Christian Voß

Automated Multidisciplinary Optimization of a Transonic Axial Compressor

The current paper describes DLR’s optimizer AutoOpti, the implementation of the metamodel “Kriging” as accelerating technique, and the process chain in the automated, multidisciplinary optimization of fans and compressors on basis of a recent full stage optimization of a highly loaded, transonic axial compressor. Methods and strategies for an aerodynamic performance map optimization coupled with a finite element analysis on the structural side are presented. The high number of 231 free design parameters, a very limited number of CFD simulations, and conflicting demands both within the aerodynamic requirements and between the disciplines are a challenging optimization task. To navigate such a multi-dimensional search space, metamodels have successfully been used as accelerating technique. Using four aerodynamic operating points at two rotational speeds allows adjusting a required stability margin and optimizing the working line performance under this constraint. The investigated compressor concept is a highly loaded transonic stage with a single row rotor and a tandem stator, designed for a very high total pressure ratio. A. Introduction ompressors for aircraft engines are constantly developed towards higher aerodynamic loading to reduce the installation length, weight, and number of parts with no degradation in efficiency. This leads to more complex geometries and consequently to more complex flow structures. An automated optimization approach is to be preferred in order to take advantage of new design freedoms, while reducing or at least maintaining development time. Automated optimization is also suggested by recent progress in simulation technologies in several fields such as steady and unsteady computational fluid dynamics (CFD), structural and thermal finite element analysis (FEM). Moreover, processors have become increasingly powerful, and parallel computing on huge clusters can be considered state of the art technology for CFD and FEM applications. Thus, it has become possible to employ optimization methods in the design of various parts of heavy duty gas turbines and aircraft engines, even when calculations require large computational resources.

Automated multiobjective optimisation in axial compressor blade design

This paper presents an automated multiobjective design methodology for the aerodynamic optimisation of turbomachinery blades. In this approach several operating-points of the compressor are considered and the flow-characteristics of the different flow-solutions are combined to one or more objective functions. The optimisation strategy is based on multiobjective asynchronous evolutionary algorithms (MOEA’S) which are accelerated using additive local neural networks and kriging procedures. Common operators: Mutation, Crossover and Differential-Evolution are used to create a new population. In addition to these common operators the optimisation runs temporarily on the response-surface created by the neural networks and/or kriging-processes respectively. Only the Pareto-optimal solutions obtained from this metamodel are evaluated using the numerical expensive flow-solver. Therefore, the response-surface is just a new operator that creates auspicious members. One of the main differences between the presented code to usual and traditional MOEA’S is the selection of parents. While traditional codes choose potential parents of a new population from the previous population, the current method selects parents from the database of all evaluated members. This approach allows the user to run the optimisation asynchronously and with a smaller size of population, treducing numerical costs, without influencing the diversity of the optimal solutions over the whole Pareto-front. This aspect is very important when evaluating very complex and/or discontinuous fronts.

Gradient Enhanced Surrogate Models Based on Adjoint CFD Methods for the Design of a Counter Rotating Turbofan

This paper studies the use of adjoint CFD solvers in combination with surrogate modelling in order to reduce the computational cost of the optimization of complex 3D turbomachinery components. The method is applied to a previously optimized counter rotating turbofan, with a shape parameterized by 104 CAD parameters.Through random changes on the reference design, a small number of design variations are created to serve as training samples for the surrogate models. A steady RANS solver and its discrete adjoint are then used to calculate objective function values and their corresponding sensitivities. Kriging and neural networks are used to build surrogate models from the training data. To study the impact of the additional information provided by the adjoint solver, each model is trained with and without the sensitivity information. The accuracy of the different surrogate model predictions is assessed by comparison against CFD calculations.The results show a considerable improvement of the fitness function approximation when the sensitivity information is taken into account. Through a gradient based optimization on one of the surrogate models, a design with higher isentropic efficiency at the aerodynamic design point is created. This application demonstrates that the improved surrogate models can be used for design and optimization.Copyright

Multi-Objective Optimization in Axial Compressor Design Using a Linked CFD-Solver

In combination with a multi-objective 3D optimization strategy, a linked CFD-solver is presented in this paper, combining 3D-Reynolds-averaged-Navier-Stokes and an inviscid throughflow method. It enables the adjustment of the 3D boundary conditions for any design variation and contains new options for configuring the objective functions. The link is achieved by matching the flow information between both CFD codes in an iterative procedure. Compared to an individual 3D-CFD calculation, the convergence does not take significantly longer. The potential of the linked CFD-solver is demonstrated in a multi-objective optimization for one blade row to be optimized and one operating point at a 3-stage axial compressor with inlet guide vane. Within the optimization, the objective functions are formulated, so that the performance of the axial compressor is enhanced in addition to the improved efficiency of the 3D-cascade.Copyright

