Aerodynamic Optimisation of Highly Loaded Turbine Cascade Blades for Heavy Duty Gas Turbine Applications

The present work deals with the development and validation of a method for the automatic aerodynamic optimisation of turbine cascade blades for high pressure stages of heavy duty gas turbines. This class of profiles features aerodynamic and geometric properties which can strongly depart from typical conditions of turbine profiles for aero engines applications. In fact, the Reynolds number and the trailing edge thickness of these profiles can be an order of magnitude higher than the corresponding values of aeronautical gas turbines. In order to gain better insight into these major differences, extensive experimental investigations were performed at the High Speed Cascade Wind Tunnel of the University of the German Armed Forces Munich on various turbine cascade blades. A comparison of the optimisation results and the reference turbine cascades attests the high potential of the developed procedure. The developed tool is conceived for the application in an industrial framework and design time scales compatible with industrial requirements have to be considered as well. In this context a method consisting of a two-dimensional RANS flow simulation approach combined with a parametric geometry generator and an optimisation algorithm is proposed. Various stochastic global optimisation techniques were tested. The Adaptive Simulated Annealing algorithm demonstrated best properties for a detailed investigation of wide parameter ranges in reduced timeframes. The main optimisation target in this work was the reduction of the cascade total pressure losses by fixing the operating point. Additional requirements on the profile pressure distribution were introduced as well in order to allow optimal conditions for an efficient cooling of the blade. In fact, a major goal of the present work was the development of an aerodynamic design method which does not merely optimise the location of the transition zone on the blade suction surface, but also ensures profile velocity distributions satisfying major aerodynamic requirements for the optimal cooling of the blade (e.g. smooth acceleration on the suction and pressure surface). All these requirements were integrated in a single value objective function. The form of the various components of the scalar function was tailored ad hoc in extensive preliminary studies. Furthermore, some major mechanic and geometric constraints were specified. In this way the optimisation task was reduced to a single-objective, constrained approach. The results of the proposed numerical design system indicate that the present method is able to generate blade geometries with reduced losses and featuring profile velocity distributions which ensure favourable conditions for the cooling of the blade. The reliability of the method at changed geometric and mechanical boundary conditions was demonstrated as well.Die Erhöhung der Turbineneintrittstemperatur ist ein wesentliches Mittel zur Wirkungsgradsteigerung der Gasturbinen. Dies kann nur durch die Anwendung fortschrittlicher Materialien und Fertigungstechniken erzielt werden. Trotz der niedrigeren Temperaturen in Kraftwerks-Gasturbinen im Vergleich zu Flugtriebwerken, sind die Lebenserwartungen für die Komponenten von Gasturbinen für Stromerzeugung deutlicher höher als die für die Komponenten von Flugtriebwerken. All dies erhöht die Kosten für die Herstellung der vorderen Stufen moderner Gasturbinen für stationäre Anwendungen. In diesem Zusammenhang stellt die Reduzierung der Schaufelanzahl einen praktikablen Weg für die Kostensenkung dar. Um die damit verbundene Erhöhung der Belastung bei gleichbleibendem Wirkungsgrad zu ermöglichen, sind neue Auslegungskriterien für diese Klasse von Schaufelprofilen notwendig. Umfangreiche experimentelle Untersuchungen wurden am Hochgeschwindigkeits-Gitterwindkanal der Universität der Bundeswehr München durchgeführt, um Erfahrungen auf typische Schaufelprofile für die Anwendung in stationärer Gasturbinen zu gewinnen. Die experimentellen Daten dienten zur Validierung vorhandener Korrelationen und Rechenverfahren für diesen Einsatzbereich. Darüberhinaus ein automatisches System für die aerodynamische Optimierung zwei-dimensionaler Schaufelgitter wurde entwickelt und auf Basis der vorhandenen experimentellen Daten validiert. Die Methode setzt sich aus einem parametrischen Geometriegenerator, einem Navier-Stokes-Rechenverfahren und einem Optimierungsalgorithmus zusammen. Ziel der Optimierung ist die Reduzierung der Totaldruckverluste bei gleichbleibender Enthalpieumsetzung unter Berücksichtigung der Anforderung an die Machzahl-Verteilung für eine effiziente Kühlung des Profils. Zusätzliche mechanische und geometrische Randbedingungen für die resultierenden Schaufelprofile wurden berücksichtigt. Das entwickelte Verfahren zeigt hohes Potential für die Auslegung hochbelasteter, verlustarmer Turbinenschaufelprofile

