The aim of this thesis is to study trust in military leaders. Empirical data was gathered through interviews and questionnaires with military personnel mostly from Sweden, but also from four other European countries. Paper I illustrates that trust in military leaders can be theoretically understood in terms of a hierarchical system of categories, higher-level categories and two superior categories labelled Individual-related and Communication- and relationship-related characteristics. Paper II examines how trust between military leaders and their subordinates is related to negative critical incidents in international operations. The results show that trust can be affected by pre-existing influences, of both an individual and contextual nature. The level of trust that develops between leaders and subordinates appears to have an influence on perceptions and re-evaluations of leaders’ trustworthiness during and after involvement in critical incidents. In Paper III, an instrument, Destrudo-L, was developed to measure destructive leadership behaviours on five different dimensions: Arrogant, unfair, Threats, punishments, overdemands, Ego-oriented, false, Passive, cowardly, and Uncertain, unclear, messy. In Paper IV the relationship between constructive and destructive leadership behaviours and trust is examined. The results show that constructive leadership contributed most to trust in the immediate supervisor. A great deal of trust in immediate supervisors can be understood by evaluating both constructive and destructive leadership behaviours. This thesis contributes with context-specific knowledge on trust in leaders in a military context and knowledge of psychological processes and individual dispositions that shape and change the willingness to trust leaders. The main findings presented in this thesis are the identification of characteristics of the trustor, the trustee, and the context which influences trust in military leaders. / Armed forces often perform tasks in life or death situations, bringing the issue of trust in military leaders to a head. Dependence on and trust in military leaders entails considerable risk, as any mistakes made by the leader may result in serious injury or death. Obeying orders is an essential aspect of the military profession and trust is critical since individuals are expected to give up their right to self-determination and follow orders (i.e. trust the leader). Refusal not only puts the individual soldier at risk, but also his or her team members and leaders. The hierarchical military system puts subordinates in a vulnerable position in relation to the leader. The aim of this thesis is to study trust in military leaders. Empirical data was gathered through interviews and questionnaires with military personnel mostly from Sweden, but also from four other European countries. This thesis contributes with context-specific knowledge on trust in leaders in a military context and knowledge on psychological processes and individual dispositions that shape and change the willingness to trust leaders. The main findings presented in this thesis are the identification of characteristics of the trustor, the trustee, and the context which influences trust in military leaders. / <p>Avhandlingen skrevs i samarbete med Försvarshögskolan i Stockholm i ämnet Ledarskap under påfrestande förhållanden</p>

