A compreensão da dependência espacial das propriedades do solo vem sendo cada vez mais requerida por pesquisadores que objetivam melhorar a interpretação dos resultados de experimentos de campo fornecendo, assim, subsídios para novas pesquisas a custos reduzidos. Em geral, variáveis como, por exemplo, o teor de cálcio no solo, estudado neste trabalho, apresentam grande variabilidade impossibilitando, na maioria das vezes, a detecção de reais diferenças estatísticas entre os efeitos de tratamentos. A consideração de amostras georreferenciadas é uma abordagem importante na análise de dados desta natureza, uma vez que amostras mais próximas são mais similares do que as mais distantes e, assim, cada realização desta variável contém informação de sua vizinhança. Neste trabalho, métodos geoestatísticos que baseiam-se na modelagem da dependência espacial, nas pressuposições Gaussianas e nos estimadores de máxima verossimilhança são utilizados para analisar e interpretar a variabilidade do teor de cálcio no solo, resultado de um experimento realizado na Fazenda Angra localizada no Estado do Rio de Janeiro. A área experimental foi dividida em três regiões em função dos diferentes períodos de adubação realizadas. Neste estudo foram utilizados dados do teor de cálcio obtidos das camadas 0-20cm e 20-40cm do solo, de acordo com as coordenadas norte e leste. Modelos lineares mistos, apropriados para estudar dados com esta característica, e que permitem a utilização de diferentes estruturas de covariâncias e a incorporação da região e tendência linear das coordenadas foram usados. As estruturas de covariâncias utilizadas foram: a exponencial e a Matérn. Para estimar e avaliar a variabilidade dos parâmetros utilizaram-se os métodos de máxima verossimilhança, máxima verossimilhança restrita e o perfil de verossimilhança. A identificação da dependência e a predição foram realizadas por meio de variogramas e mapas de krigagem. Além disso, a seleção do modelo adequado foi feita pelo critério de informação de Akaike e o teste da razão de verossimilhanças. Observou-se, quando utilizado o método de máxima verossimilhança, o melhor modelo foi aquele com a covariável região e, com o método de máxima verossimilhança restrita, o modelo com a covariável região e tendência linear nas coordenadas (modelo 2). Com o teor de cálcio, na camada 0-20cm e considerando-se a estrutura de covariância exponencial foram obtidas as menores variâncias nugget e a maior variância espacial (sill - nugget). Com o método de máxima verossimilhança e com o modelo 2 foram observadas variâncias de predição mais precisas. Por meio do perfil de verossimilhança pode-se observar menor variabilidade dos parâmetros dos variogramas ajustados com o modelo 2. Utilizando-se vários modelos e estruturas de covariâncias, deve-se ser criterioso, pois a precisão das estimativas, depende do tamanho da amostra e da especificação do modelo para a média. Os resultados obtidos foram analisados, com a subrotina geoR desenvolvida por Ribeiro Junior & Diggle (2000), e por meio dela pode-se obter estimativas confiáveis para os parâmetros dos diferentes modelos estimados. / The understanding of the spatial dependence of the properties of the soil becomes more and more required by researchers that attempt to improve the interpretation of the results of field experiments supplying subsidies for new researches at reduced costs. In general, variables as, for example, the calcium content in the soil, studied in this work, present great variability disabling, most of the time, the detection of real statistical differences among the treatment effects. The consideration of georeferenced samples is an important approach in the analysis of data of this nature, because closer samples are more similar than the most distant ones and, thus, each realization of this variable contains information of its neighborhood. In this work, geostatistics methods that are based on the modeling of the spatial dependence, under the Gaussian assumptions and the maximum likelihood estimators, are used to analyze and to interpret the variability of calcium content in the soil, obtained from an experiment carried on at Fazenda Angra, located in Rio de Janeiro, Brazil. The experimental area was divided in three areas depending on the different periods of fertilization. In this study, data of the calcium soil content from the layers 0-20cm and 20-40cm, were used, according to the north and east coordinates. Mixed linear models, ideal to study data with this characteristic, and that allow the use of different covariance structures, and the incorporation of the region and linear tendency of the coordinates, were used. The covariance structures were: the exponential and the Matérn. Maximum likelihood, maximum restricted likelihood and the profile of likelihood methods were used to estimate and to evaluate the variability of the parameters. The identification of the dependence and the prediction were realized using variograms and krigging maps. Besides, the selection of the appropriate model was made through the Akaike information criterion and the likelihood ratio test. It was observed that when maximum likelihood method was used the most appropriate model was that with the region covariate and, with the maximum restricted likelihood method, the best model was the one with the region covariate and linear tendency in the coordinates (model 2). With the calcium content, in the layer 0-20cm and considering the exponential covariance structure, the smallest nugget variances and the largest spatial variance (sill - nugget) were obtained. With the maximum likelihood method and with the model 2 more precise prediction variances were observed. Through the profile of likelihood method, smaller variability of the adjusted variogram parameters can be observed with the model 2. With several models and covariance structures being used, one should be very critical, because the precision of the estimates depends on the size of the sample and on the specification of the model for the average. The obtained results were analyzed, with the subroutine geoR developed by Ribeiro Junior & Diggle (2000), and through this subroutine, reliable estimates for the parameters of the different estimated models can be obtained.

