The modeling of freight travel demand has gained increasing attention in the recent past due to the importance of efficient and safe freight transportation to regional economic growth. Despite the attention paid to the modeling of freight travel demand, advances in modeling methods and the development of practical tools for forecasting freight flows have been limited. The development of freight demand models that incorporate the behavioral aspects of freight demand face significant hurdles, partially due to the data requirements, which are a consequence of the inherent complexity of the mechanisms driving freight demand. This research attempts to make a contribution in this context by proposing a relatively data simple, but behaviorally robust statewide modeling framework for the state of Florida, in the spirit of an aggregate level four-step planning process. The modeling framework that is developed in this research can be applied to the modeling of freight travel demand using data contained in readily available commercial databases such as the Reebie TRANSEARCH database and the InfoUSA employer database. The modeling methodology consists of a structural equations modeling framework that can accommodate multiple dependent variables simultaneously. This framework predicts freight flows on various modes between two zipcodes based on the socio-economic characteristics and the modal level of service characteristics. Separate models have been developed for various commodity groups. The estimated models for various commodity groups are found to offer statistically valid indications and plausible interpretations suggesting that these models may be suitable for application in freight transportation demand forecasting applications. The sensitivity analysis conducted on these models clearly added evidence to the fact that employment is the key factor influencing freight flows between two regions.

Cette thèse porte sur l'analyse de sensibilité dans le contexte des études de fiabilité des structures. On considère un modèle numérique déterministe permettant de représenter des phénomènes physiques complexes.L'étude de fiabilité a pour objectif d'estimer la probabilité de défaillance du matériel à partir du modèle numérique et des incertitudes inhérentes aux variables d'entrée de ce modèle. Dans ce type d'étude, il est intéressant de hiérarchiser l'influence des variables d'entrée et de déterminer celles qui influencent le plus la sortie, ce qu'on appelle l'analyse de sensibilité. Ce sujet fait l'objet de nombreux travaux scientifiques mais dans des domaines d'application différents de celui de la fiabilité. Ce travail de thèse a pour but de tester la pertinence des méthodes existantes d'analyse de sensibilité et, le cas échéant, de proposer des solutions originales plus performantes. Plus précisément, une étape bibliographique sur l'analyse de sensibilité puis sur l'estimation de faibles probabilités de défaillance est proposée. Cette étape soulève le besoin de développer des techniques adaptées. Deux méthodes de hiérarchisation de sources d'incertitudes sont explorées. La première est basée sur la construction de modèle de type classifieurs binaires (forêts aléatoires). La seconde est basée sur la distance, à chaque étape d'une méthode de type subset, entre les fonctions de répartition originelle et modifiée. Une méthodologie originale plus globale, basée sur la quantification de l'impact de perturbations des lois d'entrée sur la probabilité de défaillance est ensuite explorée. Les méthodes proposées sont ensuite appliquées sur le cas industriel CWNR, qui motive cette thèse. / This thesis' subject is sensitivity analysis in a structural reliability context. The general framework is the study of a deterministic numerical model that allows to reproduce a complex physical phenomenon. The aim of a reliability study is to estimate the failure probability of the system from the numerical model and the uncertainties of the inputs. In this context, the quantification of the impact of the uncertainty of each input parameter on the output might be of interest. This step is called sensitivity analysis. Many scientific works deal with this topic but not in the reliability scope. This thesis' aim is to test existing sensitivity analysis methods, and to propose more efficient original methods. A bibliographical step on sensitivity analysis on one hand and on the estimation of small failure probabilities on the other hand is first proposed. This step raises the need to develop appropriate techniques. Two variables ranking methods are then explored. The first one proposes to make use of binary classifiers (random forests). The second one measures the departure, at each step of a subset method, between each input original density and the density given the subset reached. A more general and original methodology reflecting the impact of the input density modification on the failure probability is then explored.The proposed methods are then applied on the CWNR case, which motivates this thesis.

