In this paper, we investigate the feasibility of using DNS data and machine learning algorithms to assist RANS turbulence model development. High-fidelity DNS data are generated with the incompressible Navier–Stokes solver implemented in the spectral/hp element software framework Nektar++. Two test cases are considered: a turbulent channel flow and a stationary serpentine passage, representative of internal turbo-machinery cooling flow. The Python framework TensorFlow is chosen to train neural networks in order to address the known limitations of the Boussinesq approximation and a clustering based on flow features is run upfront to enable training on selected areas. The resulting models are implemented in the Rolls-Royce solver HYDRA and a posteriori predictions of velocity field and wall shear stress are compared to baseline RANS. The paper presents the fundamental elements of procedure applied, including a brief description of the tools and methods and improvements achieved.

This paper describes a coupling framework for parallel execution of different solvers for multi-physics and multi-domain simulations with an arbitrary number of adjacent zones connected by different physical or overlapping interfaces. The coupling architecture is based on the execution of several instances of the same coupling code and relies on the use of smart edges (i.e., separate processes) dedicated to managing the exchange of information between two adjacent regions. The collection of solvers and coupling sessions forms a flexible and modular system, where the data exchange is handled by independent servers that are dedicated to a single interface connecting two solvers’ sessions. Accuracy and performance of the strategy is considered for turbomachinery applications involving Conjugate Heat Transfer (CHT) analysis and Sliding Plane (SP) interfaces.

The paper presents a multidisciplinary approach for aero-thermal and heat transfer analysis for internal flows. The versatility and potential benefit offered by the approach are described through the application to a realistic low pressure turbine assembly. The computational method is based on a run time code-coupling architecture that allows mixed models and simulations to be integrated together for the prediction of the subsystem aero-thermal performance. In this specific application, the model is consisting of two rotor blades, the embedded vanes, the interstage cavity, and the solid parts. The geometry represents a real engine situation. The key element of the approach is the use of a fully modular coupling strategy that aims to combine (1) flexibility for design needs, (2) variable level of modeling for better accuracy, and (3) in memory code coupling for preserving computational efficiency in large system and subsystem simulations. For this particular example, Reynolds averaged Navier–Stokes (RANS) equations are solved for the fluid regions and thermal coupling is enforced with the metal (conjugate heat transfer, CHT). Fluid–fluid interfaces use mixing planes between the rotating parts while overlapping regions are exploited to link the cavity flow to the main annulus flow as well as in the cavity itself for mapping of the metal parts and leakages. Metal temperatures predicted by the simulation are compared to those retrieved from a thermal model of the engine, and the results are discussed with reference to the underlying flow physics.

It is known that a secondary effect of rotor-casing effusion cooling is to modify and potentially spoil the rotor over-tip leakage flow. Studies have shown both positive and negative impacts on high-pressure (HP) stage aerodynamic performance and heat transfer, although there remains no consensus on whether the net effect is beneficial when both aerodynamic and thermal effects are accounted for simultaneously. An effect that has not been extensively discussed in the literature is the change in stage operating point that arises due to mass introduction midway through the machine. This effect complicates the analysis of the true performance impact on a turbine and must be accounted for in an assessment of the overall benefit of such a system. In this paper, we develop a low-order (“mean-line”) analysis in an attempt to bring clarity to this issue. We then present results from experiments conducted in the Oxford Turbine Research Facility, a 1.5-stage transonic rotating facility capable of matching non-dimensional engine conditions. In the experiments, effusion cooling was implemented over a sector of the rotor casing spanning 24 degrees or four rotor-blade pitches. Rotor-exit radial traverse and HP vane loading measurements were conducted locally to the cooled sector. Results are compared to baseline tests conducted without cooling. To assess the degree to which experimental results with only a sector of the annulus cooled would provide an accurate indication of stage operating point changes (when measured local to the annulus) in an annular (engine-like) environment, unsteady Reynolds-averaged Navier–Stokes (URANS) simulations were performed. In particular, simulations of a full annulus with an effusion-cooled sector were compared to a periodic simulation with fully annular effusion cooling. The results—perhaps surprisingly—suggest that a cooled sector is sufficient to infer the changes in an annular system, provided measurements are performed locally to the sector. Experiments conducted with fixed 1.5-stage boundary conditions showed increases in both mid-stage static pressure and stage-exit total pressure with cooling. The mean-line model and URANS predictions were in good agreement with the experimental data and also showed an increase in stage reaction and a reduction in turbine-inlet (mainstream) mass flowrate with cooling. Finally, the URANS predictions were used to show that with cooling, there are changes both locally to the cooled casing (changes to the tip-leakage and secondary flow structures) and globally (changes to the bulk-flow velocity triangles). An absolute stage efficiency benefit of 0.7% was predicted for a coolant-to-mainstream mass flowrate ratio of 2.2%. By running with a number of different boundary conditions, steady RANS simulations were used to estimate the relative contributions to the efficiency improvement due to the changes in operating point and aerodynamics in the blade-tip region. For the present configuration, both changes contribute positively to the improvement in stage efficiency.

This paper shows the current research to move towards the full digital design of a gas turbine. In the last years new manufacturing technologies, such as additive manufacturing, become more common for gas turbine applications, allowing greater flexibility in the design space. There is a need to...