Numerical modeling study of a neutron depth profiling (NDP) system for the Missouri S&T reactor

”For decades, Neutron Depth Profiling has been used for the non-destructive analysis and quantification of boron in electronic materials and lithium in lithium ion batteries. NDP is one of the few non-destructive analytical techniques capable of measuring the depth profiles of light elements to depths of several microns with nanometer spatial resolution. The technique, however, is applicable only to a handful of light elements with large neutron absorption cross sections. This work discusses the possibility of coupling Particle Induced X-ray Emission spectroscopy with Neutron Depth Profiling to yield additional information about the depth profiles of other elements within a material. The technical feasibility of developing such a system at the Missouri University of Science and Technology Reactor (MSTR) beam port is discussed. This work uses a combination of experimental neutron flux measurements with Monte Carlo radiation transport calculations to simulate a proposed NDP-PIXE apparatus at MSTR. In addition, the possibility of implementing an Artificial Neural Network to perform automated data analysis of NDP is presented. It was found that the performance of the Artificial Neural Network is at least as accurate as traditional processing approaches using stopping tables but with the added advantage that the Artificial Neural Network method requires fewer geometric approximations and accounts for all charged particle transport physics implicitly”--Abstract, page iii

Uncertainty Determination for Aeroheating in Uranus and Saturn Probe Entries by the Monte Carlo Method

The 2013-2022 Decaedal survey for planetary exploration has identified probe missions to Uranus and Saturn as high priorities. This work endeavors to examine the uncertainty for determining aeroheating in such entry environments. Representative entry trajectories are constructed using the TRAJ software. Flowfields at selected points on the trajectories are then computed using the Data Parallel Line Relaxation (DPLR) Computational Fluid Dynamics Code. A Monte Carlo study is performed on the DPLR input parameters to determine the uncertainty in the predicted aeroheating, and correlation coefficients are examined to identify which input parameters show the most influence on the uncertainty. A review of the present best practices for input parameters (e.g. transport coefficient and vibrational relaxation time) is also conducted. It is found that the 2(sigma) - uncertainty for heating on Uranus entry is no more than 2.1%, assuming an equilibrium catalytic wall, with the uncertainty being determined primarily by diffusion and H(sub 2) recombination rate within the boundary layer. However, if the wall is assumed to be partially or non-catalytic, this uncertainty may increase to as large as 18%. The catalytic wall model can contribute over 3x change in heat flux and a 20% variation in film coefficient. Therefore, coupled material response/fluid dynamic models are recommended for this problem. It was also found that much of this variability is artificially suppressed when a constant Schmidt number approach is implemented. Because the boundary layer is reacting, it is necessary to employ self-consistent effective binary diffusion to obtain a correct thermal transport solution. For Saturn entries, the 2(sigma) - uncertainty for convective heating was less than 3.7%. The major uncertainty driver was dependent on shock temperature/velocity, changing from boundary layer thermal conductivity to diffusivity and then to shock layer ionization rate as velocity increases. While radiative heating for Uranus entry was negligible, the nominal solution for Saturn computed up to 20% radiative heating at the highest velocity examined. The radiative heating followed a non-normal distribution, with up to a 3x variation in magnitude. This uncertainty is driven by the H(sub 2) dissociation rate, as H(sub 2) that persists in the hot non-equilibrium zone contributes significantly to radiation

