Gas turbine aero-engines real time on-board modelling: A review, research challenges, and exploring the future

On-board real time modelling for gas turbine aero-engines has been extensively used for engine performance improvement and reliability. This has been achieved by the utilization of on-board model for the engine's control and health management. This paper offers a historical review of on-board modelling applied on gas turbine engines and it also establishes its limitations, and consequently the challenges, which should be addressed to apply the on-board real time model to new and the next generation gas turbine aero-engines. For both applications, i.e. engine control and health management, claims and limitations are analysed via numerical simulation and publicly available data. Regarding the former, the methods for modelling clean and degraded engines are comprehensively covered. For the latter, the techniques for the component performance tracking and sensor/actuator diagnosis are critically reviewed. As an outcome of this systematic examination, two remaining research challenges have been identified: firstly, the requirement of a high-fidelity on-board modelling over the engine life cycle, especially for safety-critical control parameters during rapid transients; secondly, the dependability and reliability of on-board model, which is critical for the engine protection in case of on-board model failure. Multiple model-based on-board modelling and runtime assurance are proposed as potential solutions for the identified challenges and their potential and effectiveness are discussed in detail

Neural nonlinear autoregressive model with exogenous input (Narx) for turboshaft aeroengine fuel control unit model†

none3noOne of the most important parts of a turboshaft engine, which has a direct impact on the performance of the engine and, as a result, on the performance of the propulsion system, is the engine fuel control system. The traditional engine control system is a sensor-based control method, which uses measurable parameters to control engine performance. In this context, engine component degradation leads to a change in the relationship between the measurable parameters and the engine performance parameters, and thus an increase of control errors. In this work, a nonlinear model predictive control method for turboshaft direct fuel control is implemented to improve engine response ability also in presence of degraded conditions. The control objective of the proposed model is the prediction of the specific fuel consumption directly instead of the measurable parameters. In this way is possible decentralize controller functions and realize an intelligent engine with the development of a distributed control system. Artificial Neural Networks (ANN) are widely used as data-driven models for modelling of complex systems such as aeroengine performance. In this paper, two Nonlinear Autoregressive Neural Networks have been trained to predict the specific fuel consumption for several transient flight maneuvers. The data used for the ANN predictions have been estimated through the Gas Turbine Simulation Program. In particular the first ANN predicts the state variables based on flight conditions and the second one predicts the performance parameter based on the previous predicted variables. The results show a good approximation of the studied variables also in degraded conditions.openDe Giorgi M.G.; Strafella L.; Ficarella A.De Giorgi, M. G.; Strafella, L.; Ficarella, A

Research and Technology 1996: Innovation in Time and Space

As the NASA Center responsible for assembly, checkout, servicing, launch, recovery, and operational support of Space Transportation System elements and payloads, the John F. Kennedy Space Center is placing increasing emphasis on its advanced technology development program. This program encompasses the efforts of the Engineering Development Directorate laboratories, most of the KSC operations contractors, academia, and selected commercial industries - all working in a team effort within their own areas of expertise. This edition of the Kennedy Space Center Research and Technology 1996 Annual Report covers efforts of all these contributors to the KSC advanced technology development program, as well as our technology transfer activities

Air Force Institute of Technology Research Report 2005

This report summarizes the research activities of the Air Force Institute of Technology’s Graduate School of Engineering and Management. It describes research interests and faculty expertise; lists student theses/dissertations; identifies research sponsors and contributions; and outlines the procedures for contacting the school. Included in the report are: faculty publications, conference presentations, consultations, and funded research projects. Research was conducted in the areas of Aeronautical and Astronautical Engineering, Electrical Engineering and Electro-Optics, Computer Engineering and Computer Science, Systems and Engineering Management, Operational Sciences, and Engineering Physics

Aeronautical engineering: A continuing bibliography with indexes (supplement 268)

This bibliography lists 406 reports, articles, and other documents introduced into the NASA scientific and technical information system in July, 1991. Subject coverage includes: design, construction and testing of aircraft and aircraft engines; aircraft components, equipment and systems; ground support systems; and theoretical and applied aspects of aerodynamics and general fluid dynamics

Remote Sensing

This dual conception of remote sensing brought us to the idea of preparing two different books; in addition to the first book which displays recent advances in remote sensing applications, this book is devoted to new techniques for data processing, sensors and platforms. We do not intend this book to cover all aspects of remote sensing techniques and platforms, since it would be an impossible task for a single volume. Instead, we have collected a number of high-quality, original and representative contributions in those areas

Current Air Quality Issues

Air pollution is thus far one of the key environmental issues in urban areas. Comprehensive air quality plans are required to manage air pollution for a particular area. Consequently, air should be continuously sampled, monitored, and modeled to examine different action plans. Reviews and research papers describe air pollution in five main contexts: Monitoring, Modeling, Risk Assessment, Health, and Indoor Air Pollution. The book is recommended to experts interested in health and air pollution issues