Generic Analysis Methods for Gas Turbine Engine Performance

Abstract

Numerical modelling and simulation have played a critical role in the research and development towards today’s powerful and efficient gas turbine engines for both aviation and power generation. The simultaneous progress in modelling methods, numerical methods, software development tools and methods, and computer platform technology has provided the gas turbine community with ever more accurate design, performance prediction and analysis tools. An important element is the development towards generic tools, in order to avoid duplication of model elements for different engine types. This thesis focuses on the development of generic gas turbine system performance simulation methods. This includes the research required to find the optimal mathematical representation of the aero-thermodynamic processes in the gas turbine components in terms of fidelity, accuracy and computing power limitations. The results have been applied in the development of the Gas turbine Simulation Program GSP. GSP is a modelling tool for simulation and analysis of gas turbine system performance. This involves 0-D (i.e. zero-dimensional or parametric) component sub-models that calculate averaged values for parameters such as pressures and temperatures at the gas path stations between the components. The component sub-models are configured (‘stacked’) corresponding to the gas turbine configuration. Component performance is determined by both aero-thermodynamic equations and user specified characteristics, such as turbomachinery performance maps. If higher fidelity is required at a specific location in the system model, 1-D component models can be added to predict the change in gas state or other parameters as a function of a spatial (usually in the direction of a streamline) parameter. Non-linear differential equations (NDEs) are used to represent the conservation laws and other relations among the components. The sets of NDEs are automatically configured depending on the specific gas turbine configuration and type of simulation. Simulation types include design point (DP), steady-state off-design (OD) and transient simulations. The research and development challenge lies in the development of generic, accurate and user friendly system modelling methods with sufficient flexibility to represent any type of gas turbine configuration. The accuracy and fidelity is enhanced by the development of modelling methods capturing secondary effects on component and system performance in 0-D or 1-D sub-models. Object oriented software design methods have been used to accomplish the flexibility objectives, also resulting in a high degree of code maintainability. This allows easy adaptation and extension of functionalities to meet new requirements that are emerging since the start of the development of GSP in its current form (1997). The object oriented architecture and how it relates to the system and component modelling and the ensuing solving of the NDEs, is described in the thesis. An important element has been the development of the gas model with chemical equilibrium and gas composition calculations throughout the cycle. Fuel composition can be specified in detail for accurate prediction of effects of alternative fuels and also detailed emission prediction methods are added. The gas model uses a unique and efficient method to iterate towards chemical equilibrium . The object oriented architecture enabled the embedding of a generic adaptive modelling (AM) functionality in the GSP numerical process and NDEs, providing best AM calculation speed and stability. With AM, model characteristics are adapted for matching specified (often measured) output parameter values for engine test analysis, diagnostics and condition monitoring purposes. The AM functionality can be directly applied to any GSP engine model. The recent trend towards the development of micro turbines (with very high surface-to-volume ratios in the gas path) requires accurate representation of thermal (heat transfer) effects on performance. For this purpose, GSP has been extended with an object oriented thermal network modelling capability. Also, a 1-D thermal model for representing the significant heat soakage effects on micro turbine recuperator transient performance has been developed. For real-time transient simulation, the Turbine Engine Real-Time Simulator (TERTS) modelling tool has been derived from GSP. In TERTS, the methods from GSP are used with fidelity reduced to some extent in order to meet the real-time execution requirements. GSP has been applied to a wide variety of gas turbine performance analysis problems. The adaptive modelling (AM) based gas path analysis functionality has been applied in several gas turbine maintenance environments. Isolation of deteriorated and faulty turbofan engine components was successfully demonstrated using both test rig data and on-wing data measured on-line during flight. For a conceptual design of a 3kW recuperated micro turbine for CHP applications, design point cycle parameters were optimized based on careful component efficiency and loss estimates. Worst and best case scenarios were analysed with GSP determining sensitivity to deviations from the estimates. The predictions have proven very accurate after a test program showing 12% (electric power) efficiency on the first prototype. For increasing the efficiency towards 20%, GSP was used to predict the impact of several design improvements on system efficiency. GSP was used to study the effects on performance and losses of scaling micro turbines in the range of 3 to 36 kW. At small scales, turbomachinery losses become relatively large due to the smaller Reynolds number (larger viscous losses) and other effects. The scale effects have been analysed and modelled for the turbine and compressor and GSP has been used to predict the effects on system efficiency. Other applications include prediction of cumulative exhaust gas emissions of the different phases of commercial aircraft flights, simulation of thermal load profiles for hot section lifing studies, alternative fuel effect studies, performance prediction of vertical take-off propulsion systems and reverse engineering studies. The object oriented design of GSP has proven its value and has provided the building blocks for an ever increasing number of component models, adaptations and extensions. The flexibility of GSP is demonstrated with the modelling of novel cycles, including a parallel twin spool micro turbine with a single shared combustor, a rotating combustor micro turbine concept, a modern heavy duty gas turbine with a second (reheat) combustor and a multi-fuel hybrid turbofan engine, also with a reheat combustor. Several new capabilities have been developed following new requirements from the user community, using the original object oriented framework and component model classes. In the future, new technologies may replace today’s simulation tools. Maybe even the concept of modelling and simulation as we know it today will entirely change. However, as long as gas turbines and related systems will be developed and operated, there will be a need to understand their behaviour. The fundamental physics behind this will not change nor will the equations describing the processes. In that sense, GSP can be seen as a phase in the development of gas turbine modelling and simulation technology. An interesting question would be, how long will GSP remain before it is left behind for new ways. A lot will depend on the ability of GSP and its developers to adapt to future needs and also future opportunities emerging from new modelling, simulation, and computer and software technologies. So far however, GSP has proven a remarkable track record and will be around for quite a while, serving many scientists and engineers interested in gas turbine system performance analysis and simulation.