Mauro Carnevale

Uncertainty quantification in computational fluid dynamics and aircraft engines

Introduction to jet engine reliability and safety.- Impact of manufacturing deviations on jet engine life and performance.- Introduction to Uncertainty Quantification in Computational Fluid Dynamics: Monte Carlo Simulation and Polynomial Chaos Expansions.- The matrix of knowledge in CFD: deterministic simulations, turbulence closures, uncertainty quantification and black swans.- Robust design and optimization under uncertainty.- Future directions.

Film Cooling and Shock Interaction: An Uncertainty Quantification Analysis With Transonic Flows

This work shows an Uncertainty Quantification (UQ) study of film cooling with shock impingement. A numerical method is proposed to use high order polynomials for the reconstruction of the stochastic output, without the instabilities characteristic of UQ with shock dominated flows. At the same time it is shown that the region with highest uncertainty is driven by a complex flow physics involving shock–boundary layer interaction and the generation of tornado vortices that merge with kidney ones.High-pressure turbine stages are characterized by transonic conditions with the suction side of the nozzle affected by the shock shed by the trailing edge of the adjacent aerofoil. Due to manufacturing deviations and in service degradation the geometrical parameters, such as trailing edge thickness and hole diameter, are subjected to random variations, changing the shock location and the heat transfer loading on the stator nozzle. For these reasons an UQ methodology has been used in this study to model the interaction between the impinging shock and film cooling. The variability of the geometrical parameters has been represented with uniform probability distributions and the stochastic output is obtained using Probabilistic Collocation Method with Pade’s polynomials. Transonic flows are challenging in Uncertainty Quantification because a better reconstruction of the stochastic output can be achieved increasing the order of polynomials but higher order polynomials become unstable for the Runge’s phenomenon. This work proposes a method that allows the application of high order Pade’s polynomial without having instabilities in the stochastic output. The proposed methodology can be applied to other transonic configurations in gas turbines, requiring only a limited number of simulations to reconstruct the stochastic output. The results show that the maximum level of uncertainty is located downstream the region of interaction between shock and boundary layer. In particular the shock generates complex flow structures that develop into tornado vortices, highly dependent on the uncertainty input.Copyright

NUMERICAL STUDIES INTO INTAKE FLOW FOR FAN FORCING ASSESSMENT

Recent trends in design for civil intakes lead towards shorter diffuser sections, unorthodox installations and more loaded lips. All these features increase the risk of lip stall in flight at incidence or in cross wind and increase the level of forcing seen by the fan blades because of the interaction with non-uniform flow from the intake.In this study we analyze the behavior of prediction tools for intake distortion. In particular we compare the performance of popular turbulence models for standard intake flows and we discuss their behavior on the grounds of their behavior for elementary flows.We conclude our study by comparing forcing and distortion figures of merit from different models.Copyright

