O problema ocasionado pela contração de polimerização é crítico, pois a resina composta deve conservar-se intimamente ligada à cavidade dentária enquanto ganha rigidez e diminui suas dimensões. Forçando-se o material restaurador a se distanciar, ou se separar das paredes da cavidade, a consequente ruptura levaria a uma microinfiltração marginal responsável por outros problemas tais como a cárie secundária, sensibilidade dolorosa pós-operatória, podendo até provocar alterações pulpares. Este processo induz a alteração volumétrica do composto, dado pela união de radicais na formação da macromolécula (polímero), causando uma diminuição em seu volume. Esse estudo teve como objetivo desenvolver novos compósitos experimentais, por meio da adição de nanocomponentes argilominerais em uma matriz polimérica a base de BisGMA/TEGDMA, para que assim se avalie a possibilidade de ocorrer um comportamento dimensional diferenciado no decorrer da polimerização. Foram utilizados nesse estudo matrizes poliméricas adicionadas com nanopartículas argilominerais MMT Cloisite 10A® (nas concentrações de 50, 55, 60, 65 e 70% em massa) e Cloisite 30B® (nas concentrações de 50, 55, 60 e 65% em massa) , que posteriormente foram comparados com o desempenho de compósitos experimentais adicionados com partículas micro-híbridas de Sílica Silanizada Aerosil® OX-50 ( nas concentrações de 50, 60, 65 e 70% em massa). Foram utilizados os métodos de caracterização: Microscopia Eletrônica de Varredura (MEV), Análise Térmica-Mecânica (TMA), Análise de Termogravimetria (TGA), Calorimetria Exploratória Diferencial (DSC), Espectroscopia de Absorção na Região do Infravermelho (FTIR), Difração de Raio-X (DRX), Micro Dureza Knoop, Técnica de Interferometria Holográfica (TIH), Holografia Digital (HD), Correlação de Imagem (CI) e Termografia. Foi observado que os compósitos experimentais adicionados com as nanopartículas argilominerais Cloisite 10A® e Cloisite 30B®, apresentaram um melhor desempenho nos ensaios que mensuraram a contração de polimerização (TMA, TIH/HD/CI) e a micro dureza (Knoop), em relação aos compósitos adicionados com a Sílica Aerosil®OX-50. Esses resultados podem estar relacionados pela interação polímero /argila e pela formação de nanocompósitos, observados pela análise de DRX. Entre as nanopartículas estudadas, a Cloisite 30B® apresentou os resultados mais expressivos em relação a nanopartícula Cloisite 10A® e isso pode ser atribuído a afinidade química e a natureza polar da referida nanopartícula. / The problem caused by polymerization shrinkage is critical, because the resin must to remain closely in the tooth cavity while gaining rigidity and decrease its dimensions. Forcing the restorative material to distance or to separate the walls of the cavity, the resulting disruption would lead to microleakage, responsible for other problems such as secondary caries, postoperative soreness and may even cause pulpal changes. This process induces the volumetric change of the compound, given by the union of radicals in the formation of the macromolecule (polymer), causing a decrease in volume. This study aimed to develop new experimental composites through the addition of nano components clay minerals in a polymer matrix-based BisGMA / TEGDMA, to evaluate the possibility of a different dimensional behavior during the polymerization. Were used in this study, experimental composites added nanoparticle clay MMT Cloisite ® 10A (at concentrations of 50, 55, 60, 65 and 70 wt%) and Cloisite ® 30B (at concentrations of 50, 55, 60 and 65 wt%), which were then compared with the performance of the experimental composites added with micro-particles of silanized silica hybrid Aerosil OX-50 ® (at concentrations of 50, 60, 65 and 70 wt%). Was used the methods of characterization: Scanning Electron Microscopy (SEM), Thermal-Mechanical Analysis (TMA), Thermogravimetric Analysis (TGA), Differential Scanning Calorimetry (DSC), Absorption Spectroscopy in the Region of the Infrared (FTIR), X-ray Diffraction (XRD), Micro Hardness Knoop, Holographic Interferometry Technique (HIT), Digital Holography (DH), Correlation Image (CI) and Thermography. It was observed that the experimental composites with nanoparticles added clay Cloisite ® 10A and Cloisite ® 30B, performed better on tests that measured the polymerization shrinkage (TMA, HIT / HD / IC) and the micro hardness (Knoop), in relation to composites added with Silica Aerosil OX-50®. These results may be related to the interaction polymer / clay and the nanocomposites formation, observed by XRD analysis. Among the nanoparticles studied, the Cloisite ® 30B showed the most significant results in relation to the nanoparticle Cloisite ® 10A and this can be attributed to chemical affinity and polar nature of that nanoparticle.

