Computational Assessment of Inlet Turbulence on Boundary Layer Development and Momentum/Thermal Wakes for High Pressure Turbine Nozzle and Blade

Kopriva, James; Laskowski, Gregory M.; Sheikhi, M. Reza H.

doi:10.1115/imece2014-38620

Cited by 16 publications

(15 citation statements)

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“…Increasing the inlet turbulence to 20% results in an increased spreading of the wake and mixing losses growing further into the core flow. Kopriva et al (2014) executed the same modeling study at ~0% inlet turbulence for the trailing edge cooled VKI S1N of Kapteijn et al (1996) and found, not surprisingly, a similar trend to the uncooled results as shown in Figure 12. The trailing edge cooling for the cooled VKI vane is a simple slot.…”

Section: Ii4 High Pressure Turbinesupporting

confidence: 78%

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Future Directions of High Fidelity CFD for Aerothermal Turbomachinery Analysis and Design

Laskowski¹,

Kopriva²,

Michelassi³

et al. 2016

46th AIAA Fluid Dynamics Conference

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Computational Fluid Dynamics is a powerful tool used on a daily basis by designers and researchers in the advancement of propulsion technology. As hardware and software technology continue to evolve, the impact on propulsion systems has the potential to be disruptive. With continued development of High Performance Computing, Large Eddy Simulation, High-Order unstructured grid algorithms, optimization and uncertainty quantification it is conceivable that a new frontier of simulation based research, analysis and design capability is in the foreseeable future. In order to accelerate this development collaboration between industry, academia and government labs is required. NomenclatureBR = Bypass Ratio c = Chord Length CFD = Computational Fluid Dynamics DNS = Direct Numerical Simulation HLES = Hybrid Large Eddy Simulation HO = High-Order HPC = High Performance Computing HPC = High Pressure Compressor HPT = High Pressure Turbine IDDES = Improved Delayed Detached Eddy Simulation IDDES-T = Improved Delayed Detached Eddy Simulation with Transition LES = Large Eddy Simulation LPC = Low Pressure Compressor LPT = Low Pressure Turbine Ma = Mach Number 1 Principal Engineer high-fidelity CFD, Advanced Design Tools, 2 MDAO = Multi-Disciplinary Analysis and Optimization OPR = Overall Pressure Ratio Pt = Total Pressure RANS = Reynolds Averaged Navier Stokes Equations Re = Reynolds number Ro = Rossby Number S = Slot Height S1B = Stage 1 Blade S2B = Stage 2 Blade S1N = Stage 1 Nozzle S2N = Stage 2 Nozzle SFC = Specific Fuel Consumption St = Strouhal Number TIT = Turbine Inlet Temperature Tt = Total Temperature TVD = Total Variation Diminishing UQ = Uncertainty Quantification URANS = Unsteady Reynolds Averaged Navier Stokes Equations VKI = von Karman Institute WMLES = Wall-Modeled Large Eddy Simulation WRLES = Wall-Resolved Large Eddy Simulation

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Section: Ii4 High Pressure Turbinesupporting

confidence: 78%

“…As an example, Kopriva et al (2014Kopriva et al ( , 2015 conducted a detailed study of the uncooled VKI S1N of Arts et al (1992) focusing on SST, IDDES, IDDES with a transition model and WALE LES in ANSYS Fluent. Simulations were conducted on unstructured meshes consisting of triangular elements.…”

Section: Ii4 High Pressure Turbinementioning

confidence: 99%

Future Directions of High Fidelity CFD for Aerothermal Turbomachinery Analysis and Design

Laskowski¹,

Kopriva²,

Michelassi³

et al. 2016

46th AIAA Fluid Dynamics Conference

Self Cite

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“…Moreover, high pressure turbines operate at both transonic Mach numbers and high Reynolds numbers, which impose great challenges to modern CFD. Conventional RANS and URANS methods have many difficulties in treating unsteady vortical flows in turbines [17][18][19][20] while DNS and LES are too costly [21] especially for high pressure turbines. High pressure turbine cascades had previously not been studied with high-fidelity numerical simulations until the works by Rathakrishnan Bhaskaran [22] with the help of LES.…”

