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Accurate characterisation of fluid flow at tidal energy sites is critical for cost effective Tidal Energy Converter (TEC) design in terms of efficiency and survivability. The standard instrumentation in tidal site characterisation has been Diverging acoustic-Beam Doppler Profilers (DBDPs) which remotely measure the flow over a range of scales, resolving up to three velocity vectors. However, they are understood to have several drawbacks particularly in terms of characterising turbulent aspects of the flow. This characterisation is generally based upon a small number of key transient metrics, the accuracy of which directly impacts TEC designs. This work presents an optimisation and performance assessment of newly available Single Beam Doppler Profilers (SBDPs) mounted on a commercial-scale tidal turbine at mid-channel depth in a real operating environment. It was hypothesised that SBDPs would have advantages over DBDPs for site characterisation, in terms of reduced random error, reduced uncertainty in turbulence intensities and the ability to quantify the structure of the turbulent flow. The relationship between random error, sensor orientation and flow speed is quantified for both single and diverging beam sensor types. Random error was found to increase with increasing flow velocity as a power law, the slope of which varies for different sensor orientations. Quantification of noise offers a practical method to correct turbulence metrics. To enable the use of multiple acoustic sensors mounted in close proximity, interference was quantified and mitigation techniques examined. Cross-talk between sensors of the same type were generally shown to bias measurements towards zero. In the presence of alternate types of acoustic sensors, interference caused an increase in standard deviation of velocity results. Implementing a timing offset control mechanism was able to mitigate this effect. This work has achieved a greater understanding of the drivers (spatial separation, inclination angle, pulse power) and effects on measurements of interference along with ambient-noise for users of acoustic instruments. Lessons learned of value to the industry, as site characterisation work intensifies ahead of next generation commercial scale devices, are presented. Mid-channel depth mounted SBDPs were found to have advantages over seabed mounted DBDPs in resolving the key turbulent flow metrics. SBDPs were able to resolve integral length-scales of turbulence that show an anisotropic ratio of scales as predicted from theory and in work at similar sites, while the DBDPs results were similar for all directions. Turbulence intensity measurements were found to be similar after noise correction, with the SBDPs more able to accurately capture the turbulence dissipation rate. This evidence suggests that SBDP arrays present a significant improvement over bottom mounted DBDPs in discerning information about the nature of the turbulent flow, and thus future site characterisation work should consider the use of SBDPs alongside bottom mounted DBDPs for this purpose.

Receptor-based biological detection techniques often suffer from the problem of non-specific interactions. This is largely due to the presence of weak electrostatic and Van der Waals forces between the receptor and the non-target substances in the analyte that are not easily dissociated in practice. Most existing detection techniques are unable to probe the interaction between the bound entity and the surface and differentiate between specific and non-specific interactions in terms of bond strength or activation energy. The resulting false positive responses lead to various issues, such as misdiagnosis and mistreatment in clinical diagnostics and false alarms in biosecurity. The problem is even more significant with direct direction techniques, such as the resonant frequency shift based detection using quartz crystal microbalance (QCM) or micro-cantilevers, which involve minimal sample processing and washing steps. The work presented in this thesis investigates, through modeling and experiments, the mechanical interactions of a resonator with microparticles attached via biomolecular linkers and analyses the resulting nonlinear acoustic modulation of the resonator from the transduced electrical signal. Physisorbed and specific interactions both in air and liquid medium are studied using thickness shear mode quartz crystal resonators and streptavidin-coated polystyrene microbeads (SCPM) of various sizes. It is found that the modification in the transduced electrical signal measured at the third harmonic (3f), or three times the driving frequency f, is significant in presence of the attached particles and approximately proportional to the number of particles. A detection limit of approximately 2 SCPM of 5.6 µm diameter in air and 6700 SCPM of 0.39 µm diameter in liquid is demonstrated, which corresponds to a mass detection limit of ~200 pg. Most interestingly, the deviation in the magnitude of the 3f signal as a function of the resonator oscillation amplitude is found to hold a distinct relationship with the type of particle-surface interaction. This provides a basis for selectivity in detection over and above the efficacy of the receptor. The function is also found to correlate well with the event of SCPM diffusion on the surface. This detection technique, based on the measurement of deviation in magnitude of the transduced electrical signal measured at a higher odd harmonic of the drive frequency due to the presence of surface-bound particles on a resonator, is termed as the anharmonic detection technique (ADT). A feasibility study with Bacillus subtilis spores in phosphate buffer saline (PBS) is carried out successfully where the modeling and experimental results with SCPM are successfully reproduced. A detection limit of 430 spores is demonstrated, which corresponds to a mass detection limit of ~650 pg. Capability for differentiation of the specifically-captured spores from unwashed physisorbed SCPM of similar dimensions is demonstrated using the shape of the ADT signal. These results indicate that the spore immobilization step may be directly followed by the detection step, which are 9 mins and 2 mins respectively in these experiments. ADT thus potentially enables a rapid, sensitive, reliable and direct detection without the need for any sample processing. Moreover, being an entirely electronic technique, ADT suitably lends itself to multiplexing, large scale fabrication and implementation on a miniaturized low-cost point-of-care detection platform that is of immense need in clinical diagnostics, food and environmental monitoring and biosecurity. Furthermore, fitting the experimental results with modeling estimates enables ADT to determine the force-extension characteristics of the binding biomolecular linker. The force-extension characteristics and the estimated unbinding force for a streptavidin-biotin complex estimated using ADT agrees well with those computed using molecular dynamics (MD) simulation at similar loading rates. Thus ADT contributes a unique force-spectroscopic method, which unlike conventional techniques such as the atomic force microscopy (AFM) provides statistically averaged data for multiple biomolecules in a relatively quicker and simpler experimental format. A method for determination of activation energy of the interaction is also proposed using ADT. This potentially enables a method for rapid and large scale biomolecular screening and studying of interaction networks, which have important applications in drug discovery and individualized therapy.