Mass spectrometry (MS) is widely used for proteomic and metabolomic profiling of biological samples. Data obtained by MS are often zero-inflated. Those zero values are called point mass values (PMVs). Zero values can be further grouped into biological PMVs and technical PMVs. The former type is caused by the absence of components and the latter type is caused by detection limit. There is no simple solution to separate those two types of PMVs. Mixture models were developed to separate the two types of zeros apart and to perform the differential abundance analysis. However, we notice that the mixture model can be unstable when the number of non-zero values is small. In this dissertation, we propose a new differential abundance (DA) analysis method, DASEV, which applies an empirical Bayes shrinkage estimation on variance. We hypothesized that performance on variance estimation could be more robust and thus enhance the accuracy of differential abundance analysis. Disregarding the issue the mixture models have, the method has shown promising strategies to separate two types of PMVs. We adapted the mixture distribution proposed in the original mixture model design and assumed that the variances for all components follow a certain distribution. We proposed to calculate the estimated variances by borrowing information from other components via applying the assumed distribution of variance, and then re-estimate other parameters using the estimated variances. We obtained better and more stable estimations on variance, means abundances, and proportions of biological PMVs, especially where the proportion of zeros is large. Therefore, the proposed method achieved obvious improvements in DA analysis. We also propose to extend the method for clustering analysis. To our knowledge, commonly used cluster methods for MS omics data are only K-means and Hierarchical. Both methods have their own limitations while being applied to the zero-inflated data. Model-based clustering methods are widely used by researchers for various data types including zero-inflated data. We propose to use the extension (DASEV.C) as a model-based cluster method. We compared the clustering performance of DASEV.C with K-means and Hierarchical. Under certain scenarios, the proposed method returned more accurate clusters than the standard methods. We also develop an R package dasev for the proposed methods presented in this dissertation. The major functions DASEV.DA and DASEV.C in this R package aim to implement the Bayes shrinkage estimation on variance then conduct the differential abundance and cluster analysis. We designed the functions to allow the flexibility for researchers to specify certain input options.

Among all casting defects, shrinkage porosities could significantly reduce the strength of metal parts. As several critical components in aerospace and automotive industries are manufactured through casting processes, ensuring these parts are free of defects and are structurally sound is an important issue. This study investigates the formation of shrinkage-related defects in alloy solidification. To have a better understanding about the defect formation mechanisms, three sets of experimental studies were performed. In the first experiment, a real-time video radiography technique is used for the observation of pore nucleation and growth in a wedge-shaped A356 aluminum casting. An image-processing technique is developed to quantify the amount of through-thickness porosity observed in the real-time radiographic video. Experimental results reveal that the formation of shrinkage porosity in castings has two stages: 1-surface sink formation and 2- internal porosity evolution. The transition from surface sink to internal porosity is defined by a critical coherency limit of . In the second and third experimental sets, two Manganese-Steel (Mn-Steel) castings with different geometries are selected. Several thermocouples are placed at different locations in the sand molds and castings to capture the cooling of different parts during solidification. At the end of solidification, castings are sectioned to observe the porosity distributions on the cut surfaces. To develop alloys’ thermo-physical properties, MAGMAsoft (a casting simulation software package) is used for the thermal simulations. To assure that the thermal simulations are accurate, the properties are adjusted to get a good agreement between simulated and measured temperatures by thermocouples. Based on the knowledge obtained from the experimental observations, a mathematical model is developed for the prediction of shrinkage porosity in castings. The model, called “advanced feeding model”, includes 3D multi-phase continuity, momentum and pore growth rate equations which inputs the material properties and transient temperature fields, and outputs the feeding velocity, liquid pressure and porosity distributions in castings. To solve the model equations, a computational code with a finite-volume approach is developed for the flow calculations. To validate the model, predicted results are compared with the experimental data. The comparison results show that the advanced feeding model can accurately predict the occurrence of shrinkage porosity defects in metal castings. Finally, the model is optimized by performing several parametric studies on the model variables.

