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  1. cordis.europa.eu

    The key achievements corresponding to the four objectives are listed below. 1. Efficient use of HPC resources in the simulation of flow around a wind turbine across all relevant operating conditions: 1.1 Novel algorithms have been developed and implemented for accurate simulation for flow over turbines as well as Fluid-Structure interaction (FSI) algorithm to capture the highly non-linear ...
  2. cordis.europa.eu

    The HPCWE consortium consists of 13 partners representing the top academic institutes, HPC centres and industries in Europe and Brazil. By exploring collaborations between Europe and Brazil, this consortium will develop novel algorithms, implement them in state-of-the-art codes and test the codes in academic and industrial cases to benefit the ...
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  4. The High-Performance Computing for Wind Energy (HPCWE) project. Guidelines for using the actuator line model in a high-fidelity simulation. ... Our final results discuss the development of uncertainty quantification (UQ) methods to determine how likely a certain outcome is if particular aspects are not known when processing complex data at high ...
  5. The HPCWE consortium consists of 13 partners representing the top academic institutes, HPC centres and industries in Europe and Brazil. By exploring this collaboration, this consortium will develop novel algorithms, implement them in state-of-the-art codes and test the codes in academic and industrial cases to benefit the wind energy industry ...
  6. The HPCWE consortium consists of 11 partners representing the top academic institutes, HPC centres and industries in Europe and Brazil. By exploring this collaboration, this consortium will develop novel algorithms, implement them in state-of-the-art codes and test the codes in academic and industrial cases to benefit the wind energy industry and research in both Europe and Brazil.
  7. webarchiv.hlrs.de

    • Pre-HPCWE - tendency averaging was done as post-processing - every 5 sec (same as the model time-step) tendencies written out by WRF • In HPCWE the method of Chen et al (2020) has been implemented - tendency averaging performed during execution ("inline" averaging)
  8. The HPCWE consortium consists of 13 partners representing the top academic institutes, HPC centres and industries in Europe and Brazil. By exploring this collaboration, this consortium will develop novel algorithms, implement them in state-of-the-art codes and test the codes in academic and industrial cases to benefit the wind energy industry ...
  9. cordis.europa.eu

    Addressing this challenge are initiatives like the EU-funded HPCWE project, which aims to use high-performance computing (HPC) to improve the efficiency of wind farms and, as a result, increase the uptake of wind energy. "Our goal was to use the latest in HPC to better understand the physics of atmospheric flow affecting the behaviour and ...
  10. HPCWE main goal is to establish an EU-Brazil strategic partnership in wind energy applications. Start date: June 2019, 24 months duration EU contribution: approx. 2 Million Euros, match funding from Brazilian research council The role of HPCWE is to coordinate the action of universities, companies and consultancies with

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