Nos últimos anos grande número de modelos computacionais tem sido propostos com o intuito de descrever o movimento de solutos no perfil do solo, apesar disso, o que se observa é que existe grande dificuldade em se modelar esses fenômenos, para que o modelo possa predizer o processo de deslocamento e retenção dos solutos na natureza. Para tanto, o objetivo deste trabalho foi utilizar um modelo estatístico para descrever o transporte dos solutos no perfil do solo. Dessa forma, foi realizado um experimento em laboratório e observado os níveis de potássio e nitrato ao longo do perfil dos solos Latossolo Vermelho Amarelo e Nitossolo Vermelho. Para inferir sobre essas variáveis foram consideradas duas abordagens. Para a primeira abordagem foi utilizado um modelo de regressão não linear para cada uma das variáveis, cujos parâmetros do modelo apresentam uma interpretação prática, na área de solos. Para esse modelo foi realizado um esboço sobre a não linearidade do mesmo para verificar as propriedades assintóticas dos estimadores dos parâmetros. Para o método de estimação foi considerado, o método de mínimos quadrados e o método de bootstrap. Além disso, foi realizada uma análise de diagnóstico para verificar a adequação do modelo, bem como identificar pontos discrepantes. Por outro lado, para outra abordagem, foi utilizado um modelo multiresposta para analisar o comportamento das variáveis nitrato e potássio ao longo do perfil dos solos, conjuntamente. Para esse modelo foi utilizado o método da máxima verossimilhança para encontrar as estimativas dos parâmetros do modelo. Em ambas as situações, observou-se a adequação dos modelos para descrever o comportamento dos solutos nos solos, sendo uma alternativa para os pesquisadores que trabalham com estudo de solos. O modelo logístico com quatro parâmetros se destacou por apresentar melhores propriedades, como medidas de não linearidade e boa qualidade de ajuste. / In the last years, several computational models have been proposed to describe the movement of solutes in the soil profile, but what is observed is that there is great difficulty in model these phenomena, so that model can predict the displacement process and retention of solutes in nature. Thus, the aim of this study was to use a statistical model to describe the transport of solutes in the soil profile. Therefore, an experiment was conducted in the laboratory and observed levels of potassium and nitrate along the depth of soil Oxisol (Haplustox) and Hapludox,. To make inferences about these variables were considered two approaches. For the first approach was utilized a non-linear regression model for each variable and the model parameters have a practical interpretation on soil. For this model we performed a sketch on the nonlinearity of the model to check the asymptotic properties of parameter estimators. To estimate the parameters were considered the least squares method and the bootstrap method. In addition, we performed a diagnostic analysis to verify the adequacy of the model and identify outliers. In the second approach considered was using a multi-response model to analyze the behavior of the variables nitrate and potassium throughout the soil profile together. For this model we used the maximum likelihood method to estimate the model parameters. In both cases, we observed the suitability of the models to describe the behavior of solutes in soils, being an alternative for researchers working on the study of soils. The logistic model with four parameters stood out with better properties, such as non-linearity and good fit.

We study nonlinear least-squares problem that can be transformed to linear problem by change of variables. We derive a general formula for the statistically optimal weights and prove that the resulting linear regression gives an optimal estimate (which satisfies an analogue of the Rao–Cramer lower bound) in the limit of small noise.

No description available.