A case study in CAD design automation

Computer-aided design (CAD) software and other product life-cycle management (PLM) tools have become ubiquitous in industry during the past 20 years. Over this time they have continuously evolved, becoming programs with enormous capabilities, but the companies that use them have not evolved their design practices at the same rate. Due to the constant pressure of bringing new products to market, commercial businesses are not able to dedicate the resources necessary to tap into the more advanced capabilities of their design tools that have the potential to significantly reduce both time-to-market and quality of their products. Taking advantage of these advanced capabilities would require little time and out-of-pocket expense, since the companies already own the licenses to the software. This article details the work of a small research team working in conjunction with a major turbine engine manufacturer endeavoring to make better use of the underutilized capabilities of their design software. By using the scripting language built into their CAD package for design automation, knowledge-based engineering applications, and efficient movement of data between design packages, the company was able to significantly reduce design time for turbine design, increase the number of feasible design iterations, increase benefits from relational modeling techniques, and increase the overall quality of their design processes

A geometric framework for immersogeometric analysis

The purpose of this dissertation is to develop a geometric framework for immersogeometric analysis that directly uses the boundary representations (B-reps) of a complex computer-aided design (CAD) model and immerses it into a locally refined, non-boundary-fitted discretization of the fluid domain. Using the non-boundary-fitted mesh which does not need to conform to the shape of the object can alleviate the challenge of mesh generation for complex geometries. This also reduces the labor-intensive and time-consuming work of geometry cleanup for the purpose of obtaining watertight CAD models in order to perform boundary-fitted mesh generation. The Dirichlet boundary conditions in the fluid domain are enforced weakly over the immersed object surface in the intersected elements. The surface quadrature points for the immersed object are generated on the parametric and analytic surfaces of the B-rep models. In the case of trimmed surfaces, adaptive quadrature rule is considered to improve the accuracy of the surface integral. For the non-boundary-fitted mesh, a sub-cell-based adaptive quadrature rule based on the recursive splitting of quadrature elements is used to faithfully capture the geometry in intersected elements. The point membership classification for identifying quadrature points in the fluid domain is based on a voxel-based approach implemented on GPUs. A variety of computational fluid dynamics (CFD) simulations are performed using the proposed method to assess its accuracy and efficiency. Finally, a fluid--structure interaction (FSI) simulation of a deforming left ventricle coupled with the heart valves shows the potential advantages of the developed geometric framework for the immersogeomtric analysis with complex moving domains

State-of-the-art in aerodynamic shape optimisation methods

Aerodynamic optimisation has become an indispensable component for any aerodynamic design over the past 60 years, with applications to aircraft, cars, trains, bridges, wind turbines, internal pipe flows, and cavities, among others, and is thus relevant in many facets of technology. With advancements in computational power, automated design optimisation procedures have become more competent, however, there is an ambiguity and bias throughout the literature with regards to relative performance of optimisation architectures and employed algorithms. This paper provides a well-balanced critical review of the dominant optimisation approaches that have been integrated with aerodynamic theory for the purpose of shape optimisation. A total of 229 papers, published in more than 120 journals and conference proceedings, have been classified into 6 different optimisation algorithm approaches. The material cited includes some of the most well-established authors and publications in the field of aerodynamic optimisation. This paper aims to eliminate bias toward certain algorithms by analysing the limitations, drawbacks, and the benefits of the most utilised optimisation approaches. This review provides comprehensive but straightforward insight for non-specialists and reference detailing the current state for specialist practitioners

Development of a Methodology for Performance Optimisation and Manufacturing Sensitivity Studies for Radial Flow Turbocharger Compressors for 21st Century Legislation

