The development of a parametric-based indirect aircraft structural usage monitoring system using artificial neural networks is described. Flight parametric data, captured during Operational Loads Measurement have been used to predict strains or stresses at key structural locations for several military aircraft types, using mapping relationships determined by artificial neural networks. A framework for the development of a neural network-based structural usage monitor is discussed and the basic architecture of the multilayer perceptron artificial neural network is described. Additionally, results from case studies are presented. It is concluded that this technology could provide the basis for accurate, cost-effective structural usage monitoring systems across the range of military aircraft types and roles.

Numerous military platforms (land, sea and air) feature serial data bus technology based on the US MIL-STD-1553B data bus standard for integration of their digital systems. Many of these platforms have 15-20 years of operational life remaining, but the installed 1553B data buses (data networks) having only a 1Mbit/sec transfer rate are unable to meet many of the future data networking requirements. Research into new, higher performance data networks has concentrated on modern alternatives with throughput increases of two to three orders of magnitude (100Mbit/sec to 1Gbit/sec). These are generally based on modern commercial-off-the-shelf (COTS) standards, good examples being Ethernet and Fibre Channel. Some are already being employed in military platforms having been ruggedised for the harsh physical and electro-magnetic environment. However these COTS systems while being a natural choice for new platforms may not be cost effective for upgrading older platforms. This paper plots the history of MIL-STD-1553, possibly the most successful military platform standard of all time, and discusses some of the options for increasing its performance and economically extending its life into the future.

A solution methodology is developed to solve plane stress problem of composite plates with variable stiffness by using Galerkin technique and polynomials as trial functions. In the solution process, analytical computation has been done wherever it is possible, and analytical-numerical type approach has been made for all problems. The methodology is applied to two known case problems, composite plate with variable fibre content and laminated plate with spatially varying fibre orientations. The formulation of these problems results into coupled partial differential equations (with variable coefficients). The solutions of these equations are obtained using the polynomials as trial functions in the Galerkin method. The results are compared to that of Ritz and collocation technique published elsewhere. The method is found to determine closely both the displacements and the stresses with a few number of terms and in good agreement with other approximating methods. Computations on some examples show that, the method with the help of a symbolic math package is simple and efficient for solving these types of problems in engineering applications.

This paper describes how it is possible to reduce the profile losses on ultra high lift low pressure (LP) turbine blade profiles with the application of selected surface roughness and wake unsteadiness. Over the past several years, an understanding of wake interactions with the suction surface boundary layer on LP turbines has allowed the design of blades with ever increasing levels of lift. Under steady flow conditions, ultra high lift profiles would have large (and possibly open) separation bubbles present on the suction side which result from the very high diffusion levels. The separation bubble losses produced by it are reduced when unsteady wake flows are present. However, LP turbine blades have now reached a level of loading and diffusion where profile losses can no longer be controlled by wake unsteadiness alone.

The ultra high lift profiles investigated here were created by attaching a flap to the trailing edge of another blade in a linear cascade — the so called flap-test technique. The experimental set-up used in this investigation allows for the simulation of upstream wakes by using a moving bar system. Hotwire and hotfilm measurements were used to obtain information about the boundary-layer state on the suction surface of the blade as it evolved in time. Measurements were taken at a Reynolds numbers ranging between 100,000 and 210,000.

Two types of ultra high lift profile were investigated; ultra high lift and extended ultra high lift, where the latter has 25% greater back surface diffusion as well as a 12% increase in lift compared to the former. Results revealed that distributed roughness reduced the size of the separation bubble with steady flow. When wakes were present, the distributed roughness amplified disturbances in the boundary layer allowing for more rapid wake induced transition to take place, which tended to eliminate the separation bubble under the wake. The extended ultra high lift profile generated only slightly higher losses than the original ultra high lift profile, but more importantly it generated 12% greater lift.

The human factors analysis and classification system (HFACS) was developed as an analytical framework for the investigation of the role of human error in aviation accidents. A total of 523 accidents in the Republic of China (ROC) Air Force between 1978 and 2002 were analysed using this framework. The results showed that in a great many cases, poor pilot decision making was implicated. Following a survey of flight instructors’ opinions, two of most promising mnemonic-based methods currently available to guide the decision making of pilots were identified (SHOR and DESIDE). These methods were developed into a short (four hour) aeronautical decision making training course. A total of 41 pilots from the Republic of China Tactical Training Wing then participated in a study to evaluate the effectiveness of this training course. Half of the participants received the short ADM training programme and half did not. Their decision making skill was evaluated in a series of emergency situations presented in a full-flight simulator. Furthermore, their decision making processes were examined in a series of pencil-and-paper based tests. The results clearly showed significant improvements in the quality of pilots’ situation assessment and risk management (underpinning processes in pilot decision making) although this was usually at the expense of speed of response. Pilots used the quicker to apply SHOR mnemonic in situations that which required a fast decision and the more comprehensive but slower to perform DESIDE method when there were fewer time pressures. The results do strongly suggest that ADM is trainable and the short programme devised was effective.

In this Technical Note, is shown that relationships exist between flying qualities levels 1, 2 and 3 and flight conditions expressed in terms of Mach numbers, altitudes and angles-of-attack for the F/A-18 SRA (System Research Aircraft). These relationships are helpful in detecting if derivatives are well calculated for flight tests intermediate conditions.