En raison de l'augmentation de la demande d’allègement pour les véhicules automobiles, des solutions doivent être créées pour permettre aux constructeurs automobiles de passer d'aciers hautement formables mais lourds à des alliages d'aluminium moins formables mais plus légers pour les carrosseries en blanc. Les alliages d'aluminium de la série 6xxx, basés sur le système Al-Mg-Si-Cu, se sont révélés prometteurs en termes de résistance mécanique et de résistance à la corrosion, mais, l'une de leurs principales limitations concerne leur formabilité. Cette thèse vise à comprendre l'effet des additions de Si, Mg et Cu sur les propriétés mécaniques et de formabilité de la série AA6xxx. La calorimétrie différentielle à balayage et les essais de dureté sont utilisés pour identifier les effets de l'addition de solutés sur la microstructure d’amas de solutés après vieillissement naturel et pré-vieillissement. Les essais de traction donnent accès aux principales propriétés mécaniques : limite d'élasticité, résistance à la traction, taux d’écrouissage et allongement uniforme. Le test de sensibilité à la vitesse de déformation est effectué à l'aide de sauts de vitesse afin d'obtenir non seulement la sensibilité à la vitesse ascendante, mais moins classiquement la sensibilité à la vitesse descendante. Enfin, à l'aide d'équations constitutives, les propriétés mécaniques sont utilisées dans une modélisation par éléments finis pour saisir l'évolution de la déformation et de la vitesse de déformation dans la transition de la striction diffuse à localisée. Dans le cas du vieillissement naturel d'un mois (NA1m), deux types d'amas ont été détectés, une espèce moins stable thermiquement ayant une forte dépendance aux teneurs en Cu et Mg, et une espèce plus stable thermiquement ayant la même sensibilité à toutes les espèces de solutés. Lorsque les échantillons sont pré-vieillis, puis laissés pendant un mois (sNA1m), seule l’espèce d’amas thermiquement plus stables et également sensible à tous les ajouts de solutés existe. La formation de ces différents types d’amas en fonction du traitement thermique s'est traduite par les effets de l'ajout de solutés spécifiques sur les propriétés mécaniques observées. Dans l'état NA1m, les effets des additions de Cu et de Mg à l'alliage ont montré les plus fortes augmentations de la limite d'élasticité et du taux d’écrouissage, par rapport aux additions de Si. Ceci contraste avec la condition sNA1m pour laquelle les additions de Cu, Mg et Si augmentent toutes la limite d'élasticité de façon égale tandis que les additions de Cu se sont avérées avoir le plus fort effet sur l'augmentation du taux de durcissement par déformation, suivies par l'effet d’additions de Si, tandis que les additions de Mg n'ont pas eu d'effet. Les tests de sensibilité à la vitesse de déformation ont révélé une asymétrie entre les tests de variation vers le haut et vers le bas, selon laquelle la sensibilité à la vitesse de variation vers le bas est plus grande que la sensibilité à la vitesse de variation vers le haut. De plus, on a constaté que les ajouts de Si augmentent à la fois la sensibilité à la vitesse de déformation à variation ascendante et à variation descendante dans les conditions NA1m et sNA1m. Enfin, l'application de ces propriétés mécaniques à l'étude de l'évolution des strictions diffuse et locale a démontré que l'augmentation de l'exposant d’écrouissage retarde l'apparition du col diffus, par ailleurs l’augmentation de la sensibilité à la vitesse de déformation permet une distribution plus uniforme des déformations et des vitesses de déformation, permettant ainsi la stabilisation et la propagation du col de striction et retardant l'apparition du col local. L'effet de la sensibilité à la vitesse de déformation ascendante s'est révélé plus important que la variation descendante en raison de l'intensité de l'augmentation de la vitesse de déformation à l'intérieur du col sur une zone beaucoup plus petite. / Due to the increased demand for light weighting in automotive vehicles, solutions need to be created to allow automotive manufacturers to switch from highly formable but heavy steels to less formable but lighter aluminium alloys for body-in-white components; doors, roofs, hood. The 6xxx-series of aluminium alloys, based on the system of Al-Mg-Si-Cu, have shown promise for providing adequate strength and corrosion resistance but still, in the current state, one of their main limitations concerns their formability. This thesis aims to understand the effect of Si, Mg, and Cu additions under two different processing routes on the mechanical and formability properties of the AA6xxx-series. Differential scanning calorimetry and hardness testing are used to identify the effects of solute additions on the cluster states after natural ageing and pre-ageing. Tensile testing is used to capture the main mechanical properties: yield strength, tensile strength, strain hardening rate, and uniform elongation. Strain rate sensitivity testing is performed using dynamic strain rate changes to obtain not only the strain rate sensitivity due to rate-change increases (termed up-change), but uniquely, the strain rate sensitivity for rate-change decreases (termed down-change). Finally, using constitutive equations, the mechanical properties are used in combination with finite element modeling to capture the evolution of the strain and strain rate distribution in the evolution and transition of diffuse to local necking. It was found that in the case of natural ageing for one month (NA1m) two cluster types were detected, a less thermally stable species having a high dependency on the Cu and Mg contents, and a more thermally stable species being equally sensitive to all solute species. When samples were first pre-aged, then allowed to naturally age for one month (sNA1m) only the more thermally stable cluster species being equally sensitive to all solute additions existed. The formation of these different cluster types dependent on the heat treatment translated into the effects of specific solute additions on the observed mechanical properties. In the NA1m condition, the effects of Cu and Mg additions to the alloy showed the largest increases on the yield strength and strain hardening rate, as compared to Si additions. This is in contrast to the sNA1m condition whereby Cu, Mg, and Si additions all increased the yield strength equally while Cu additions proved to have the strongest effect on increasing the strain hardening rate, followed by the effect of Si additions, while Mg additions did not have an effect. From the strain rate sensitivity tests, an asymmetry between the up-change and down-change tests was observed whereby the down-change strain rate sensitivity was found to be larger than the up-change strain rate sensitivity. Additionally, Si additions were found to increase both the up-change and down-change strain rate sensitivity in both the NA1m and sNA1m conditions. Finally, the application of these mechanical properties to the onset and evolution of the diffuse and local neck demonstrated that increasing the strain hardening exponent delays the onset of diffuse necking, while increasing both the up-change and down-change strain rate sensitivities provides a more uniform strain and strain rate distribution around the neck, permitting the stabilization and propagation of the neck and delaying the onset of local necking. The effect of the up-change strain rate sensitivity was found to be more important than the down-change due to the intensity of the strain rate increase in the interior of the neck occurring over a much smaller area.