TRAPIL est une société Française ayant à charge l'exploitation et l'entretien de pipelines d'hydrocarbures. L'entretien de pipelines enterrés nécessite le passage de racleurs équipés de sondes ultrasons réalisant une cartographie de la structure du pipeline, qui est ensuite analysée à la main afin de détecter et d'identifier les différents défauts pouvant apparaître ou évoluer.L'objectif de ce travail de thèse est d'apporter une solution algorithmique permettant d'accélérer et de compléter le travail des analystes à l'aide des méthodes modernes de traitement d'images et du signal.Notre approche suit le mode opératoire des experts et est découpée en trois partie.Tout d'abord nous réalisons une détection des soudures d'aboutage permettant de séparer le pipelines en les différents tubes qui le composent. Les signaux de sondes représentant la circonférence du tube sont regroupés et compressés dans une détection de rupture par comparaison de moyenne à court et long terme, puis les signaux résultants sont fusionnés à l'aide d'une pondération unique permettant une augmentation majeure du contraste entre bruit et soudure, offrant une détection et une localisation presque sans faille.Les tubes subissent ensuite une première segmentation visant à éliminer le plus grand nombre de pixels sains. Usant de modélisation d'histogramme des valeurs d'épaisseur par un algorithme EM initialisé pour notre problématique, l'algorithme suit un principe récursif comparable aux méthodes de type split and merge pour détecter et isoler les zones dangereuses.Enfin, Les zones dangereuses sont identifiées à l'aide d'une foret aléatoire, apprise sur un grand nombre d'exemples de défauts. Cette troisième partie est centrée sur l'étude de différentes méthodes de reconnaissance de forme appliquées à notre nouvelle problématique.Au travers de ces différentes étapes, les solutions que nous avons apportées permettent à TRAPIL un gain de temps significatif sur les tâches les plus fastidieuses du processus d'analyse (par exemple 30% sur la détection de soudures) et leur offre de nouvelles possibilités commerciales, par exemple la possibilité de fournir un pré-rapport à leur clientèle en quelques jours pendant que l'analyse manuelle est réalisée pouvant prendre plus d'un mois. / TRAPIL is a French society who is in charge of exploitation and maintenance of oil pipelines. Maintenance of buried pipeline implies the use of ultrasonic sensor-equipped devices, providing thickness and structural maps of the pipe, which are analysed by experts in order to detect and identify defects that may appear or evolve.The objective of this work is to provide an algoritmic solution allowing to accelerate and aid the experts's work with modern image and signal processing methods.Our approach follows the experts's operating mode and is divided in three sections.First, a weld detection is realized allowing to split the pipe in tubes. The signals of probes representing the circumference of the pipe are regrouped and compressed through an abrupt change detection, using short and long-term average comparison, then the resulting signals are merged using a unique weightening function allowing a massive increase of the contrast between welds and noise, offering near-perfect detection and localization.The tubes then undergoes a first segmentation aiming at eliminating a large amount of sane pixels. Using histogram modelization through an EM algorithm tuned specially for our purpose, the algorithm follows a recursive approach comparable to split and merge methods to detect and isolate dangerous areas.Finally, those dangerous areas are identified with a Random Forest, which has been learnt on a large amount of defect examples. This third part is greatly focused on the study of different pattern recognition methods applied on our new problematic.Through those different steps, the solution we brought allows TRAPIL to save a lot of time on the most tedious tasks of the analysis process (for example 30% of gain in processing time for the weld detection) and offers new commercial possibilities, like for example the possibility to provide their clients a first report in a matter of days, while the manual analysis is completed, which can take more than a month.

The purpose of this study was to explore a phenomenon known as pexing that is prevalent in South Africa‟s Black youth. The study aimed to explore the nature of pexing in relation to other conspicuous consumption behaviours and understand the drivers for this behaviour. The study interviewed a sample of 10 participants. Findings of the study indicated that pexing is similar to conspicuous consumption but also has aspects that are distinct to it and the researcher proposes a framework and term (destructive conspicuous consumption) for this noted consumption activity. The study also shows that although different to anti-consumption pexing has some anti-consumption behaviours. The study also identifies antecedents that lead to the noted behaviour and these range from a low income environment to adult modelling. Relationships and links between antecedents; coping strategies and the resultant consumption activity (Pexing) was demonstrated. The research then concludes by making recommendation to both government and marketers in light of the findings of this research. The research also highlights some socio-economic considerations of pexing and also suggests other variables to be researched that are key to further understanding of pexing. / Dissertation (MBA)--University of Pretoria, 2012. / Gordon Institute of Business Science (GIBS) / unrestricted

Structural Health Monitoring (SHM) techniques are widely used in a number of Non – destructive Evaluation (NDE) applications. There is a need to develop effective techniques for SHM, so that the safety and integrity of the structures can be improved. Two most widely used SHM methods for plates and rods use either the spectrum of the impedances or monitor the propagation of lamb waves. Piezoelectric wafer – active sensors (PWAS) were used for excitation and sensing. In this study, surface response to excitation (SuRE) and Lamb wave propagation was monitored to estimate the integrity of the round objects including the pipes, tubes and cutting tools. SuRE obtained the frequency response by applying sweep sine wave to surface. The envelope of the received signal was used to detect the arrival of lamb waves to the sensor. Both approaches detect the structural defects of the pipes and tubes and the wear of the cutting tool.

