abstract: The growing use of synthetic population, which is a disaggregate representation of the population of an area similar to the real population currently or in the future, has motivated the analysis of its sensitivity in the population generation procedure. New methods in PopGen have enhanced the generation of synthetic populations whereby both household-level and person-level characteristics of interest can be matched in a computationally efficient manner. In the process of set up, population synthesis procedures need sample records for households and persons to match the marginal totals with a specific set of control variables for both the household and person levels, or only the household level, for a specific geographic resolution. In this study, an approach has been taken to analyze the sensitivity by changing and varying this number of controls, with and without taking person controls. The implementation of alternative constraints has been applied on a sample of three hundred block groups in Maricopa County, Arizona. The two datasets that have been used in this study are Census 2000 and a combination of Census 2000 and ACS 2005-2009 dataset. The variation in results for two different rounding methods: arithmetic and bucket rounding have been examined. Finally, the combined sample prepared from the available Census 2000 and ACS 2005-2009 dataset was used to investigate how the results differ when flexibility for drawing households is greater. Study shows that fewer constraints both in household and person levels match the aggregate total population more accurately but could not match distributions of individual attributes. A greater number of attributes both in household and person levels need to be controlled. Where number of controls is higher, using bucket rounding improves the accuracy of the results in both aggregate and disaggregates level. Using combined sample gives the software more flexibility as well as a rich seed matrix to draw households which generates more accurate synthetic population. Therefore, combined sample is another potential option to improve the accuracy in matching both aggregate and disaggregate level household and person distributions. / Dissertation/Thesis / M.S. Civil and Environmental Engineering 2012

[pt] Este trabalho apresenta uma metodologia para priorização de obras de Subtransmissão. Explorando-se as características radiais destes sistemas, utilizou-se a análise de Sensibilidade como ferramenta principal para se obter um índice que caracterizasse a Prioridade das Obras. / [en] This work presents a methodology for Priority Evaluation of Projects in Subtransmission System. The network particular characteristics were useful in using the Sensitivity Analysis applied as the principal tool in order to obrain an index to characterize Priority of the Project.

In this study, Hazus-MH (v 2.1 SP 2) flood-loss estimation tools were assessed for their sensitivity to an array of different building and model parameters. The purpose of this study is to help guide users of the Hazus-MH flood-loss modeling tool in the selection of most appropriate model parameters. Six model parameters (square footage of the building, building age, construction types, foundation types, first floor heights, and the number of stories in the building) were assessed for their impacts on flood losses using the Hazus-MH user defined and aggregate flood-loss models. Building stock databases for these analyses were developed using county assessor records from two Illinois counties. A validation assessment was also performed using observed flood-damage survey data collected after the 2011 Mississippi River Flood which inundated the Olive Branch Area in Alexander County, Illinois. This analysis was performed to assess the accuracy of the detailed Hazus-MH User Defined Facility (UDF) flood-loss modeling tool. The foundation types and its associated first floor heights and number of stories in the building were found to substantially impact flood-loss estimates using the Hazus-MH flood-loss modeling tool. The model building parameters square footage, building age and construction type had little or no effect on the flood-loss estimates. The validation assessment reveled Hazus-MH UDF flood-loss modeling tool is capable of providing a reasonable estimate of actual flood losses. The validation assessment showed the modeled results to be within 23% of actual losses. The validation study results attained in this study using the detailed UDF flood-loss modeling tool where more realistic (within 23% of actual losses versus > 50% of actual losses) than previous Hazus-MH flood-loss validation assessments. The flood-loss estimates could be further improved by modifying or choosing a more region specific depth-damage curve, using higher resolution DEM and improving the flood-depth grid by incorporating more detailed flood elevation data or estimates using detailed hydraulic models that better reflects the local inundation conditions.

Thermoacoustic instability is one of the most significant problems faced in the design of some combustion systems. Thermoacoustic oscillations arise due to feedback between acoustic waves and unsteady heat release rate when the fluctuating heat release rate is sufficiently in phase with the unsteady pressure. The primary aim of designers is to design linearly stable thermoacoustic systems in which these dangerous oscillations do not arise. In thermoacoustics, adjoint-based sensitivity analysis has shown promise at predicting the parameters which have the most influence on the linear growth and decay rates as well as oscillation frequency observed during periods of linear growth and decay. Therefore, adjoint-based methods could prove to be a valuable tool for developing optimal passive control solutions. This thesis aims to develop novel experimental sensitivity analysis techniques and provide a first comparison with the predictions of adjoint-based sensitivity analysis. In this thesis experimental sensitivity analysis is performed on (i) a vertical electrically-driven Rijke tube, and (ii) a vertical flame-driven Rijke tube. On the electrically-driven Rijke tube, the feedback sensitivity is studied by investigating the shift in linear growth and decay rates and oscillation frequency observed during periods of linear growth and decay due to the introduction of a variety of passive control devices. On the flame-driven Rijke tube, the base-state sensitivity is studied by investigating how the linear growth and decay rates as well as oscillation frequency during periods of linear growth and decay change as the convective time delay of the flame is modified. Adjoint-based sensitivity analysis gives the shift in linear growth and decay rate and the oscillation frequency when parameters are changed. This thesis provides experimental measurements of the same quantities, for comparison with the numerical sensitivity analysis, opening up new avenues for the development, implementation and validation of optimal passive control strategies for more complex thermoacoustic systems.