Regional flood frequency techniques are commonly used to estimate flood quantiles when flood data are unavailable or the record length at an individual gauging station is insufficient for reliable analyses. These methods compensate for limited or unavailable data by pooling data from nearby gauged sites. This requires the delineation of hydrologically homogeneous regions in which the flood regime is sufficiently similar to allow the spatial transfer of information. Therefore, several Regional Flood Frequency Analysis (RFFA) methods are applied to the Ceyhan Basin. Dalyrmple (1960) Method is applied as a common RFFA method used in Turkey. Multivariate statistical techniques which are Stepwise and Nonlinear Regression Analysis are also applied to flood statistics and basin characteristics for gauging stations. Rainfall, Perimeter, Length of Main River, Circularity, Relative Relief, Basin Relief, Hmax, Hmin, Hmean and H&Delta / are the simple additional basin characteristics. Moreover, before the analysis started, stations are clustered according to their basin characteristics by using the combination of Ward&rsquo / s and k-means clustering techniques. At the end of the study, the results are compared considering the Root Mean Squared Errors, Nash-Sutcliffe Efficiency Index and % difference of results. Using additional basin characteristics and making an analysis with multivariate statistical techniques have positive effect for getting accurate results compared to Dalyrmple (1960) Method in Ceyhan Basin. Clustered region data give more accurate results than non-clustered region data. Comparison between clustered region and non-clustered region Q100/Q2.33 reduced variate values for whole region is 3.53, for cluster-2 it is 3.43 and for cluster-3 it is 3.65. This show that clustering has positive effect in the results. Nonlinear Regression Analysis with three clusters give less errors which are 29.54 RMSE and 0.735 Nash-Sutcliffe Index, when compared to other methods in Ceyhan Basin.

Although there exist some consensus regarding seismic soil liquefaction assessment of free field soil sites, estimating the liquefaction triggering potential beneath building foundations still stays as a controversial and difficult issue. Assessing liquefaction triggering potential under building foundations requires the estimation of cyclic and static stress state of the soil medium. For the purpose of assessing the effects of the presence of a structure three-dimensional, finite difference-based total stress analyses were performed for generic soil, structure and earthquake combinations. A simplified procedure was proposed which would produce unbiased estimates of the representative and maximum soil-structure-earthquake-induced iv cyclic stress ratio (CSRSSEI) values, eliminating the need to perform 3-D dynamic response assessment of soil and structure systems for conventional projects. Consistent with the available literature, the descriptive (input) parameters of the proposed model were selected as soil-to-structure stiffness ratio, spectral acceleration ratio (SA/PGA) and aspect ratio of the building. The model coefficients were estimated through maximum likelihood methodology which was used to produce an unbiased match with the predictions of 3-D analyses and proposed simplified procedure. Although a satisfactory fit was achieved among the CSR estimations by numerical seismic response analysis results and the proposed simplified procedure, validation of the proposed simplified procedure further with available laboratory shaking table and centrifuge tests and well-documented field case histories was preferred. The proposed simplified procedure was shown to capture almost all of the behavioral trends and most of the amplitudes. As the concluding remark, contrary to general conclusions of Rollins and Seed (1990), and partially consistent with the observations of Finn and Yodengrakumar (1987), Liu and Dobry (1997) and Mylonakis and Gazetas, (2000), it is proven that soil-structure interaction does not always beneficially affect the liquefaction triggering potential of foundation soils and the proposed simplified model conveniently captures when it is critical.