The populations of the ghost-crab Ocypode quadrata have been evaluated as bioindicators at sandy beaches, but for this purpose some shortcomings need to be addressed. This study assessed several features of the species biology, from daily activity cycles to effectively its role as bioindicator. Between that, the occupation of burrows was evaluated at several morphodymically distinct beaches and it differed temporally, among the areas and within beach strata, indicating that assessing these populations through the indirect method require more caution. The period of the year after major cold fronts showed the most similar values between individuals and burrows, followed by the greater entrance of young recorded. No trend according to beach type was identified for mean size, dissipative beaches tended to have higher densities, while body growth performance index was higher at reflective beaches, gathering therefore both similarities and differences concerning the trends known for other crustaceans from these environments. The use of the species as bioindicator was effective and gathered distinct areas, through the use of a new method. Increasing levels of erosion were associated to increasing mean densities and mean sizes, followed by a sharp decrease of both, especially mean size. Connectivity breakage, e.g., armoring and vegetation removal, proved to be a threat to the populations structure, worsened when associated to erosion process, to an extent that compromise the populations viability. / As populações do caranguejo Ocypode quadrata, conhecido no Brasil como guaruçá ou maria-farinha, têm sido exploradas como bioindicadores da qualidade de praias arenosas, mas para tal algumas lacunas precisam ser preenchidas. Este trabalho levantou diversas características da espécie no litoral sudeste brasileiro, desde ciclos diários de atividade até sua aplicação como bioindicador. Nesse entremeio, as taxas de ocupação das tocas foram avaliadas em diversas praias morfodinamicamente distintas, sendo que houve variação temporal, entre praias e mesmo entre estratos de uma mesma praia, indicando que avaliações dessas populações através do método indireto requerem maior cautela. O período pós frentes frias teve o número de tocas e de animais mais semelhante, seguido da maior entrada de recrutas. O tamanho médio dos indivíduos não apresentou tendências de acordo com o tipo praial, a densidade de indivíduos foi maior nas praias dissipativas e a performance de crescimento estimada foi maior em praias reflexivas, agregando características tanto similares quanto opostas aos outros crustáceos desses ambientes. O uso da espécie como bioindicador foi válido e incorporou áreas distintas, através do emprego de um novo método. Níveis crescentes de erosão foram associados a um inicial aumento de densidade e tamanho médios, seguido de um decréscimo severo de ambos, especialmente de tamanho. A quebra de conectividade, e.g. construções e remoção da vegetação, foi também responsável pela alteração da estrutura das populações, sendo a condição agravada em casos de associação com erosão, a ponto de comprometer a viabilidade das populações.

