This paper explores the conjugate heat transfer (CHT) numerical simulation approach to calculate the metal temperature for the gas turbine cooled stator. ANSYS CFX12.1 code was selected to be the computational fluid dynamic (CFD) tool to perform the CHT simulation. The 2-equation RNG k-ε turbulence model with scalable modified wall function was employed. A full engine test with thermocouple measurement was performed and used to validate the CHT results. Metal temperatures calculated with the CHT model were compared to engine test data. The results demonstrated good agreement between test data and airfoil metal temperatures and cooling flow temperatures using the CHT model. However, the CHT calculations in the outer end wall had a discrepancy compared to the measured temperatures, which was due to the fact that the CHT model assumed an adiabatic wall as a boundary condition. This paper presents a process to calculate convection heat transfer coefficient (HTC) for cooling passages and airfoil surfaces using CHT results. This process is possible because local wall heat flux and fluid temperatures are known. This approach assists in calibrating an in-house conduction thermal model for steady state and transient thermal analyses.

This paper explores the conjugate heat transfer (CHT) numerical simulation approach to calculate the metal temperature for a cooled gas turbine blade. ANSYS CFX14.0 code was selected as the computational fluid dynamic (CFD) tool to perform the CHT simulation. The two-equation SST turbulence model with automatic wall treatment was employed. A full engine test with Silicon Carbide (SiC) chip measurements was performed and used to validate the CHT results. Metal temperatures calculated with the CHT model were compared to engine test data. The results demonstrated good agreement between predicted and measured airfoil metal temperatures. The blade cooling flow prediction was matched to the flow network analysis. This paper describes a process to calculate convection heat transfer coefficients (HTC) for cooling passages and airfoil surfaces using CHT results. This process was made possible because local wall heat flux and fluid temperatures were known. This approach assisted in calibrating an in-house conduction thermal model for steady state thermal analyses.

In recent years, conjugate heat transfer (CHT) computational fluid dynamics (CFD) simulation in turbomachinery played an important role in predicting metal temperature. Most of research papers of CHT CFD simulation were emphasized on the mixing plane method. In this paper the ANSYS CFX 14.0 CHT simulation using the frozen rotor approach is employed to predict the blade temperatures. The frozen rotor included five time instances in which the stator-rotor wake influence could be captured. In this study, the temperature predictions using the frozen rotor approach were compared to the mixing plane predictions and Silicon Carbide (SiC) chip measurements on three different radial spans. The frozen rotor results predicted the minimum and maximum temperatures that bounded the SiC chip data. Compared to the mixing plane predictions, the frozen rotor approach results were similar within 8 K at the mid-span. However, the frozen rotor approach provided more insight information and detailed guidance for model calibration. Finally several future works were suggested to continue striving for high performance gas turbines.

Although turbo-machinery main stream flows are predominantly turbulent, the low pressure turbine airfoil surface boundary layer may be either laminar or turbulent. When boundary layer flow is laminar and passes through a zone of adverse pressure gradient, bypass or separation transition can occur via the Tollmien-Schlichting or Kelvin-Helmholtz instabilities. As the gas turbine’s low pressure turbine operating condition changes from sea level take-off to the altitude cruise, Reynolds number is significantly lowered and the turbine’s performance loss increases significantly. This fall-off in performance characteristic is known as lapse rate. Ability to accurately model such phenomenon is a prerequisite for reliable loss prediction and essential for improving low pressure turbine designs. Establishing such capability requires the validation and evaluation of existing low Reynolds number turbulence models, with laminar-turbulent transition modeling capability, against test cases with measured data. This paper summarizes the results of evaluating and validating two 3D viscous “RANS” Reynolds-Averaged Navier-Stokes programs for two test cases with test data. The first test case is the ERCOFTAC’ flat plate with and without pressure gradient, and the second is a Honeywell three-and-half-stage low pressure turbine with available test data at high and low Reynolds number operations. In addition to evaluating the CFD codes against test data, the flat plate test cases were used to establish the meshing and modeling best practice for each code before performing the validation for the Honeywell multistage low pressure turbine. The RANS CFD programs are Numeca’s Fine Turbo and ANSYS/CFX. Numeca’s Fine Turbo employs a two-equation K-ε turbulence model without laminar-turbulent transition modeling capability and the one-equation Spallart-Allmaras turbulence model with laminar-turbulent transition modeling capability. The ANSYS/CFX, on the other hand, employs a two-equation K-ω turbulence model (AKA SST or shear stress transport) with ability to model laminar-turbulent transition. Predictions of the CFD codes are compared with test data and the impact of modeling the laminar-turbulent transition on the prediction accuracy is assessed and presented. Both CFD codes are commercially available and the evaluation presented here is based on users’ prospective that targets the applicability of such predictive tools in the turbine design process.

A new aerodynamic design system has been developed that includes a through-flow solver for fans, axial compressors and turbines, and radial compressors and turbines. Three earlier papers gave an overview of the system and described the interactive interface and geometry generators. This paper focuses on several special features in the through-flow solver that provide increases in aerodynamic designer productivity. Some of the key features are stations decoupled from flow paths, ability to accept a wide variety of input parameters, use of gas property routines, ability to inject flow non-uniformly with a different composition than the main flow gas composition, ability to access information from several airfoil geometry generator solutions, and clear, comprehensive error handling. These special features and others have provided major savings from productivity improvements and reductions in design cycle time.