The use of algorithmic optimisation techniques whereby several designs are evaluated automatically in batches using Computational Structural Mechanics (CSM) and or Computational Fluid Dynamics (CFD) modelling to improve performance, has become an integral part of turbomachinery design process. Designing radial compressors for better performance as well as manufacturing the impeller such that there are no discrepancies between the designed surface and machined surface represents a significant challenge for the industry. Accounting for geometric variability (to model manufacturing errors) during the design/optimisation phase where hundreds of candidate geometries are evaluated is costly due to the large number of calculations required to analyse the possible combinations of manufacture errors for each new geometry design. This thesis addressed the problem by separating the design phase from the manufacture uncertainty calculations phase, focusing on a common 5-axis milling type error – undercut; and using a low cost high throughput computing cluster to meet the computational requirements of both phases. A bespoke parametric CAD algorithm was developed to automate the geometry creation during the optimisation phase. The Differential Evolution for Multi-Objective Optimisation (DEMO) algorithm was used to drive the optimisation calculations. In-house meshing software from Napier Turbochargers Ltd, subsequently referred to as Napier, was used to mesh the computational domain, which was then solved using a commercial CFD solver. The compressor in the high-pressure (HP) stage of a two-stage turbocharger was optimised, and shows significant improvements in measured parameters - up to 1.6 points of efficiency gain and 20% increase in map width, respectively. The calculations were carried out on a HTCondor cluster of 8 Linux workstations. Moreover, a study on the sensitivity of radial compressor aerodynamic performance to the presence of an undercut on the impeller surface was also carried out. In-house software from Napier was used to create an undercut on the impeller surface by modifying the CAD geometry file. The impact of the undercut on performance was quantified using detail 3D CFD analysis. Various undercut height and width levels at 13 different locations on the blade surface were analysed for three compressor designs. A unique sensitivity distribution for each compressor impeller is calculated and used to create a variable tolerance map on the impeller surface. This approach was shown to facilitate savings in cost by reducing scrap rate. In addition, a bespoke 1-D algorithm for estimating the size of a radial compressor impeller required to meet a design mass flow and pressure ratio at a given rotor speed was developed. The model can be used PhD Thesis – O. F. Okhuahesogie Page 5 as a preliminary tool when designing a new compressor (where there is no previous experimental or numerical data). The algorithm is based on a combination of fundamental turbomachinery physics equations, correlations extracted from literature and statistical modelling. Finally, an algorithm for calculating the flow area and air mass flow of the low pressure (LP) and high pressure (HP) compressors and turbines in a two-stage turbocharger required to meet a diesel engine specification was developed. The algorithm was used to validate the flow specification of a two-stage turbocharger for a test diesel engine

AN INVESTIGATION OF EVOLUTIONARY COMPUTING IN SYSTEMS IDENTIFICATION FOR PRELIMINARY DESIGN

This research investigates the integration of evolutionary techniques for symbolic regression. In particular the genetic programming paradigm is used together with other evolutionary computational techniques to develop novel approaches to the improvement of areas of simple preliminary design software using empirical data sets. It is shown that within this problem domain, conventional genetic programming suffers from several limitations, which are overcome by the introduction of an improved genetic programming strategy based on node complexity values, and utilising a steady state algorithm with subpopulations. A further extension to the new technique is introduced which incorporates a genetic algorithm to aid the search within continuous problem spaces, increasing the robustness of the new method. The work presented here represents an advance in the Geld of genetic programming for symbolic regression with significant improvements over the conventional genetic programming approach. Such improvement is illustrated by extensive experimentation utilising both simple test functions and real-world design examples

