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Energy Procedia 00 (2017) 000–000www.elsevier.com/locate/procedia

IV International Seminar on ORC Power Systems, ORC201713-15 September 2017, Milano, Italy

Preliminary verification of the open-source CFD solver SU2 forradial-inflow turbine applications

Joshua A. Keepa,∗, Salvatore Vitaleb, Matteo Pinib, Matteo Buriganab

aSchool of Mechanical & Mining EngineeringThe University of Queensland

St Lucia 4072, Australiab Propulsion & Power

Delft University of TechnologyKluyverweg 1, 2629 HS Delft, The Netherlands

Abstract

There is a need for reliable CFD tools for design and performance prediction of Organic Rankine Cycle turbines. The open-sourcesolver SU2 has gained recognition in the ORC community for the possibility to efficiently perform analysis and design of devicesoperating with organic flows. This paper presents a preliminary verification of the open-source tool SU2 for the simulation of or-ganic flows in radial inflow turbines. A comparison is performed against the well established commercial ANSYS CFX solver fortwo exemplary test-cases. Results show that the solvers predict quantitatively and qualitatively similar fluid-dynamic performanceand flow features.

c© 2017 The Authors. Published by Elsevier Ltd.Peer-review under responsibility of the scientific committee of the IV International Seminar on ORC Power Systems.

Keywords: ORC, SU2, Mixing-plane, Radial Inflow Turbine, CFD

1. Introduction

The interest in decentralized power generation (DPG), whereby electricity is produced by smaller power plants inthe same location as the demand, has recently increased. With respect to the traditional centralized power generationparadigm, DPG has shown advantages for reducing carbon-dioxide emissions. Firstly, it avoids network distributionlosses. Second, it promotes the exploitation of diverse renewable energy sources. Lastly, it allows cogeneration.

Among the various technologies that are used for DPG, ORC turbogenerators are arguably one of the mostpromising[1], particularly, for applications below 100kW. For this power capacity, recent work has outlined that, re-gardless of the cycle configuration, the use of a single stage radial inflow turbine (RIT) provides the best performance[2].

∗ Corresponding author. Tel.: +61 0490 400 157.E-mail address: j.keep@uq.edu.au

1876-6102 c© 2017 The Authors. Published by Elsevier Ltd.Peer-review under responsibility of the scientific committee of the IV International Seminar on ORC Power Systems.

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As documented, the fluid-dynamic design of a RIT is a challenging task[3], especially for ORC applications,whereby design practices and experimental information are much more limited. Reliable steady-state computationalfluid dynamic (CFD) simulations and optimization are therefore key tools to design high-efficient RITs for ORCapplications.

The open-source CFD platform SU2 has recently gained recognition within the ORC community [4–6]. Withrespect to other CFD tools, SU2 has been developed specifically for solving constrained shape optimization problemvia adjoint methods [7]. Recent effort has been devoted to the extension of the solver for turbomachinery calculationswith complex thermodynamic models [4,8]. A flux-conservative mixing-plane is now available to simulate multi-stageturbomachinery. Nonetheless, a verification of the implementation has not been performed.

This paper presents three-dimensional turbomachinery calculations obtained with SU2 on single-stage RITs. Toverify the SU2 results, a comparison is performed against the well established commercial ANSYS CFX[9] CFDtool for two applications. The first test-case features a radial inflow gas turbine for an auxiliary power unit (APU)application, for which experimental data is available. For the second test-case, the SU2 solver is benchmarked bysimulating a supersonic single-stage RIT for high-temperature ORC applications, currently under development at thePropulsion & Power Lab of TU Delft [10].

2. Methodology

Steady-state turbomachinery simulations are performed using the Reynolds-averaged Navier-Stokes (RANS) equa-tions closed with SST k-ω turbulence model of Menter [11]. Stator and rotor domains are coupled with a mixing-planeinterface[12], and the rotor solution is computed in a rotating reference frame. Second order discretization schemesare applied in both cases. For further details regarding the numerical algorithms implemented in the two CFD tools,the interested reader is referred to[4,7–9].