An Investigation of Target Poisoning during Reactive Magnetron Sputtering

Objective of the present work is a broad investigation of the so called target poisoning during magnetron deposition of TiN in an Ar/N2 atmosphere. Investigations include realtime in-situ ion beam analysis of nitrogen incorporation at the Ti sputter target during the deposition process and the analysis of particle uxes towards and from the target by means of energy resolved mass spectrometry. For experiments a planar, circular DC magnetron, equipped with a 2 inch titanium target was installed in an ultrahigh vacuum chamber which was attached to the beam line system of a 5 MV tandem accelerator. A manipulator allows to move the magnetron vertically and thereby the lateral investigation of the target surface. During magnetron operation the inert and reactive gas flow were adjusted using mass flow controllers resulting in an operating pressure of about 0.3 Pa. The argon flow was fixed, whereas the nitrogen flow was varied to realize different states of target poisoning. In a fi?rst step the mass spectrometer was used to verify and measure basic plasma properties e.g. the residual gas composition, the behavior of reactive gas partial pressure, the plasma potential and the dissociation degree of reactive gas molecules. Based on the non-uniform appearance of the magnetron discharge further measurements were performed in order to discuss the role of varying particle fluxes across the target during the poisoning process. Energy and yield of sputtered particles were analyzed laterally resolved, which allows to describe the surface composition of the target. The energy resolving mass spectrometer was placed at substrate position and the target surface was scanned by changing the magnetron position correspondingly. It was found, that the obtained energy distributions (EDF) of sputtered particles are influenced by their origin, showing signi?ficant differences between the center and the erosion zone of the target. These results are interpreted in terms of laterally different states of target poisoning, which results in a variation of the surface binding energy. Consequently the observed energy shift of the EDF indicates the metallic or already poisoned fraction on target surface. Furthermore the EDF's obtained in reactive sputtering mode are broadened. Thus a superposition of two components, which correspond to the metallic and compound fractions of the surface, is assumed. The conclusion of this treatment is an discrete variation of surface binding energy during the transition from metallic to compound target composition. The reactive gas target coverage as derived from the sputtered energy distributions is in reasonable agreement with predictions from model calculations. The target uptake of nitrogen was determined by means of ion beam analysis using the 14N(d, )12C nuclear reaction. Measurements at varying nitrogen gas flow directly demonstrate the poisoning eff?ect. The reactive gas uptake saturates at a maximum nitrogen areal density of about 1.1016 cm-2 which corresponds to the stoichiometric limit of a 3 nm TiN layer. At sufficiently low reactive gas flow a scan across the target surface discloses a pronounced lateral variation of target poisoning, with a lower areal density in the target race track compared to the target center and edge. Again the findings are reproduced by model calculations, which confirm that the balance of reactive gas injection and sputter erosion is shifted towards erosion in the race track. Accomplished computer simulations of the reactive sputtering process are similar to Berg's well known model. Though based on experimental findings the algorithm was extended to an analytical two layer model which includes the adsorption of reactive gas as well as its different kinds of implantation. A distribution of ion current density across the target diameter is introduced, which allows a more detailed characterization of the processes at the surface. Experimental results and computer simulation have shown that at sufficiently low reactive gas flow, metallic and compound fractions may exist together on the target surface, which is in contradiction to previous simulations, where a homogeneous reactive gas coverage is assumed. Based on the results the dominant mechanisms of nitrogen incorporation at different target locations and at varying reactive gas admixture were identified

Calibration Bayésienne et évaluation de modèles et expériences d’interaction gaz-surface pour les plasmas d'entrée atmosphérique