Theory and Application of Axisymmetric Endwall Contouring for Compressors

Engine operating range and efficiency are of increasing importance in modern compressor design for heavy duty gas turbines and aircraft engines. These highly challenging objectives can only be met if all components provide high aerodynamic performance and stability. The aerodynamic losses of highly loaded axial compressors are mainly influenced by the leakage flow through clearance gaps. Especially the leakage flow due to the radial clearances of rotor blades affects negatively both, the efficiency and the operating range of the engine. Recent publications showed that the clearance flow and the clearance vortex can be influenced by an additional static pressure gradient at the outer casing, which is created by an axisymmetric wavy casing shape. A notable performance increase of up to 0.4% stage efficiency at design point conditions was reported for high pressure stages with large tip clearance heights [1] as well as for a transonic stage with a relatively small radial clearance gap [2]. An analytic approach to predict the effects of axisymmetric casing contouring has been developed at DLR, Institute of Propulsion Technology, and is outlined in the first part of this work. The characteristic behavior of the clearance vortex in an adverse pressure gradient is discussed by means of an inviscid vortex model [3]. The critical vortex parameters are isolated and related to the static pressure increase due to the casing contour. The second part illustrates the application of an axisymmetric endwall contour. A three dimensional optimization of the outer casing and the corresponding blade tip airfoil section of a typical gas turbine high pressure compressor stage with a high number of free variables is presented. The optimization led to a significant increase in aerodynamic performance of about 0.8% stage efficiency and to a notable reduction of the endwall blockage at ADP conditions. Furthermore, an improved off-design performance was found and a simple design rule is given to transfer both, the casing contour and the blade tip section modification on similar high pressure compressor blades. Based on these design rules the results of the optimized stages were applied to the rear stages of a Siemens gas turbine compressor CFD model. An increase of 0.3% full compressor performance was reached at design point conditions.© 2011 ASME

Generalized Optimization of Counter-Rotating and Single-Rotating Fans

On possible fan concept for future high and ultra-high bypass ratio turbofan engines is the counter-rotating (CR) fan. Several studies [1][2][3][4] dealt already with the optimization of CR fans, however the mass flow and the total pressure ratio were typically given and fixed for a specified application. The results of these studies showed a benefit of the CR fan compared to the conventional single-rotating (SR) fan, which strongly depended on the engine cycle. Following this experience, it was necessary to further specify the efficiency benefits more precisely in association with fan total pressure ratio and fan inlet axial Mach number. The results are discussed in this present paper. A special emphasis was given on determining the optimal pressure ratio, for which the CR-fan expectably achieves the maximal efficiency benefit.The idea was to perform a global optimization study without any constraints for the operating point inside of a broad (ΠFan, Max) –range, for the rotational speeds and with only a few constraints for the geometry of the blades to avoid infeasible geometries. An adequate range for the fan pressure ratio (ΠFan) and for the axial Mach number (Max) was chosen for the global optimization covering the entire range from current to potential future ultra-high bypass ratio engine applications, also taking into account a reduced nacelle diameter and thus high axial fan inflow Mach numbers.The focus of the present study was to develop a method for the global optimization of a fan stage.As a result of this study, the maximal achievable efficiency is shown as a function of the fan pressure ratio and the axial Mach number. Thus the efficiency differences between the CR and SR fan can be calculated through the differences between the surfaces for any given set of parameters defining a potential engine. This allows for a generalized assessment of this particular fan concept over the entire range of relevant applications.Copyright

Automated Optimization of an Axial-Slot Type Casing Treatment for a Transonic Compressor

It has been shown in many cases that a notable aerodynamic stability enhancement can be achieved using casing treatments (CTs) on transonic compressors. This advantage, however, often involves degradation in efficiency at design point conditions. In order to analyze the correlations between efficiency, surge margin and other flow quantities on the one hand and the geometric parameters related to axial slots on the other, an automated multi objective geometry optimization of axial slots is performed. This involves the usage of time accurate URANS simulations for each new CT design the optimization tool proposes. The axial slots are generated using a parametric design, which can produce slots of different size, shape and position. Three operating points are simulated. One at design point (ADP) conditions, a second at reduced speed working line conditions and a third at reduced speed close to the stability limit. Based on the results of the CFD simulations two objective values are calculated. These are, first, an increased efficiency at working line conditions and, second, an increased surge margin at reduced speed. The test case used for the study is the first stage of DLR’s transonic research compressor Rig250. The rig is representative for the front stages of a heavy duty gasturbine compressor. The computational domain includes the IGV as well as the first rotor and stator. The rotor of the configuration is tip-critical for the studied part speed condition. The result of the optimization is a Pareto front with all optimal geometries regarding surge margin and efficiency. It is found that efficiency at design point can be exchanged against surge margin at reduced speed. The working principles and flow phenomena of the Pareto-optimal axial slots are analyzed in detail to obtain a better understanding of the mechanisms leading to the extension in surge margin.