Simulation of Multi-Stage Compressor at Off-Design Conditions

Computational Fluid Dynamics (CFD) has been widely used for compressor design, yet the prediction of performance and stage matching for multi-stage, high-speed machines remain challenging. This paper presents the authors’ effort to improve the reliability of CFD in multistage compressor simulations. The endwall features (e.g. blade fillet and shape of the platform edge) are meshed with minimal approximations. Turbulence models with linear and non-linear eddy viscosity models are assessed. The non-linear eddy viscosity model predicts a higher production of turbulent kinetic energy in the passages, especially close to the endwall region. This results in a more accurate prediction of the choked mass flow and the shape of total pressure profiles close to the hub. The non-linear viscosity model generally shows an improvement on its linear counterparts based on the comparisons with the rig ∗Corresponding author (feng.wang@eng.ox.ac.uk) TURBO-17-1165 Wang 1 data. For geometrical details, truncated fillet leads to thicker boundary layer on the fillet and reduced mass flow and efficiency. Shroud cavities are found to be essential to predict the right blockage and the flow details close to the hub. At the part speed the computations without the shroud cavities fail to predict the major flow features in the passage and this leads to inaccurate predictions of massflow and shapes of the compressor characteristic. The paper demonstrates that an accurate representation of the endwall geometry and an effective turbulence model, together with a good quality and sufficiently refined grid result in a credible prediction of compressor matching and performance with steady state mixing planes. Introduction Three-dimensional CFD simulations of multiple blade rows were developed by Adamczyk [1] using the average passage approach. Each blade row was modelled seperately and only one passage of each blade row was required in the simulation. Blade row interactions were evaluated by including additional force terms in the equations. This approach was further simplified by Denton and the resulting approach was termed as the mixing plane approach [2]. The mixing plane assumes a mixed-out state at the bladerow interface by conserving mass, momentum and energy fluxes. The drawback of this approach is that the unsteady blade interactions are removed. Despite its simplicity, the performance of turbomachines is predicted reasonably well using mixing planes. Consequently, steady state RANS simulations have been the work-horse of turbomachinery design. The capability of RANS simulations in assisting turbomachinery design was already demonstrated by early researchers [3, 4], even if limitations in computer power, meshing techniques and physical modelling restricted the spatial resolution as well as the amount of geometric detail present in the simulations. Typical examples of features omitted from the computational models in the early days were blade fillets, stator shrouds, Variable Stator Vane (VSV) penny gaps etc. Typical grids used were H-grids with pinched tip gaps. Fully meshed tip gaps were introduced and comparisons with pinched tip gaps were summarized by Denton [5]. As the meshing techniques evolved, multiblock structured meshes were introduced into the turbomachinery design and allowed the generation of optimal grids on the blade-to-blade section [6,7]. However, geometrical approximations (e.g. truncated fillets) are still commonplace because of the limitations in the way the geometries of the endwalls and of the blades are represented in the mesh technique. The effect of endwall geometric features is important in predicting the endwall flows and contributes to setting the flow capacity. One of the most important endwall features for modern machines is the shroud cavities. A typical configuration is shown in Fig. 1. Shabbir et al [8] studied the effect of the hub leakage flow on high speed compressor rotors and the pressure deficit close to the hub was well captured by including the hub leakage flow. Wellborn and Okashi [9] reported the effect of shroud cavities on the performance of multi-stage compressor experimentally. Their data showed that the shroud cavities have considerable negative impact on the compressor performance. In their numerical study, the shroud cavities were not meshed as CFD domains, instead they were introduced through a Knife-to-Knife (K2K) model [10]. Another important element in the construction of steady models for turbomachinery is the turbulence model. The flows in multistage compressor passages are highly viscous and three-dimensional around endwall regions. Furthermore the flow is prone to separation due to strong adverse pressure gradient even at design conditions. Predicting the complex flow features TURBO-17-1165 Wang 2

Stochastic Variation of the Aero-Thermal Flow Field in a Cooled High-Pressure Transonic Vane Configuration

In transonic high-pressure turbine stages, oblique shocks originated from vane trailing edges impact the rear suction side of each adjacent vane. High-pressure vanes are usually cooled to tolerate the combustor exit temperature levels, which would reduce dramatically the residual life of a solid vane. Then, it is highly probable that shock impingement will occur in proximity of one of the coolant rows. It has already been observed that the presence of an adverse pressure gradient generates non-negligible effects on heat load due to the increase in boundary layer thickness and turbulence level, with a detrimental impact on the local adiabatic effectiveness values. Furthermore, the generation of a tornado-like vortex has been recently observed that could further decrease the efficacy of the cooling system by moving cold flow far from the vane wall. It must be also underlined that manufacturing deviations and in-service degradation are responsible for the stochastic variation of geometrical parameters. This latter phenomenon greatly alters the unsteady location of the shock impingement and the time-dependent thermal load on the vane. Present work starts from what is shown in literature and provides a highly-detailed description of the aero-thermal field that occurs on a model that represents the flow conditions occurring on the rear suction side of a cooled vane. The numerical model is initially validated against the experimental data obtained by the University of Karlsruhe during TATEF2 EU project, and then an uncertainty quantification methodology based on the probabilistic collocation method and on Pades polynomials is used to consider the probability distribution of the geometrical parameters. The choice of aleatory unknowns allows to consider the mutual effects between shock-waves, trailing edge thickness and hole diameter. Turbulence is modelled by using the Reynolds Stress Model already implemented in ANSYS® Fluent®. Special attention is paid to the description of the flow field in the shock/boundary layer interaction region, where the presence of a secondary effects will completely change the local adiabatic effectiveness values.

