Turbulent Scale Resolving Modelling of Rotating Stall in Low-Pressure Steam Turbines Operated Under Low Volume Flow Conditions

Abstract

Non-synchronous excitation under low volume operation is a major risk to the mechanical integrity of last stage moving blades (LSMBs) in low-pressure (LP) steam turbines. These vibrations are often induced by a rotating aerodynamic instability similar to rotating stall in compressors. Unsteady computational fluid dynamics (CFD) has been applied to simulate the rotating stall phenomenon in two model turbines. It is shown that the investigated flow field presents a challenge to conventional Reynolds-averaged Navier–Stokes equations simulations. The modelling has been enhanced by applying scale-resolving turbulence modelling, which can simulate large-scale turbulent fluctuations. With this type of simulation a qualitative and quantitative agreement between CFD and measurement for the unsteady and time averaged flow field has been achieved. The results of the numerical investigation allow for a detailed insight into the dynamic flow field and reveal information on the nature of the excitation mechanism. It is concluded that the CFD approach developed can be used to assess LSMB blade designs prior to model turbine tests to check whether they are subjected to vibration under LVF caused by rotating stall.

Numerical investigation on flow instabilities in low-pressure steam turbine last stage under different low-load conditions

“…Also, the induced dynamic stress level may have been underestimated in the previous design. These research results and conclusions are consistent with Megerle et al 20 Furthermore, thanks to the annulus monitoring settings, information about circumferential mode number over time can be obtained. Figure 11 illustrates time history of unsteady pressure circumferential mode number in the two turbulence models.…”

“…For this purpose, higher-quality but more costly turbulence modeling approaches must be used. 20 However, Shibukawa et al 21 came to a different conclusion that although there was a difference in pressure amplitude, compared with the test results, the quasi-steady RANS model could make good predictions of frequencies of flow unstable perturbations. Both studies only compared individual monitoring point and did not involve unsteady aerodynamic distribution.…”

Numerical Investigation of Potential Flow Induced Vibrations of Steam Turbine Last Stage Rotor at Low Load Operation - Part 2: Rotating Instabilities Detection

“…Temperature and pressure measurements highlight how the steam at L1 inlet is superheated during LVF conditions. This justifies the ideal gas assumption adopted in many investigations [18,19,20]. They also demonstrated how a flow coefficient of 0.17 is the transition point for the ventilation of the last stage.…”

“…A discrepancy in the fractional speed between numerical prediction and experiment was also reported in this work. In order to enhance the numerical accuracy, a scale-resolving turbulence modeling, Scale Adaptive Simulation (SAS) approach, has been used by Megerle et al [19] to simulate large-scale turbulent fluctuations. The comparison between URANS, SAS and experiments shows small differences between the numerical models in resolving the flow field and both fail to predict the axial velocity near the casing, most likely attributed to using a coarse mesh.…”

Numerical analysis of condensation effects on final-stage rotor-blade rows in low-pressure steam turbine

“…These oscillations, owing to stator-rotor flow interactions or suboptimal operating conditions, may cause otherwise unforeseen accidents. Low-flow operation (Filippenko et al, 2011) (Stanciu et al, 2013) (Tanuma et al, 2015) (Rzadkowski et al, 2016) and rotational instability (Zhang et al, 2011) (Qi et al, 2013) (Megerle et al, 2015) have already been investigated numerically and experimentally. A numerical study concluded that blowing steam jets into the final stage was effective for suppressing the large-scale vortex that can occur under low-load conditions (Haller et al, 2016).…”