Two models of a self-stabilizing hydrofoil system is developed where the effects from the struts and hydrofoil give torques for angular rotations. Lifting line theory for the hydrofoil which can twist is used. Nonlinear versions of the models are also developed and compared to find that the linear models use valid approximations. Backward Differentiation Formula is used to get numerical solutions, and eigenvalues of linear system matrices are used to get stability regions. The models did not accurately capture what has been seen in testing. / Två modeller för ett självstabiliserande bärplanssystem utvecklas där effekter från stöttor och bärplan ger vridmoment för vinkelrotationer. Lyftande linjeteori för det skevande bärplanet används. Icke-linjära versioner av modellerna tas också fram och jämförs för att finna att de linjära modellerna använder giltiga approximationer. Backward Differentiation Formula används för att fram numeriska lösningar, och egenvärden i det linjära systemetsmatriser används för att hitta stabilitetsregioner. Modellerna fångade inte korrekt vad som har setts i testning.

Problemas provenientes de química atmosférica, possuem uma característica especial denominada stiffness, indicando que as soluções dos sistemas de equações diferenciais ordinárias envolvidos variam em diferentes ordens de grandeza. Isso faz com que métodos numéricos adequados devam ser aplicados no intuito de obter soluções numéricas convergentes e estáveis. Os métodos mais eficazes para tratar este tipo de problema são os métodos implícitos, pois possuem uma região de estabilidade ilimitada que permite grandes variações no tamanho do passo, mantendo o erro de discretização dentro de uma dada tolerância. Mais precisamente, estes métodos possuem a propriedade de A-estabilidade ou A(alpha)-estabilidade. Neste trabalho, comparamos dois métodos numéricos com estas características: o método de Rosenbrock e a fórmula de diferenciação regressiva (métodos BDF). O primeiro é usado no módulo de Química do modelo CCATT-BRAMS do Centro de Previsão de Tempo e Estudos Climáticos (CPTEC), sendo incluído na previsão numérica de regiões com intensas fontes de poluição. Este é um método de passo simples implícito com um controle de passo adaptativo. Aqui empregamos também o segundo, um método de passo múltiplo que dispõe de uma fórmula que permite variação no tamanho do passo e na ordem, empregando o pacote LSODE. Os resultados de nossas comparações indicam que os métodos BDF podem se constituir em interessante alternativa para uso no CCATT-BRAMS. / Problems from atmospheric chemistry have a special characteristic denominated stiffness, indicating that the solutions of the involved ordinary differential equations systems vary in different scales. This means that appropriate methods should be applied in order to get convergent and stable numerical solutions. The most powerful methods to treat problems like this are implicit schemes, since they have unlimited stabity regions, allowing large variations in step size, keeping the discretization error within a given tolerance. More precisely, these methods have the A-stability or A(alpha)-stability properties. In this work, we compared two numerical methods with those characteristics: the Rosenbrock method and the backward differentiation formula (BDF). The first one is employed in the Chemistry package within CCATT-BRAMS local weather model of CPTEC (Center for Weather Forecasts and Climate Studies), which is mainly used for the numerical forecasting of regions with intense pollution. This is a implicit one-step method with an adaptative stepsize control. We compare it with the second method, a multistep method with a formula that allows variations in step size and order, with the help of the LSODE package. The results of our comparisons indicate that BDF methods are an interesting alternative to be used within CCATT-BRAMS.

Problemas provenientes de química atmosférica, possuem uma característica especial denominada stiffness, indicando que as soluções dos sistemas de equações diferenciais ordinárias envolvidos variam em diferentes ordens de grandeza. Isso faz com que métodos numéricos adequados devam ser aplicados no intuito de obter soluções numéricas convergentes e estáveis. Os métodos mais eficazes para tratar este tipo de problema são os métodos implícitos, pois possuem uma região de estabilidade ilimitada que permite grandes variações no tamanho do passo, mantendo o erro de discretização dentro de uma dada tolerância. Mais precisamente, estes métodos possuem a propriedade de A-estabilidade ou A(alpha)-estabilidade. Neste trabalho, comparamos dois métodos numéricos com estas características: o método de Rosenbrock e a fórmula de diferenciação regressiva (métodos BDF). O primeiro é usado no módulo de Química do modelo CCATT-BRAMS do Centro de Previsão de Tempo e Estudos Climáticos (CPTEC), sendo incluído na previsão numérica de regiões com intensas fontes de poluição. Este é um método de passo simples implícito com um controle de passo adaptativo. Aqui empregamos também o segundo, um método de passo múltiplo que dispõe de uma fórmula que permite variação no tamanho do passo e na ordem, empregando o pacote LSODE. Os resultados de nossas comparações indicam que os métodos BDF podem se constituir em interessante alternativa para uso no CCATT-BRAMS. / Problems from atmospheric chemistry have a special characteristic denominated stiffness, indicating that the solutions of the involved ordinary differential equations systems vary in different scales. This means that appropriate methods should be applied in order to get convergent and stable numerical solutions. The most powerful methods to treat problems like this are implicit schemes, since they have unlimited stabity regions, allowing large variations in step size, keeping the discretization error within a given tolerance. More precisely, these methods have the A-stability or A(alpha)-stability properties. In this work, we compared two numerical methods with those characteristics: the Rosenbrock method and the backward differentiation formula (BDF). The first one is employed in the Chemistry package within CCATT-BRAMS local weather model of CPTEC (Center for Weather Forecasts and Climate Studies), which is mainly used for the numerical forecasting of regions with intense pollution. This is a implicit one-step method with an adaptative stepsize control. We compare it with the second method, a multistep method with a formula that allows variations in step size and order, with the help of the LSODE package. The results of our comparisons indicate that BDF methods are an interesting alternative to be used within CCATT-BRAMS.

