456 research outputs found

    Radiation Sensing: Design and Deployment of Sensors and Detectors

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    Radiation detection is important in many fields, and it poses significant challenges for instrument designers. Radiation detection instruments, particularly for nuclear decommissioning and security applications, are required to operate in unknown environments and should detect and characterise radiation fields in real time. This book covers both theory and practice, and it solicits recent advances in radiation detection, with a particular focus on radiation detection instrument design, real-time data processing, radiation simulation and experimental work, robot design, control systems, task planning and radiation shielding

    Generalisable FPCA-based Models for Predicting Peak Power in Vertical Jumping using Accelerometer Data

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    Peak power in the countermovement jump is correlated with various measures of sports performance and can be used to monitor athlete training. The gold standard method for determining peak power uses force platforms, but they are unsuitable for field-based testing favoured by practitioners. Alternatives include predicting peak power from jump flight times, or using Newtonian methods based on body-worn inertial sensor data, but so far neither has yielded sufficiently accurate estimates. This thesis aims to develop a generalisable model for predicting peak power based on Functional Principal Component Analysis applied to body-worn accelerometer data. Data was collected from 69 male and female adults, engaged in sports at recreational, club or national levels. They performed up to 16 countermovement jumps each, with and without arm swing, 696 jumps in total. Peak power criterion measures were obtained from force platforms, and characteristic features from accelerometer data were extracted from four sensors attached to the lower back, upper back and both shanks. The best machine learning algorithm, jump type and sensor anatomical location were determined in this context. The investigation considered signal representation (resultant, triaxial or a suitable transform), preprocessing (smoothing, time window and curve registration), feature selection and data augmentation (signal rotations and SMOTER). A novel procedure optimised the model parameters based on Particle Swarm applied to a surrogate Gaussian Process model. Model selection and evaluation were based on nested cross validation (Monte Carlo design). The final optimal model had an RMSE of 2.5 W·kg-1, which compares favourably to earlier research (4.9 ± 1.7 W·kg-1 for flight-time formulae and 10.7 ± 6.3 W·kg-1 for Newtonian sensor-based methods). Whilst this is not yet sufficiently accurate for applied practice, this thesis has developed and comprehensively evaluated new techniques, which will be valuable to future biomechanical applications

    Radiation Sensing: Design and Deployment of Sensors and Detectors

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    Guidebook on Detection Technologies and Systems for Humanitarian Demining

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    The aim of this publication is to provide the mine action community, and those supporting mine action, with a consolidated review and status summary of detection technologies that could be applied to humanitarian demining operations. This Guidebook is meant to provide information to a wide variety of readers. For those not familiar with the spectrum of technologies being considered for the detection of landmines and for area reduction, there is a brief overview of the principle of operation for each technology as well as a summary listing of the strengths, limitations, and potential for use of the technology to humanitarian demining. For those with an intermediate level of understanding for detection technologies, there is information regarding some of the more technical details of the system to give an expanded overview of the principles involved and hardware development that has taken place. Where possible, technical specifications for the systems are provided. For those requiring more information for a particular system, relevant publications lists and contact information are also provided

    Radar Technology

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    In this book “Radar Technology”, the chapters are divided into four main topic areas: Topic area 1: “Radar Systems” consists of chapters which treat whole radar systems, environment and target functional chain. Topic area 2: “Radar Applications” shows various applications of radar systems, including meteorological radars, ground penetrating radars and glaciology. Topic area 3: “Radar Functional Chain and Signal Processing” describes several aspects of the radar signal processing. From parameter extraction, target detection over tracking and classification technologies. Topic area 4: “Radar Subsystems and Components” consists of design technology of radar subsystem components like antenna design or waveform design