Non-Proportional Fatigue by Example of Fiber-Reinforced Rotor Blade Adhesive

Structural optimization relies on precisely known material data and accurate yet computationally efficient damage prediction models. In this regard, non-proportional fatigue represents a major source of uncertainty due to a more complex material behavior. While non-proportional loads are found in a large variety of industries, the associated modeling uncertainties lead to increased levelized cost of energy in terms of wind turbines, an unacceptable condition given the urgency of a sustainable global economy. In the wind energy industry tests on the coupon, sub-component and full-scale level are predominantly based on uniaxial loads. In addition, the specimen quality in these tests does not always match the mass-production quality. This is particularly true for the design-driving adhesive joints of rotor blades, where hand-mixed specimens are the state of the art even though dosing machines are applied in rotor blade manufacture. The numerical uncertainty regarding non-proportional fatigue is thus amplified based on a deficit of experiments with representative specimens. This thesis presents a new concept to both accurately and efficiently predict the non-proportional fatigue life by example of a fiber-reinforced rotor blade adhesive. In order to achieve this, the influence of non-proportional loads on the cycles to failure of the adhesive needed to be identified with high certainty. Therefore, manufacturing-induced defects such as pores or stress concentrations on account of the specimen geometry were minimized, resulting in the first virtually defect-free rotor blade adhesive specimens that are suitable for multiaxial experiments. A detailed multiaxial material characterization in static and fatigue loading conditions revealed several misconceptions in comparison to literature such as a rather ductile material behavior, associated modeling differences of (elasto-plastic) shear stresses, a more representative yield criterion (Drucker-Prager) and S-N model (Stüssi-Haibach). Based on the unique experimental data, it was demonstrated that global rainflow-counted equivalent stresses lead to a good fatigue life prediction for proportional loads, while an over-prediction of the fatigue life of up to two orders of magnitude in non-proportional loads is possible. Critical plane algorithms were calibrated using the new experimental data set and found to be substantially more accurate, but impractical due to an extensive computation time and complicated validation. However, a FFT-based re-proportionalization of the stress state in combination with a S-N-based correction factor allows to use global equivalent stresses again in phase shift-induced non-proportional conditions. This way, accurate fatigue life predictions are possible that are several orders of magnitude faster than the critical plane approach. Although demonstrated with a rotor blade adhesive, the new approach can be used with any equivalent stress criterion and thus for any material when a phase shift is the main source of non-proportionality.Federal Ministry for Economic Affairs and Climate Action (BMWK)/ReliaBlade/0324335B/E

Structured grid generation for gas turbine combustion systems

Commercial pressures to reduce time-scales encourage innovation in the design and analysis cycle of gas turbine combustion systems. The migration of Computational Fluid Dynamics (CFD) from the purview of the specialist into a routine analysis tool is crucial to achieve these reductions and forms the focus of this research. Two significant challenges were identified: reducing the time-scale for creating and solving a CFD prediction and reducing the level of expertise required to perform a prediction. The commercial pressure for the rapid production of CFD predictions, coupled with the desire to reduce the risk associated with adopting a new technology led, following a review of available techniques, to the identification of structured grids as the current optimum methodology. It was decided that the task of geometry definition would be entirely performed within commercial Computer Aided Design (CAD) systems. A critical success factor for this research was the adoption of solid models for the geometry representation. Solids ensure consistency, and accuracy, whilst eliminating the need for the designer to undertake difficult, and time consuming, geometry repair operations. The versatility of parametric CAD systems were investigated on the complex geometry of a combustion system and found to be useful in reducing the overhead in altering the geometry for a CFD prediction. Accurate and robust transfer between CAD and CFD systems was achieved by the use of direct translators. Restricting the geometry definition to solid models allowed a novel two stage grid generator to be developed. In stage one an initial algebraic grid is created. This reduces user interaction to a minimum, by the employment of a series of logical rules based on the solid model to fill in any missing grid boundary condition data. In stage two the quality of the grid is improved by redistributing nodes using elliptical partial differential equations. A unique approach of improving grid quality by simultaneously smoothing both internal and surface grids was implemented. The smoothing operation was responsible for quality, and therefore reduced the level of grid generation expertise required. The successful validation of this research was demonstrated using several test cases including a CFD prediction of a complete combustion system

An inverse design methodology for long last-stage steam turbine blades

The last stage of an axial steam turbine is characterized by transonic flow and high volume flow rates. The resulting turbine blades are very large in size and complex in shape. This poses great design challenges, which last-stage blades are infamous for amongst steam turbine designers. Additionally, two-phase flows of condensing steam are always the case, and accurate numerical predictions of performance become often arduous. Inverse design has been used for several years and with great success in a variety of turbomachinery applications. However, no specific inverse design strategy has been developed for large axial steam turbines, and last-stage blades in particular. The first requirement that comes to mind for a steam-turbine specific inverse method is the inclusion of two-phase e↵ects. However, several other problems arise when dealing with the geometries typical of the last stage. The aim of this project is to identify and analyse the problems and requirements, and then develop some specific solutions which will allow the creation of a dedicated inverse design procedure. The first part of the project deals with a traditional inverse method and the inclusion of two-phase effects. The problems are then highlighted and two attempts are made to create a methodology that would work for last-stage blades. After devising a new way of describing blade profiles, the first method is introduced, based on a transpiration model. The second method is circulation based, and works through the prescription of circumferentially averaged swirl velocity. Finally, a design strategy is suggested for the whole redesign of a last stage rotor