Physiological signals, which are controlled by the autonomic nervous system (ANS), could be used to detect the affective state of computer users and therefore find applications in medicine and engineering. The Pupil Diameter (PD) seems to provide a strong indication of the affective state, as found by previous research, but it has not been investigated fully yet. In this study, new approaches based on monitoring and processing the PD signal for off-line and on-line affective assessment (“relaxation” vs. “stress”) are proposed. Wavelet denoising and Kalman filtering methods are first used to remove abrupt changes in the raw Pupil Diameter (PD) signal. Then three features (PDmean, PDmax and PDWalsh) are extracted from the preprocessed PD signal for the affective state classification. In order to select more relevant and reliable physiological data for further analysis, two types of data selection methods are applied, which are based on the paired t-test and subject self-evaluation, respectively. In addition, five different kinds of the classifiers are implemented on the selected data, which achieve average accuracies up to 86.43% and 87.20%, respectively. Finally, the receiver operating characteristic (ROC) curve is utilized to investigate the discriminating potential of each individual feature by evaluation of the area under the ROC curve, which reaches values above 0.90. For the on-line affective assessment, a hard threshold is implemented first in order to remove the eye blinks from the PD signal and then a moving average window is utilized to obtain the representative value PDr for every one-second time interval of PD. There are three main steps for the on-line affective assessment algorithm, which are preparation, feature-based decision voting and affective determination. The final results show that the accuracies are 72.30% and 73.55% for the data subsets, which were respectively chosen using two types of data selection methods (paired t-test and subject self-evaluation). In order to further analyze the efficiency of affective recognition through the PD signal, the Galvanic Skin Response (GSR) was also monitored and processed. The highest affective assessment classification rate obtained from GSR processing is only 63.57% (based on the off-line processing algorithm). The overall results confirm that the PD signal should be considered as one of the most powerful physiological signals to involve in future automated real-time affective recognition systems, especially for detecting the “relaxation” vs. “stress” states.

<p>Thorium dioxide (ThO₂) and metallic uranium (alpha-U) represent important alternative nuclear fuels. Investigating the behavior of defects introduced into these materials in an irradiation environment is critical for understanding microstructure evolution and property changes. The objective of this dissertation is to investigate the clustering of point defects in ThO₂ and alpha-U under irradiation, into voids and prismatic dislocation loops as a function of irradiation dose rate and temperature. To achieve this, we have developed a mean-field cluster dynamics (CD) model based on reaction rate theory to predict the evolution of self-interstitial atom (SIA) and vacancy loops in neutron-irradiated alpha-U. Detailed atomistic simulations have been carried out using molecular dynamics (MD) to study the configuration of such loops and compute their energetics, which are essential parameters of the CD model. Bond-boost hyper-MD simulations have been performed to compute the diffusivity of uranium SIA and vacancies, which govern the kinetics of the clustering phenomenon. Another CD model has been demonstrated for proton-irradiated ThO₂, considering the clustering of Th and O SIA and vacancies into SIA loops and voids, respectively, with varying sizes and stoichiometry. The compositions of all SIA loops and voids dictated by crystallography of ThO₂ in its fluorite structure have been presented in their respective cluster composition space (CCS). The CD model solves the density evolution of off-stoichiometric loops and voids, with irradiation, in their respective CCS. MD simulations have been performed to compute the energetics of different clusters in their CCS, as parameters of the CD model. Temperature-accelerated MD simulations have been performed to compute the diffusivity of Th and O point defects, that dictates the kinetics of defect clustering on irradiation. In alpha-U, the CD predictions show an accumulation of small sized vacancy loops and the growth of SIA loops with irradiation dose, which closely fits the reported size distribution of loops in neutron-irradiated alpha-U by Hudson and coworkers. The CD predicted density of defect clusters in proton-irradiated ThO₂, shows the evolution of near-stoichiometric SIA loops in their CCS. The size distribution of SIA loops at high irradiation doses closely corresponds to the transmission electron microscopy (TEM) observations reported in the literature. Also, the CD model did not predict the growth of voids and vacancy clusters, which is consistent with findings in literature. The model was further used to predict the density of sub-nanometric defect clusters and point defects, on low-dose irradiation, that significantly impairs the thermal conductivity of ThO₂. An extensive TEM and CD investigation has also been carried out to study the growth and coarsening of SIA loop and voids during post-irradiation isochronal annealing of ThO₂ at high temperatures.</p>