Band 35, Heft 2 -

ANTICIPATED UNITED STATES CONGRESS ACT should lead to reversing a neglected duty to the people by supporting FAA induced bill to civilize classified military air combat technology to maximize flight safety of airliners and cargo jet transports, in addition to FAA certifying pilots to master Jet-Engine Steering (“JES”) as automatic or pilot recovery when Traditional Aerodynamic-only Flight Control (“TAFC”) fails to prevent a crash and other related damages [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42]. Replacement of propeller driven air vehicles with jet engines marks the first jet-engine historical revolution. Yet designers of TAFC still a priori arrest jet engines to provide only brute force forward – a practice leading to wrong freezing of wings, tails, canards, landing gear, airframe and avionics prior to selection of off-the-shelf jet engine to fit that non-integrated design. A second jet-engine revolution is currently in. It originated by failures of TAFC to function and prevent catastrophes especially in post-stall flight domains, takeoff and landing, which mark the JES-Revolution . Full scale JES implementation started in 1986 in the U.S. by YF-22 design [24, 31, 32, 33, 34]. Three years later the YF-22 prototype was selected over the YF-23 that lacked IPA-78402 JES Technologies [31] like 60+ to 1 kill-ratio advantage during WVR air combat – a revolution gradually followed by RUSSIA, CHINA, INDIA, JAPAN and South KOREA [20, 21, 28]. Civilizing JES to maximize future passengers flight safety by preventing various airlines catastrophes [8] had been successfully first flight tested by a subscale JES-Boeing-727 under U.S. FAA support [8, 25]. Pro and cons of military vs. civil JES-technologies are presented by this editorial.

In this work, the area-averaged film cooling effectiveness (AAFCE) on a gas turbine blade leading edge was predicted by employing an artificial neural network (ANN) using as input variables: hole diameter, injection angle, blowing ratio, hole and columns pitch. The database used to train the network was built using computational fluid dynamics (CFD) based on a two level full factorial design of experiments. The CFD numerical model was validated with an experimental rig, where a first stage blade of a gas turbine was represented by a cylindrical specimen. The ANN architecture was composed of three layers with four neurons in hidden layer and Levenberg-Marquardt was selected as ANN optimization algorithm. The AAFCE was successfully predicted by the ANN with a regression coefficient R 2 <0.99 and a root mean square error RMSE=0.0038. The ANN weight coefficients were used to estimate the relative importance of the input parameters. Blowing ratio was the most influential parameter with relative importance of 40.36 % followed by hole diameter. Additionally, by using the ANN model, the relationship between input parameters was analyzed.

Over the last decade, sustainable energy consumption has attracted the attention of scientists and researchers. The current paper presents sustainability indicators of a small scale turbojet engine, operated on micro-aerial vehicles, for discussion of the sustainable development of the aviation industry from a different perspective. Experimental data was obtained from an engine at full power load and utilized to conduct an exergy-based sustainability analysis. Exergy efficiency, waste exergy ratio, recoverable exergy ratio, environmental effect factor, exergy destruction factor and exergetic sustainability index are evaluated as exergetic sustainability indicators of the turbojet engine under investigation in the current study. The exergy efficiency of the small scale turbojet engine is calculated as 27.25 % whereas the waste exergy ratio, the exergy destruction factor and the sustainability index of the engine are found to be 0.9756, 0.5466 and 0.2793, respectively.

Through establishing control parameters from blade outside to inside, the parametric design of air-cooled turbine blade based on airfoil has been implemented. On the basis of fast updating structure features and generating solid model, a complex cooling system has been created. Different flow units are modeled into a complex network topology with parallel and serial connection. Applying one-dimensional flow theory, programs have been composed to get pipeline network physical quantities along flow path, including flow rate, pressure, temperature and other parameters. These inner units parameters set as inner boundary conditions for external flow field calculation program HIT-3D by interpolation, thus to achieve full field thermal coupling simulation. Referring the studies in literatures to verify the effectiveness of pipeline network program and coupling algorithm. After that, on the basis of a modified design, and with the help of iSIGHT-FD, an optimization platform had been established. Through MIGA mechanism, the target of enhancing cooling efficiency has been reached, and the thermal stress has been effectively reduced. Research work in this paper has significance for rapid deploying the cooling structure design.

Wave rotors are rotating equipment designed to exchange energy between high and low enthalpy fluids by means of unsteady pressure waves. In turbomachinery, they can be used as topping devices to gas turbines aiming to improve performance. The integration of a wave rotor into a ground power unit is far more attractive than into an aeronautical application, since it is not accompanied by any inconvenience concerning the over-weight and extra dimensioning. Two are the most common types of ground industrial gas turbines: The one-shaft and the two-shaft engines. Cycle analysis for both types of gas turbine engines topped with a four-port wave rotor is calculated and their performance is compared to the performance of the baseline engine accordingly. It is concluded that important benefits are obtained in terms of specific work and specific fuel consumption, especially compared to baseline engines with low compressor pressure ratio and low turbine inlet temperature.

