Force measurement techniques in short duration hypersonic facilities

In this thesis, the free-flight force measurement technique is commissioned, validated and implemented with increasing complexity in geometries within the University of Oxford High Density Tunnel, a short-duration, heated Ludwieg Tube. The motivation of the work was to improve the current capability of force measurement techniques through the free-flight methodology, allowing for the measurement of high quality, flight representative forces with lower uncertainties than established force measurement techniques. Rather than rigidly mount a sub-scale model through a sting and measure forces through a load cell, the free-flight technique allows the model to move in six degrees of freedom during the test time. This allows for forces and moments to be measured that are not impacted by the mounting structure but require non-intrusive methods to measure the model's kinematics. In this work, kinematics are measured through a 3 degree of freedom image tracking algorithm with sub-pixel accuracy and through accelerometers mounted internally to the model on an on-board data acquisition system. This thesis introduces the static free-flight technique, whereby the aerodynamic pitching moment is minimised by matching the location of centre of gravity to centre of pressure, reducing the static margin of the model. This technique limits the dynamic influence on the measured aerodynamic coefficients and allows for only the static derivatives to be measured. This technique was conducted with a 7 degree half-angle cone, a simple geometry in which the measured coefficients can be validated against a numerical panel method code, giving confidence in the methodology. The tests were conducted at a Mach 7 condition representative of a hypersonic vehicle’s trajectory at 35 km altitude. Non-intrusive image tracking and on-board inertial measurement units were used to determine accelerations to calculate the aerodynamic forces acting on the cone. Results for lift, drag and pitching moment coefficients were obtained over a range of angles of attack and compared with predictions from a hypersonic panel method code. The experimental and numerical data sets agreed well over the range of angles of attack with the experimental uncertainties remaining below 3.1 \% for all coefficients. Following validation of the static free-flight technique, tests were conducted to directly compare free-flight against force balance techniques. The force balance was calibrated using two methods; a static calibration and by dynamically calibrating the balance by generating a global impulse response function of the model and using the stress wave deconvolution methodology. The experimental model was a blunted 7 degree half-angle cone and experiments were conducted at a Mach 5 test condition which provided sufficient dynamic pressure to generate aerodynamic forces suitable for the measurement range of the force balance. Results for lift, drag and pitching moment coefficients were obtained over a range of angles of attack and compared with predictions from a hypersonic panel method code. Agreement between the independent force techniques and numerical data sets was good over the range of angles of attack. Maximum uncertainties were shown to be +/- 0.56 N and + /- 0.44 N for free-flight for lift and drag respectively and + /- 1.59 N and + /- 1.27 N for the dynamically calibrated force balance. Finally, after showing that the free-flight methodology in the High Density Tunnel resulted in lower uncertainties than other force measurement techniques, it was applied to a 7 degree half-angle cone with fins, at a flight-representative Mach 7 condition. The fins resulted in a centre of pressure that was a function of angle of attack. Longitudinal static force and moment coefficients were measured at the Mach 7 condition with the experimental data agreeing well with numerical predictions. Forces were obtained using both image tracking at 76,000 fps as well as the direct measurement of accelerations using an on-board inertial measurement unit. Uncertainties remained below + /- 0.0075 for lift coefficient and + /- 0.0051 for drag coefficient. The fins were also angled to allow the model to roll in free-flight so that roll coefficient could also be determined

Bio-Inspired Information Extraction In 3-D Environments Using Wide-Field Integration Of Optic Flow

A control theoretic framework is introduced to analyze an information extraction approach from patterns of optic flow based on analogues to wide-field motion-sensitive interneurons in the insect visuomotor system. An algebraic model of optic flow is developed, based on a parameterization of simple 3-D environments. It is shown that estimates of proximity and speed, relative to these environments, can be extracted using weighted summations of the instantaneous patterns of optic flow. Small perturbation techniques are utilized to link weighting patterns to outputs, which are applied as feedback to facilitate stability augmentation and perform local obstacle avoidance and terrain following. Weighting patterns that provide direct linear mappings between the sensor array and actuator commands can be derived by casting the problem as a combined static state estimation and linear feedback control problem. Additive noise and environment uncertainties are incorporated into an offline procedure for determination of optimal weighting patterns. Several applications of the method are provided, with differing spatial measurement domains. Non-linear stability analysis and experimental demonstration is presented for a wheeled robot measuring optic flow in a planar ring. Local stability analysis and simulation is used to show robustness over a range of urban-like environments for a fixed-wing UAV measuring in orthogonal rings and a micro helicopter measuring over the full spherical viewing arena. Finally, the framework is used to analyze insect tangential cells with respect to the information they encode and to demonstrate how cell outputs can be appropriately amplified and combined to generate motor commands to achieve reflexive navigation behavior

