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ArtEmis is an EU project that today consists of 14 differentinstitutions collectively working towards the final goal of buildinga system that can make trustworthy earthquake predictions withthe help of radon gas. The purpose of this report is to analyse theconcentration of radon measured by four out of six prototype sensorsinstalled by the ArtEmis project. In the occurrence of an earthquake, tectonic plates slide together,causing stress levels to rise within the Earth’s crust and microcracksbegin to form. When these microcracks form, specific elements suchas radon gas can ascend toward the surface and reach groundwater.Once in groundwater, the concentration of radon can be measuredby analysing the amount of γ rays at certain energies using γ-rayspectroscopy. With energy spectra measured by these sensors, an energy intervalcorresponding to the presence of the isotope 222Rn could be identified,namely the interval around 609 keV. This stems from a daughterisotope of 222Rn. Further analysis on the activity over time, andcomparisons to instances when earthquakes occurred, could thenbe done. These measurements were also tested against a statisticalmodel based on Gaussian distribution, showing correlation in severalcases. One sensor location had an extra interesting find. Here it wasable to see, on two different occasions, a distinct increase in 222Rnconcentration roughly 10 days prior to an earthquake.Considering that these sensors are active for the very first timeduring the time span of this report, unintended behaviour occurredon several occasions. A large focus of the project currently lies onfixing these issues. This leads to limited conclusions being able tobe drawn from such a short time span, but could give indication ofpositive results moving forward.

Nesta dissertação estudamos como os efeitos das inomogeneidades da matéria (escura e bariônica) modificam as distâncias e afetam a determinação dos parâmetros cosmológicos. As inomogeneidades são fenomenologicamente descritas pelo parâmetro de aglomeramento alpha e quantificadas pela equação da distância proposta por ZeldovichKantowskiDyer Roeder (ZKDR). Além disso, utilizando amostras de Supernovas e Gamma-Ray Bursts, aplicamos um teste chi quadrado para vincular os parâmetros de dois modelos cosmológicos distintos, a saber: o modelo LambdaCDM plano e o modelo com criação de matéria escura fria. Para o modelo LambdaCDM plano, vinculamos os parâmetros alpha e ­OmegaM considerando um prior gaussiano para a constante de Hubble. Realizamos também uma análise detalhada envolvendo duas calibrações distintas associadas aos dados de Gamma-Ray Bursts: uma calibração para o modelo LambdaCDM plano e outra para o modelo cardassiano. Verificamos que os resultados são fracamente dependentes da calibração adotada. Uma análise conjunta envolvendo Supernovas e Gamma-Ray Bursts permitiu quebrar a degenerescência entre o parâmetro de aglomeramento alpha e o parâmetro de densidade da matéria ­OmegaM. Considerando a calibração dos Gamma-Ray Bursts para o modelo LambdaCDM plano, o melhor ajuste obtido foi alpha = 1.0 e ­OmegaM = 0.30, com os parâmetros restritos ao intervalos 0.78 < alpha < · 1.0 e 0.26 < ­OmegaM < 0.36 (2sigma). Para o modelo com criação de matéria escura consideramos também um prior gaussiano para a constante de Hubble e as amostras de Supernovas e Gamma-Ray Bursts (calibrados para o modelo LambdaCDM plano). A degenerescência entre o parâmetro alpha e o parâmetro de criação gamma foi novamente quebrada através de uma análise conjunta das 2 amostras de dados. Para o melhor ajuste obtivemos alpha = 1.0 e gamma = 0.61, com os parâmetros restritos aos intervalos 0.85 < alpha < 1.0 e 0.56 < gamma < 0.66 (2sigma). / In this dissertation we study how the effects of matter (baryonic and dark) inhomogeneities modify the distances thereby affecting the determination of cosmological parameters. The inhomogeneities are phenomenologically described by the clumpiness parameter alpha and quantified through the equation distance proposed by ZeldovichKantowskiDyer Roeder (ZKDR). Further, by using Supernovae and Gamma-Ray Bursts separately, a chi-squared analysis was performed to constrain the parameter space for two distinct cosmological models, namely: the flat LambdaCDM model and the cold dark matter creation model. For the flat LambdaCDM model we have constrained the parameters alpha and ­OmegaM by considering a Gaussian prior for the Hubble parameter. A detailed analysis was also performed involving two different calibrations associated to the Gamma-Ray Bursts data: a calibration for the flat LambdaCDM model as well as for the cardassian model. We have verified that the results are weakly dependent on the adopted calibration. A joint analysis involving Supernovae and Gamma-Ray Bursts allowed us to break the degenerescence between the clumpiness parameter alpha and the matter density parameter ­OmegaM. By considering the calibration for the flat LambdaCDM model, the best fits obtained were equal to alpha = 1.0 and ­OmegaM = 0.30 with the parameters restricted on the intervals 0.78 < alpha < 1.0 and 0.26 < ­OmegaM < 0.36 (2sigma). For the dark matter creation model we have also adopted a Gaussian prior for the Hubble constant and the Supernovae and Gamma-Ray Bursts (calibrated for the flat LambdaCDM model) samples. The degenerescence between the clumpiness parameter alpha and the creation parameter gamma was again broken trough a joint analysis of the two data sample. For the best fits we have obtained alpha = 1.0 and gamma = 0.61 with the parameters restricted on the intervals 0.85 < alpha < 1.0 and 0.56 < gamma < 0.66 (2sigma).