Section: Introductionmentioning

confidence: 99%

“…High pressure turbine cascades had previously not been studied with high-fidelity numerical simulations until the works by Rathakrishnan Bhaskaran [22] with the help of LES. Kopriva et al conducted a detailed study of a high pressure turbine guide vane focusing on the performance comparison of RANS, URANS, hybrid-LES and LES methods in ANSYS Fluent and found that RANS and URANS give worse predictions of the total pressure wake while hybrid-LES and LES produce much better results [20,23]. However, no local loss analysis is carried out in these studies.…”

Section: Introductionmentioning

confidence: 99%

Local Entropy Generation in Compressible Flow through a High Pressure Turbine with Delayed Detached Eddy Simulation

Lin

Yuan

Chen

2017

Entropy

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Gas turbines are important energy-converting equipment in many industries. The flow inside gas turbines is very complicated and the knowledge about the flow loss mechanism is critical to the advanced design. The current design system heavily relies on empirical formulas or Reynolds Averaged Navier-Stokes (RANS), which faces big challenges in dealing with highly unsteady complex flow and accurately predicting flow losses. Further improving the efficiency needs more insights into the loss generation in gas turbines. Conventional Unsteady Reynolds Averaged Simulation (URANS) methods have defects in modeling multi-frequency, multi-length, highly unsteady flow, especially when mixing or separation occurs, while Direct Numerical Simulation (DNS) and Large Eddy Simulation (LES) are too costly for the high-Reynolds number flow. In this work, the Delayed Detached Eddy Simulation (DDES) method is used with a low-dissipation numerical scheme to capture the detailed flow structures of the complicated flow in a high pressure turbine guide vane. DDES accurately predicts the wake vortex behavior and produces much more details than RANS and URANS. The experimental findings of the wake vortex length characteristics, which RANS and URANS fail to predict, are successfully captured by DDES. Accurate flow simulation builds up a solid foundation for accurate losses prediction. Based on the detailed DDES results, loss analysis in terms of entropy generation rate is conducted from two aspects. The first aspect is to apportion losses by its physical resources: viscous irreversibility and heat transfer irreversibility. The viscous irreversibility is found to be much stronger than the heat transfer irreversibility in the flow. The second aspect is weighing the contributions of steady effects and unsteady effects. Losses due to unsteady effects account for a large part of total losses. Effects of unsteadiness should not be neglected in the flow physics study and design process.

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“…Denton and Pullan [12] and Zlatinov et al [13] analyzed the local entropy generation rate in turbines with unsteady RANSs. However, Kopriva et al [14,15] found that RANSs have much lower accuracy than large eddy simulations (LESs). Tucker [16,17] indicated that it is particularly difficult to predict unsteady separations in turbines with RANSs.…”

Section: Introductionmentioning

confidence: 99%

Second-Law Analysis of Irreversible Losses in Gas Turbines

Jin

et al. 2017

Entropy

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Several fundamental concepts with respect to the second-law analysis (SLA) of the turbulent flows in gas turbines are discussed in this study. Entropy and exergy equations for compressible/incompressible flows in a rotating/non-rotating frame have been derived. The exergy transformation efficiency of a gas turbine as well as the exergy transformation number for a single process step have been proposed. The exergy transformation number will indicate the overall performance of a single process in a gas turbine, including the local irreversible losses in it and its contribution to the exergy obtained the combustion chamber. A more general formula for calculating local entropy generation rate densities is suggested. A test case of a compressor cascade has been employed to demonstrate the application of the developed concepts.

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Computational Assessment of Inlet Turbulence on Boundary Layer Development and Momentum/Thermal Wakes for High Pressure Turbine Nozzle and Blade

Cited by 16 publications

References 0 publications

Future Directions of High Fidelity CFD for Aerothermal Turbomachinery Analysis and Design

Future Directions of High Fidelity CFD for Aerothermal Turbomachinery Analysis and Design

Local Entropy Generation in Compressible Flow through a High Pressure Turbine with Delayed Detached Eddy Simulation

Second-Law Analysis of Irreversible Losses in Gas Turbines

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