Achieving autonomous in complex natural environments has the potential to transform society by bringing the benefits of automation from the confines of the factory floor to the outdoors. There, it could benefit areas such as environmental monitoring and clean-up, precision agriculture, delivery of goods. A fundamental requirement for achieving these goals are sensors that can provide reliable support for navigation, e.g., a drone, in natural environments. In this thesis, sonar-based navigation has been investigated as an approach to parsimonious autonomous sensing for drones. Bats living in dense vegetation have demonstrated that autonomous navigation in a complex, natural environment based on two one-dimensional ultrasonic echo streams is feasible. Here, a biomimetic sonar head has been used to collect echo data from recreations of natural foliage in the lab under controlled conditions. This data was used to address the research question whether the grazing angle at which the sonar is looking at a surface can be estimated from the echoes -- despite the random three-dimensional nature of the scatter from the foliage. To investigate this, the echoes have been subjected to statistical analysis such as spectral coherence and cross-correlation. Most importantly, the foliage data was compared against predictions made by the Endura method (energy, duration, and range method) that has been devices for two-dimension random scatterers. The results of this analysis shows that -- despite their profoundly random nature -- echoes can be used to estimate the sonar grazing angle directly, i.e., without the need to resort to reconstructions of the foliage geometry. This opens the possibility of developing simple devices for navigation control in natural environments that can control the direction of motion at a very little computational cost. / Master of Science / Autonomously flying drones is a potential technology that could bring benefits to the society and improve the quality of life for humans[22]. Therefore, a study of autonomously flying in a natural environment is necessary, and this thesis will focus on drone that could recognize objects with different grazing angle and acoustic signal by collecting data from near foliage surface. For example, when a bush wall is in front of the drone, a on board computer could inform drone whether the drone airline will collide with the bush wall or the bush wall is safely out of drone’s path[5]. If on board computer reads that there will be a collision with bush wall, then drone needs to make decision (change direction or stop immediately) to avoid crush on to bush wall. A sonar based navigation system has been investigated as an approach to achieve autonomous sensing for drones, which is inspired by bats. Bats use their natural sonar system to navigate in cave or forest, hence, it is hardly to see bats slam into any obstacles while flying. Bats navigation behaviours could be reconstructed as a sonar based autonomy. Hence, this thesis is inspired by bats to determine if there is a computational way to illustrate that sonar based sensor could be a solution to achieve reactive autonomy by using different grazing angle of the surface’s acoustic signals.