Conversion, the process by which natural uranium ore (yellowcake) is purified and converted through a series of chemical processes into uranium hexafluoride gas (UF6), has historically been excluded from the nuclear safeguards requirements of the 235U-based nuclear fuel cycle. With each step in the conversion process from yellowcake to feedstock for UF6, intermediary uranium oxide and uranium fluoride compounds become progressively attractive products for diversion toward activities noncompliant with international treaties. The diversion of this product material could potentially provide feedstock for a clandestine or undeclared enrichment for weapons development for state or non-state entities. With the realization of this potential, the International Atomic Energy Agency (IAEA) has only recently reinterpreted its policies to emphasize safeguarding this feedstock in response to such diversion pathways. This project employs a combination of simulation models and experimental measurements to develop and validate concepts of nondestructive assay monitoring systems in a natural uranium conversion plant (NUCP). In particular, uranyl nitrate (UN) solution exiting solvent extraction was identified as a key measurement point (KMP), where gamma-ray spectroscopy was selected as the process-monitoring tool. The Uranyl Nitrate Calibration Loop Equipment (UNCLE) facility at Oak Ridge National Laboratory was employed to simulate the full-scale operating conditions of a purified uranium-bearing aqueous stream exiting the solvent extraction process in an NUCP. This work investigates gamma-ray signatures UN circulating in the UNCLE facility and evaluates various gamma-ray detector (HPGe, LaBr3 and NaI) sensitivities to UN.

Environmental gamma-ray spectroscopy provides a powerful tool that can be used in environmental monitoring given that it offers a compromise between measurement time and accuracy allowing for large areas to be surveyed quickly and relatively inexpensively. Depending on monitoring objectives, spectral information can then be analysed in real-time or post survey to characterise contamination and identify potential anomalies. Smaller volume detectors are of particular worth to environmental surveys as they can be operated in the most demanding environments. However, difficulties are encountered in the selection of an appropriate detector that is robust enough for environmental surveying yet still provides a high quality signal. Furthermore, shortcomings remain with methods employed for robust spectral processing since a number of complexities need to be overcome including: the non-linearity in detector response with source burial depth, large counting uncertainties, accounting for the heterogeneity in the natural background and unreliable methods for detector calibration. This thesis aimed to investigate the application of machine learning algorithms to environmental gamma-ray spectroscopy data to identify changes in spectral shape within large Monte Carlo calibration libraries to estimate source characteristics for unseen field results. Additionally, a 71 × 71 mm lanthanum bromide detector was tested alongside a conventional 71 × 71 mm sodium iodide to assess whether its higher energy efficiency and resolution could make it more reliable in handheld surveys. The research presented in this thesis demonstrates that machine learning algorithms could be successfully applied to noisy spectra to produce valuable source estimates. Of note, were the novel characterisation estimates made on borehole and handheld detector measurements taken from land historically contaminated with 226Ra. Through a novel combination of noise suppression and neural networks the burial depth, activity and source extent of contamination was estimated and mapped. Furthermore, it was demonstrated that Machine Learning techniques could be operated in real-time to identify hazardous 226Ra containing hot particles with much greater confidence than current deterministic approaches such as the gross counting algorithm. It was concluded that remediation of 226Ra contaminated legacy sites could be greatly improved using the methods described in this thesis. Finally, Neural Networks were also applied to estimate the activity distribution of 137Cs, derived from the nuclear industry, in an estuarine environment. Findings demonstrated the method to be theoretically sound, but practically inconclusive, given that much of the contamination at the site was buried beyond the detection limits of the method. It was generally concluded that the noise posed by intrinsic counts in the 71 × 71 mm lanthanum bromide was too substantial to make any significant improvements over a comparable sodium iodide in contamination characterisation using 1 second counts.