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L'analyse de sensibilité globale a un rôle clé à jouer dans la conception et la paramétrisation des modèles structure-fonction de la croissance des plantes (FSPM). Ceux-ci combinent la description du développement structurel des plantes (organogénèse et géométrie) et de leur croissance fonctionnelle (accumulation de biomasse et allocation). Les modèles de ce type décrivent généralement de nombreux processus en interaction, comptent un grand nombre de paramètres et leur coût de calcul peut être important. L'objectif de cette thèse est de développer une méthodologie appropriée pour l'analyse de sensibilité des modèles structure-fonction des plantes et d'étudier comment l'analyse de sensibilité peut aider à la conception et la paramétrisation de ces modèles, ainsi qu'à l'analyse et la compréhension des processus biologiques en jeu. Notre contribution peut être vue en deux parties : du point de vue méthodologique Et du point de vue de l'application des méthodes aux modèles. D'un point de vue méthodologique, nous avons tout d'abord amélioré les performances de la méthode de Sobol pour le calcul des indices de sensibilité en termes d'efficacité de calcul, avec un meilleur contrôle de l'erreur d'estimation par les simulations de Monte Carlo. Nous avons _également conçu une stratégie d'analyse adaptée aux systèmes biophysiques complexes. Du point de vue applicatif, nous avons implémenté notre stratégie pour 3 FSPMs avec des niveaux de complexité différents, et nous avons analysé les résultats selon différents aspects, paramétrisation et diagnostic de modèles. / Global sensitivity analysis has a key role to play in the design and parameterization of functional-structural plant growth models (FSPM) which combine the description of plant structural development (organogenesis and geometry) and functional growth (biomass accumulation and allocation). Models of this type generally describe many interacting processes, count a large number of parameters, and their computational cost can be important. The general objective of this thesis is to develop a proper methodology for the sensitivity analysis of functional structural plant models and to investigate how sensitivity analysis can help for the design and parameterization of such models as well as providing insights for the understanding of underlying biological processes. Our contribution can be summarized in two parts: from the methodology point of view, we first improved the performance of the existing Sobol's method to compute sensitivity indices in terms of computational efficiency, with a better control of the estimation error for Monte Carlo simulation, and we also designed a proper strategy of analysis for complex biophysical systems; from the application point of view, we implemented our strategy for 3 FSPMs with different levels of complexity, and analyzed the results from different perspectives (model parameterization, model diagnosis).

Made available in DSpace on 2014-06-12T15:58:19Z (GMT). No. of bitstreams: 2 arquivo3464_1.pdf: 2672787 bytes, checksum: 9bee33c2153182c2ce64b9027453243a (MD5) license.txt: 1748 bytes, checksum: 8a4605be74aa9ea9d79846c1fba20a33 (MD5) Previous issue date: 2011 / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior / Sistemas computacionais estão em constante evolução para satisfazer crescimentos na demanda, ou novas exigências dos usuários. A administração desses sistemas requer decisões que sejam capazes de prover o nível mais alto nas métricas de desempenho e dependabilidade, com mudanças mínimas `a configuração existente. É comum realizar análises de desempenho, confiabilidade, disponibilidade e performabilidade de sistemas através de modelos analíticos, e as cadeias de Markov representam um dos formalismos matemáticos mais utilizados, permitindo estimar algumas métricas de interesse, dado um conjunto de parâmetros de entrada. No entanto, a análise de sensibilidade, quando feita, é executada simplesmente variando o conjunto de parâmetros dentro de suas faixas de valores e resolvendo repetidamente o modelo escolhido. A análise de sensibilidade diferencial permite a quem está modelando encontrar gargalos de uma maneira mais sistemática e eficiente. Este trabalho apresenta uma abordagem automatizada para análise de sensibilidade, e almeja guiar a melhoria de sistemas computacionais. A abordagem proposta é capaz de acelerar o processo de tomada de decisão, no que se refere a optimização de ajustes de hardware e software, além da aquisição e substituição de componentes. Tal metodologia usa as cadeias de Markov como técnica de modelagem formal, e a análise de sensibilidade desses modelos, preenchendo algumas lacunas encontradas na literatura sobre análise de sensibilidade. Por fim, a análise de sensibilidade de alguns sistemas distribuídos selecionados, conduzida neste trabalho, destaca gargalos nestes sistemas e fornece exemplos da acurácia da metodologia proposta, assim como ilustra sua aplicabilidade

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