Other affiliations: Saga University, Sultan Qaboos University, Okinawa Institute of Science and Technology
Bio: Paresh Halder is an academic researcher from Indian Institute of Technology Madras. The author has contributed to research in topics: Turbine & Wells turbine. The author has an hindex of 9, co-authored 25 publications receiving 279 citations. Previous affiliations of Paresh Halder include Saga University & Sultan Qaboos University.
TL;DR: In this paper, a new tip grooving scheme is introduced and the performance is compared for different tip groove depths and tip clearance zones of a Wells turbine, which is used in a bi-directional flow Wells turbine of an ocean wave energy device.
Abstract: Delaying a stall improves the performance of any turbomachinery system. TC (tip clearance), which is used in a bi-directional flow Wells turbine of an ocean wave energy device, changes the flow pattern on the turbine blade suction surface, while changing or modifying the TC zone can help obtaining a delayed stall. In the present work, a new tip grooving scheme is introduced and the performance is compared for different tip groove depths and TCs of a Wells turbine. The performance is defined in terms of wider operating range or stall delay, power production and efficiency. The problem was solved by a numerical analysis technique. A multi-block meshing scheme was employed to generate structured and hexahedral elements in the computational domain and the flow was solved in ANSYS CFX® v14.5 by solving Reynolds-averaged Navier Stokes equations. It was found that the grooves improve the turbine operating range and power production as compared to those of the turbine without a groove. The groove depth of 3% of the chord length produced highest power and widest operating range. Using the circumferential groove, 26% increase in turbine power output for a particular operating point is achieved.
TL;DR: In this article, a numerical work relying on design optimization is reported to show the dependency of power extraction capability to the operating range of the turbine, and a surrogate approximation model was constructed to find an optimal design.
Abstract: The oscillating water column (OWC), which is a wave energy extracting device, uses a bidirectional flow turbine to generate power. The device performance largely depends on the efficiency, torque and operating range of the turbine. The turbine with a larger operating range produces power during a wider wave height and period, both properties changing throughout the year or during each wave cycle. In this article, a numerical work relying on design optimization is reported to show the dependency of power extraction capability to the operating range of the turbine. Reynolds-averaged Navier-Stokes (RANS) equations were solved and a surrogate approximation model was constructed to find an optimal design. Design variables were blade sweep angles at the tip and mid sections. The objective function, to be maximized, is the torque coefficient. The optimal design delayed the flow separation and the peak efficiency dropped by 3.1%. At the same time, the relative power output and the relative stall point were increased by 29% and 18% compared to the reference case, respectively.
TL;DR: In this article, a multi-objective optimization of blade sweep for a Wells turbine was performed by solving 3D RANS equations based on k-w SST turbulence model.
Abstract: The present work focuses multi-objective optimization of blade sweep for a Wells turbine. The blade-sweep parameters at the mid and the tip sections are selected as design variables. The peak-torque coefficient and the corresponding efficiency are the objective functions, which are maximized. The numerical analysis has been carried out by solving 3D RANS equations based on k-w SST turbulence model. Nine design points are selected within a design space and the simulations are run. Based on the computational results, surrogate-based weighted average models are constructed and the population based multi-objective evolutionary algorithm gave Pareto optimal solutions. The peak-torque coefficient and the corresponding efficiency are enhanced, and the results are analysed using CFD simulations. Two extreme designs in the Pareto solutions show that the peak-torque-coefficient is increased by 28.28% and the corresponding efficiency is decreased by 13.5%. A detailed flow analysis shows the separation phenomena change the turbine performance.
TL;DR: In this paper, an oscillating water column wave energy harvesting system uses pneumatic power to run a turbine and generate power, both reaction (mainly Wells turbine) and impulse type turbines are tested in oscilla.
Abstract: Oscillating water column wave energy harvesting system uses pneumatic power to run a turbine and generate power. Both reaction (mainly Wells turbine) and impulse type turbines are tested in oscilla...
TL;DR: In this paper, the performance of axial turbine is investigated through numerical analysis and optimization, and the results concluded that the reference blade with GC performs better in terms of torque coefficient and efficiency if the flow is attached.
Abstract: Modified Wells turbines allow an efficient use of the power contained in the ocean and sea waves. The present study introduces the performance of an axial turbine which called Wells turbine. This turbine is used in oscillating water column (OWC) wave energy conversion devices. This type of axial turbine is investigated through numerical analysis and optimization. Unsteady 3D Reynolds-averaged Navier-Stokes equations were solved with k-ω SST turbulence closer model. A comparative study of optimized and conventional blades with steady and unsteady flows has been presented. For shape optimization, blade profile-thickness and sweep modifications along with and without grooved-casing, (GC) designs are considered. The results concluded that the reference blade with GC performs better in terms of torque coefficient and efficiency if the flow is attached. The unsteady flow gives a stream-wise circulation near the blade suction surface. The groove changes the tip vortex and helps to suppress the flow separation. In addition, the effect of blade sweep, profile variation and groove depth on the hysteresis behavior of the Wells turbine has been investigated in this work.
TL;DR: In this article, the authors provide an updated and a comprehensive account of the state of the art research on Wells turbine and draw a roadmap for the contemporary challenges which may hinder future reliance on such systems in the renewable energy sector.
Abstract: In the past twenty years, the use of wave energy systems has significantly increased, generally depending on the oscillating water column (OWC) concept. Wells turbine is one of the most efficient OWC technologies. This article provides an updated and a comprehensive account of the state of the art research on Wells turbine. Hence, it draws a roadmap for the contemporary challenges which may hinder future reliance on such systems in the renewable energy sector. In particular, the article is concerned with the research directions and methodologies which aim at enhancing the performance and efficiency of Wells turbine. The article also provides a thorough discussion of the use of computational fluid dynamics (CFD) for performance modeling and design optimization of Wells turbine. It is found that a numerical model using the CFD code can be employed successfully to calculate the performance characteristics of W-T as well as other experimental and analytical methods. The increase of research papers about CFD, especially in the last five years, indicates that there is a trend that considerably depends on the CFD method.