Virtual Gas Turbine: Pre-Processing and Numerical Simulations

The design process of a gas turbine engine involves interrelated multi-disciplinary and multi-fidelity designs of engine components. Traditional component-based design process is not always able to capture the complicated physical phenomenon caused by component interactions. It is likely that such interactions are not resolved until hardware is built and tests are conducted. Component interactions can be captured by assembling all these components into one computational model. Nowadays, numerical solvers are fairly easy to use and the most time-consuming (in terms of man-hours) step for large scale gas turbine simulations is the preprocessing process. In this paper, a method is proposed to reduce its time-cost and make large scale gas turbine numerical simulations affordable in the design process. The method is based on a novel featured-based in-house geometry database. It allows the meshing modules to not only extract geometrical shapes of a computational model and additional attributes attached to the geometrical shapes as well, such as rotational frames, boundary types, materials, etc. This will considerably reduce the time-cost in setting up the boundary conditions for the models in a correct and consistent manner. Furthermore, since all the geometrical modules access to the same geometrical database, geometrical consistency is satisfied implicitly. This will remove the time-consuming process of checking possible mismatching in geometrical models when many components are present. The capability of the proposed method is demonstrated by meshing the whole gas path of a modern three-shaft engine and the Reynold’s Averaged Navier-Stokes (RANS) simulation of the whole gas path.© 2016 ASME

Limitations in Turbomachinery CFD

Nowadays, Computational Fluid Dynamics (CFD) is a widely used method for the analysis and the design of gas turbines. The accuracy of CFD is rapidly increasing thanks to the available computational resources that allow simulating high-speed flows using hi-fidelity methodologies. However CFD uses models, and several approximations and errors derive from the process, for example from the truncation errors due to the discretization of the Navier-Stokes equations and from the turbulence models. Typical examples of such kind of limitations may be the steady flow assumption, the turbulence closure or the mesh resolution. The impact of approximations could be minimum to evaluate the trends of variation of global parameters, but it will have a strong impact on the prediction of local values of important parameters such as flow temperature and heat transfer. It is worth highlighting that the available computational resources are pushing towards the so called high fidelity CFD and it is important to highlight what is needed to achieve this goal and to reduce the impact of approximations.

Fan Similarity Model for the Fan-Intake Interaction Problem

Very high bypass ratio turbofans with large fan tip diameter are an effective way of improving the propulsive efficiency of civil aero-engines. Such engines, however, require larger and heavier nacelles, which partially offset any gains in specific fuel consumptions. This drawback can be mitigated by adopting thinner walls for the nacelle and by shortening the intake section. This binds the success of very high bypass ratio technologies to the problem of designing an intake with thin lips and short diffuser section, which is well matched to a low speed fan. Consequently, the prediction of the mutual influence between the fan and the intake flow represents a crucial step in the design process. Considerable effort has been devoted in recent years to the study of models for the effects of the fan on the lip stall characteristics and the operability of the whole installation. The study of such models is motivated by the wish to avoid the costs incurred by full, three-dimensional (3D) computational fluid dynamics (CFD) computations. The present contribution documents a fan model for fan–intake computations based on the solution of the double linearization problem for unsteady, transonic flow past a cascade of aerofoils with finite mean load. The computation of the flow in the intake is reduced to a steady problem, whereas the computation of the flow in the fan is reduced to one steady problem and a set of solutions of the linearized model in the frequency domain. The nature of the approximations introduced in the fan representation is such that numerical solutions can be computed inexpensively, while the main feature of the flow in the fan passage, namely the shock system and an approximation of the unsteady flow encountered by the fan are retained. The model is applied to a well-documented test case and compares favorably with much more expensive 3D, time-domain computations.

Overview of Uncertainty Quantification Methods

This chapter presents an overview of the mathematical methods employed in Uncertainty Quantification (UQ) for turbomachinery. The UQ computational framework is defined and one method for each uncertainty propagation technique is presented and examined. Some examples are provided which underline the motivation of UQ analyses.

Manufacturing and in Service Uncertainty and Impact on Life and Performance

This chapter highlights the impact of manufacturing errors on aircraft engines performance. The reader should use this chapter to identify the regions where Uncertainty Quantification should be used to improve the performance of a gas turbine.