open-cell foams. The analysis covers a range of flow regimes and is aimed at determining the effects of important morphological parameters on the pressure drop. The adoption of micro-CT technology along with detailed CFD modeling allows the investigation of phenomena occurring in real foam micro-structures. Moreover, by means of image processing tools, the geometry can be artificially modified in order to investigate the effects of mathematical transformation of the geometrical parameters of a real foam, one parameter at a time, e.g. varying pore size without affecting the porosity. Non-dimensional coefficients have been defined for the analysis of the results, with the purpose of describing the pressure drop as a function of the Reynolds number. The proposed formulation allows us to relate the permeability properties of an open-cell foam to its morphology alone, without any dependence on the properties of the fluid adopted or on the effective characteristic dimension of the foam micro-structure (pore or cell size). Comparison with experimental results available in the literature is also provided for one of the cases studied

Redesign of Industrial Apparatus using Multi-Objective Bayesian Optimisation

This is the author accepted manuscriptIntroduction. Design optimisation using Computational Fluid Dynamics (CFD) often requires extremising multiple (and often conflicting) objectives simultaneously. For instance, a heat exchanger design will require maximising the heat transfer across the media, while minimising the pressure drop across the apparatus. In such cases, usually there is no unique solution, but a range of solutions trading off between the objectives. The set of solutions optimally trading off the objectives are known as the Pareto set, and in practice only an approximation of the set may be achieved. Multi-Objective Evolutionary Algorithms (MOEAs) are known to perform well in estimating the optimal Pareto set. However, they require thousands of function evaluations, which is impractical with computationally expensive simulations. An alternative is to use Multi-Objective Bayesian Optimisation (MOBO) method that has been proved to be an effective approach with limited budget on function evaluations [1]. In this work, we illustrate a newly developed MOBO framework in [1] with OpenFOAM 2.3.1 to locate a good estimation of the optimal Pareto set for a range of industrial cases.This work was supported by the UK Engineering and Physical Sciences Research Council (EPSRC) grant (reference number: EP/M017915/1) for the CEMPS, University of Exeter, UK

Application of multi-objective Bayesian shape optimisation to a sharp-heeled Kaplan draft tube

The draft tube of a hydraulic turbine plays an important role for the efficiency and power characteristics of the overall system. The shape of the draft tube affects its performance, resulting in an increasing need for data-driven optimisation for its design. In this paper, shape optimisation of an elbow-type draft tube is undertaken, combining Computational Fluid Dynamics and a multi-objective Bayesian methodology. The chosen design objectives were to maximise pressure recovery, and minimise wall-frictional losses along the geometry. The design variables were chosen to explore potential new designs, using a series of subdivision-curves and splines on the inflow cone, outer-heel, and diffuser. The optimisation run was performed under part-load for the Kaplan turbine. The design with the lowest energy-loss identified on the Pareto-front was found to have a straight tapered diffuser, chamfered heel, and a convex inflow cone. Analysis of the performance quantities showed the typically used energy-loss factor and pressure recovery were highly correlated in cases of constant outflow cross-sections, and therefore unsuitable for use of multi-objective optimisation. Finally, a number of designs were tested over a range of discharges. From this it was found that reducing the heel size increased the efficiency over a wider operating range

Optimisation of a conceptual aircraft model using a genetic algorithm and 3D Computational Fluid Dynamics (CFD)

This is the author accepted manuscript. The final version is available from UKACM via the link in this recordAircraft design is fundamentally a multidisciplinary design activity which involves different models and tools for various aspects of the design. This paper uses a Multidisciplinary Design Optimisation (MDO) for design of a simplified commercial aircraft, aiming to optimise the objectives of cost, weight and drag. NSGA-II is used to optimise the weight and cost by changing the geometry to introduce lightweight airframe materials and composites with lower density. Reducing weight of the structure is one of the major ways to improve the performance of aircraft. Lighter, stronger material will allow a higher speed and greater range which may contribute to reducing operational costs. Drag reduction is also a major factor in aircraft design. Reduction of drag in an aircraft means that it can have a lower fuel consumption or travel at higher speed, both of which are beneficial to plane performance. A smart structural optimisation algorithm helps to optimise the cost, weight and drag, while drag is analysed based on CFD modelling results. The results are validated against some wind tunnel tests

Derivation of the adjoint drift flux equations for multiphase flow

This is the final version. Available on open access from MDPI via the DOI in this recordThe continuous adjoint approach is a technique for calculating the sensitivity of a flow to changes in input parameters, most commonly changes of geometry. Here we present for the first time the mathematical derivation of the adjoint system for multiphase flow modeled by the commonly used drift flux equations, together with the adjoint boundary conditions necessary to solve a generic multiphase flow problem. The objective function is defined for such a system, and specific examples derived for commonly used settling velocity formulations such as the Takacs and Dahl models. We also discuss the use of these equations for a complete optimisation process.Engineering and Physical Sciences Research Council (EPSRC)Innovate U

Prediction of flow around a sharp-nosed bridge pier: Influence of the Froude number and free surface variation on the flow field (article)

This is the final version. Available on open access from Taylor & Francis via the DOI in this recordThe dataset associated with this article is located in ORE at: https://doi.org/10.24378/exe.1503Author accepted manuscript replaced with published version by Caroline Huxtable on 2019-10-11This study investigates the influence of free surface variation on the velocity field using numerical simulations of flow around a sharp-nosed pier that is representative of a typical masonry bridge pier. This study evaluates the assumption that free surface effects are negligible at small Froude numbers by comparing the change in flow field predictions due to the use of a free surface model (i.e. multi-phase simulation with a Volume of Fluid (VOF) model in place of a rigid-lid approximation (i.e. single phase simulation). Results show that simulations using the VOF model are in better agreement with experimental data than those using the rigid-lid approximation. Importantly, results show that even though the change in free surface height near the pier is small comparative to the approach flow, it still has a significant effect on velocities in front of the pier and in the wake region, and that too at low Froude numbers.Engineering and Physical Sciences Research Council (EPSRC