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Efficiency Optimization of a Water Turbine via CFD Simulation on the Cloud

Checking and assessing the aerodynamic or hydrodynamic performance of newly designed geometric parts by using Computational Fluid Dynamics (CFD) is a common practice in large(r) industry. The end user Stellba of this case study is a Germany-based SME active in hydropower plant maintenance, repair and overhaul, engineering and manufacturing one-of-a-kind products for the green energy sector with the goal to optimize energy efficiency. Every turbine they engineer and manufacture is different and tailored to the needs of a given specific power plant, which results in an extremely high development effort making CFD simulations a major component of Stellba’s engineering tool set.

Using 'cloudified' CFD software of NUMECA (a Belgian independent software vendor SME) and Product Lifecycle Management (PLM) software by JOTNE (a Norwegian SME), speeds up and simplifies the CFD process, thus reducing the development costs and increasing the competitiveness of Stellba by raising the product quality and reducing the development times (better time-to-market). By increasing the accuracy of the CFD, Stellba can reduce the security margin for their efficiency guarantees, which increases the competitiveness in the market. If the efficiency of a 40 MW turbine can be increased by 2% with the help of efficient and sophisticated simulation, the turbine owner will gain more electricity output from his water plant worth 200.000€ per year.

The evaluation of the hydrodynamic performance, e.g. the prediction of the increase in energy efficiency of a newly designed or repaired turbine blade, involves many CFD simulations. The full characterisation (hill chart) of a complex hydraulic turbine may require several hundreds of such simulations, where each simulation can take several hours to several days, depending on the available computing resources. Such a complete calculation is time and cost prohibitive when using traditional desktop machines. Thus, so far the turbine characteristics are only calculated (simulated) partially. By leveraging cloud-based HPC power in conjunction with an automated process chain, this case study aims at enabling Stellba to calculate the full turbine characteristics in an economic manner. The ambition is to perform 10 times more calculations in a third of the time currently being used for just a sub-set of the problem, resulting in an overall performance benefit of a factor of 30.

For NUMECA, the much higher accessibility of the cloud-based CFD solution, from virtually anywhere, will largely enhance the end-user experience in evaluating and using CFD solutions in design processes. Consequently it is expected that the number of SMEs using CFD will increase largely in the short and medium term, resulting in new customers for NUMECA. Due to this increase 1-2 new jobs will be created in the short term.

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