Made available in DSpace on 2015-03-26T14:02:17Z (GMT). No. of bitstreams: 1 texto completo.pdf: 627381 bytes, checksum: b98c2d603d0b5930a8386f8bc84fc09a (MD5) Previous issue date: 2013-07-24 / This study aimed to evaluate the growth curve of Holstein heifers. For this purpose, 839 weight and height measurements of heifers raised in Animal Science Department of Federal University of Viçosa was collected. Data collection was performed every 30 days in confined animals fed with sugarcane and corn silage, receiving on average 1 kg / head / day of concentrate. The correlation between body weight and age of heifers was describe by four nonlinear models: Brody: Weight (W) = A x (1 be-kt)3; Gompertz: W = A x exp(- be-kt); Logistics: W = A x (1 + be-kt)-1; Von Bertalanffy: W = A x (1 be-kt), where A = represents the adult weight; k = maturity rate; b = mathematical constant, no biological definition; t = age in days. The estimation model of body weight from the wither heightwas tested using the general dataset, i.e., using 839 measurements, and separately analyzed different weight categories: 0-500 kg; 0 -400 kg and 0-300 kg, which contained, respectively, 770, 647 and 530 observations.The weight / height ratio was evaluated as function of age, adjusted a simple linear regression in function of age. Was adjusted Heinrichs and exponential models to describe the weight of heifers in function of wither height. All models were fitted using SAS®software using MODEL, NLIN and GLM procedures. Regarding the setting of nonlinear models, the Logistic model showed better results, resulting in the estimates for the parameters: mature weight of 615 kg, maturity rate of 0.0056 and sexual maturity at about 307 kg. The wither height stabilization occurred at the age of 632 days (21 months at a height of 138 cm). Exponential model showed better results compared to Heinrichs model, therefore was chosen to describe the correlation between wither height and body weight. An estimated equation for this model was given by: Weight = 4.3577 x EXP (0.0343 x ALT), where ALT = wither height. The use of body measurements as wither height to estimate body weight of Holstein heifers can be performed until the age of 21 months, allowing small farmers,who do not have scales to monitor the development of the heifers. / O presente trabalho foi conduzido para avaliar a curva de crescimento de novilhas Holandesas. Foram obtidas 839 medidas de peso e altura de novilhas criadas no Setor de Gado de Leite do Departamento de Zootecnia da Universidade Federal de Viçosa, MG. A coleta de dados foi realizada a cada 30 dias. Os animais foram criados em sistema confinado, com alimentação de cana de açúcar e silagem de milho, recebendo diariamente 1 kg de concentrado. A relação entre peso vivo e idade de novilhas foi descritapor meio de quatro diferentes modelos não lineares: Brody: Peso = A x (1 be-kt)3; Gompertz: Peso = A x exp(-be-kt); Logístico: Peso = A x (1 + be-kt)-1; Von Bertalanffy: Peso = A x (1 be-kt), onde: A = representa o peso adulto; k = taxa de maturidade, ou velocidade de crescimento; b = constante matemática, sem definição biológica; t = idade em dias.O modelo de estimação do peso corporal a partir da altura de cernelha foi testado com o conjunto geral de dados, i.e., utilizando as 839 medidas, e também analisou-se separadamente as categorias de peso: 0-500 kg; 0-400 kg; e 0-300 kg, as quais continham, respectivamente, 770, 647 e 530 observações. Foi realizada uma avaliação da relação peso/altura em função da idade utilizando-se uma regressão linear simples. Foram ajustadosos modelos Heinrichs e exponencial para descrever o peso das novilhas em função da altura da cernelha. Todos os modelos foram ajustados por meio do software SAS® usando os procedimentos MODEL, NLIN e GLM. Em relação ao ajuste dos modelos não lineares, o modelo Logístico apresentou melhor resultado, resultando nas seguintes estimativas para os parâmetros: peso à maturidade de 615 kg, taxa de maturidade de 0,0056 e maturidade sexual com cerca de 307 kg. A estabilização da altura de cernelha ocorreu na idade de 632 dias (21 meses a uma altura de 138 cm). O modelo exponencial apresentou melhor resultados em relação ao modelo Heinrichs, portanto foi escolhido para descrever a relação entre altura de cernelha e peso corporal. A equação estimada para este modelo foi dada por: Peso = 4,3577 x EXP(0,0343 x ALT), onde ALT é altura de cernelha. O uso de medidas corporais, como altura de cernelha, para estimar o peso corporal de novilhas Holandesas pode ser realizado até a idade de 21 meses, possibilitando aos pequenos produtores rurais, que não possuem balança, a acompanhar o desenvolvimento ponderal de suas novilhas.

