Figure 2 - uploaded by Jonathan Fahlbeck
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Flow chart of iteration procedure to obtain the friction loss coefficient f . Here Tol is a tolerance, Nitr is the maximum number of iterations for the Colebrook Eq. (10), and fDiff is the maximum allowed difference between the Haaland Eq. (11) and Colebrook Eq. (10), index i and o are for initial and old, respectively.
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![Figure 3. Illustration of the experimental test rig [6]. The flow is...](profile/Jonathan-Fahlbeck/publication/357991477/figure/fig2/AS:1114583246876672@1642748762454/Illustration-of-the-experimental-test-rig-6-The-flow-is-driven-by-gravity-from-the_Q320.jpg)
Despite the increase in computational power of HPC clusters, it is in most cases not possible to include the entire hydraulic system when doing detailed numerical studies of the flow in one of the components in the system. The numerical models are still most often constrained to a small part of the system and the boundary conditions may in many cas...
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Citations
... The flow rate is thus part of the solution. The inlet and outlet boundary conditions for pressure is handled with the novel headLossPressure boundary condition developed by Fahlbeck et al. [21]. This special boundary condition allows the user to specify the head of the system and it also considers head losses up-and downstream of the computational domain. ...
A larger part of the electricity is today from intermittent renewable sources of energy. However, the energy production from such sources varies in time. Energy storage is one solution to compensate for this variation. Today pumped hydro storage (PHS) is the most common form of energy storage. Usually, it requires a large head, which limits where it can be built. In the EU project ALPHEUS, PHS technologies for low- to ultra-low heads are explored. One of the concepts is a contra-rotating pump-turbine (CRPT). The behaviour of this design at time-varying load conditions is today scarce. In the present work, the impact of the startup time for a CRPT is analysed through computational fluid dynamics (CFD) simulations. The analysis includes a comparison between a coarse and a fine CFD model. The coarse model produces acceptable results and is 50 times cheaper, this model is thus used to assess the startup time. It is found that longer startup times generate lesser loads and peak values. A startup time of 10 s may be a sufficient alternative as the peak loads are heavily reduced compared to faster startups. Furthermore, there is not much difference between a startup time of 20–30 s.