A phenomenon explored in the field of the cognitive neuroscience of morality is moral sensitivity, which is a collective name for a subjective experience related to the ability to detect and respond to morally relevant cues in a given social situation. This thesis will review the underlying neural mechanisms of moral sensitivity and three key components: Empathy, moral disgust and moral intuition, also called moral “gut-feeling.” Initially, the thesis provides a basic explanation of what moral sensitivity entails and the primary observations of which brain regions are often associated with moral sensitivity. Studies show that emotion and cognition seem to be essential to the experience of moral sensitivity, which will be further emphasized by reviewing the chosen key components. Research on morality and empathy suggests that the affective and the cognitive components of empathy each are essential to moral sensitivity. The second key component, moral disgust, describes how moral sensitive people react to violations to society by being motivated to keep away from social interactions with poor moral influence. Research on the third key component explains how moral sensitivity can be affected by moral intuitions, here moral “gut-feelings,” depending on the closeness and emotional salience in a given situation.

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Abstract not available

In recent years, the popularity of wind energy has grown. It is starting to play a large role in generating renewable, clean energy around the world. In New Zealand, there is increasing recognition and awareness of global warming and the pollution caused by burning fossil fuels, as well as the increased difficulty of obtaining oil from foreign sources, and the fluctuating price of non-renewable energy products. This makes wind energy a very attractive alternative to keep New Zealand clean and green. There are many issues involved in wind farm development. These issues can be grouped into two categories - economic issues and environmental issues. Wind farm developers often use site selection process to minimise the impact of these issues. This thesis aims to develop GIS based models that provide effective decision support tool for evaluating, at a regional scale, potential wind farm locations. This thesis firstly identifies common issues involved in wind farm development. Then, by reviewing previous research on wind farm site selection, methods and models used by academic and corporate sector to solve issues are listed. Criteria for an effective decision support tool are also discussed. In this case, an effective decision support tool needs to be flexible, easy to implement and easy to use. More specifically, an effective decision support tool needs to provide users the ability to identify areas that are suitable for wind farm development based on different criteria. Having established the structure and criteria for a wind farm analysis model, a GIS based tool was implemented using AML code using a Boolean logic model approach. This method uses binary maps for the final analysis. There are a total of 3645 output maps produced based on different combination of criteria. These maps can be used to conduct sensitivity analysis. This research concludes that an effective GIS analysis tool can be developed for provide effective decision support for evaluating wind farm sites.