Nos últimos anos grande número de modelos computacionais tem sido propostos com o intuito de descrever o movimento de solutos no perfil do solo, apesar disso, o que se observa é que existe grande dificuldade em se modelar esses fenômenos, para que o modelo possa predizer o processo de deslocamento e retenção dos solutos na natureza. Para tanto, o objetivo deste trabalho foi utilizar um modelo estatístico para descrever o transporte dos solutos no perfil do solo. Dessa forma, foi realizado um experimento em laboratório e observado os níveis de potássio e nitrato ao longo do perfil dos solos Latossolo Vermelho Amarelo e Nitossolo Vermelho. Para inferir sobre essas variáveis foram consideradas duas abordagens. Para a primeira abordagem foi utilizado um modelo de regressão não linear para cada uma das variáveis, cujos parâmetros do modelo apresentam uma interpretação prática, na área de solos. Para esse modelo foi realizado um esboço sobre a não linearidade do mesmo para verificar as propriedades assintóticas dos estimadores dos parâmetros. Para o método de estimação foi considerado, o método de mínimos quadrados e o método de bootstrap. Além disso, foi realizada uma análise de diagnóstico para verificar a adequação do modelo, bem como identificar pontos discrepantes. Por outro lado, para outra abordagem, foi utilizado um modelo multiresposta para analisar o comportamento das variáveis nitrato e potássio ao longo do perfil dos solos, conjuntamente. Para esse modelo foi utilizado o método da máxima verossimilhança para encontrar as estimativas dos parâmetros do modelo. Em ambas as situações, observou-se a adequação dos modelos para descrever o comportamento dos solutos nos solos, sendo uma alternativa para os pesquisadores que trabalham com estudo de solos. O modelo logístico com quatro parâmetros se destacou por apresentar melhores propriedades, como medidas de não linearidade e boa qualidade de ajuste. / In the last years, several computational models have been proposed to describe the movement of solutes in the soil profile, but what is observed is that there is great difficulty in model these phenomena, so that model can predict the displacement process and retention of solutes in nature. Thus, the aim of this study was to use a statistical model to describe the transport of solutes in the soil profile. Therefore, an experiment was conducted in the laboratory and observed levels of potassium and nitrate along the depth of soil Oxisol (Haplustox) and Hapludox,. To make inferences about these variables were considered two approaches. For the first approach was utilized a non-linear regression model for each variable and the model parameters have a practical interpretation on soil. For this model we performed a sketch on the nonlinearity of the model to check the asymptotic properties of parameter estimators. To estimate the parameters were considered the least squares method and the bootstrap method. In addition, we performed a diagnostic analysis to verify the adequacy of the model and identify outliers. In the second approach considered was using a multi-response model to analyze the behavior of the variables nitrate and potassium throughout the soil profile together. For this model we used the maximum likelihood method to estimate the model parameters. In both cases, we observed the suitability of the models to describe the behavior of solutes in soils, being an alternative for researchers working on the study of soils. The logistic model with four parameters stood out with better properties, such as non-linearity and good fit.

Orientador: Cláudia Pio Ferreira / Abstract: This thesis presents two manuscripts previously sent to publication in scientific journals. In the first manuscript, a delay differential equation model is developed to study the dynamics of two Aedes aegypti mosquito populations: infected by the intracellular bacteria Wolbachia and non-infected (wild) individuals. All the steady states of the system are determined, namely extinction of both populations, extinction of the infected population and persistence of the non-infected one, and coexistence. Their local stability is analyzed, including Hopf bifurcation, which promotes periodic solutions around the nontrivial equilibrium points. Finally, one investigates the global asymptotic stability of the trivial solution. In the second manuscript, after rearing soybean looper Chrysodeixis includens in laboratory conditions, thermal requirements for this insect-pest are estimated, from linear and nonlinear regression models, as well as the intrinsic growth rate. This parameter depends on the life-history traits and can provide a measure of population viability of the species. / Doutor

