This dissertation presents a synthesis of methods for structural optimization of aircraft wing boxes. The optimization problem considered herein is the minimization of structural weight with respect to component sizes, subject to stress constraints. Different aspects of structural optimization methods representing the current state-of-the-art are discussed, including sequential quadratic programming, sensitivity analysis, parameterization of design variables, constraint handling, and multiple load treatment. Shortcomings of the current techniques are identified and a B-spline parameterization representing the structural sizes is proposed to address them. A new configurable B-spline parameterization method for structural optimization of wing boxes is developed that makes it possible to flexibly explore design spaces. An automatic scheme using different levels of B-spline parameterization configurations is also proposed, along with a constraint aggregation method in order to reduce the computational effort. Numerical results are compared to evaluate the effectiveness of the B-spline approach and the constraint aggregation method. To evaluate the new formulations and explore design spaces, the wing box of an airliner is optimized for the minimum weight subject to stress constraints under multiple load conditions. The new approaches are shown to significantly reduce the computational time required to perform structural optimization and to yield designs that are more realistic than existing methods.

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Title: Dynamic model for estimation of radon concentration in buildings Author: Barbora Vaňková Department: Department of probability and mathematical statistics Supervisor: Ing. Marek Brabec, Ph.D. Supervisor's e-mail address: mbrabec@cs.cas.cz Abstract: In the present work there is described the method for estimation of functi- onal data from discrete values and basic methods of functional data analysis. 1

In this thesis, two topics in asymptotic statistics and spline functions are studied. / The first one is a study of testing the equality of Sharpe ratios. We compare two approaches to testing for the equality of many Sharpe ratios: the multivariate test of Wright et al. (2014) and Ledoit and Wolf's (2008) pairwise test. Firstly, Ledoit and Wolf's pairwise test is generalized to a multivariate one for direct comparison. We conclude by proposing a modified version that incorporates the Warp-Speed calibration method of Giacomini et al. (2013). The resulting procedure is much less computationally expensive but is comparable in its accuracy. / The second one is a study of the theoretical properties of an exponential weighting aggregated (EWA) penalized spline estimator, where the smoothing parameter is being averaged over an exponential reweighted posterior distribution. We show that the finite sample mean squared error of the EWA estimator is smaller than that of the smooth penalized spline estimator when the smoothing parameter is chosen to be a fixed value. Consistency and asymptotic normality of the EWA estimator are also developed under general situations. / 這篇論文研究了兩個關於漸近統計和樣條函數的話題。 / 其一是在假設檢驗夏普比率的相等性這個問題中的應用。我們首先比較了Wright et al.（2014）的多元檢驗方法和Ledoit & Wolf（2008）的二元檢驗方法。我們先將Ledoit & Wolf (2008)的二元檢驗法拓展到多元層面，以方便比較。最後，我們提出了採用Giacomini et al.（2013）的曲速法修改后的自助抽樣檢驗法。這種方法極大地降低了實際計算成本，同時保持了其準確性。 / 其二是對樣條估計的漸近表現的研究。我們研究了指數權重合計平滑樣條（EWA）估計，這種方法通過貝葉斯法給予平滑參數一個後驗分佈并將其加權合計。我們通過擴展一個oracle不等式驗證了EWA估計的方差比選定了一個平滑參數的一般平滑樣條估計的方差要小。此外，我們還驗證了EWA估計在一般情況下的一致性和漸近正態性。 / Huang, Wei. / Thesis M.Phil. Chinese University of Hong Kong 2014. / Includes bibliographical references (leaves 80-84). / Abstracts also in Chinese. / Title from PDF title page (viewed on 13, September, 2016). / Detailed summary in vernacular field only. / Detailed summary in vernacular field only. / Detailed summary in vernacular field only.

by Tat-Ming Tso. / Thesis (M.Phil.)--Chinese University of Hong Kong, 1997. / Includes bibliographical references (p. 43-45). / Chapter Chapter 1 --- INTRODUCTION --- p.1 / Chapter §1.1 --- Introduction --- p.1 / Chapter §1.2 --- Preconditioned Conjugate Gradient Method --- p.3 / Chapter §1.3 --- Outline of Thesis --- p.3 / Chapter Chapter 2 --- CIRCULANT AND NON-CIRCULANT PRECONDITIONERS --- p.5 / Chapter §2.1 --- Circulant Matrix --- p.5 / Chapter §2.2 --- Circulant Preconditioners --- p.6 / Chapter §2.3 --- Circulant Preconditioners from Kernel Function --- p.8 / Chapter §2.4 --- Non-circulant Band-Toeplitz Preconditioners --- p.9 / Chapter Chapter 3 --- B-SPLINES --- p.11 / Chapter §3.1 --- Introduction --- p.11 / Chapter §3.2 --- New Version of B-splines --- p.15 / Chapter Chapter 4 --- CIRCULANT PRECONDITIONERS CONSTRUCTED FROM B-SPLINES --- p.24 / Chapter Chapter 5 --- NUMERICAL RESULTS AND CONCLUDING REMARKS --- p.28 / Chapter Chapter 6 --- APPLICATIONS TO SIGNAL PROCESSING --- p.37 / Chapter §6.1 --- Introduction --- p.37 / Chapter §6.2 --- Preconditioned regularized least squares --- p.39 / Chapter §6.3 --- Numerical Example --- p.40 / REFERENCES --- p.43