Made available in DSpace on 2017-07-10T19:24:46Z (GMT). No. of bitstreams: 1 Marcio Paulo de Oliveira.pdf: 1960743 bytes, checksum: 7438fe00d388d47b01b27d6cfdf2e229 (MD5) Previous issue date: 2010-02-04 / The knowledge about soil and plant attributes is important for the improvement of agricultural management. Intense tillage activities may induce not only alterations in the soil attributes but also decrease in productivity. Studies directed to the soil and plant spatial variability identification and the relations amid these variables are tools for agriculture, with the potential to increase productivity. The data set for this study was sampled in a Rhodic Acrudox soil, at a farmland that has been being cultivated for over five years under no-tillage system, with soybean and wheat in crop succession. At 252 m long transect, 84 points were demarcated, with 3 m of spacing between each of them. The relations between soybean productivity and soil water content, micro, macro and total porosity, soil density and soil resistance to penetration at 0,0-0,10 m and 0,10-0,20 m deep layers, were evaluated, as well as the respective variabilities. The relations between soybean productivity and soil attributes were determined using simple and cross correlations, followed by the state space models determinations, compared to linear and multiple regression models. The results have shown that the soybean productivity and soil mechanical resistance variables presented not only autocorrelation structure but also crosscorrelation structure. The state space models, relating to the soybean productivity at a point i, with the same attribute at point i-1, at the two layers, were more efficient than the equivalent models in simple and multiple regression. With geoestatistics, the spatial dependence structure was determined with envelopes and models for the semivariograms, allowing identification and classification of the spatial dependence for the variables under study. The thematic maps were obtained with simple kriging and indicated the soil attributes behavior, related to the soybean productivity. / O conhecimento do comportamento dos atributos do solo e da planta é importante para a melhoria das práticas agrícolas. A intensa atividade de cultivo pode provocar modificações dos atributos do solo e reduzir a produtividade de uma cultura em determinada região. Os estudos que visam identificar a variabilidade espacial dos atributos do solo e da planta e a relação entre esses atributos surgem como um recurso para a agricultura, podendo ser utilizados para realização de um manejo adequado dos recursos disponíveis, ampliando a produtividade e preservando o meioambiente. Os dados para a realização deste estudo foram obtidos em um Latossolo Vermelho distroférrico, em uma área cultivada há mais de cinco anos com alternância entre as culturas de soja e trigo, com o sistema de plantio direto. Em uma transeção de 252 m de comprimento foram demarcados 84 elementos amostrais, espaçados de 3 m entre si. As relações da produtividade da soja com os seguintes atributos físicos e hídricos do solo: teor de água no solo, microporosidade, macroporosidade e porosidade total do solo, densidade do solo e resistência mecânica do solo à penetração, nas camadas 0,0-0,10 m e 0,10-0,20 m, foram avaliadas bem como a variabilidade espacial desses atributos. A relação entre a produtividade da soja e os atributos do solo foi determinada através das correlações simples e cruzada entre os elementos amostrais de cada atributo, seguida da estimação dos modelos em espaço de estados, comparados aos modelos equivalentes em regressão linear múltipla. Os resultados mostraram que as variáveis produtividade da soja e resistência do solo a penetração apresentaram estrutura de autocorrelação e de correlação cruzada entre si. Os modelos estimados em espaço de estados, relacionando a produtividade da soja em um ponto i com a produtividade da soja e resistência do solo a penetração nas duas camadas no ponto i -1 mostraram-se mais eficientes do que os modelos equivalentes estimados em regressão linear simples e múltipla. Por meio da geoestatística, a estrutura de dependência espacial foi avaliada por meio dos envelopes e modelos para os semivariogramas experimentais, permitindo identificar e classificar a dependência espacial das variáveis em estudo. Os mapas temáticos foram obtidos por meio de interpolação por krigagem ordinária e indicaram o comportamento dos atributos do solo ligadas a produtividade da soja.

