Deterministic Stress Modeling of Hot Gas Segregation in a Turbine

Busby, Judy; Sondak, Doug; Staubach, Brent; Davis, Roger L.

doi:10.1115/99-gt-076

Cited by 8 publications

(4 citation statements)

References 4 publications

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“…In this formulation each blade row has a steady average-passage flow field, which extends from the inlet to the exit of the machine. Neighboring blade rows are replaced with circumferentially uniform systems of body forces, energy sources and (not necessarily uniform) deterministic stresses (Adamczyk [1], Adamczyk et al [2], Adamczyk et al [3], Rhie et al [4], LeJambre et al [5], Busby et al [6]). The effects of phase-dependent unsteadiness on the average-passage flow field are accounted for through the deterministic stresses, which must be modeled in order to obtain a closed system of equations.…”

Section: Introductionmentioning

confidence: 99%

Average Passage Flow Field and Deterministic Stresses in the Tip and Hub Regions of a Multi-Stage Turbomachine

Uzol

Chow

Katz

et al. 2003

Volume 6: Turbo Expo 2003, Parts a and B

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This paper continues our effort to study the dynamics of deterministic stresses in a multistage turbomachine using experimental data. Here we focus on the tip and hub regions and compare them to mid span data obtained in previous studies. The analysis is based on data obtained in PIV measurements performed in the second stage of a two-stage turbomachine. A complete data set is obtained using blades and fluid with matched optical index of refraction. Previous measurements at mid span have shown that at mid span and close to design conditions, the deterministic kinetic energy is smaller than the turbulent kinetic energy. The primary contributor to the deterministic stresses at mid span is the interaction of a blade with the upstream wakes. Conversely, we find that the tip vortex is the dominant source of phase-dependent unsteadiness and deterministic stresses in the tip region. Along the trajectory of the tip vortex, the deterministic kinetic energy levels are more than one order of magnitude higher than the levels measured in the hub and mid-span, and are of the same order of magnitude as the turbulent kinetic energy levels. Reasons for this trend are explained using a sample distribution of phase-averaged flow variables. Outside of the region affected by tip vortex transport, within the rotor-stator gap and within the stator passages, the turbulent kinetic energy is still 3–4 times higher than the deterministic kinetic energy. The deterministic and turbulent shear stress levels are comparable in all spanwise locations, except for the wakes of the stator blades, where the turbulent stresses are higher. However, along the direction of tip vortex transport, the deterministic shear stresses are about an order of magnitude higher than the turbulent shear stresses. The decay rates of deterministic kinetic energy in the hub and mid-span regions are comparable to each other, whereas at the tip, the decay rate is higher. The decay rates of turbulent kinetic energy are much smaller than those of the deterministic kinetic energy. The paper also examines terms in the deterministic kinetic energy transport equation. The data indicate that “Deterministic Production” and a new term, called here “Dissipation due to Turbulence” are the dominant source/sink terms. Regions with alternating signs of Deterministic Production indicate that the energy transfer between the phase-averaged and average-passage flow fields can occur in both directions. The divergence of the Pressure-Velocity correlation, obtained from a balance of all the other terms, is dominant and appears to be much larger than the deterministic production (source/sink) term. This trend indicates that there are substantial deterministic pressure fluctuations in the flow field, especially within the rotor-stator gap and within the stator passage.

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Section: Introductionmentioning

confidence: 99%

Average Passage Flow Field and Deterministic Stresses in the Tip and Hub Regions of a Multi-Stage Turbomachine

Uzol

Chow

Katz

et al. 2003

Volume 6: Turbo Expo 2003, Parts a and B

View full text Add to dashboard Cite

show abstract

“…When these operators are applied to the Navier-Stokes equations one obtains the average-passage RANS equations. In this formulation each blade row has a steady average-passage flow field, and neighboring blade rows are coupled (replaced with) through circumferencially uniform systems of body forces, energy sources and deterministic stresses (Adamczyk [1], Adamczyk et al [2], Adamczyk et al [3], Rhie et al [4], LeJambre et al [5], Busby et al [6]). The effects of phase-dependent unsteadiness on the average-passage flow field are accounted for through the "deterministic stresses".…”

Section: Introductionmentioning

confidence: 99%

Experimental Investigation of Unsteady Flow Field Within a Two-Stage Axial Turbomachine Using Particle Image Velocimetry