En esta investigación se hace un estudio preliminar de la regresión en general y sus tipos para luego centrarse en el estudio teórico del Modelo de Regresión no Paramétrico Spline, que es un polinomio cúbico por secciones o trozos, demostrándose sus bondades y ductilidad con respecto a los polinomios en general. Al unir dos polinomios para obtener un polinomio por secciones mayormente el punto de unión no es suave o simplemente no se unen, lo que deriva en cambios bruscos, pero si se utilizan polinomios Spline que es un caso particular de los polinomios por secciones, y que tiene como una de sus propiedades que la primera derivada de la función Spline hace que la unión no sea brusca y la segunda derivada permite la concavidad al unir dos polinomios, lográndose una curva suavizada de tendencia continua. En las últimas décadas investigadores están utilizando modelos de regresión no paramétricos para suavizar curvas correspondientes a un conjunto de pares de datos, en demografía para hacer aproximaciones de la tendencia de los componentes demográficos tales como la fecundidad, mortalidad y la población propiamente dicha, por ello en la presente investigación se aplica el modelo de regresión no paramétrico Spline en la suavización la curva correspondiente a la estructura de mortalidad por sexo y edad utilizando datos de las defunciones de 14 las Estadísticas Vitales del año 2007 y Censo Nacional de Población del 2007, correspondientes al departamento de Lima. Se concluye que la suavización de la estructura de la mortalidad con el Spline es adecuado y se sugiere su utilización como una forma alternativa de suavizamiento de dicha estructura. / Tesis

Publicación a texto completo no autorizada por el autor / Estudia la regresión en general y sus tipos, para luego centrarse en el estudio teórico del modelo de regresión no paramétrico Spline, que es un polinomio cúbico por secciones o trozos, demostrándose sus bondades y ductilidad con respecto a los polinomios en general. Al unir dos polinomios para obtener un polinomio por secciones mayormente el punto de unión no es suave o simplemente no se unen, lo que deriva en cambios bruscos, pero si se utilizan polinomios Spline que es un caso particular de los polinomios por secciones, y que tiene como una de sus propiedades que la primera derivada de la función Spline hace que la unión no sea brusca y la segunda derivada permite la concavidad al unir dos polinomios, lográndose una curva suavizada de tendencia continua. En las últimas décadas investigadores están utilizando modelos de regresión no paramétricos para suavizar curvas correspondientes a un conjunto de pares de datos, en demografía para hacer aproximaciones de la tendencia de los componentes demográficos tales como la fecundidad, mortalidad y la población propiamente dicha, por ello en la presente investigación se aplica el modelo de regresión no paramétrico Spline en la suavización la curva correspondiente a la estructura de mortalidad por sexo y edad utilizando datos de las defunciones de las estadísticas vitales del año 2007 y Censo Nacional de Población del 2007, correspondientes al departamento de Lima. Se concluye que la suavización de la estructura de la mortalidad con el Spline es adecuado y se sugiere su utilización como una forma alternativa de suavizamiento de dicha estructura. / Tesis

In the dissertation, a monotone spline-based nonparametric estimation method is proposed for analyzing longitudinal data with mixture distributions. The innovative and efficient algorithm combining the concept of projected Newton-Raphson algorithm with linear mixed model estimation method is developed to obtain the nonparametric estimation of monotone B-spline functions. This algorithm provides an efficient and flexible approach for modeling longitudinal data monotonically. An iterative 'one-step-forward' algorithm based on the K-means clustering is then proposed to classify mixture distributions of longitudinal data. This algorithm is computationally efficient, especially for data with a large number of underlying distributions. To quantify the disparity of underlying distributions of longitudinal data, we also propose an index measure on the basis of the aggregated areas under the curve (AAUC), which makes no distributional assumptions and fits the theme of nonparametric analysis. An extensive simulation study is conducted to assess the empirical performance of our method under different AAUC values, covariance structures, and sample sizes. Finally, we apply the new approach in the PREDICT-HD study, a multi-site observational study of Huntington Disease (HD), to explore and assess clinical markers in motor and cognitive domains for the purpose of distinguishing participants at risk of HD from healthy subjects.

Here we search for the curve which has the smallest integral of the square of curvature, while passing through two given points with given orientation. This is the true shape of a spline used in lofting. In computer-aided design, curves have been sought which maximize "smoothness". The curve discussed here is the one arising in this way from a commonly used measure of smoothness. The human visual system may use such a curve when it constructs a subjective contour.

An evolutionary geometry parametrization is established to represent aerodynamic configurations. This geometry parametrization technique is constructed by integrating the classical B-spline formulation with the knot insertion algorithm. It is capable of inserting control points to a given parametrization without modifying its geometry. Taking advantage of this technique, a shape design problem can be solved as a sequence of optimizations from the basic parametrization to more refined parametrizations. Owing to the nature of the B-spline formulation, feasible parametrization refinements are not unique; guidelines based on sensitivity analysis and geometry constraints are developed to assist the automation of the proposed optimization sequence. Test cases involving airfoil optimization and induced drag minimization are solved adopting this method. Its effectiveness is demonstrated through comparisons with optimizations using uniform refined parametrizations.