Co-rotating twin-screw extruders are unique and versatile machines that are used widely in the plastics and food processing industries. Due to the large number of operating variables and design parameters available for manipulation and the complex interactions between them, it cannot be claimed that these extruders are currently being optimally utilised. The most significant improvement to the field of twin-screw extrusion would be through the provision of a generally applicable dynamic process model that is both computationally inexpensive and accurate. This would enable product design, process optimisation and process controller design to be performed cheaply and more thoroughly on a computer than can currently be achieved through experimental trials. This thesis is divided into three parts: dynamic modelling, measurement and control. The first part outlines the development of a dynamic model of the extrusion process which satisfies the above mentioned criteria. The dynamic model predicts quasi-3D spatial profiles of the degree of fill, pressure, temperature, specific mechanical energy input and concentrations of inert and reacting species in the extruder. The individual material transport models which constitute the dynamic model are examined closely for their accuracy and computational efficiency by comparing candidate models amongst themselves and against full 3D finite volume flow models. Several new modelling approaches are proposed in the course of this investigation. The dynamic model achieves a high degree of simplicity and flexibility by assuming a slight compressibility in the process material, allowing the pressure to be calculated directly from the degree of over-fill in each model element using an equation of state. Comparison of the model predictions with dynamic temperature, pressure and residence time distribution data from an extrusion cooking process indicates a good predictive capability. The model can perform dynamic step-change calculations for typical screw configurations in approximately 30 seconds on a 600 MHz Pentium 3 personal computer. The second part of this thesis relates to the measurement of product quality attributes of extruded materials. A digital image processing technique for measuring the bubble size distribution in extruded foams from cross sectional images is presented. It is recognised that this is an important product quality attribute, though difficult to measure accurately with existing techniques. The present technique is demonstrated on several different products. A simulation study of the formation mechanism of polymer foams is also performed. The measurement of product quality attributes such as bulk density and hardness in a manner suitable for automatic control is also addressed. This is achieved through the development of an acoustic sensor for inferring product attributes using the sounds emanating from the product as it leaves the extruder. This method is found to have good prediction ability on unseen data. The third and final part of this thesis relates to the automatic control of product quality attributes using multivariable model predictive controllers based on both direct and indirect control strategies. In the given case study, indirect control strategies, which seek to regulate the product quality attributes through the control of secondary process indicators such as temperature and pressure, are found to cause greater deviations in product quality than taking no corrective control action at all. Conversely, direct control strategies are shown to give tight control over the product quality attributes, provided that appropriate product quality sensors or inferential estimation techniques are available.

The objective of this project is to develop a device that can monitor the heart rate and respiration of cetaceans. This would provide a way to quantitatively measure stress and determine the impact of human activity on cetaceans, especially for certain species that have been difficult to monitor in the past. There are many challenges to developing such a device, including determining the appropriate type of sensor, reducing the effect of flow noise, and designing an effective attachment method; this paper primarily focuses on determining the most suitable acoustic transducer. Experiments were conducted to compare various acoustic sensors in detecting heart rate. The electronic stethoscope performed the best in the experiments, but the results showed that other transducers, such as accelerometers and pressure sensors, also performed well and could be successful options with further development. Data processing methods to identify heartbeats and characterize signals are also discussed in this paper. Future work on the project involves subsequent tests to address other design variables as well as replicate experiments on animals.

Developing cost-effective tools for population monitoring and research is fundamental to wildlife management programs. This is a major challenge for solitary-nesting, secretive seabirds distributed throughout remote areas of Alaska: the marbled murrelet (Brachyramphus marmoratus) and Kittlitz’s murrelet (B. brevirostris). Both species have experienced major population declines in Alaska, which is the centre of the distribution of their global populations. In 2010-2012, I tested the reliability of two new remote-sensing approaches, marine radar surveys and autonomous acoustic monitoring, to assess population size, trends and distributions of Brachyramphus murrelets in the Kodiak Archipelago. The goals were to compare new and existing assessment tools, to identify differences in spatial and temporal patterns of activity by Brachyramphus murrelets at high latitudes, and to make recommendations for integrating remote-sensing methods into existing monitoring programs. Autonomous acoustic sensors provided a reliable index of marbled murrelet abundance at fine spatial scales (2-3 ha forest stands). Detections of marbled murrelet vocalizations by acoustic sensors and human observers were not statistically different across weekly means. Because high temporal replication could be achieved at no extra cost, automated acoustic sampling provided the best seasonal resolution in patterns of murrelet activity. Radar surveys identified a prolonged (150 min) duration of pre-sunrise inland flight activity relative to lower-latitude populations, reflecting the longer duration of twilight at high latitude. A clear trend in seasonal activity, increasing from June to late July, was identified by radar, audio-visual, and acoustic surveys. The strong seasonal increase in activity detected by radar surveys appears to be an important factor to consider in planning population monitoring programs. Radar surveys could not distinguish between Kittlitz’s and marbled murrelets, but identified potentially greater frequency of inland flight by Kittlitz’s murrelets during darkness based on comparisons between sites. Spatial patterns of abundance, estimated by radar counts, were best predicted by combinations of marine and terrestrial habitat variables within 5 km of nesting flyways, including area of steep slopes (45-90˚), area of old-growth forest, and at-sea densities < 200 m from shore in June. The largest murrelet populations occurred in both forested and unforested watersheds with steep topography; indicating that unforested steep slopes appear to be of greater importance to nesting marbled murrelets in Alaska than previously recognized, particularly in areas adjacent to marine productivity hotspots. I recommend that radar sampling protocols be modified for high latitude surveys to begin 2 h before sunrise to accommodate longer activity periods, and that surveys be repeated at similar dates across years to avoid confounding population change with seasonal changes in abundance. I propose integrating new remote-sensing tools into existing monitoring programs to increase power to detect population trends, reduce costs and risks associated with field personnel, and increase capacity for long-term monitoring of murrelet response to environmental change at multiple spatial scales. / Graduate / 0329 / 0472 / jenna.cragg@gmail.com