<div> <div> <div> <p>Composite materials have become widely used in engineering applications, in order to reduce the overall weight of structures while retaining their required strength. Due to their light weight, relatively high stiffness properties, and formability into complex shapes, discontinuous fiber composites are advantageous for producing small and medium size components. However, qualifying their mechanical properties can be expensive, and therefore there is a need to improve predictive capabilities to help reduce the overall cost of large scale testing. To address this challenge, a composite material consisting of discontinuous glass fibers in a polypropylene matrix is studied at the microstructural level through coupled experiments and simulations, in order to uncover the mechanisms that cause microvoids to initiate and progress, as well as certain fiber breakage events to occur, during macroscopic tension. Specifically, this work coupled in-situ X-ray micro computed tomography (μ-CT) experiments with a finite element simulation of the exact microstructure to enable a 3D study that tracked damage initiation and propagation, and computed the local stresses and strains in the microstructure. In order to have a comprehensive 3D understanding of the evolution of the microstructure, high fidelity characterization procedures were developed and applied to the μ-CT images in order to understand the exact morphology of the microstructure. To aid in this process, ModLayer - an interactive image processing tool - was created as a MATLAB executable, and the 3D microstructural feature detection techniques were compared to traditional destructive optical microscopy techniques. For damage initiation, this work showed how high hydrostatic stresses in the matrix can be used as a metric to explain and predict the exact locations of microvoid nucleation within the composite’s microstructure. From a damage propagation standpoint, matrix cracking - a mechanism that has been notably difficult to predict because of its apparent stochastic nature - was studied during damage propagation. The analysis revealed the role of shear stress in fiber mediated flat matrix cracking, and the role of hydrostatic stress in fiber-avoidance conoidal matrix cracking. Overall, a sub-fiber simulation and an in-situ experimental analysis provided the microstructural physical phenomena that govern certain damage initiation and progression mechanisms, further enabling the strength and failure predictions of short fiber thermoplastic composites. </p></div></div></div>

The need for reliable and cost-effective testing procedures for Additive Manufacturing (AM) is growing. In this Dissertation, the development of a new computational-experimental method based on the realization of specific testing artifacts to address this need is presented. This research is focused on one of the widely utilized AM technologies, Fused Deposition Modeling (FDM), and can be extended to other AM technologies as well. In this method, testing artifacts are designed with simplified boundary conditions and computational domains that minimize uncertainties in the analyses. Testing artifacts are a combination of thin and thick cantilever structures, which allow measurement of natural frequencies, mode shapes, and dimensions as well as distortions and deformations. We apply Optical Non-Destructive Testing (ONDT) together with computational methods on the testing artifacts to predict their natural frequencies, thermal flow, mechanical properties, and distortions as a function of 3D printing parameters. The complementary application of experiments and simulations on 3D printed testing artifacts allows us to systematically investigate the density, porosity, moduli of elasticity, and Poisson’s ratios for both isotropic and orthotropic material properties to better understand relationships between these characteristics and the selected printing parameters. The method can also be adapted for distortions and residual stresses analyses. We optimally collect data using a design of experiments technique that is based on regression models, which yields statistically significant data with a reduced number of iterations. Analyses of variance of these data highlight the complexity and multifaceted effects of different process parameters and their influences on 3D printed part performance. We learned that the layer thickness is the most significant parameter that drives both density and elastic moduli. We also observed and defined the interactions among density, elastic moduli, and Poisson’s ratios with printing speed, extruder temperature, fan speed, bed temperature, and layer thickness quantitatively. This Dissertation also shows that by effectively combining ONDT and computational methods, it is possible to achieve greater understanding of the multiphysics that governs FDM. Such understanding can be used to estimate the physical and mechanical properties of 3D printed components, deliver part with improved quality, and minimize distortions and/or residual stresses to help realize functional components.

Terms of acoustic emission (AE) and electromagnetic emission (EME) designated physical effects and also as diagnostic methods based on these effects. These effects are caused by generated cracks in materials that rank among non-destructive techniques of material diagnostics. The advantage of them is that they do not affect the measured object and give us information about the current dynamic state of a tested material. One disadvantage of these effects is that they provide very low energy of signal emissions and make it difficult for broader usage. It is expected better localization of cracks in non-conductive materials by connecting of these two techniques (diagnostics). There are designed and described new methods for crack detection with usage of AE and EME signals in this work. Also there is description of measuring arrangement intended of crack detection and experimental sample for checking accuracy of methods for crack detection. There was performed comparison of accuracy of methods in crack detection.