    Notranja oksidacija Cu-C in Ag-C kompozitov

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    The internal oxidation in copper-carbon and silver-carbon composites occurs when they are exposed to air or oxygen at high temperature. Solubility of carbon in copper or in silver is very low. The kinetics of oxidation at high temperature and activation energy were determined and the mechanism of internal oxidation was analysed. The kinetics of internal oxidation was determined for both cases and it is depended from the diffusion of oxygen following parabolic time dependence according to Wagner\u27s theory. The activation energy for Cu-C composite is 70.5 kJ/mol, and for Ag-C composite is 50.1 kJ/mol, what is in both cases close to the activation energy for the volume diffusion of oxygen in copper or in silver. In both cases gas products are formed during the internal oxidation of composites. In the internal oxidation zone pores, bubbles occur. The carbon oxidates directly with the oxygen from solid solution as long there is a contact, which breaks down with the presence of gas products. Then the oxidation occurs over the gas mixture of CO and CO2.Pri visokih temperaturah kompoziti bakra in srebra z ogljikom na zraku ali v kisiku reagirajo po mehanizmu notranje oksidacije. Topnost ogljika v trdnem bakru in trdnem srebru je zelo majhna. Analizirali smo kinetiko oksidacije kompozitov, določili aktivacijsko energijo in mehanizem notranje oksidacije. Kinetika oksidacije je pri obeh skupinah materialov odvisna od difuzije kisika in sledi parabolični odvisnosti od časa v skladu z Wagnerjevo teorijo. Aktivacijska energija procesa je za kompozit Cu-C enaka 70,5 kJ/mol, za kompozit Ag-C pa 50,1 kJ/mol, kar je blizu aktivacijski energiji za volumsko difuzijo kisika v trdnem bakru oziroma srebru. Pri oksidaciji kompozita nastajajo plinski produkti. Oksidacija ogljika poteka neposredno s kisikom iz trdne raztopine, ko pa se zaradi nastanka plinske faze stik prekine, pa preko plinske zmesi CO in CO2

    Development of a Grade Control Technique Optimizing Dilution and Ore Loss Trade-off in Lateritic Bauxite Deposits

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    This thesis focusses on the development of new techniques to improve the resource estimation of laterite-type bauxite deposits. Contributions of the thesis include (1) a methodology to variogram-free modelling of the ore boundaries using multiple-point statistics, (2) an approach to automate the parameter tuning process for multiple-point statistical algorithms and (3) a grade control technique to minimise the economic losses due to dilution and ore loss

    Characterisation of the subglacial environment using geophysical constrained Bayesian inversion techniques

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    An accurate characterization of the inaccessible subglacial environment is key to accurately modelling the dynamic behaviour of ice sheets and glaciers, crucial for predicting sea-level rise. The composition and water content of subglacial material can be inferred from measurements of shear wave velocity (Vs) and bulk electrical resistivity (R), themselves derived from Rayleigh wave dispersion curves and transient electromagnetic (TEM) soundings. Conventional Rayleigh wave and TEM inversions can suffer from poor resolution and non-uniqueness. In this thesis, I present a novel constrained inversion methodology which applies a Markov chain Monte Carlo implementation of Bayesian inversion to produce probability distributions of geophysical parameters. MuLTI (Multimodal Layered Transdimensional Inversion) is used to derive Vs from Rayleigh wave dispersion curves, and its TEM variant, MuLTI-TEM, for evaluating bulk electrical resistivity. The methodologies can include independent depth constraints, drawn from external data sources (e.g., boreholes or other geophysical data), which significantly improves the resolution compared to conventional unconstrained inversions. Compared to such inversions, synthetic studies suggested that MuLTI reduces the error between the true and best-fit models by a factor of 10, and reduces the vertically averaged spread of the Vs distribution twofold, based on the 95% credible intervals. MuLTI and MuLTI-TEM were applied to derive Vs and R profiles from seismic and TEM electromagnetic data acquired on the terminus of the Norwegian glacier Midtdalsbreen. Three subglacial material classifications were determined: sediment (Vs 1600 m/s, R > 500 Ωm) and weathered/fractured bedrock containing saline water (Vs > 1900 m/s, R < 50 Ωm). These algorithms offer a step-change in our ability to resolve and quantify the uncertainties in subsurface inversions, and show promise for constraining the properties of subglacial aquifers beneath Antarctic ice masses. MuLTI and MuLTITEM have both been made publicly available via GitHub to motivate users, in the cryosphere and other environmental settings, for continued advancement
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