Geometry is represented as a single stator and rotor blade passage without diffuser or tip clearance. Hexahedralmeshes are generated in an automated manner using ANSYS TurboGrid. Near wall refinements are made usingautomated scaling for y+ based on estimated stage Reynolds number. Mesh statistics for the respective turbines aresummarised in Table. 1.

Table 1: Mesh statistics

Turbine Stator Nodes [x1000] Rotor Nodes [x1000] y+ [-]

APU 552 687 <1.0ORC 1000 500 stator <1.0 ; rotor <5.0

3. Results and Discussion

3.1. APU Turbine

A well documented example of a conventional RIT is the 100 kW APU turbine described in [13]. Nominal bound-ary conditions based on the test-rig conditions described in [13] are listed in Table 2. The inlet turbulence intensityand the inlet turbulent-laminar viscosity ratio are set to 5 % and 100 %, respectively.

To determine a suitable mesh size, a preliminary grid convergence study monitoring the total to static stage effi-ciency was performed. It was observed that there was no change in performance estimation for meshes of approxi-mately 1.2 million and 6 million nodes, thus the smaller mesh was selected for the comparison study.

The the two solvers are initially compared at the nominal conditions listed in Table 2. Results are summarised inTable 3. Solvers are further compared for Mach triangles in Fig. 1.

Further to quantitiative comparisons, qualitative comparisons are made for both Mach number and entropy inFig. 3 and 4 respectively. Fig. 3 shows close qualitative correlation of the predicted flow fields particularly for the

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Table 2: APU turbine boundary conditions.

Fluid EoS Shaft speed [RPM] Ptot,in [kPa] Ttot,in [K] Ps,out [kPa]

Air Ideal Gas (γ=1.4) 71700 413.6 477.6 66.71

Table 3: Performance summary and loss breakdown for APU turbine at nominal shaft speed.

Solver ηt,s Mass flow rate [kg/s] Stator KE [%] Stator Ptot [%] Rotor Ptot [%]

CFX 90.96 0.359 9.00 12.33 61.17SU2 89.95 0.357 10.60 15.25 68.0

(a) Stator outlet .

(b) Rotor outlet .

Fig. 1: Mach triangles for design speed, APU turbine.

Fig. 2: APU Turbine total to static efficiency at design pressure ratio for 80 %- 110 % nominal shaft speed estimated with CFX and SU2, and predicted withexperiments.

rotor. A key difference however appears in the stator outlet region where the solution obtained from SU2 shows amore pronounced wake. The same trend can be observed in the entropy contours in Fig.4, where it is shown thathigher entropy generation occurs in the stator wake. This leads to an overall higher entropy value at the rotor inlet forthe SU2 prediction. Although this is a purely qualitative comparison, the highlighted entropy difference may explainthe lower efficiency value predicted by SU2.

Next, the two solvers are compared with experimental data for total to static efficiency at off-design conditions. Foroff-design considerations the rotational speed is varied from 80% to 110% of the nominal value with pressure ratioset as the design value. Results are illustrated in Fig.2. Both solvers predict higher efficiencies through the operatingrange. Furthermore, the efficiency peak is estimated at lower rotational speed. One causal factor for the discrepancybetween numerical and experimental results is the tip-leakage flow, which is not modelled in numerical calculationsand generally causes an efficiency decay at on and off-design conditions. A further potential causal factor for thisdiscrepancy is the use of Cp evaluated at room temperature for the gas model in the numerical calculations.

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(a) CFX . (b) SU2 .

Fig. 3: Contour plots for relative Mach number at design speed, APU turbine.

(a) CFX . (b) SU2 .

Fig. 4: Contour plots for static entropy normalised by CFX inlet values, APU turbine.

Note that when comparing experimental and numerical observations for global performance parameters it is crucialto know the location of pressure and temperature measurements [14]. For the present APU turbine comparison,the locations of total and static pressure measurements downstream of the rotor were not disclosed [13], howeverappropriate values were selected from a prior numerical study [14]. Further to uncertainty in measurement locations,the geometry is not fully replicated, namely the interface between stator and rotor which includes a scalloped backface in the original geometry as shown in images presented by Jones [13]. The impact of such simplifications shouldbe investigated if RANS simulations are to be matched to experimental data.

