Turbofan

About: Turbofan is a research topic. Over the lifetime, 4114 publications have been published within this topic receiving 39490 citations. The topic is also known as: fanjet & turbofan engine.

Separate boundary layer engine inlet

Abstract: A dual boundary layer engine inlet for a turbofan propulsion engine of an aircraft having a first air inlet positioned generally within the boundary layer flowing around the exterior surface of the aircraft. A first passageway fluidly interconnects the first air inlet and the turbofan propulsion engine to provide air from the boundary layer to the bypass to reduce aerodynamic drag. A second air inlet is positioned generally outside of the boundary layer. This second passageway fluidly interconnecting the second air inlet and the turbofan propulsion engine to provide air outside of the boundary layer to the core and compressor of the turbofan engine to maintain engine efficiency.

Generic Analysis Methods for Gas Turbine Engine Performance: The development of the gas turbine simulation program GSP

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.

Static test-stand performance of the YF-102 turbofan engine with several exhaust configurations for the Quiet Short-Haul Research Aircraft (QSRA)

Abstract: The performance of a YF-102 turbofan engine was measured in an outdoor test stand with a bellmouth inlet and seven exhaust-system configurations. The configurations consisted of three separate-flow systems of various fan and core nozzle sizes and four confluent-flow systems of various nozzle sizes and shapes. A computer program provided good estimates of the engine performance and of thrust at maximum rating for each exhaust configuration. The internal performance of two different-shaped core nozzles for confluent-flow configurations was determined to be satisfactory. Pressure and temperature surveys were made with a traversing probe in the exhaust-nozzle flow for some confluent-flow configurations. The survey data at the mixing plane, plus the measured flow rates, were used to calculate the static-pressure variation along the exhaust nozzle length. The computed pressures compared well with experimental wall static-pressure data. External-flow surveys were made, for some confluent-flow configurations, with a large fixed rake at various locations in the exhaust plume.

Steady-State Modeling of Gas Turbine Engines Using the Numerical Propulsion System Simulation Code

Abstract: The Numerical Propulsion System Simulation (NPSS) code was created through a joint United States industry and National Aeronautics and Space Administration (NASA) effort to develop a state-of-the-art aircraft engine cycle analysis simulation tool. Written in the computer language C++, NPSS is an object-oriented framework allowing the gas turbine engine analyst considerable flexibility in cycle conceptual design and performance estimation. Furthermore, the tool was written with the assumption that most users would desire to easily add their own unique objects and calculations without the burden of modifying the source code. The purpose of this paper is twofold: first, to present an introduction to the discipline of thermodynamic cycle analysis to those who may have some basic knowledge in the individual areas of fluid flow, gas dynamics, thermodynamics, and turbomachinery theory but not necessarily how they are collectively used in engine cycle analysis. Second, this paper will show examples of performance modeling of gas turbine engine cycles specifically using Numerical Propulsion System Simulation concepts and model syntax. Current practices in industry and academia will also be discussed. While NPSS allows both steady-state and transient simulations and is written to facilitate higher orders of analysis fidelity, the pedagogical example will focus primarily on steady-state analysis of an aircraft mixed flow turbofan at the 0-D and 1-D level. Ultimately it is hoped that this paper will provide a starting point by which both the novice cycle analyst and the experienced engineer looking to transition to a superior tool can use NPSS to analyze any kind of practical gas turbine engine cycle in detail.

Relighting a turbofan engine

Abstract: The method and apparatus for in-flight relighting of a turbofan engine involve in one aspect selectively controlling an accessory drag load on one or more windmilling rotors to permit control of the windmill speed to an optimum value for relight conditions.