TL;DR: In this paper, a modular RANS turbulence modelling strategy is proposed and the need for improved measurements with well defined boundary conditions that have Reynolds stress and even spectral information, at Reynolds and Mach numbers that connect with typically powerful turbomachinery systems is identified.
Abstract: General forms of turbulence models are outlined along with their defects and palliatives for these in relation to turbomachinery. The turbulence modelling hierarchy available in turbomachinery is set out, moving from RANS (Reynolds Averaged Navier–Stokes) to the eddy resolving DNS (Direct Numerical Simulation) approach. New vistas for techniques are discussed. A modular RANS turbulence modelling strategy is outlined. Simple scaling arguments for Unsteady RANS (URANS) spectral gaps in turbomachinery are presented and the presence of such gaps shown not always to be guaranteed. The power of computers continues to steadily rise. Hence, the use of eddy resolving simulations in their various forms is expected to increase and also their use for the refinement of lower order models. Current examples for the latter are given. The use of eddy resolving simulations in the coupled and sometimes multi-physics turbomachinery environment is considered. The need for improved measurements with well defined boundary conditions that have Reynolds stress and even spectral information, at Reynolds and Mach numbers that connect with typically powerful turbomachinery systems is identified. This is necessary to refine both RANS and eddy resolving strategies. Most available ‘Best Practices’ are centred on RANS. Hence, new guidance needs to be developed for eddy resolving methods. Expert systems, based around flow taxonomies, that can assist with for example making initial grid estimates and guiding aerodynamicists through the eddy resolving simulation process are discussed. The need for more turbomachinery relevant strategies for generating turbulence inflow is identified.
TL;DR: This paper reviews all different approaches to wave energy converter optimisation, with a view to distilling the main findings and best practices; it then formulates recommendations based on these.
Abstract: Reducing the cost of energy of wave energy converters is key for the advancement of the technology. The costs associated with the device structure show the highest potential to achieve this reduction. For this reason, many hull geometry optimisation studies have been performed over the last 20 years, with the aim of finding improved hull shapes, that maximise the power generation and minimise the costs. These studies have been performed for different types of devices, applying a number of optimisation algorithms and representing power generation and costs with various strategies. The definition of the optimisation problem and the use of the most suitable strategies is key for a successful optimisation process, which will provide meaningful results and support device design at early development stages. This paper reviews all these different approaches, with a view to distilling the main findings and best practices; it then formulates recommendations based on these. The work is intended to serve as reference for any technology developer wishing to perform wave energy converter optimisation and for any funding body wanting to assess different device designs.
TL;DR: STML can be used along with the HOA, which reduces the computational time required for energy system optimization by 84%.
Abstract: This study evaluates the potential of supervised and transfer learning techniques to assist energy system optimization. A surrogate model is developed with the support of a supervised learning technique (by using artificial neural network) in order to bypass computationally intensive Actual Engineering Model (AEM). Eight different neural network architectures are considered in the process of developing the surrogate model. Subsequently, a hybrid optimization algorithm (HOA) is developed combining Surrogate and AEM in order to speed up the optimization process while maintaining the accuracy. Pareto optimization is conducted considering Net Present Value and Grid Integration level as the objective functions. Transfer learning is used to adapt the surrogate model (trained using supervised learning technique) for different scenarios where solar energy potential, wind speed and energy demand are notably different. Results reveal that the surrogate model can reach to Pareto solutions with a higher accuracy when grid interactions are above 10% (with reasonable differences in the decision space variables). HOA can reach to Pareto solutions (similar to the solutions obtained using AEM) around 17 times faster than AEM. The Surrogate Models developed using Transfer Learning (SMTL) shows a similar capability. SMTL combined with the optimization algorithm can predict Pareto fronts efficiently even when there are significant changes in the initial conditions. Therefore, STML can be used along with the HOA, which reduces the computational time required for energy system optimization by 84%. Such a significant reduction in computational time enables the approach to be used for energy system optimization at regional or national scale.
TL;DR: In this paper, the effects of blade thickness on the performance of a Wells turbine are discussed based on aerodynamic and entropy generation analysis, and the results reveal that entropy generation seems to give an advantageous effect of reducing the separation at the tip section of the VTB in deep stall condition.
Abstract: The inherent disadvantages, due to the narrow operational range and low efficiency of Wells turbine, are investigated based on aerodynamic and entropy generation analysis. To overcome these issues, the effects of blade thickness on the performance of a Wells turbine are discussed. In this study, two kinds of blade profiles are being investigated: the original design, a constant thickness blade (CTB) and the proposed design, a variable thickness blade (VTB). The computation is performed by solving the 3D steady incompressible Reynolds-averaged Navier-Stokes (RANS) equations with shear stress transport (SST) turbulence model in a non-inertial reference frame rotating with the turbine. The results show the interaction between tip leakage vortex (TLV) and suction surface of the blade is substantially reduced by using the VTB. The results reveal that entropy generation seems to give an advantageous effect of reducing the separation at the tip section of the VTB in the deep stall condition. At most, a 63.37% increase in torque coefficient and 72.8% increase in efficiency are achieved are achieved by the VTB in the deep stall condition. Moreover, a detail entropy generation and aerodynamic analysis show the main sources of losses are due to blade profile and secondary flows.