Nesta dissertação estudamos como os efeitos das inomogeneidades da matéria (escura e bariônica) modificam as distâncias e afetam a determinação dos parâmetros cosmológicos. As inomogeneidades são fenomenologicamente descritas pelo parâmetro de aglomeramento alpha e quantificadas pela equação da distância proposta por ZeldovichKantowskiDyer Roeder (ZKDR). Além disso, utilizando amostras de Supernovas e Gamma-Ray Bursts, aplicamos um teste chi quadrado para vincular os parâmetros de dois modelos cosmológicos distintos, a saber: o modelo LambdaCDM plano e o modelo com criação de matéria escura fria. Para o modelo LambdaCDM plano, vinculamos os parâmetros alpha e ­OmegaM considerando um prior gaussiano para a constante de Hubble. Realizamos também uma análise detalhada envolvendo duas calibrações distintas associadas aos dados de Gamma-Ray Bursts: uma calibração para o modelo LambdaCDM plano e outra para o modelo cardassiano. Verificamos que os resultados são fracamente dependentes da calibração adotada. Uma análise conjunta envolvendo Supernovas e Gamma-Ray Bursts permitiu quebrar a degenerescência entre o parâmetro de aglomeramento alpha e o parâmetro de densidade da matéria ­OmegaM. Considerando a calibração dos Gamma-Ray Bursts para o modelo LambdaCDM plano, o melhor ajuste obtido foi alpha = 1.0 e ­OmegaM = 0.30, com os parâmetros restritos ao intervalos 0.78 < alpha < · 1.0 e 0.26 < ­OmegaM < 0.36 (2sigma). Para o modelo com criação de matéria escura consideramos também um prior gaussiano para a constante de Hubble e as amostras de Supernovas e Gamma-Ray Bursts (calibrados para o modelo LambdaCDM plano). A degenerescência entre o parâmetro alpha e o parâmetro de criação gamma foi novamente quebrada através de uma análise conjunta das 2 amostras de dados. Para o melhor ajuste obtivemos alpha = 1.0 e gamma = 0.61, com os parâmetros restritos aos intervalos 0.85 < alpha < 1.0 e 0.56 < gamma < 0.66 (2sigma). / In this dissertation we study how the effects of matter (baryonic and dark) inhomogeneities modify the distances thereby affecting the determination of cosmological parameters. The inhomogeneities are phenomenologically described by the clumpiness parameter alpha and quantified through the equation distance proposed by ZeldovichKantowskiDyer Roeder (ZKDR). Further, by using Supernovae and Gamma-Ray Bursts separately, a chi-squared analysis was performed to constrain the parameter space for two distinct cosmological models, namely: the flat LambdaCDM model and the cold dark matter creation model. For the flat LambdaCDM model we have constrained the parameters alpha and ­OmegaM by considering a Gaussian prior for the Hubble parameter. A detailed analysis was also performed involving two different calibrations associated to the Gamma-Ray Bursts data: a calibration for the flat LambdaCDM model as well as for the cardassian model. We have verified that the results are weakly dependent on the adopted calibration. A joint analysis involving Supernovae and Gamma-Ray Bursts allowed us to break the degenerescence between the clumpiness parameter alpha and the matter density parameter ­OmegaM. By considering the calibration for the flat LambdaCDM model, the best fits obtained were equal to alpha = 1.0 and ­OmegaM = 0.30 with the parameters restricted on the intervals 0.78 < alpha < 1.0 and 0.26 < ­OmegaM < 0.36 (2sigma). For the dark matter creation model we have also adopted a Gaussian prior for the Hubble constant and the Supernovae and Gamma-Ray Bursts (calibrated for the flat LambdaCDM model) samples. The degenerescence between the clumpiness parameter alpha and the creation parameter gamma was again broken trough a joint analysis of the two data sample. For the best fits we have obtained alpha = 1.0 and gamma = 0.61 with the parameters restricted on the intervals 0.85 < alpha < 1.0 and 0.56 < gamma < 0.66 (2sigma).