3.2. ORC Turbine

A single-stage RIT for high-temperature ORC applications with 12 kW shaft power has been designed for theORCHID facility [10] at TU Delft. A preliminary design of this turbine is investigated as the present test case for anORC turbine. The full geometry of the turbine is described in a companion paper.

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Boundary conditions are listed in Table 4. As with the previous test case, the inlet turbulence intensity and the inletturbulent-laminar viscosity ratio are set to 5 % and 100 % respectively. After performing a mesh sensitivity study, amesh of 1.5 million nodes was selected. Fluid properties are modelled using the Peng-Robinson equation of state forboth solvers, with parameters for the equation obtained from REFPROP [17]. The Peng-Robinson implementation forSU2 is detailed in a prior publication [4].

Table 4: ORCHID turbine boundary conditions.

Fluid EoS Shaft speed [RPM] Ptot,in [kPa] Ttot,in [K] Ps,out [kPa]

Siloxane MM Peng-Robinson 98119 1809.3 573.16 44.3

Table 5 shows that the predicted mass-flow rate, inter-stage static pressure (Pint) and absolute Mach number(Mstat,out) are within a few percent for the two solvers. Further to bulk performance, pressure distribution on thestator blades is investigated in Fig. 5. A key difference in the pressure distributions, shown in Fig. 5, is the suctionside of the blade trailing edge where CFX predicts shocks.

Table 5: Summary of ORCHID results.

Solver m [kg/s] Pint [kPa] Mstat,out [-]

CFX 0.137 150.36 2.04SU2 0.132 148.37 2.04∆ 3.6% 1.3% -

Fig. 5: Stator blade pressure distributions, ORC turbine.

As can be observed in Fig. 6, both solvers qualitatively predict similar Mach number distribution. The span-wise Mach number distribution correlates qualitatively well along the expansion. As noted for the blade pressure

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(a) CFX . (b) SU2 .

Fig. 6: Contour plots for relative Mach number, ORC turbine.

(a) CFX . (b) SU2 .

Fig. 7: Contour plots for static entropy normalised by CFX inlet values, ORC turbine.

distribution, a key difference between solvers in Fig. 6 is the shocks predicted by CFX. This difference can likely beattributed to the boundary condition implementations of the respective solvers. The same considerations for Machnumber hold for the entropy distribution, depicted in Fig. 7.

4. Conclusion

This work presents preliminary verification of the SU2 open-source solver against the well-established ANSYSCFX for the simulation of air-based and ORC RIT’s. For the first test case, the APU turbine, the two solvers showquantitative performance parameters within a few percent of each other at design and off-design conditions. For theORC turbine, a good qualitative and quantitative match in performance and 3D flow features is found for design

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conditions. The close agreement between the solvers suggests that SU2 is a capable tool for the analysis and designof such turbines.

Future work should focus on validating SU2 with more accurate experimental data. Such data should prescribeexact locations of pressure and temperature measurements. Ideally such data would also contain rotor exit traces ofstatic and total pressure.

Acknowledgements

This research was performed as part of the Australian SolarThermal Research Initiative (ASTRI), a project sup-ported by the Australian Government. The authors greatly acknowledge the Dutch Technology Foundation STW andthe partner Robert Bosch GmbH (grant number 13385) and DANA Holding Corporation (grant number 12171) forfunding this work.

Joshua Keep also wishes to personally acknowledge the support of the Australian Government Research TrainingProgram Scholarship as well as the UQ Graduate School International Travel Award (GSITA).

Special thanks to Mostafa Odabaee for supplying the meshes used as the basis for the APU turbine study, and toVicente Molla for his contribution in the development of the mixing-plane interface in SU2.