The present research seeks to advance the understanding and application of Principal Component Analysis (PCA)-based combustion modelling for practical systems application. This work is a consistent extension to the standard PC-transport model, and integrates the use of Gaussian Process Regression (GPR) in order to increase the accuracy and the potential of size reduction offered by PCA. This new model, labelled PC-GPR, is successively applied and validated in a priori and a posteriori studies.In the first part of this dissertation, the PC-GPR model is validated in an a priori study based on steady and unsteady perfectly stirred reactor (PSR) calculations. The model showed its great accuracy in the predictions for methane and propane, using large kinetic mechanisms. In particular, for methane, the use of GPR allowed to model accurately the system with only 2 principal components (PCs) instead of the 34 variables in the original GRI-3.0 kinetic mechanism. For propane, the model was applied to two different mechanisms consisting of 50 species and 162 species respectively. The PC-GPR model was able to achieve a very significant reduction, and the thermo-chemical state-space was accurately predicted using only 2 PCs for both mechanisms.The second part of this work is dedicated to the application of the PC-GPR model in the framework of non-premixed turbulent combustion in a fully three-dimensional Large Eddy Simulation (LES). To this end, an a posteriori validation is performed on the Sandia flames D, E and F. The PC-GPR model showed very good accuracy in the predictions of the three flames when compared with experimental data using only 2 PCs, instead of the 35 species originally present in the GRI 3.0 mechanism. Moreover, the PC-GPR model was also able to handle the extinction and re-ignition phenomena in flames E and F, thanks to the unsteady data in the training manifold. A comparison with the FPV model showed that the combination of the unsteady data set and the best controlling variables for the system defined by PCA provide an alternative to the use of steady flamelets parameterized by user-defined variables and combined with a PDF approach.The last part of this research focuses on the application of the PC-GPR model in a more challenging case, a lifted methane/air flame. Several key features of the model are investigated: the sensitivty to the training data set, the influence of the scaling methods, the issue of data sampling and the potential of a subgrid scale (SGS) closure. In particular, it is shown that the training data set must contain the effects of diffusion in order to accurately predict the different properties of the lifted flame. Moreover, the kernel density weighting method, used to address the issue of non-homogenous data density usually found in numerical data sets, allowed to improve the predictions of the PC-GPR model. Finally, the integration of subgrid scale closure to the PC-GPR model allowed to significantly improve the simulations results using a presumed PDF closure. A qualitative comparison with the FPV model showed that the results provided by the PC-GPR model are overall very comparable to the FPV results, with a reduced numerical cost as PC-GPR requires a 4D lookup table, instead of a 5D in the case of FPV. / Le double défi de l'énergie et du changement climatique mettent en avant lanécessité de développer des nouvelles technologies de combustion, étantdonné que les projections les plus réalistes montrent que la plus grandeaugmentation de l'offre d'énergie pour les décennies à venir se fera à partirde combustibles fossiles. Ceci représente donc une forte motivation pour larecherche sur l'efficacité énergétique et les technologies propres. Parmicelles-ci, la combustion sans flamme est un concept nouvellementdéveloppé qui permet d'obtenir des rendements thermiques élevés avecdes économies de carburant tout en maintenant les émissions polluantes àun niveau très bas. L'intérêt croissant pour cette technologie est égalementmotivé par sa grande flexibilité de carburant, ce qui représente uneprécieuse opportunité pour les carburants à faible valeur calorifique, lesdéchets industriels à haute valeur calorifique et les combustibles à based'hydrogène. Etant donné que cette technologie est plutôt récente, elle estde ce fait encore mal comprise. Les solutions d'une application industriellesont très difficiles à transposer à d'autres. Pour améliorer les connaissancesdans le domaine de la combustion sans flamme, il est nécessaire de menerdes études fondamentales sur ce nouveau procédé de combustion afin defavoriser son développement. En particulier, il y a deux différencesmajeures par rapport aux flammes classiques :d’une part, les niveaux deturbulence rencontrés dans la combustion sans flamme sont rehaussés, enraison des gaz de recirculation, réduisant ainsi les échelles de mélange.D'autre part, les échelles chimiques sont augmentées, en raison de ladilution des réactifs. Par conséquent, les échelles turbulentes et chimiquessont du même ordre de grandeur, ce qui conduit à un couplage très fort.Après un examen approfondi de l'état de l'art sur la modélisation de lacombustion sans flamme, le coeur du projet représentera le développementd'une nouvelle approche pour le traitement de l'interaction turbulence /chimie pour les systèmes sans flamme dans le contexte des simulationsaux grandes échelles (Large Eddy Simulations, LES). Cette approche serafondée sur la méthode PCA (Principal Component Analysis) afin d'identifierles échelles chimiques de premier plan du processus d'oxydation. Cetteprocédure permettra de ne suivre sur la grille LES qu'un nombre réduit descalaires non conservés, ceux contrôlant l'évolution du système. Destechniques de régression non-linéaires seront couplées avec PCA afind’augmenter la précision et la réductibilité du modèle. Après avoir été validégrâce à des données expérimentales de problèmes simplifiés, le modèlesera mis à l'échelle afin de gérer des applications plus grandes, pertinentespour la combustion sans flamme. Les données expérimentales etnumériques seront validées en utilisant des indicateurs de validationappropriés pour évaluer les incertitudes expérimentales et numériques. / Doctorat en Sciences de l'ingénieur et technologie / info:eu-repo/semantics/nonPublished

No description available.