This thesis is aimed at analysis of sampled-data feedback systems. Our approach is in the frequency-domain, and stresses the study of sensitivity and complementary sensitivity operators. Frequency-domain methods have proven very successful in the analysis and design of linear time-invariant control systems, for which the importance and utility of sensitivity operators is well-recognized. The extension of these methods to sampled-data systems, however, is not straightforward, since they are inherently time-varying due to the intrinsic sample and hold operations. In this thesis we present a systematic frequency-domain framework to describe sampled-data systems considering full-time information. Using this framework, we develop a theory of design limitations for sampled-data systems. This theory allows us to quantify the essential constraints in design imposed by inherent open-loop characteristics of the analog plant. Our results show that: (i) sampled-data systems inherit the difficulty imposed upon analog feedback design by the plant's non-minimum phase zeros, unstable poles, and time-delays, independently of the type of hold used; (ii) sampled-data systems are subject to additional design limitations imposed by potential non-minimum phase zeros of the hold device; and (iii) sampled-data systems, unlike analog systems, are subject to limits upon the ability of high compensator gain to achieve disturbance rejection. As an application, we quantitatively analyze the sensitivity and robustness characteristics of digital control schemes that rely on the use of generalized sampled-data hold functions, whose frequency-response properties we describe in detail. In addition, we derive closed-form expressions to compute the L2-induced norms of the sampled-data sensitivity and complementary sensitivity operators. These expressions are important both in analysis and design, particularly when uncertainty in the model of the plant is considered. Our methods provide some interesting interpretations in terms of signal spaces, and admit straightforward implementation in a numerically reliable fashion. / PhD Doctorate

This thesis details a continuing body of research investigating the contribution of personality to disordered eating and alcohol abuse in young women. There is growing evidence of high levels of reward sensitivity in women with both disorders, and high levels of punishment sensitivity in dysfunctional eating women. However, it is unlikely that personality alone accounts for the development of such dysfunctional behaviour. Two studies were conducted to further examine the contribution of reward and punishment sensitivity to these disorders. In the first study, 443 university women completed self-report measures of alcohol use, dysfunctional eating, reinforcement sensitivity, parental drinking, family environment and maternal eating. Reward and punishment sensitivity were better predictors of disordered behaviour than family factors, although maternal dysfunctional eating significantly increased the risk of daughters' dysfunctional eating. Punishment sensitive daughters of bulimic mothers reported the highest level of bulimic symptoms themselves. Punishment sensitivity also functioned as a partial pathway variable between family risk and disordered eating. Given the stronger contribution of personality to disordered behaviour, a second study was conducted in which 131 women completed behavioural tasks under conditions of reward and punishment. Performance on a computerised measure of punishment sensitivity was associated with greater levels of dysfunctional eating but not drinking. However, performance on a card-sorting task of reward sensitivity failed to correlate with self-reported reward sensitivity or disordered behaviour. It was concluded that an innate sensitivity to reward increases the risk of disorders characterised by strong approach tendencies, whilst high punishment sensitivity, perhaps due to a chaotic family, increases the risk of dysfunctional eating, particularly daughters of eating disordered mothers.

Appropriately constructed pollutant export models can help set management priorities for catchments, identify critical pollutant source areas, and are important tools for developing and evaluating economically viable ways of minimising surface water pollution.¶ This thesis presents a comparison, an evaluation and an integration of models for predicting the export of environmental pollutants, in particular sediment, through river systems. A review of the capabilities and limitations of current water quality modelling approaches is made. Several water quality and quantity modelling approaches are applied and evaluated in the catchment of the upper Murrumbidgee River.¶ The IHACRES rainfall-runoff model and a simple hydrologic routing model are applied with the aim of developing a capacity to predict streamflow at various catchment scales and to enable integration with other pollutant load estimation techniques. Methods for calculating pollutant loads from observed pollutant concentration and modelled streamflow data are also investigated. Sediment export is estimated using these methods over a 10-year period for two case study subcatchments. Approaches for water quality sampling are discussed and a novel monitoring program using rising stage siphon samplers is presented. Results from a refinement of the Sediment River Network model in the upper Murrumbidgee catchment (SedNet-UM) are presented. The model provides a capacity to quantify sediment source, transport and to simulate the effects of management change in the catchment. The investigation of the model includes rigorous examination of the behaviour of the model through sensitivity assessment and comparison with other sediment modelling studies. The major conclusion reached through sensitivity assessment was that the outputs of the model are most sensitive to perturbation of the hydrologic parameters of the model.¶ The SedNet-UM application demonstrates that it is possible to construct stream pollutant models that assist in prioritising management across catchment scales. It can be concluded that SedNet and similar variants have much potential to address common resource management issues requiring the identification of the source, propagation and fate of environmental pollutants. In addition, incorporating the strengths of a conceptual rainfall-runoff model and the semi-distributed SedNet model has been identified as very useful for the future prediction of environmental pollutant export.