Development of sustainable georesources for the built environment in the United Kingdom

The character of the UK’s built heritage has been largely determined by the country’s diverse geology. Indigenous natural stone forms a major component of the nation’s pre-1919 building stock. Stone has been used traditionally for roofing, roads, pavements, bridges, engineering works, and all forms of walling. Today it is mostly employed as thin panel cladding to concrete frameworks in modern construction and is now increasingly being used in large volumes for new city streetscapes.This paper outlines the material requirements for the repair and maintenance of the stone-built heritage and illustrates a range of initiatives across the UK aimed at safeguarding and redeveloping indigenous resources. The importance, particularly for the repair and conservation sector, of selecting appropriate replacement stone is being recognized by architectural and conservation professionals and by local authority officials. There is also increasing recognition of the importance to the economy of the local character of the built environment in terms of its value to tourism and to architectural, historical, and cultural identity. The paper also examines the historical sources of information on stone in the UK and offers recommendations for databasing and disseminating stone resource information. This may assist the redevelopment of a healthy indigenous stone industry and ensure that the unique built heritage character of the UK is maintained and enhanced

Ground Simulation of an Autonomous Satellite Rendezvous and Tracking System Using Dual Robotic Systems

A hardware-in-the-loop ground system was developed for simulating a robotic servicer spacecraft tracking a target satellite at short range. A relative navigation sensor package "Argon" is mounted on the end-effector of a Fanuc 430 manipulator, which functions as the base platform of the robotic spacecraft servicer. Machine vision algorithms estimate the pose of the target spacecraft, mounted on a Rotopod R-2000 platform, relay the solution to a simulation of the servicer spacecraft running in "Freespace", which performs guidance, navigation and control functions, integrates dynamics, and issues motion commands to a Fanuc platform controller so that it tracks the simulated servicer spacecraft. Results will be reviewed for several satellite motion scenarios at different ranges. Key words: robotics, satellite, servicing, guidance, navigation, tracking, control, docking

Pose Measurement Performance of the Argon Relative Navigation Sensor Suite in Simulated Flight Conditions

Argon is a flight-ready sensor suite with two visual cameras, a flash LIDAR, an on- board flight computer, and associated electronics. Argon was designed to provide sensing capabilities for relative navigation during proximity, rendezvous, and docking operations between spacecraft. A rigorous ground test campaign assessed the performance capability of the Argon navigation suite to measure the relative pose of high-fidelity satellite mock-ups during a variety of simulated rendezvous and proximity maneuvers facilitated by robot manipulators in a variety of lighting conditions representative of the orbital environment. A brief description of the Argon suite and test setup are given as well as an analysis of the performance of the system in simulated proximity and rendezvous operations

Antiphospholipid autoantibodies as blood biomarkers for detection of early stage Alzheimer's disease

A robust blood biomarker is urgently needed to facilitate early prognosis for those at risk for Alzheimer's disease (AD). Redox reactive autoantibodies (R-RAAs) represent a novel family of antibodies detectable only after exposure of cerebrospinal fluid (CSF), serum, plasma or immunoglobulin fractions to oxidizing agents. We have previously reported that R-RAA antiphospholipid antibodies (aPLs) are significantly decreased in the CSF and serum of AD patients compared to healthy controls (HCs). These studies were extended to measure R-RAA aPL in serum samples obtained from Alzheimer's Disease Neuroimaging Initiative (ADNI). Serum samples from the ADNI-1 diagnostic groups from participants with mild cognitive impairment (MCI), AD and HCs were blinded for diagnosis and analyzed for R-RAA aPL by ELISA. Demographics, cognitive data at baseline and yearly follow-up were subsequently provided by ADNI after posting assay data. As observed in CSF, R-RAA aPL in sera from the AD diagnostic group were significantly reduced compared to HC. However, the sera from the MCI population contained significantly elevated R-RAA aPL activity relative to AD patient and/or HC sera. The data presented in this study indicate that R-RAA aPL show promise as a blood biomarker for detection of early AD, and warrant replication in a larger sample. Longitudinal testing of an individual for increases in R-RAA aPL over a previously established baseline may serve as a useful early sero-epidemiologic blood biomarker for individuals at risk for developing dementia of the Alzheimer's type

Using 3D Imaging and Machine Learning to Predict Liveweight and Carcass Characteristics of Live Finishing Beef Cattle