References

[1] Colonna, P., Casati, E., Trapp, C., Mathijssen, T., Larjola, J., Turunen-Saaresti, T., et al. Organic rankine cycle power systems: From theconcept to current technology, applications, and an outlook to the future. ASME J Eng Gas Turbines Power 2015;137(10).

[2] Bahamonde, S., Pini, M., De Servi, C., Rubino, A., Colonna, P.. Method for the preliminary fluid dynamic design of high-temperaturemini-orc turbines. ASME J Eng Gas Turbines Power 2017;.

[3] Whitfield, A., Baines, N.C.. Design of radial turbomachines. New York, NY (USA); John Wiley and Sons Inc.; 1990.[4] Vitale, S., Gori, G., Pini, M., Guardone, A., Economon, T.D., Palacios, F., et al. Extension of the su2 open source cfd code to the simulation

of turbulent flows of fuids modelled with complex thermophysical laws. In: 22nd AIAA Computational Fluid Dynamics Conference. 2015, p.2760.

[5] Pini, M., Vitale, S., Colonna, P., Gori, G., Guardone, A., Economon, T., et al. Su2: the open-source software for non-ideal compressibleflows. IOP Journal of Physics: Conference Series NICFD 2016 for propulsion and power, Varenna, Italy, () 20-21 October 2016 2016;.

[6] Gori, G., Molesini, P., Persico, G., Guardone, A.. Non-ideal compressible-fluid dynamics on fast-response pressure probes for unsteadyflow measurements in turbomachinery. IOP Journal of Physics: Conference Series NICFD 2016 for propulsion and power, Varenna, Italy, ()20-21 October 2016 2016;.

[7] Economon, T.D., Palacios, F., Copeland, S.R., Lukaczyk, T.W., Alonso, J.J.. Su2: An open-source suite for multiphysics simulation anddesign. AIAA Journal 2015;54(3):828–846.

[8] Vitale, S., Albring, T., Pini, M., Gauger, N., Colonna, P.. Fully turbulent discrete adjoint solver for non-ideal compressible flow applications.ready for submission to the GPPS Journal 2017;.

[9] ANSYS, I.. Ansys cfx-pre user’s guide. Release 15.0; 2013,.[10] Head, A.J., De Servi, C., Casati, E., Pini, M., Colonna, P.. Preliminary design of the orchid: A facility for studying non-ideal compressible

fluid dynamics and testing orc expanders. In: ASME Turbo Expo 2016: Turbomachinery Technical Conference and Exposition. AmericanSociety of Mechanical Engineers; 2016, p. V003T25A001–V003T25A001.

[11] Menter, F.R.. Two-equation eddy-viscosity turbulence models for engineering applications. AIAA journal 1994;32(8):1598–1605.[12] Saxer, A.P., Giles, M.B.. Quasi-three-dimensional nonreflecting boundary conditions for euler equations calculations. Journal of Propulsion

and Power 1993;9(2):263–271.[13] Jones, A.. Design and test of a small, high pressure ratio radial turbine. Journal of Turbomachinery 1996;118:363.[14] Sauret, E.. Open design of high pressure ratio radial-inflow turbine for academic validation. In: ASME 2012 International Mechanical

Engineering Congress and Exposition. American Society of Mechanical Engineers; 2012, p. 3183–3197.[15] Zangeneh-Kazemi, M., Dawes, W., Hawthorne, W.. Three dimensional flow in radial-inflow turbines. In: ASME 1988 International Gas

Turbine and Aeroengine Congress and Exposition. American Society of Mechanical Engineers; 1988, p. V001T01A046–V001T01A046.[16] Bosdas, I., Mansour, M., Kalfas, A.I., Abhari, R.S.. Experimental methods for performance and reliability of steam and gas turbines. In:

Proceedings of the 1st Global Power and Propulsion Forum GPPF 2017 Jan 16-18, 2017, Zurich, Switzerland. GPPF-2017-88; 2017,.[17] Lemmon, E., Huber, M., McLinden, M.. Refprop: Reference fluid thermodynamic and transport properties. NIST standard reference

database 2007;23(8.0).