This paper presents a new adaptive algorithm for the statistical filtering of miniaturised inertial sensor noise. The algorithm uses the minimum variance method to perform a best estimate calculation of the accelerations or angular speeds on each of the three axes of an Inertial Measurement Unit (IMU) by using the information from some accelerometers and gyros arrays placed along the IMU axes. Also, the proposed algorithm allows the reduction of both components of the sensors’ noise (long term and short term) by using redundant linear configurations for the sensors dispositions.

A numerical simulation is performed to illustrate how the algorithm works, using an accelerometer sensor model and a four-sensor array (unbiased and with different noise densities). Three cases of ideal input acceleration are considered: 1) a null signal; 2) a step signal with a no-null time step; and 3) a low frequency sinusoidal signal.

To experimentally validate the proposed algorithm, some bench tests are performed. In this way, two sensors configurations are used: 1) one accelerometers array with four miniaturised sensors (n = 4); and 2) one accelerometers array with nine miniaturised sensors (n = 9). Each of the two configurations are tested for three cases of input accelerations: 0ms−1, 9·80655m/s2 and 9·80655m/s2.

As Large Eddy Simulation is increasingly applied to flows containing complex geometry, grid generation becomes difficult and time consuming when using software originally developed for RANS flow solvers. The traditional ‘pipeline’ approach of grid generation → solve → visualise entails the time consuming transfer of large files and conversion of file formats. This work demonstrates a grid generation methodology developed specifically to be integrated with parallel LES. The current approach is to use a Cartesian grid with adaptive refinement based upon geometry intersection, surface detail and surface curvature. The grid is defined by an octree data structure with the geometry defined by triangular facets using the STL file format. The result is a set of ‘cubical’ subdomains, each with identical numbers of cells and uniform distributions within the cube. Some subdomains will be entirely fluid and can be solved using straightforward CFD techniques, whilst some cubes will be cut by the surfaces. Individual cells are then tagged as ‘solid’, ‘fluid’ or ‘cut’ with the solver expected to use an immersed boundary approach to model the surface. A key feature is the design of the algorithm to be parallelisable on both shared and distributed memory systems. The distributed memory parallel dynamically partitions the grid as it is being generated, so that the partitioning is suitable for a subsequent flow solver. Grid generation testing has been carried out on a variety of input CAD files ranging up to 350,000 facets. A landing gear case shows how the grid generator correctly finds the fluid inside of the tire and other cavities within the hub. In scalar mode, a grid with 4,916 cubes and 468 million cells is generated in less than 100 seconds, whilst in parallel on 32 processor cores this can be achieved in 4·6 seconds.

In this paper a single camera vision guidance system for fixed wing UAV is developed. This system searches for and identifies a target object with known colour and shape from images captured by an onboard camera. HSV colour space and moment invariants are utilised to describe the colour and shape features of the target object. Position, area and rotation angle of the target object in the image plane are collected. This information is then processed by the Extended Kalman Filter to estimate the relative positions and attitudes of the UAV. The vision guidance system guides the UAV towards the target object automatically based on these estimated states by using a proportional controller. A Senior Telemaster aircraft model kit installed with an onboard camera and computer is used for flight test. The target object for the flight test is a white flag with a red cross. Flight simulations and flight tests results are presented in this paper, showing that the vision guidance system can recognise the target object and guide the UAV effectively.

This work presents a study of acoustic oscillations generated and the wave structure associated with supersonic flow past wall mounted 3D open cavities of varying length-to-width (L/W) ratio. Experiments were conducted to investigate the acoustic signature generated by the cavities at freestream Mach number of 1·7. The effect of L/W ratio of the cavity on the dominant modes of the acoustic signature registered on different walls of the cavities is investigated for an L/W range of 0·83-4. Shift in the dominant acoustic mode is observed as L/W ratio changes from 3 to 4. Statistical analysis of pressure data showed existence of acoustic waves and spreading of acoustic energy over different modes with change in cavity width. Time averaged schlieren visualisation indicated variation of shock and shear layer structure in the mainstream for the different cavities. Acoustic waves generated by the presence of the cavity and the dynamic behaviour of the shear layer were observed during instantaneous shadowgraph visualisation. Numerical simulation was done to make a prior assessment of the flow structure and the results are in good agreement with those from experiments. Ratio of mass exchange between cavity and mainflow and the cavity volume was observed to have profound effect on the magnitude of pressure oscillations generated by the cavities.

This paper presents the experimental results of the role of struts in supersonic mixing. Experiments were carried out with novel strut configurations to show their capabilities on mixing with reasonable total pressure losses. The performances were compared with the Baseline Strut configurations (BSPI and BSNI). The analysis presented includes the mixing quantifications using Mie scattering signature, flow field visualisation, measurement of wall static pressure and the total pressure loss calculations. The results clearly demonstrated that the proposed strut configurations achieved increased mixing (7-8%) compared to BSPI with increase in total pressure loss (2%). On the other hand, when compared with BSNI, the mixing performance was found to be decreased by 6% with reduced total pressure loss (12%).

The engine/airframe integration design is one key differentiating factor for making efficient transport aircraft and this topic will become more important for future aircraft as the turbofan engine diameter is increased leading to a stronger engine-airframe interaction. Hopefully, the capabilities of advanced numerical simulations allow the involved complex phenomena to be taken into account and this is illustrated in this paper through several research studies: the use of the Reynolds averaged Navier-Stokes equations together with the drag extraction techniques to predict the drag, the simulation of unsteady complex interaction between the jet and the pylon with the zonal detached eddy simulation method, the pylon and nacelle design through multi disciplinary optimisation and the flow control technologies.