High-Performance Simulation of Turbulent Pump Flow

Principal Investigator:
Romuald Skoda

Lehrstuhl für Hydraulische Strömungsmaschinen, Ruhr-Universität Bochum

Local Project ID:
chbo46, chbo48

HPC Platform used:

Date published:

Pumps are used in many technical, industrial and household applications for conveying any kind of fluids, including multi-phase flow. Due to increasing requirements on a flexible operation, pumps are often run at off-design operation, where for example by legislature, demands on efficiency are continuously increasing. The optimization of high-efficiency pumps can only be achieved by modern computational fluid dynamics methods (CFD) in combination with accurate turbulence models. While for the design point operation of centrifugal pumps, where an essentially steady flow field is present and statistical turbulence models yield an appropriate prediction of the characteristics, the flow field gets increasingly unsteady towards off-design operation.

Special designs as e.g. sewage pumps are characterized by a single-blade impeller and show significantly unsteady characteristics even in the design point [1]. The same holds for positive displacement pumps where due to the periodic piston oscillation, the flow field is inherently unsteady and turbulent.

For such highly-unsteady and turbulent flow fields, statistical turbulence models tend to fail. On the other hand, Large-Eddy Simulation (LES) models, in which the large-vortex part of the turbulent spectrum is directly resolved, show a much better flow prediction. However, LES requires the direct resolution of the major part of the turbulent kinetic energy and, for the high Reynolds numbers encountered in pump flows, the spatial resolution and thus computational effort are tremendously high, even on modern HPC systems. Therefore, an assessment of scale-adaptive turbulence simulation (SAS) models is provided, which recover a statistical flow solution in regions of low unsteadiness and – like Large-Eddy Simulation – resolve a part of the turbulent spectrum down to the available grid resolution for highly unsteady flow regions. An in-depth analysis of the SAS model and a comparison with a LES reference solution on simplified benchmark test cases on separated flow [2] reveals that the SAS provides a significantly improved flow solution compared to an under-resolved LES.

An application of the SAS on a centrifugal pump flow and comparison to measurement data [2,3,4,5] confirms its beneficial properties for high Reynolds number pump flow. Time and space-resolved measurement data is available in the highly unsteady impeller–stator flow interaction region for validation. In Figure 1, the research pump configuration is demonstrated by its meridional impeller view (Figure 1 a), an axial view of the volute casing with the circumferential coordinate ε  (Figure 1 b) and the time coordinate x/t , which corresponds to the time range when one impeller blade spacing passes the measurement position (Figure 1 c).

The ensemble-averaged mean flow angle α  and turbulence intensity TI  is illustrated in Figure 2 in the measurement plane for part-load operation. While α  is well predicted even with a conventional statistical turbulence model (STM), the TI  is significantly overpredicted, in particular for the circumferential position ε= 0°  close to the tongue. By the SAS on the other hand, even the TI  is well predicted for any circumferential location. This example flow configuration demonstrates that by the SAS, turbulence-scale resolving capabilities are retained even by the complex high Reynolds number flow, and the turbulence fluctuations in terms of the TI  are accurately predicted, which has also been demonstrated by different rotating machinery applications as e.g. pump mixers [6].

Summarizing, the application of scale adaptive turbulence models opens the opportunity for an optimization of the pump design and the development of high-efficiency pumps even at off-design operation.

Publications as an outcome of the HPC projects

[1] Pesch, A., Melzer, S., Schepeler, S., Kalkkuhl, T., & Skoda, R. (2020). Pressure and Flow Rate Fluctuations in Single- and Two-Blade Pumps. ASME. J. Fluids Eng. 143(1): 011203-011203-12. DOI: 10.1115/1.4048142.

[2] Hundshagen, M., Casimir, N., Pesch, A., Falsafi, S. & Skoda, R. (2020). Assessment of scale-adaptive turbulence models for volute-type centrifugal pumps at part load operation. International Journal of Heat and Fluid Flow. 85, 108621. DOI: 10.1016/j.ijheatfluidflow.2020.108621.

[3] Casimir, N., Xiangyuan, Z., Ludwig, G. & Skoda, R. (2019). Assessment of statistical turbulence models for unsteady flow at part and overload operation in centrifugal pumps. Proc. 13th European Conference on Turbomachinery Fluid Dynamics & Thermodynamics (ETC13), Paper-ID: ETC2019-047, Lausanne, Switzerland, April 8-12, 2019. DOI: 10.29008/ETC2019-047.

[4] Casimir, N., Zhu, X., Hundshagen, M., Ludwig, G. & Skoda, R. (2020). Numerical Study of Rotor–Stator Interaction of a Centrifugal Pump at Part Load With Special Emphasis on Unsteady Blade Load. ASME. J. Fluids Eng. 2020, 142(8): 081203-081203-14. DOI: 10.1115/1.4046622.

[5] Hundshagen, M., Casimir, N., Pesch, A. & Skoda, R. (2020). High-Performance Flow Simulation and Scale-Adaptive Turbulence Modelling of Centrifugal Pumps. Proc. NIC Symposium 2020, Jülich, Germany, 27 Feb 2020 - 28 Feb 2020. Forschungszentrum Jülich GmbH Zentralbibliothek, Verlag, Publication Series of the John von Neumann Institute for Computing (NIC) NIC Series 50, 367 - 378.

[6] Rave, K., Lehmenkühler, M., Wirz, D., Bart, H.-J., Skoda, R. (2021). 3D flow simulation of a baffled stirred tank for an assessment of geometry simplifications and a scale-adaptive turbulence model. Chemical Engineering Science. 231, 116262. DOI: 10.1016/j.ces.2020.116262.

Research Team

M. Sc. Nicolas Casimir, M. Sc. Pascal Munsch, Prof. Dr.-Ing. Romuald Skoda (PI)
all: Lehrstuhl für Hydraulische Strömungsmaschinen, Ruhr-Universität Bochum (RUB)

Scientific Contact

Prof. Dr.-Ing. Romuald Skoda
Ruhr-Universität Bochum
Lehrstuhl für Hydraulische Strömungsmaschinen
Universitätsstraße 150, D-44801 Bochum (Germany)
e-mail:  Romuald.Skoda [@]

Local project IDs: chbo 46, chbo48

April 2021

Tags: JSC Ruhr-University Bochum LES CFD