During the late 70's and early 80's, several precast deck panel bridges were constructed in Florida. These utilize prestressed precast panels as stay-in-place forms and are designed to act compositely with a cast-in-place deck which is poured subsequently. Such bridges offer advantages of quicker construction and lower costs. However, several such bridges built in Florida developed extensive cracking and spalling. Following localized failures, the Florida Department of Transportation has decided to replace all 127 precast panel deck bridges in Districts 1 and 7. Since deck replacement is contingent on funding, it is necessary to develop a rational procedure to decide the order in which they are replaced. This requires a better understanding of the deterioration process and failure mechanism in such bridge decks. The methodology used in this study was to first analyze in detail 5 cases of sudden localized deck failures to identify the causes of the failures and any common factors in the failed bridges. Also, forensic studies were conducted on eight bridges scheduled for deck replacements during 2003 and 2004. In these studies it was possible to investigate in detail the condition of the deck at different stages of deterioration. Based on the information collected, a deck failure model was developed.

A cement material has been developed that has a controllable set time, compressive strength of about 50 MPa and shrinkage of under 2% when heated to 960 degrees centigrade. The main compound of this material has been shown to be the potassium analogue of struvite, in which potassium ion is substituted for the ammonium ion. The cement is formed by reacting a slurry made with potassium carbonate and monoammonium phosphate with magnesium oxide. Ihe amount and rate of addition of water to the mixture is controlled to determine the set time. It has been demonstrated that this cement may be used as a matrix in conjunction with cenospheres or cellulose fibres to form a low density composite material, and with silica powder to form a high strength composite. As well as optimising the cement mix for maximum strength and minimum shrinkage, a variety of properties of the K-cement were investigated. It was found that long term exposure of the cement to the atmosphere does not result in the formation of magnesium carbonate, but long term exposure to saline solutions can result in the formation of dypingite on the surface. No effect on strength was observed as a consequence of the age of the slurry or the cement, within 1-2 weeks / Doctor of Philosophy (PhD)

Low Pressure Die Casting (LPDC) process is one the most common casting process to produce structural automotive components, such as alloy wheels and suspension components. It has been identified that cavity filling and solidification process are two most critical aspects to produce premium quality casting components.During the solidification process of casting alloy, it is a well known phenomenon that metal experiences volumetric shrinkage due to its density difference between liquid and solid phase. When this volumetric shrinkage is not properly compensated, then a casting defect commonly known as solidification shrinkage occurs. The solidification shrinkage has very detrimental effects on structural integrity required for premium quality casting such as aluminium alloy wheels.Literature and practical experiences of foundry men show that it is critical to achieve unidirectional solidification pattern by avoiding an isolated hot spot in order to minimise the solidification shrinkage. However, it is found that the geometry of industrial casting applications is often constrained by other design factors that would not naturally avoid these isolated hot spots. The subject of this research, aluminium alloy wheels, is not excluded from this constraint.In aluminium alloy wheels, an isolated hot spot is commonly observed in an area known as rim and spoke junction due to its geometry constraints. Consequently, the solidification shrinkage is commonly experienced, which is undesirable due to its detrimental effects for the structural integrity of alloy wheels. In order to minimise the solidification shrinkage, forced cooling method is applied to avoid an isolated hot spot. The control of this forced cooling is achieved by cooling media, flow rate of cooling media and duration cooling circuit. Foundry experiments in industrial environment were conducted producing aluminium alloy wheels using commercially treated A356 (Al-Si) alloy, where different durations of cooling circuit were used to understand the sensitivity of solidification shrinkage formation to the duration of cooling circuit. This was followed by metallurgical structure analysis and numerical modelling to suggest the sensitivity of cooling circuit duration in controlling solidification shrinkage.The major finding conclusion of this research is that control of the shrinkage formation is not very sensitive to the duration cooling circuit. It is suggested that as casting solidifies initially from the mould wall, it retracts away from the cast-mould interface due to thermal contraction. Consequently, air gap is formed between casting and mould interface, creating an effective thermal resistance layer. Thereafter, heat transfer across the cast-mould interface is not sensitive to the change in the cooling channel which is a distance to the cast-mould interface.Some limitations of numerical modelling and metallurgical analysis were also identified during this research and recommendations were made to improve the accuracy of local hot spot prediction in production of aluminium alloy wheels. More specifically, numerical modelling of the effect of grain refinement and use of non homogeneous material property (particularly fraction of solid) for rapidly chilled area. Fraction of eutectic rather than secondary dendrites arm spacing is a proper microstructure parameter that can be used to locate the hot spot.