Selection of finishing beef cattle for slaughter and evaluation of performance is currently achieved through visual assessment and/or by weighing through a crush. Consequently, large numbers of cattle are not meeting target specification at the abattoir. Video imaging analysis (VIA) is increasingly used in abattoirs to grade carcasses with high accuracy. There is potential for three-dimensional (3D) imaging to be used on farm to predict carcass characteristics of live animals and to optimise slaughter selections. The objectives of this study were to predict liveweight (LW) and carcass characteristics of live animals using 3D imaging technology and machine learning algorithms (artificial neural networks). Three dimensional images and LW's were passively collected from finishing steer and heifer beef cattle of a variety of breeds pre-slaughter (either on farm or after entry to the abattoir lairage) using an automated camera system. Sixty potential predictor variables were automatically extracted from the live animal 3D images using bespoke algorithms; these variables included lengths, heights, widths, areas, volumes, and ratios and were used to develop predictive models for liveweight and carcass characteristics. Cold carcass weights (CCW) for each animal were provided by the abattoir. Saleable meat yield (SMY) and EUROP fat and conformation grades were also determined for each individual by VIA of half of the carcass. Performance of prediction models was assessed using R2 and RMSE parameters following regression of predicted and actual variables for LW (R2 = 0.7, RMSE = 42), CCW (R2 = 0.88, RMSE = 14) and SMY (R2 = 0.72, RMSE = 14). The models predicted EUROP fat and conformation grades with 54 and 55% accuracy (R2), respectively. This study demonstrated that 3D imaging coupled with machine learning analytics can be used to predict LW, SMY and traditional carcass characteristics of live animals. This system presents an opportunity to reduce a considerable inefficiency in beef production enterprises through autonomous monitoring of finishing cattle on the farm and marketing of animals at the optimal time

An exploration of cognitive subgroups in Alzheimer's disease

Heterogeneity is observed in the patterns of cognition in Alzheimer's disease (AD). Such heterogeneity might suggest the involvement of different etiological pathways or different host responses to pathology. A total of 627 subjects with mild/moderate AD underwent cognitive assessment with the Mini-Mental State Examination (MMSE) and the Dementia Rating Scale-2 (DRS-2). Latent class analysis (LCA) was performed on cognition subscale data to identify and characterize cognitive subgroups. Clinical, demographic, and genetic factors were explored for association with class membership. LCA suggested the existence of four subgroups; one group with mild and another with severe global impairment across the cognitive domains, one group with primary impairments in attention and construction, and another group with primary deficits in memory and orientation. Education, disease duration, age, Apolipoprotein E-ε4 (APOE ε4) status, gender, presence of grasp reflex, white matter changes, and early or prominent visuospatial impairment were all associated with class membership. Our results support the existence of heterogeneity in patterns of cognitive impairment in AD. Our observation of classes characterized by predominant deficits in attention/construction and memory respectively deserves further exploration as does the association between membership in the attention/construction class and APOE ε4 negative status. (JINS, 2010, 16, 233-243.

ALADIN laser frequency stability and its impact on the Aeolus wind error

The acquisition of atmospheric wind profiles on a global scale was realized by the launch of the Aeolus satellite, carrying the unique Atmospheric LAser Doppler INstrument (ALADIN), the first Doppler wind lidar in space. One major component of ALADIN is its high-power, ultraviolet (UV) laser transmitter, which is based on an injection-seeded, frequency-tripled Nd:YAG laser and fulfills a set of demanding requirements in terms of pulse energy, pulse length, repetition rate, and spatial and spectral beam properties. In particular, the frequency stability of the laser emission is an essential parameter which determines the performance of the lidar instrument as the Doppler frequency shifts to be detected are on the order of 10^8 smaller than the frequency of the emitted UV light. This article reports the assessment of the ALADIN laser frequency stability and its influence on the quality of the Aeolus wind data. Excellent frequency stability with pulse-to-pulse variations of about 10 MHz (root mean square) is evident for over more than 2 years of operations in space despite the permanent occurrence of short periods with significantly enhanced frequency noise (> 30 MHz). The latter were found to coincide with specific rotation speeds of the satellite's reaction wheels, suggesting that the root cause are micro-vibrations that deteriorate the laser stability on timescales of a few tens of seconds. Analysis of the Aeolus wind error with respect to European Centre for Medium-Range Weather Forecasts (ECMWF) model winds shows that the temporally degraded frequency stability of the ALADIN laser transmitter has only a minor influence on the wind data quality on a global scale, which is primarily due to the small percentage of wind measurements for which the frequency fluctuations are considerably enhanced. Hence, although the Mie wind bias is increased by 0.3 m/s at times when the frequency stability is worse than 20 MHz, the small contribution of 4 % from all Mie wind results renders this effect insignificant (< 0.1 m/s) when all winds are considered. The impact on the Rayleigh wind bias is negligible even at high frequency noise. Similar results are demonstrated for the apparent speed of the ground returns that are measured with the Mie and Rayleigh channel of the ALADIN receiver. Here, the application of a frequency stability threshold that filters out wind observations with variations larger than 20 or 10 MHz improves the accuracy of the Mie and Rayleigh ground velocities by only 0.05 and 0.10 m/s, respectively, however at the expense of useful ground data