The design and verification of assembly operations is essential for planning product production operations. Recently, virtual prototyping has witnessed tremendous progress, and has reached a stage where current environments enable rich and multi-modal interaction between designers and models through stereoscopic visuals, surround sound, and haptic feedback. The benefits of building and using Virtual Reality (VR) models in assembly process verification are discussed in this paper. In this paper, we present the virtual assembly (VA) of an aircraft turbine engine. The assembly parts and sequences are explained using a virtual reality design system. The system enables stereoscopic visuals, surround sounds, and ample and intuitive interaction with developed models. A special software architecture is suggested to describe the assembly parts and assembly sequence in VR. A collision detection mechanism is employed that provides visual feedback to check the interference between components. The system is tested for virtual prototype and assembly sequencing of a turbine engine. We show that the developed system is comprehensive in terms of VR feedback mechanisms, which include visual, auditory, tactile, as well as force feedback. The system is shown to be effective and efficient for validating the design of assembly, part design, and operations planning.

A novel modeling method for aircraft engine using nonlinear autoregressive exogenous (NARX) models based on wavelet neural networks is proposed. The identification principle and process based on wavelet neural networks are studied, and the modeling scheme based on NARX is proposed. Then, the time series data sets from three types of aircraft engines are utilized to build the corresponding NARX models, and these NARX models are validated by the simulation. The results show that all the best NARX models can capture the original aircraft engine’s dynamic characteristic well with the high accuracy. For every type of engine, the relative identification errors of its best NARX model and the component level model are no more than 3.5 % and most of them are within 1 %.

The aircraft industry, along with other industries, is considered responsible these days regarding environmental issues. Therefore, the performance evaluation of aircraft propulsion systems should be conducted with respect to environmental and ecological considerations. The current paper aims to present the ecological coefficient of performance calculation methodology for aircraft propulsion systems. The ecological coefficient performance is a widely-preferred performance indicator of numerous energy conversion systems. On the basis of thermodynamic laws, the methodology used to determine the ecological coefficient of performance for an aircraft propulsion system is parametrically explained and illustrated in this paper for the first time. For a better understanding, to begin with, the exergy analysis of a turbojet engine is described in detail. Following this, the outputs of the analysis are employed to define the ecological coefficient of performance for a turbojet engine. At the end of the study, the ecological coefficient of performance is evaluated parametrically and discussed depending on selected engine design parameters and performance measures. The author asserts the ecological coefficient of performance to be a beneficial indicator for researchers interested in aircraft propulsion system design and related topics.

Film cooling effectiveness on flat plates with double rows of holes has been studied experimentally and numerically in this paper. This configuration is widely used to simulate the multi-row film cooling on turbine vane. Film cooling effectiveness of double rows of holes and each single row was used to study the accuracy of superposition predictions. Method of stable infrared measurement technique was used to measure the surface temperature on the flat plate. This paper analyzed the factors that affect the film cooling effectiveness including hole shape, hole arrangement, row-to-row spacing and blowing ratio. Numerical simulations were performed to analyze the flow structure and film cooling mechanisms between each film cooling row. Results show that the blowing ratio within the range of 0.5 to 2 has a significant influence on the accuracy of superposition predictions. At low blowing ratios, results obtained by superposition method agree well with the experimental data. While at high blowing ratios, the accuracy of superposition prediction decreases. Another significant factor is hole arrangement. Results obtained by superposition prediction are nearly the same as experimental values of staggered arrangement structures. For in-line configurations, the superposition values of film cooling effectiveness are much higher than experimental data. For different hole shapes, the accuracy of superposition predictions on converging-expanding holes is better than cylinder holes and compound angle holes. For two different hole spacing structures in this paper, predictions show good agreement with the experiment results.

Computational investigations on the rib turbulated flow inside a convergent and divergent rectangular channel with square ribs of different rib heights and different Reynolds numbers (Re=20,000, 40,000 and 60,000). The ribs were arranged in a staggered fashion between the upper and lower surfaces of the test section. Computational investigations are carried out using computational fluid dynamic software ANSYS Fluent 14.0. Suitable solver settings like turbulence models were identified from the literature and the boundary conditions for the simulations on a solution of independent grid. Computations were carried out for both convergent and divergent channels with 0 (smooth duct), 1.5, 3, 6, 9 and 12 mm rib heights, to identify the ribbed channel with optimal performance, assessed using a thermo hydraulic performance parameter. The convergent and divergent rectangular channels show higher Nu values than the standard correlation values.