<p>Denna uppsats syftar till att undersöka användbarheten av metoden Independent Component Analysis (ICA) för brusreducering av bilder tagna av infraröda kameror. Speciellt fokus ligger på att reducera additivt brus. Bruset delas upp i två delar, det Gaussiska bruset samt det sensorspecifika mönsterbruset. För att reducera det Gaussiska bruset används en populär metod kallad sparse code shrinkage som bygger på ICA. En ny metod, även den byggandes på ICA, utvecklas för att reducera mönsterbrus. För varje sensor utförs, i den nya metoden, en analys av bilddata för att manuellt identifiera typiska mönsterbruskomponenter. Dessa komponenter används därefter för att reducera mönsterbruset i bilder tagna av den aktuella sensorn. Det visas att metoderna ger goda resultat på infraröda bilder. Algoritmerna testas både på syntetiska såväl som på verkliga bilder och resultat presenteras och jämförs med andra algoritmer.</p> / <p>The purpose of this thesis is to evaluate the applicability of the method Independent Component Analysis (ICA) for noise reduction of infrared images. The focus lies on reducing the additive uncorrelated noise and the sensor specific additive Fixed Pattern Noise (FPN). The well known method sparse code shrinkage, in combination with ICA, is applied to reduce the uncorrelated noise degrading infrared images. The result is compared to an adaptive Wiener filter. A novel method, also based on ICA, for reducing FPN is developed. An independent component analysis is made on images from an infrared sensor and typical fixed pattern noise components are manually identified. The identified components are used to fast and effectively reduce the FPN in images taken by the specific sensor. It is shown that both the FPN reduction algorithm and the sparse code shrinkage method work well for infrared images. The algorithms are tested on synthetic as well as on real images and the performance is measured.</p>

In spectral analysis of high dimensional multivariate time series, it is crucial to obtain an estimate of the spectrum that is both numerically well conditioned and precise. The conventional approach is to construct a nonparametric estimator by smoothing locally over the periodogram matrices at neighboring Fourier frequencies. Despite being consistent and asymptotically unbiased, these estimators are often ill-conditioned. This is because a kernel smoothed periodogram is a weighted sum over the local neighborhood of periodogram matrices, which are each of rank one. When treating high dimensional time series, the result is a bad ratio between the smoothing span, which is the effective local sample size of the estimator, and dimension. In classification, clustering and discrimination, and in the analysis of non-stationary time series, this is a severe problem, because inverting an estimate of the spectrum is unavoidable in these contexts. Areas of application like neuropsychology, seismology and econometrics are affected by this theoretical problem. We propose a new class of nonparametric estimators that have the appealing properties of simultaneously having smaller L2-risk than the smoothed periodogram and being numerically more stable due to a smaller condition number. These estimators are obtained as convex combinations of the averaged periodogram and a shrinkage target. The choice of shrinkage target depends on the availability of prior knowledge on the cross dimensional structure of the data. In the absence of any information, we show that a multiple of the identity matrix is the best choice. By shrinking towards identity, we trade the asymptotic unbiasedness of the averaged periodogram for a smaller mean-squared error. Moreover, the eigenvalues of this shrinkage estimator are closer to the eigenvalues of the real spectrum, rendering it numerically more stable and thus more appropriate for use in classification. These results are derived under a rigorous general asymptotic framework that allows for the dimension p to grow with the length of the time series T. Under this framework, the averaged periodogram even ceases to be consistent and has asymptotically almost surely higher L2-risk than our shrinkage estimator. Moreover, we show that it is possible to incorporate background knowledge on the cross dimensional structure of the data in the shrinkage targets. We derive an exemplary instance of a custom-tailored shrinkage target in the form of a one factor model. This offers a new answer to problems of model choice: instead of relying on information criteria such as AIC or BIC for choosing the order of a model, the minimum order model can be used as a shrinkage target and combined with a non-parametric estimator of the spectrum, in our case the averaged periodogram. Comprehensive Monte Carlo studies we perform show the overwhelming gain in terms of L2-risk of our shrinkage estimators, even for very small sample size. We also give an overview of regularization techniques that have been designed for iid data, such as ridge regression or sparse pca, and show the interconnections between them.