Co-rotating twin-screw extruders are unique and versatile machines that are used widely in the plastics and food processing industries. Due to the large number of operating variables and design parameters available for manipulation and the complex interactions between them, it cannot be claimed that these extruders are currently being optimally utilised. The most significant improvement to the field of twin-screw extrusion would be through the provision of a generally applicable dynamic process model that is both computationally inexpensive and accurate. This would enable product design, process optimisation and process controller design to be performed cheaply and more thoroughly on a computer than can currently be achieved through experimental trials. This thesis is divided into three parts: dynamic modelling, measurement and control. The first part outlines the development of a dynamic model of the extrusion process which satisfies the above mentioned criteria. The dynamic model predicts quasi-3D spatial profiles of the degree of fill, pressure, temperature, specific mechanical energy input and concentrations of inert and reacting species in the extruder. The individual material transport models which constitute the dynamic model are examined closely for their accuracy and computational efficiency by comparing candidate models amongst themselves and against full 3D finite volume flow models. Several new modelling approaches are proposed in the course of this investigation. The dynamic model achieves a high degree of simplicity and flexibility by assuming a slight compressibility in the process material, allowing the pressure to be calculated directly from the degree of over-fill in each model element using an equation of state. Comparison of the model predictions with dynamic temperature, pressure and residence time distribution data from an extrusion cooking process indicates a good predictive capability. The model can perform dynamic step-change calculations for typical screw configurations in approximately 30 seconds on a 600 MHz Pentium 3 personal computer. The second part of this thesis relates to the measurement of product quality attributes of extruded materials. A digital image processing technique for measuring the bubble size distribution in extruded foams from cross sectional images is presented. It is recognised that this is an important product quality attribute, though difficult to measure accurately with existing techniques. The present technique is demonstrated on several different products. A simulation study of the formation mechanism of polymer foams is also performed. The measurement of product quality attributes such as bulk density and hardness in a manner suitable for automatic control is also addressed. This is achieved through the development of an acoustic sensor for inferring product attributes using the sounds emanating from the product as it leaves the extruder. This method is found to have good prediction ability on unseen data. The third and final part of this thesis relates to the automatic control of product quality attributes using multivariable model predictive controllers based on both direct and indirect control strategies. In the given case study, indirect control strategies, which seek to regulate the product quality attributes through the control of secondary process indicators such as temperature and pressure, are found to cause greater deviations in product quality than taking no corrective control action at all. Conversely, direct control strategies are shown to give tight control over the product quality attributes, provided that appropriate product quality sensors or inferential estimation techniques are available.

The analysis and development of robust sensing platforms based on solidly-mounted ZnO bulk acoustic wave devices was proposed. The exploitation of acoustic energy trapping was investigated and demonstrated as a method to define active sensing areas on a substrate. In addition, a new "hybrid" acoustic mode experiencing acoustic energy trapping was studied theoretically and experimentally. This mode was used as an explanation of historical inconsistencies in observed thickness-shear mode velocities. Initial theoretical and experimental results suggest that this mode is a coupling of thickness-shear and longitudinal particle displacements and, as such, may offer more mechanical and/or structural information about a sample under test. Device development was taken another step further and multi-mode ZnO resonators operating in the thickness-shear, hybrid, and longitudinal modes were introduced. These devices were characterized with respect to sample viscosity and conductivity and preliminary results show that, with further development, the multi-mode resonators provide significantly more information about a sample than their single-mode counterparts. An alternative to resonator-based platforms was also presented in the form of bulk acoustic delay lines. Initial conceptual and simulation results show that these devices provide a different perspective of typical sensing modalities by using properly designed input pulses, device tuning, and examining overall input and output signal spectra.

The master’s thesis expresses an opinion on trends in UAV integration into non-segregated airspace issue. In the beginning, barriers to integration are characterized and a broader context is shown. Since necessity of the technical realization of the “see and be seen” principle exists, requirements for so called Sense and Avoid systems are presented. Various methods of Sense and Avoid are briefly described, highlighting their contribution to air safety and their potential for future development. The UAV communication topic is described in the last chapter, providing a list of the volume of transmitted messages, analyzing data link frequencies and selecting appropriate means of UAV operations.