Small Engine Component Technology (SECT) study. Program report

The study was conducted to identify high payoff technologies for year 2000 small gas turbine applications and to provide a technology plan for guiding future research and technology efforts. A regenerative cycle turboprop engine was selected for a 19 passenger commuter aircraft application. A series of engines incorporating eight levels of advanced technologies were studied and their impact on aircraft performance was evaluated. The study indicated a potential reduction in fuel burn of 38.3 percent. At $1.00 per gallon fuel price, a potential DOC benefit of 12.5 percent would be achieved. At$2.00 per gallon, the potential DOC benefit would increase to 17.0 percent. Four advanced technologies are recommended and appropriate research and technology programs were established to reach the year 2000 goals

An Intelligent Fuse-box for use with Renewable Energy Sources integrated within a Domestic Environment

This paper outlines a proposal for an intelligent fuse-box that can replace existing fuse-boxes in a domestic context such that a number of renewable energy sources can easily be integrated into the domestic power supply network, without the necessity for complex islanding and network protection. The approach allows intelligent control of both the generation of power and its supply to single or groups of electrical appliances. Energy storage can be implemented in such a scheme to even out the power supplied and simplify the control scheme required, and environmental monitoring and load analysis can help in automatically controlling the supply and demand profiles for optimum electrical and economic efficiency. Simulations of typical scenarios are carried out to illustrate the concept in operation

Design and evaluation of an integrated Quiet, Clean General Aviation Turbofan (QCGAT) engine and aircraft propulsion system

The design was based on the LTS-101 engine family for the core engine. A high bypass fan design (BPR=9.4) was incorporated to provide reduced fuel consumption for the design mission. All acoustic and pollutant emissions goals were achieved. A discussion of the preliminary design of a business jet suitable for the developed propulsion system is included. It is concluded that large engine technology can be successfully applied to small turbofans, and noise or pollutant levels need not be constraints for the design of future small general aviation turbofan engines

Heat transfer in aeropropulsion systems

Aeropropulsion heat transfer is reviewed. A research methodology based on a growing synergism between computations and experiments is examined. The aeropropulsion heat transfer arena is identified as high Reynolds number forced convection in a highly disturbed environment subject to strong gradients, body forces, abrupt geometry changes and high three dimensionality - all in an unsteady flow field. Numerous examples based on heat transfer to the aircraft gas turbine blade are presented to illustrate the types of heat transfer problems which are generic to aeropropulsion systems. The research focus of the near future in aeropropulsion heat transfer is projected

NARX models for simulation of the start-up operation of a single-shaft gas turbine

In this study, nonlinear autoregressive exogenous (NARX) models of a heavy-duty single-shaft gas turbine (GT) are developed and validated. The GT is a power plant gas turbine (General Electric PG 9351FA) located in Italy. The data used for model development are three time series data sets of two different maneuvers taken experimentally during the start-up procedure. The resulting NARX models are applied to three other experimental data sets and comparisons are made among four significant outputs of the models and the corresponding measured data. The results show that NARX models are capable of satisfactory prediction of the GT behavior and can capture system dynamics during start-up operation

Modelling the transitional boundary layer

Recent developments in the modelling of the transition zone in the boundary layer are reviewed (the zone being defined as extending from the station where intermittency begins to depart from zero to that where it is nearly unity). The value of using a new non-dimensional spot formation rate parameter, and the importance of allowing for so-called subtransitions within the transition zone, are both stressed. Models do reasonably well in constant pressure 2-dimensional flows, but in the presence of strong pressure gradients further improvements are needed. The linear combination approach works surprisingly well in most cases, but would not be so successful in situations where a purely laminar boundary layer would separate but a transitional one would not. Intermittency-weighted eddy viscosity methods do not predict peak surface parameters well without the introduction of an overshooting transition function whose connection with the spot theory of transition is obscure. Suggestions are made for further work that now appears necessary for developing improved models of the transition zone

RANS closure approximation by artificial neural networks

Turbulence modelling remains a challenge for the simulation of turbomachinery flows. Reynolds Averaged Navier-Stokes (RANS) equations will still be used for high-Reynolds number flows for several years and so there is interest in improving their prediction capability. Machine learning techniques offer several strategies which could be exploited for this purpose. In this work, an approach to improve the Spalart-Allmaras model is investigated. In particular, the model is used to predict the flow around the T106c low pressure gas turbine cascade. As a first step, an Artificial Neural Network (ANN) is trained on the data generated by the original model. Then, an optimisation procedure is applied in order to find the weights of the network which minimise the error between the predicted results and the available experimental data. The new model is tested at different Reynolds numbers on the T106c cascade and on a wind turbine airfoil in post-stall conditions. Significant improvements are observed in the condition chosen for the optimisation. Future work will be devoted to the generalisation of the approach by including multiple working conditions optimisations and adding new physical variables as inputs of the ANN

Aeronautical Engineering. A continuing bibliography with indexes, supplement 156

This bibliography lists 288 reports, articles and other documents introduced into the NASA scientific and technical information system in December 1982

Consistency Index-Based Sensor Fault Detection System for Nuclear Power Plant Emergency Situations Using an LSTM Network

A nuclear power plant (NPP) consists of an enormous number of components with complex interconnections. Various techniques to detect sensor errors have been developed to monitor the state of the sensors during normal NPP operation, but not for emergency situations. In an emergency situation with a reactor trip, all the plant parameters undergo drastic changes following the sudden decrease in core reactivity. In this paper, a machine learning model adopting a consistency index is suggested for sensor error detection during NPP emergency situations. The proposed consistency index refers to the soundness of the sensors based on their measurement accuracy. The application of consistency index labeling makes it possible to detect sensor error immediately and specify the particular sensor where the error occurred. From a compact nuclear simulator, selected plant parameters were extracted during typical emergency situations, and artificial sensor errors were injected into the raw data. The trained system successfully generated output that gave both sensor error states and error-free states