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Various assessments of RANS and Hybrid RANS-LES turbulence models have been conducted for automotive applications. However, their applicability for high performance vehicles which exhibit much more complex flow phenomena is not well studied yet. In this work, the predictive capabilities of RANS and DDES models are investigated through a comparative study on a high performance configuration of the DrivAer Fastback model at a low ground clearance in an open road computational domain. The results show much agreement in the general pressure distribution, except in areas of highly unsteady flow. Visualisation of the flow field depicts that the DDES simulation is able to capture a wider range of turbulent scales with a higher fidelity. Lastly, variation in the magnitude, distribution and decay of pressure losses in the wake are observed between both simulations. The presented results are used to illustrate the capabilities and limitations of these turbulence models for other academic or industrial users to make an informed decision on the turbulence model suited for their objectives.

Autonomous survey vessels can increase the efficiency and availability of wide-area river environment surveying as a tool for environment protection and conservation. A key challenge is the accurate localisation of the vessel, where bank-side vegetation or urban settlement preclude the conventional use of line-of-sight global navigation satellite systems (GNSS). In this paper, we evaluate unaided visual odometry, via an on-board stereo camera rig attached to the survey vessel, as a novel, low-cost localisation strategy. Feature-based and appearance-based visual odometry algorithms are implemented on a six degrees of freedom platform operating under guided motion, but stochastic variation in yaw, pitch and roll. Evaluation is based on a 663 m-long trajectory (&gt, 15,000 image frames) and statistical error analysis against ground truth position from a target tracking tachymeter integrating electronic distance and angular measurements. The position error of the feature-based technique (mean of ±0.067 m) is three times smaller than that of the appearance-based algorithm. From multi-variable statistical regression, we are able to attribute this error to the depth of tracked features from the camera in the scene and variations in platform yaw. Our findings inform effective strategies to enhance stereo visual localisation for the specific application of river monitoring.

The construction of fish passes has been a longstanding measure to improve river ecosystem status by ensuring the passability of weirs, dams and other in- channel structures for migratory fish. Many fish passes have a low biological effectiveness because of unsuitable hydrodynamic conditions hindering fish to rapidly detect the pass entrance. There has been a need for techniques to quantify the hydrodynamics surrounding fish pass entrances in order to identify those passes that require enhancement and to improve the design of new passes. This PhD thesis presents the development of a methodology for the rapid, spatially continuous quantification of near-pass hydrodynamics in the field. The methodology involves moving-vessel Acoustic Doppler Current Profiler (ADCP) measurements in order to quantify the 3-dimensional water velocity distribution around fish pass entrances. The approach presented in this thesis is novel because it integrates a set of techniques to make ADCP data robust against errors associated with the environmental conditions near engineered in-channel structures. These techniques provide solutions to (i) ADCP compass errors from magnetic interference, (ii) bias in water velocity data caused by spatial flow heterogeneity, (iii) the accurate ADCP positioning in locales with constrained line of sight to navigation satellites, and (iv) the accurate and cost-effective sensor deployment following pre-defined sampling strategies. The effectiveness and transferability of the methodology were evaluated at three fish pass sites covering conditions of low, medium and high discharge. The methodology outputs enabled a detailed quantitative characterisation of the fish pass attraction flow and its interaction with other hydrodynamic features. The outputs are suitable to formulate novel indicators of hydrodynamic fish pass attractiveness and they revealed the need to refine traditional fish pass design guidelines.

Nowadays, research in automotive and construction industries focuses on materials that offer low density along with superior dynamic and static performance. This goal has led to increasing use of composites in general, and carbon fibre (CF) composites in particular. CF composites have been adopted widely in the space industry and motorsports. However, their high stiffness and low density leads to low damping performance, which is responsible for increased levels of noise and reduction in service life. On the other hand, natural fibres (NF) like flax fibres (FF) are capable of delivering a much better damping performance. A hybrid composite comprising of FF and CF can potentially deliver both on strength and higher damping performance. In this study the mechanical and damping properties of CF, FF and their hybrid composites were examined. Composites' anisotropic nature affects their response to vibrations and so traditional damping experimental setups used for metals had to be ruled out. A damping set up based on Centre Impedance Method (CIM) was adopted for the purpose of this study which was based on an ISO standard originally developed for glass laminates. Standard tensile and flexural tests were conducted in order to characterise the performance of the hybrid composite. The experimental work was accompanied by finite elements analysis (FEA). The experimental data and FEA were used to optimize the hybrid structure layup with respect to damping and structural response. MSc by Research