Description of Ultrasonic Cleaning technology. Description of Non-destructive testing technology process. Design of Ultrasonic Cleaning equipment. Design of equipment for the ultrasonic cleaning machine. Design of non-destructive testing equipment (Liquid Penetrant Inspection and Magnetic Testing). Feasibility study of designed technologies and supporting processes.

The diploma thesis deals with the problematics of weld defects of cranes localisation and check. The aim is to analyse non-destructive methods, monitor the occurence of defects and their form and also to suggest the procedure of correction. The work is divided into a theoretical and practical part. In the theoretical part, there is an analysis of individual methods of non-destructive testing that are used for weld check on a particular girder. There is also an analysis of welding technologies used when making a crane girder. The practical part deals with evaluation of weld defects using two methods of non-destructive testing. Furthermore, statistics of defects is realised. In conclusion, the statistics outcome is resumed and evaluated.

La tomographie en 2D et 3D sont largement utilisée dans l’imagerie médicale ainsi que dans le Contrôle Non Destructif (CND) pour l’industrie. Dans toutes les deux applications, il est nécessaire de réduire le nombre de projections. Dans certains cas, la reconstruction doit être faite avec un nombre d’angle de projections limité. Les données mesurées sont toujours avec des erreurs (erreurs de mesure et de modélisation). Nous sommes donc presque toujours dans la situation de problèmes inversés mal posés. Le rôle des méthodes probabilistes et de la modélisation a priori devient crucial. Pour la modélisation a priori, en particulier dans les applications NDT, l’objet à l’examen est composé de plusieurs matériaux homogènes, avec plusieurs blocs continus séparés par des discontinuités et des contours. Ce type d’objet est dit continu par morceaux. L’objet de cette thèse est sur la reconstruction des objets continu ou constante par morceaux, ou plus généralement homogène par morceaux. En résumé, deux méthodes principales sont proposées dans le contexte de l’inférence bayésienne. La première méthode consiste à reconstruire l’objet en imposant que sa transformée de Haar soit parcimonieuse. Un modèle bayésien hiérarchique est proposé. Dans cette méthode, les variables et les paramètres sont estimés et les hyper-paramètres sont initialisés selon la définition des modèles antérieurs. La deuxième méthode reconstruit les objets en estimant simultanément les contours. L’objet continu par morceaux est modélisé par un modèle markovien non-homogène, qui dépend du gradient de l’objet, et le gradient dépend aussi de l’estimation de l’objet. Cette méthode est également semi-supervisé, avec les paramètres estimés automatiquement. Ces méthodes sont adaptées aux reconstructions de grande taille de données 3D, dans lesquelles le processeur GPU est utilisé pour accélérer les calculs. Les méthodes sont validées avec des données simulées et des données réelles, et sont comparées avec plusieurs méthodes classiques. / 2D and 3D X-ray Computed Tomography (CT) is widely used in medical imaging as well as in Non Destructive Testing (NDT) for industrial applications. In both domains, there is a need to reduce the number of projections. In some cases we may also be limited in angles. The measured data are always with errors (measurement and modelling errors). We are consequently almost always in the situation of ill-posed inverse problems. The role of the probabilistic methods and the prior modelling become crucial. For prior modelling, in particular in NDT applications, the object under examination is composed with several homogeneous materials, with several continuous blocs separated by some discontinuities and contours. This type of object is called the piecewise-continuous object. The focus of this thesis on the reconstruction of the picewise continuous or constant, or more generally piecewise homogeneous objects. In summary two main methods are proposed in the context of the Bayesian inference. The first method consists in reconstructing the object while enforcing the sparsity of the discrete Haar transformation coefficients of the object. A hierarchical Bayesian model is proposed. In this method, the unknown variables and parameters are estimated and the hyper-parameters are initialized according to the definition of prior models. The second method reconstruct objects while the contours are estimated simultaneously. The piecewise continuous object is modeled by a non-homogeneous Markovian model, which depends on the gradient of the object, while the gradient also depends on the estimation of the object. In this methods, the semi-supervised system model is also achieved, with the parameters estimated automatically. Both methods are adapted to the 3D big data size reconstructions, in which the GPU processor is used to accelerate the computation. The methods are validated with both simulated and real data, and are compared with several conventional state-of-the-art methods.