Les sursauts gamma sont des événements fascinants de par leur origine longtemps restée mystérieuse, leur apparition imprévisible dans le ciel, et la formidable énergie qu'ils libèrent sous forme de bouffées de rayonnement gamma. Découverts fortuitement au début des années 1970, ils se traduisent par un intense flash de rayons gamma de brève durée (de quelques ms à quelques min), appelé émission prompte, suivi d'une émission longue, appelée rémanence, qui décroît rapidement, en émettant depuis les rayons X jusqu'au domaine radio. L'origine des sursauts gamma est encore largement discutée mais ces phénomènes extrêmes sont très vraisemblablement associés à la formation de nouveaux trous noirs stellaires. Mon sujet de thèse se situe au coeur de la mission sino-française SVOM dont le lancement du satellite est prévu en 2021, qui scrutera le ciel pour observer les sursauts avec une précision inégalée, associant observations spatiales et terrestres. Mon travail concerne l'instrument principal de la mission, le télescope spatial ECLAIRs. Il s'agit d'une caméra à masque codé sensible aux rayons X et gamma de basse énergie, en charge de la détection et de la localisation de l'émission prompte des sursauts. Durant mon travail de thèse, j'ai travaillé sur les performances scientifiques de l'instrument ECLAIRs et j'ai en particulier estimé le nombre de sursauts qui seront détectés et leurs caractéristiques. Pour cela, j'ai mis en place des simulations de performances utilisant les prototypes des algorithmes de détection embarqués combinés au modèle de l'instrument ECLAIRs. Les données en entrée des simulations comportent un bruit de fond simulé, et une population synthétique de sursauts gamma générée à partir de catalogues existants issus des observations des missions antérieures (CGRO, HETE-2, Swift et Fermi). Mon étude a permis d'estimer finement l'efficacité de détection d'ECLAIRs et prédit un taux de sursauts attendu par ECLAIRs entre 40 et 70 sursauts par an. Par ailleurs, mon travail a montré qu'ECLAIRs sera particulièrement sensible à une population de sursauts très riches en rayons X, population encore mal connue. Ma thèse présente plusieurs autres études complémentaires portant sur la performance de localisation, le taux de fausses alertes et les caractéristiques des déclenchements des algorithmes. Enfin, j'ai proposé deux nouvelles méthodes originales de détection de sursauts dont les résultats préliminaires présentés dans ma thèse sont très encourageants. Ils montrent que la sensibilité d'ECLAIRs aux sursauts courts (population d'intérêt particulier en raison de son lien attendu avec les ondes gravitationnelles) peut être encore améliorée. / Discovered in the early 1970s, gamma-ray bursts (GRBs) are amazing cosmic phenomena appearing randomly on the sky and releasing large amounts of energy mainly through gamma-ray emission. Although their origin is still under debate, they are believed to be produced by some of the most violent explosions in the Universe leading to the formation of stellar black-holes. GRBs are detected by their prompt emission, an intense short burst of gamma-rays (from a few millisecondes to few minutes), and are followed by a lived-afterglow emission observed on longer timescales from the X-ray to the radio domain. My thesis participates to the developement of the SVOM mission, which a Chinese-French mission to be launched in 2021, devoted to the study of GRBs and involving space and ground instruments. My work is focussed on the main instrument ECLAIRs, a hard X-ray coded mask imaging camera, in charge of the near real-time detection and localization of the prompt emission of GRBs. During my thesis, I studied the scientific performances of ECLAIRs and in particular the number of GRBs expected to be detected by ECLAIRs and their characteristics. For this purpose, I performed simulations using the prototypes of the embedded trigger algorithms combined with the model of the ECLAIRs instrument. The input data of the simulations include a background model and a synthetic population of gamma-ray bursts generated from existing catalogs (CGRO, HETE-2, Fermi and Swift). As a result, I estimated precisely the ECLAIRs detection efficiency of the algorithms and I predicted the number of GRBs to be detected by ECLAIRs : 40 to 70 GRBs per year. Moreover, the study highlighted that ECLAIRs will be particularly sensitive to the X-ray rich GRB population. My thesis provided additional studies about the localization performance, the rate of false alarm and the characteristics of the triggers of the algorithms. Finally, I also proposed two new methods for the detection of GRBs.The preliminary results were very promising and demonstrate that the sensitivity of ECLAIRs to the short GRBs (an interesting population due to the predicted association with gravitational waves) could be improved further.