The investigation of gas-surface interaction phenomena for atmospheric entry vehicles relies on the development of predictive theoretical models and the capabilities of current experimental facilities. However, due to the complexity of the physics and the various phenomena that need to be investigated in ground-testing facilities, both numerical and experimental processes generate data subjected to uncertainties. Nevertheless, it remains a common practice in the field of aerothermodynamics to resort to calibration and validation methods that are not apt for rigorous uncertainty treatment.This thesis investigates the process of scientific inference and its ramifications for selected gas-surface interaction experiments. Its main contributions are the improvement and re-formulation of model calibrations as statistical inverse problems with the consequent extension of current databases for catalysis and ablation. The model calibrations are posed using the Bayesian formalism where a complete characterization of the posterior probability distributions of selected parameters are computed.The first part of the thesis presents a review of the theoretical models, experiments and numerical codes used to study catalysis and ablation in the context of the von Karman Institute's Plasmatron wind tunnel. This part ends with a summary on the potential uncertainty sources present in both theoretical-numerical and experimental data. Subsequently, the methods used to deal with these uncertainty sources are introduced in detail. The second part of the thesis presents the various original contributions of this thesis. For catalytic materials, an optimal likelihood framework for Bayesian calibration is proposed. This methodology offers a complete uncertainty characterization of catalytic parameters with a decrease of 20\% in the standard deviation with respect to previous works. Building on this framework, a testing strategy which produces the most informative catalysis experiments to date is proposed. Experiments and consequent stochastic analyses are performed, enriching existing catalysis experimental databases for ceramic matrix composites with accurate uncertainty estimations. The last contribution deals with the re-formulation of the inference problem for nitridation reaction efficiencies of a graphite ablative material from plasma wind tunnel data. This is the first contribution in the literature where different measurements of the same flowfield are used jointly to assess their consistency and the resulting ablation parameters. An Arrhenius law is calibrated using all available data, extending the range of conditions to lower surface temperatures where no account of reliable experimental data is found. Epistemic uncertainties affecting the model definition and ablative wall conditions are gauged through various hypothesis testing studies. The final account on the nitridation reaction efficiency uncertainties is given by averaging the results obtained under the different models.This thesis highlights the fact that the process of scientific inference can also carry deep assumptions about the nature of the problem and it can impact how researchers reach conclusions about their work. Ultimately, this thesis contributes to the early efforts of introducing accurate and rigorous uncertainty quantification techniques in atmospheric entry research. The methodologies here presented go in line with developing predictive models with estimated confidence levels.L'étude des phénomènes d'interaction gaz-surface pour les véhicules d'entrée atmosphérique est basée sur le développement de modèles théoriques prédictifs et sur les capacités des installations expérimentales actuelles. Toutefois, en raison de la complexité de la physique et des divers phénomènes qui doivent être étudiés dans ces installations, les simulations tant numériques qu'expérimentales génèrent des données qui présentent des incertitudes. Cependant, il est courant dans le domaine de l'aérothermodynamique de recourir à des méthodes de calibration et de validation non adaptées à un traitement rigoureux de ces incertitudes.Cette thèse étudie le processus d'inférence scientifique et ses ramifications dans certaines expériences d'interaction gaz-surface. Ses principales contributions sont l'amélioration et la reformulation de la calibration de modèles en tant que problème statistique inverse et l'extension résultante des bases de données actuelles pour la catalyse et l'ablation. La calibration des modèles utilise le formalisme Bayésien où la caractérisation complète des distributions de probabilités postérieures des paramètres sélectionnés est calculée.La première partie de la thèse présente une revue des modèles théoriques, des expériences et des codes de simulation numérique utilisés pour étudier la catalyse et l'ablation dans le Plasmatron, la soufflerie à plasma de l'Institut von Karman. Cette partie se termine par un résumé des sources possibles d'incertitude présentes dans les données théoriques-numériques et expérimentales. Ensuite, les méthodes utilisées pour traiter mathématiquement ces sources d'incertitude sont présentées en détail.La deuxième partie présente les différentes contributions originales de cette thèse. Pour les matériaux catalytiques, une méthodologie de vraisemblance optimale pour l'inférence Bayésienne est développée. Cette méthodologie offre une caractérisation complète de l'incertitude des paramètres catalytiques avec une diminution de 20\% de l'écart type par rapport aux travaux antérieurs. En utilisant cette méthodologie, une stratégie de test produisant les données expérimentales de catalyse les plus informatives à ce jour est proposée. Ensuite, des expériences et des analyses stochastiques sont effectuées, enrichissant les bases de données expérimentales de catalyse existantes pour les composés à matrice céramique à l'aide d'estimations précises de l'incertitude.La dernière contribution est la reformulation du problème d'inférence des efficacités de réaction de l'azote à la surface d'un matériau ablatif en graphite à partir des données de soufflerie à plasma. Il s'agit de la première étude dans la litérature où différentes observations de la même expérience sont utilisées ensemble pour évaluer leur cohérence et les paramètres d'ablation qui en résultent. Une loi d'Arrhenius stochastique est déduite en utilisant toutes les données disponibles, étendant la gamme de conditions à des températures de surface plus basses, là où il n'y a pas de données expérimentales fiables. L'incertitude épistémique qui affecte la définition du modèle et les conditions aux limites d'ablation sont étudiées par des méthodes de test d'hypothèses. L'incertitude finale sur l'efficacité de la réaction azotée est obtenue en moyennant les résultats obtenus avec les différents modèles.Cette thèse met en évidence que le processus d'inférence scientifique peut également imposer des hypothèses sur la nature du problème et avoir un impact sur la manière dont les chercheurs parviennent à des conclusions sur leur travail. En fin de compte, cette thèse contribue aux premiers efforts d'introduction de techniques précises et rigoureuses de quantification de l'incertitude dans le domaine de recherche de l'entrée atmosphérique. Les méthodologies présentées ici permettront in fine le développement de modèles prédictifs avec estimation de niveaux de confiance