2021
DOI: 10.1016/j.ast.2021.106623
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Using a CFD analysis of the flow capacity in a twin-entry turbine to develop a simplified physics-based model

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Cited by 12 publications
(24 citation statements)
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“…The model proposed studies twin-entry turbines as two separated single-entry turbines. This hypothesis is based on the results obtained in Galindo et al 19…”
Section: Hypotheses To Validatementioning
confidence: 95%
See 2 more Smart Citations
“…The model proposed studies twin-entry turbines as two separated single-entry turbines. This hypothesis is based on the results obtained in Galindo et al 19…”
Section: Hypotheses To Validatementioning
confidence: 95%
“…They help to extrapolate and predict twin-entry turbines performance. The authors of this work are also developing a one-dimensional loss-based model described in Galindo et al 19,20 It takes into account the losses due to the momentum exchange between flow branches. These losses produce a strong effect on the performance prediction in unequal admission conditions.…”
Section: Introductionmentioning
confidence: 99%
See 1 more Smart Citation
“…These variable geometry nozzles in the stator help to extend the operating range of the turbine; meanwhile, the matching with the compressor side can be achieved by the use of a ported shroud [21]. Uniform distribution over the 360 degrees of the radial stator is important to then adapt the flow at the rotor inlet, a matter of interest in [22], where they tested flow behavior for twin-entry turbines as two separated single VGT volutes. Therefore, while some authors focus on a volute casing optimization, as in [23], the stator and its vanes must be designed according to an aerodynamic geometry that has the least possible amount of energy losses [24][25][26].…”
Section: Introductionmentioning
confidence: 99%
“…where a substantial deviation between the mixed flow turbine performance under pulsating flow at different frequencies and that at steady flow conditions was reported. Recently Galindo et al [21] employed 3D CFD modelling capability to analyse the flow behaviours of twin-entry turbines as well as improving the predictability of 1D twin-entry turbine model.…”
Section: Introductionmentioning
confidence: 99%