京都大学 / 0048 / 新制・課程博士 / 博士(エネルギー科学) / 甲第17918号 / エネ博第290号 / 新制||エネ||60(附属図書館) / 30738 / 京都大学大学院エネルギー科学研究科エネルギー応用科学専攻 / (主査)教授 大垣 英明, 教授 白井 康之, 教授 松田 一成 / 学位規則第4条第1項該当 / Doctor of Energy Science / Kyoto University / DGAM

Thesis (MSc)--Stellenbosch University, 2005. / Some digitised pages may appear illegible due to the condition of the original hard copy. / ENGLISH ABSTRACT: Airborne gamma-ray spectrometry is used for exploration and environmental monitoring over large areas. Such datasets of 7-ray are acquired using large 16l NaI(T1) detector crystals mounted in an aircraft. The response of these detectors to naturally occurring radioactive isotopes is a function of detector volume, efficiency and resolution. This response is modelled using the Monte Carlo method. A photon-electron transport computer code, NIPET, is written to calculate the intrinsic efficiency and photofraction of these large prismatic crystals. The intrinsic efficiency indicates the number of incident photons that interact in some way with the detector resulting in a deposition of energy in the crystal. The photofraction, on the other hand, indicates how many of these photons that impinge on the detector are actually recorded with their full initial energy. This study presents explicity calculated photofraction values for 16l NaI(Tl) crystals. Comparison of these new values, calculated with this computer program, with that of published values for small 3" x 3" crystals shows good agreement. However, for large crystals, the calculated values differ from those in the literature by almost 15%. The study also finds that for the gamma-ray energy range between 0.2 - 3.0 MeV, these detectors have an intrinsic efficiency above 90%, whereas the photofraction values range from 80% for low energy photons to above 40% for high energy photons in the case of large crystals. / AFRIKAANSE OPSOMMING: Lug gamma-straal spektroskopie is nuttig vir eksplorasie en omgewings ondersoeke oor groot areas. Metings word tipies gedoen met 16l NaI(T1) detektors wat monteer is in ’n vliegtuig. Die respons van hierdie detektors ten opsigte van natuurlike radioaktiewe isotope is ’n funksie van detektorvolume, doeltreffendheid en oplosvermoë. Hierdie respons word gemodeleer deur gebruik te maak van ’n Monte Carlo tegniek. ’n Rekenaarprogram, NIPET, is geskryf om die intrinsieke doeltreffendheid en fotofraksie vir hierdie groot prismatiese kristalle te bereken. Die intrinsieke doeltreffendheid dui die breukdeel van die invallende fotone aan wat ’n interaksie ondergaan binne die detektor kristal en sodoende energie deponeer. Die fotofraksie, daarenteen, dui die breukdeel invallende fotone aan wat absorbeer word deur die kristal met hul voile invallende energie. In hierdie tesis word eksplisiete fotofraksiewaardes vir 16l NaI(T1) kristale bereken. Goeie ooreenstemming word gevind tussen fotofraksie waardes bereken met hierdie program en die waardes gepubliseer in die literatuur vir klein 3" x 3" kristalle. Vir groter kristalle is daar egter swakker ooreenstemming. Berekende fotofraksie waardes verskil met 15% van die waardes in die literatuur. Daar word ook bevind dat vir gamma-energie tussen 0.2 - 3.0 MeV, die intrinsieke doeltreffendheid vir hierdie tipe detektors bo 90% is en dat fotofraksiewaardes wissel tussen 80% vir lae energie tot bo 40% vir hoë foton energie.