Computational aerodynamic analysis on perimeter reinforced （PR）-compliant wing

Abstract Implementing the morphing technique on a micro air vehicle （MAV） wing is a very chal- lenging task, due to the MAWs wing size limitation and the complex morphing mechanism. As a result, understanding aerodynamic characteristics and flow configurations, subject to wing structure deformation of a morphing wing MAV has remained obstructed. Thus, this paper presents the investigation of structural deformation, aerodynamics performance and flow formation on a pro- posed twist morphing MAV wing design named perimeter reinforced （PR）-compliant wing. The numerical simulation of two-way fluid structure interaction （FSI） investigation consist of a quasi- static aeroelastic structural analysis coupled with 3D incompressible Reynolds-averaged Navier- Stokes and shear-stress-transport （RANS-SST） solver utilized throughout this study. Verification of numerical method on a rigid rectangular wing achieves a good correlation with available exper- imental results. A comparative aeroelastic study between PR-compliant to PR and rigid wing per- formance is organized to elucidate the morphing wing performances. Structural deformation results show that PR-compliant wing is able to alter the wing＇s geometric twist characteristic, which has directly influenced both the overall aerodynamic performance and flow structure behavior. Despite the superior lift performance result, PR-compliant wing also suffers from massive drag penalty, which has consequently affected the wing efficiency in general. Based on vortices investigation, the results reveal the connection between these aerodynamic performances with vortices formation on PR-comoliant wing.     

Ship target recognition using low resolution radar and neuralnetworks

The classification of ship targets using low resolution down-range radar profiles together with preprocessing and neural networks is investigated. An implementation of the Fourier-modified discrete Mellin transform is used as a means for extracting features which are insensitive to the aspect angle of the radar. Kohonen's self-organizing map with learning vector quantization (LVQ) is used for the classification of these feature vectors. The use of a feedforward network trained with the backpropagation algorithm is also investigated. The classification system is applied to both simulated and real data sets. Classification accuracies of up to 90% are reported for the real data, provided target aspect angle information is available to within an error not exceeding 30 deg     

Standardisation of the graphical and operator input device modulesfor tactical command and control man/machine interfaces

Since many of the MMI systems designed for Tactical Command and Control operating environments are similar in nature, there is a need to standardise certain elements of the systems. This paper gives a summary of the investigation into standardising certain graphical MMI elements, and operator input device elements for Tactical Command and Control systems. This standardisation allows for rapid prototyping on low-cost platforms, as well as enabling the code to be transferred easily between different operating platforms     

Standardisation of the graphical and operator input device modulesfor tactical command and control man-machine interfaces

Since many of the MMI systems designed for tactical command and control operating environments are similar in nature, there is a need to standardise certain elements of the systems. This paper gives a summary of the investigation into standardising certain graphical MMI elements, and operator input device elements for tactical command and control systems. This standardisation allows for rapid prototyping on low-cost platforms, as well as enabling the code to be transferred easily between different operating platforms