Uzol

Chow

Katz

et al. 2002

Journal of Turbomachinery

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Detailed measurements of the flow field within the entire 2nd stage of a two-stage axial turbomachine are performed using particle image velocimetry. The experiments are performed in a facility that allows unobstructed view on the entire flow field, facilitated using transparent rotor and stator and a fluid that has the same optical index of refraction as the blades. The entire flow field is composed of a “lattice of wakes,” and the resulting wake-wake and wake-blade interactions cause major flow and turbulence nonuniformities. The paper presents data on the phase averaged velocity and turbulent kinetic energy distributions, as well as the average-passage velocity and deterministic stresses. The phase-dependent turbulence parameters are determined from the difference between instantaneous and the phase-averaged data. The distributions of average passage flow field over the entire stage in both the stator and rotor frames of reference are calculated by averaging the phase-averaged data. The deterministic stresses are calculated from the difference between the phase-averaged and average-passage velocity distributions. Clearly, wake-wake and wake-blade interactions are the dominant contributors to generation of high deterministic stresses and tangential nonuniformities, in the rotor-stator gap, near the blades and in the wakes behind them. The turbulent kinetic energy levels are generally higher than the deterministic kinetic energy levels, whereas the shear stress levels are comparable, both in the rotor and stator frames of references. At certain locations the deterministic shear stresses are substantially higher than the turbulent shear stresses, such as close to the stator blade in the rotor frame of reference. The nonuniformities in the lateral velocity component due to the interaction of the rotor blade with the 1st-stage rotor-stator wakes, result in 13 percent variations in the specific work input of the rotor. Thus, in spite of the relatively large blade row spacings in the present turbomachine, the nonuniformities in flow structure have significant effects on the overall performance of the system.

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“…Recently, Orkwis, et al [6,7] and Busby, et al [8] have used field source terms rather than just interface source terms to model accurately the unsteady effect of hot streak migration with considerable success.…”

Section: Introductionmentioning

confidence: 99%

Modeling unsteadiness in steady cavity simulations. I - Parametric solutions

Gangwar

Lukovic

Orkwis

et al. 2001

39th Aerospace Sciences Meeting and Exhibit

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The goal of this research was to develop a source term module to model the effect of cavity unsteadiness in gas-path only simulations. In this approach the unsteady effect of the cavity on the main gas-path solution is modeled by adding source terms to the right hand side of the Navier-Stokes equations instead of resolving the cavity geometry. This idea increases considerably the numerical efficiency of the scheme by avoiding the computation of small-scale fluid dynamic structures and the geometric details of the cavity. The paper is a two-part work. In the first part the source terms are developed via a lumped deterministic source term (LDST) approach using unsteady complete cavity geometry simulations. A simplified rectangular cavity has been used for the present work. A parametric study of the source term variation with Mach number is presented. Steady simulations of the passage only (i.e., sans cavity) with source terms inserted have been performed and the results obtained compared to timeaveraged solutions that resolve the cavity. The steady state solution using source terms was able to correctly incorporate all unsteady effects present in the time average of the unsteady cavity solution. The second part of the paper discusses the modeling of cavity source terms via back-propagation neural networks. Sample analyses for subsonic Mach numbers, input pressures and boundary layer thicknesses, are presented. A background neural network is trained to generate a source term for any combination of parameters. The resultant flow field is computed for a finite number of test cases. Neural networks are then utilized to model the complex data dependencies instead of computing source terms for every test case. The neural network can be trained to generate quickly a source term for any combination of input parameters. The steady state flow through the passage including the unsteady effect of the cavity was obtained using neural network generated source terms. The resultant flow fields are only slightly different from the calculated time average results and thus encourage the further development of this method.

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Deterministic Stress Modeling of Hot Gas Segregation in a Turbine

Cited by 8 publications

References 4 publications

Average Passage Flow Field and Deterministic Stresses in the Tip and Hub Regions of a Multi-Stage Turbomachine

Average Passage Flow Field and Deterministic Stresses in the Tip and Hub Regions of a Multi-Stage Turbomachine

Experimental Investigation of Unsteady Flow Field Within a Two-Stage Axial Turbomachine Using Particle Image Velocimetry

Modeling unsteadiness in steady cavity simulations. I - Parametric solutions

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