The major cause of cracking in bridge decks, concrete pavements, as well as slabs on grade, is restrained shrinkage of the concrete. The resulting steel corrosion problem causes tremendous increase of maintenance and replacement cost. Shrinkage-compensating concrete (SHCC) and fiber-reinforced polymer (FRP) are explored to develop a hybrid slab system as one possible method of delaying the cracking and eliminating corrosion. To achieve the objective, a hybrid FRP reinforced SHCC structural system was developmed, and short-term and long-term behavior of this hybrid FRP-SHCC beams were investigated in this dissertation. In the first-stage development, a series of “coffee can” tests were carried out to measure and compare the expansion of SHCC from two candidate materials which were ettringite-system SHCC and lime-system SHCC. The selected SHCC candidate mix was then optimized to get the maximum expansion as well as a reasonable concrete strength. The optimized SHCC mix was used to make FRP-SHCC beams. The expansion of the concrete was measured through strain gauges on the FRP composite sheets during curing. Both glass FRP (GFRP) composite sheets and carbon FRP (CFRP) composite sheets were used for comparison. A series of third-point loading experiments were conducted to study the behavior of the proposed hybrid FRP-SHCC beams. In the second-stage development, long term prestress loss and static structural test of the proposed beams are investigated. Test results were evaluated based on maximum expansion strain, cracking load, crack width, load-deflection and ultimate load.The results indicate that the proposed system is promising in terms of its ability to develop a residual pre-stressing effect. Tests also show that the pre-stressing effect from the expansion of SHCC increases as the axial stiffness of the FRP reinforcement increases. A lime-system SHCC structural system shows higher prestress strain and less prestress loss than an ettringite-system SHCC system over the long term.

En los últimos años, el análisis numérico de problemas acoplados, como los procesos de degradación de materiales y estructuras relacionados con los efectos medioambientales, ha cobrado especial importancia en la comunidad científica de la mecánica del hormigón. Problemas de este tipo son por ejemplo el ataque químico, el efecto de altas temperaturas o la retracción por secado.Tradicionalmente, los análisis acoplados existentes en la literatura se han realizado a nivel macroscópico, considerando el material como un medio continuo y homogéneo. Sin embargo, es bien conocido que el origen de la degradación observada a nivel macroscópico, a menudo es debida a la interacción entre los áridos y el mortero, sobre todo cuando se dan cambios de volumen diferenciales entre los dos componentes. Esta es la razón por la que el análisis mesomecánico está emergiendo como una herramienta potente para estudios de materiales heterogéneos, aunque actualmente existen escasos modelos numéricos capaces de simular un problema acoplado a esta escala de observación.En esta tesis, la aplicabilidad del modelo meso-mecánico de elementos finitos, desarrollado en el seno del grupo de investigación durante los últimos quince años, se extiende al análisis de problemas acoplados higro-mecánicos y químico-mecánicos, con el fin de estudiar la retracción por secado y el ataque sulfático externo en muestras de hormigón. La generación numérica de mesogeometrías y mallas de elementos finitos con los áridos de mayor tamaño rodeados de la fase mortero se consigue mediante la teoría de Voronoï/Delaunay Adicionalmente, con el fin de simular las principales trayectorias de fisuración, se insertan a priori elementos junta de espesor nulo, equipados con una ley constitutiva basada en la mecánica de fractura no lineal, a lo largo de todos los contactos entre árido y matriz, y también en algunas líneas matriz-matriz.La aportación principal de esta tesis es, conjuntamente con la realización de análisis acoplados sobre una representación mesoestructural del material, la simulación no solo de la formación y propagación de fisuras, sino también la consideración explícita de la influencia de éstas en el proceso de difusión.Los cálculos numéricos se realizan mediante el uso de los códigos de elementos finitos DRAC y DRACFLOW, previamente desarrollados en el seno del grupo de investigación, y acoplados mediante una estrategia staggered. Las simula-ciones realizadas abarcan, entre otros aspectos, la evaluación del compor-tamiento acoplado, el ajuste de parámetros del modelo con resultados experimentales disponibles en la bibliografía, diferentes estudios del efecto de los áridos en la microfisuración inducida por el secado y las expansiones debidas al ataque sulfático, así como el efecto simultáneo de los procesos gobernados por difusión y cargas de origen mecánico. Los resultados obtenidos concuerdan con observaciones experimentales de la fisuración, el fenómeno de spalling y la evolución de las deformaciones, y muestran la capacidad del modelo para ser utilizado en el estudio de problemas acoplados en los que la naturaleza heterogénea y cuasi-frágil del material tiene un papel predominante.