Virtual prototyping of gas turbines

Gas turbines (GTs) must be designed to produce energy as efficiently as possible.Components have to sustain reliable operation under extreme conditions. Complex aerodynamic and thermodynamic interactions are a major determinant of a turbine’s performance. As such, flow and thermal analysis methods are fundamentally important to the design process.

Many manufacturers rely on 1- and 2-dimensional correlation-based approximations. But these methods limit the accuracy of temperature predictions. Competing demands for improved efficiency, reliability, emissions and unit costs have amplified the need for tools capable of moving beyond simple correlation-based methods.

However, 3-dimensional computational fluid dynamics (CFD) simulations can be used to predict the complex flow field and turbine blade metal temperatures accurately and rapidly.

The environment in which turbine blades operate is harsh, with temperatures significantly higher than the melting point of the metal blades themselves. Safe and efficient operation of gas turbines relies on the cooling provided by air routed through internal passageways built into the blades. As such, a goal of cooled turbine blade simulation is to determine metal temperatures throughout the blade. These temperatures and the predicted aerodynamic loads allow for stress predictions to be performed, and the durability of the blade to be established. Approaches to obtaining these temperatures and loads have evolved as computational methods have improved and become more practical. Each of the three analysis methods outlined below describe tools and process of predicting the blade temperature of a candidate blade design.

1. Legacy Design System: Internal and external turbine blade flow-fields are approximated using 1D correlations obtained from experimental data and simple relations. The correlation-based results are then used as inputs to a 3D finite element analysis (FEA)to predict blade temperatures.

The process, shown in figure 2, begins by specifying the cooling air being delivered to the blade and a specification of the aerodynamic conditions the blade will experience (boundary conditions).Additionally, a blade wall temperature is assumed. These inputs are used to determine the internal and external flow-field using low-fidelity methods. These flow-field estimates provide the necessary boundary conditions for a 3D FEA analysis, which will result in a blade surface temperature distribution. This analysis cycle is repeated until the predicted blade surface temperature agrees with the assumed input.

Each iteration of the analysis loop is fast due to the simplicity of the models used, however those simplifications yield lower accuracy leaving a greater uncertainty of how the actual engine will perform. The correlation methods used rely on engine test data for correlation, meaning that expensive experiments must be performed and only designs similar to what has been tested can be considered. Additionally, the analysis process relies on the maintenance of multiple tools, and a cumbersome workflow to pass data between the tools.

2. CFD-based Design System: The correlation-based flow-field predictions of the Legacy Design Systemare replaced by separate 3D CFD simulations of the internal and external blade flow paths. The results from these separate CFD simulations are then used directly as inputs to 3D FEA analyses in order to obtain the metal temperatures.

Performing a multi physics simulation using the high-fidelity 3D model of the turbine blade allows for a far more accurate characterization of the system than that provided by the other approaches. Solving both the aerodynamics and solid conduction domains simultaneously further increases accuracy, while eliminating the need to iterate within the analysis process. When these modeling techniques are combined into a streamlined design system, the shortened design time allows for efficient design-space exploration and the ability to analyze truly novel designs that fall well outside the scope of empirical correlation-based methods.

Validating the 3D CHT/CFD design system

Validation is important when implementing any analysis method. It is important to determine how to appropriately use the tool to model the system of interest. The Siemens team validated the CHT/CFD methodology in two stages. First, they performed simulations of individual turbine blade features and compared the results against experiments in order to determine a set of best-practices to be used for subsequent simulations. They then performed simulations of the full blade geometry under engine operating conditions using the recently developed best-practices. The engine predictions were then compared to experimental data from engine tests conducted at the Siemens Berlin Test Facility (BTF) to verify accuracy of the simulation process.

Feature validations were performed on simplified representations of specific turbine blade features, each representing a geometry and flow phenomenon relevant to the turbine blade’s operation. These fundamental tests included single and multi jet impingement, turbulated ducts and pin fins. The experimental data against which these simulations were compared was gathered in controlled environments and therefore considered to have less uncertainty than the data gathered from full-on engine validations. The sensitivity of the flow simulations to mesh refinement and turbulence model selection was systematically examined, providing insights into the settings that might prove most effective in the full turbine blade simulation.

For the second validation stage, measurements were taken of the solid blade temperature of an H-class engine’s vane 1. This engine test was conducted at the Siemens BTF. The blade temperature was measured using more than 1,500 micron-sized thermal crystals embedded into a total of 12 vanes.

The full-fidelity geometry of the experimental blade was simulated under the same operating conditions as the test. Figure 6 shows the complex geometry of the blade used in the full blade CHT/CFD simulation, along with the predicted blade temperature and flow-field on the suction and pressure sides of the vane (shown in figure 6a and figure 6b, respectively). Temperature measurement locations are marked as black points on the surface of the vane.

Conclusion

The integrated CFD/CHT workflow developed by the Siemens team based on Simcenter technology is an integrated and automated analysis process capable of accurately predicting turbine blade metal temperatures of novel blade designs. The method provides detailed physical insight within the time constraints imposed by a tight production schedule. The integrated, 3D, multiphysics-based approach represents a more accurate characterization of the system, enabling engineers to analyze and explore novel concepts well outside the scope of correlation-based methods-- a significant progression beyond traditional workflows.

The automated, pipelined workflow based on NX and STAR-CCM+ also means that the Siemens engineers can quickly perform simulations of multiple design variants, to assess the effects on the metal temperatures due to changes in geometry and/or flow conditions.

As Philipp Cavadiniof Siemens PG said, “Our use of STAR-CCM+ with NX has enabled us to streamline our workflow and obtain way faster thermal prediction capability for our gas turbines, impacting our day-to-day design iterations.  Now we are looking forward to leveraging additional data management technology, such as Teamcenter for efficiently managing the large quantities of product models and simulation data.”

Javier Garriz, Chad Custer, Jim Ryan – Siemens PLM Software

This workflow is based on the Siemens PLM Simcenter platform using NX for 3D CAD geometry generation and STAR-CCM+ software for multiphysics CFD simulation.