An efficient computational framework for hydrofoil characterisation and tidal turbine design

Blade element momentum (BEM) modelling offers a computationally inexpensive means of analysing turbine performance. Lift and drag coefficient data-sets specific to the operating conditions of the turbine must be input into a BEM model. However, such data is not typically available over the wide range of Reynolds number (Re) and angle of attack (a) encountered by vertical axis turbines. This paper presents a computational fluid dynamics (CFD) approach, based on transitional flow turbulence modelling, to determine lift and drag coefficients for a symmetric hydrofoil. Results are validated against published experimental data for a wide range of a and Re. It is demonstrated that BEM models provide improved predictions of vertical axis turbine performance when CFD generated lift and drag coefficients are used as input, rather than coefficients generated by the widely used panel-method. The combined CFD-based BEM methodology achieves a similar level of accuracy to a full CFD turbine model while providing a significant reduction in computational cost. The modelling approach and hydrofoil data-set developed in this study can be directly utilised for the design and optimisation of next-generation non-straight bladed vertical axis turbine designs which operate over a wide range of a and Re.This research is funded by Science Foundation Ireland under Grant Number SFI/12/RC/2302 and also by Bernard McGuire and Bobby Willis of Bri Toinne Teoranta. The authors wish to acknowledge the DJEI/DES/SFI/HEA Irish Centre for High-End Computing (ICHEC) for the provision of computational facilities and support.peer-reviewed2020-11-1

An efficient computational framework for hydrofoil characterisation and tidal turbine design

Blade element momentum (BEM) modelling offers a computationally inexpensive means of analysing turbine performance. Lift and drag coefficient data-sets specific to the operating conditions of the turbine must be input into a BEM model. However, such data is not typically available over the wide range of Reynolds number (Re) and angle of attack (a) encountered by vertical axis turbines. This paper presents a computational fluid dynamics (CFD) approach, based on transitional flow turbulence modelling, to determine lift and drag coefficients for a symmetric hydrofoil. Results are validated against published experimental data for a wide range of a and Re. It is demonstrated that BEM models provide improved predictions of vertical axis turbine performance when CFD generated lift and drag coefficients are used as input, rather than coefficients generated by the widely used panel-method. The combined CFD-based BEM methodology achieves a similar level of accuracy to a full CFD turbine model while providing a significant reduction in computational cost. The modelling approach and hydrofoil data-set developed in this study can be directly utilised for the design and optimisation of next-generation non-straight bladed vertical axis turbine designs which operate over a wide range of a and Re.This research is funded by Science Foundation Ireland under Grant Number SFI/12/RC/2302 and also by Bernard McGuire and Bobby Willis of Bri Toinne Teoranta. The authors wish to acknowledge the DJEI/DES/SFI/HEA Irish Centre for High-End Computing (ICHEC) for the provision of computational facilities and support.2020-11-1

An efficient computational framework for hydrofoil characterisation and tidal turbine design

Blade element momentum (BEM) modelling offers a computationally inexpensive means of analysing turbine performance. Lift and drag coefficient data-sets specific to the operating conditions of the turbine must be input into a BEM model. However, such data is not typically available over the wide range of Reynolds number (Re) and angle of attack (a) encountered by vertical axis turbines. This paper presents a computational fluid dynamics (CFD) approach, based on transitional flow turbulence modelling, to determine lift and drag coefficients for a symmetric hydrofoil. Results are validated against published experimental data for a wide range of a and Re. It is demonstrated that BEM models provide improved predictions of vertical axis turbine performance when CFD generated lift and drag coefficients are used as input, rather than coefficients generated by the widely used panel-method. The combined CFD-based BEM methodology achieves a similar level of accuracy to a full CFD turbine model while providing a significant reduction in computational cost. The modelling approach and hydrofoil data-set developed in this study can be directly utilised for the design and optimisation of next-generation non-straight bladed vertical axis turbine designs which operate over a wide range of a and Re.This research is funded by Science Foundation Ireland under Grant Number SFI/12/RC/2302 and also by Bernard McGuire and Bobby Willis of Bri Toinne Teoranta. The authors wish to acknowledge the DJEI/DES/SFI/HEA Irish Centre for High-End Computing (ICHEC) for the provision of computational facilities and support.peer-reviewed2020-11-1

Analysis of the influence of the environment, stakeholder integration capability, absorptive capacity, and technological skills on organizational performance through corporate entrepreneurship

This research seeks to analyze how factors such as the environment, stakeholder integration capability, absorptive capacity, and technological skills influence corporate entrepreneurship, and the repercussions of corporate entrepreneurship for the organization’s results. The hypotheses are tested empirically using a sample of 160 European technology firms. A positive relationship is found between the factors of the environment and stakeholder integration capability, and corporate entrepreneurship. The uncertainty and complexity of the environment in which the organization operates and its relationship with stakeholders require the firm to be involved in constant updating, collaboration between parties, and innovation of processes, products, and system to maintain competitive advantage. Further, the capacity to absorb new knowledge and develop technological skills can generate new, advanced technological processes. These processes foster corporate entrepreneurship to detect opportunities on the market and transform them into additional advantage over competitors. Corporate entrepreneurship increases organizational performance, as it entrusts entrepreneurs with the task of utilizing potentially value-creating resources more effectively than competitors.Excellence Research Projects P08- SEJ-04057 from the Andalusian Regional GovernmentExcellence Research Projects P11-SEJ-7988 from the Andalusian Regional GovernmentProjects ECO2009-09241 from the Spanish Ministry of Innovation.Projects ECO2012-31780 from the Spanish Ministry of Innovation