Made available in DSpace on 2017-05-12T14:48:09Z (GMT). No. of bitstreams: 1 Marcio Paulo de Oliveira.pdf: 1960743 bytes, checksum: 7438fe00d388d47b01b27d6cfdf2e229 (MD5) Previous issue date: 2010-02-04 / The knowledge about soil and plant attributes is important for the improvement of agricultural management. Intense tillage activities may induce not only alterations in the soil attributes but also decrease in productivity. Studies directed to the soil and plant spatial variability identification and the relations amid these variables are tools for agriculture, with the potential to increase productivity. The data set for this study was sampled in a Rhodic Acrudox soil, at a farmland that has been being cultivated for over five years under no-tillage system, with soybean and wheat in crop succession. At 252 m long transect, 84 points were demarcated, with 3 m of spacing between each of them. The relations between soybean productivity and soil water content, micro, macro and total porosity, soil density and soil resistance to penetration at 0,0-0,10 m and 0,10-0,20 m deep layers, were evaluated, as well as the respective variabilities. The relations between soybean productivity and soil attributes were determined using simple and cross correlations, followed by the state space models determinations, compared to linear and multiple regression models. The results have shown that the soybean productivity and soil mechanical resistance variables presented not only autocorrelation structure but also crosscorrelation structure. The state space models, relating to the soybean productivity at a point i, with the same attribute at point i-1, at the two layers, were more efficient than the equivalent models in simple and multiple regression. With geoestatistics, the spatial dependence structure was determined with envelopes and models for the semivariograms, allowing identification and classification of the spatial dependence for the variables under study. The thematic maps were obtained with simple kriging and indicated the soil attributes behavior, related to the soybean productivity. / O conhecimento do comportamento dos atributos do solo e da planta é importante para a melhoria das práticas agrícolas. A intensa atividade de cultivo pode provocar modificações dos atributos do solo e reduzir a produtividade de uma cultura em determinada região. Os estudos que visam identificar a variabilidade espacial dos atributos do solo e da planta e a relação entre esses atributos surgem como um recurso para a agricultura, podendo ser utilizados para realização de um manejo adequado dos recursos disponíveis, ampliando a produtividade e preservando o meioambiente. Os dados para a realização deste estudo foram obtidos em um Latossolo Vermelho distroférrico, em uma área cultivada há mais de cinco anos com alternância entre as culturas de soja e trigo, com o sistema de plantio direto. Em uma transeção de 252 m de comprimento foram demarcados 84 elementos amostrais, espaçados de 3 m entre si. As relações da produtividade da soja com os seguintes atributos físicos e hídricos do solo: teor de água no solo, microporosidade, macroporosidade e porosidade total do solo, densidade do solo e resistência mecânica do solo à penetração, nas camadas 0,0-0,10 m e 0,10-0,20 m, foram avaliadas bem como a variabilidade espacial desses atributos. A relação entre a produtividade da soja e os atributos do solo foi determinada através das correlações simples e cruzada entre os elementos amostrais de cada atributo, seguida da estimação dos modelos em espaço de estados, comparados aos modelos equivalentes em regressão linear múltipla. Os resultados mostraram que as variáveis produtividade da soja e resistência do solo a penetração apresentaram estrutura de autocorrelação e de correlação cruzada entre si. Os modelos estimados em espaço de estados, relacionando a produtividade da soja em um ponto i com a produtividade da soja e resistência do solo a penetração nas duas camadas no ponto i -1 mostraram-se mais eficientes do que os modelos equivalentes estimados em regressão linear simples e múltipla. Por meio da geoestatística, a estrutura de dependência espacial foi avaliada por meio dos envelopes e modelos para os semivariogramas experimentais, permitindo identificar e classificar a dependência espacial das variáveis em estudo. Os mapas temáticos foram obtidos por meio de interpolação por krigagem ordinária e indicaram o comportamento dos atributos do solo ligadas a produtividade da soja.

Le comportement géomécanique des ouvrages géotechniques à l’exemple des rideaux de palplanches est entaché d’incertitudes épistémiques liées aux hypothèses régissant le modèle géomécanique de calcul, mais aussi d’incertitudes aléatoires liées à la variabilité spatiale du sol. L’objectif principal de cette thèse est de mieux appréhender l’effet de ces incertitudes sur le comportement d’un rideau de palplanches. Pour cela le présent mémoire s’articule autour de quatre points principaux : Le premier point est relatif d’une part à l’analyse des hypothèses utilisées pour la modélisation géomécanique d’un rideau de palplanches et d’autre part à l’extension de la méthode des coefficients de réaction d’un système unidimensionnel basé sur une poutre et des appuis élastoplastiques à un système bidimensionnel de plaque orthotrope sur le même type d’appuis (MISS-CR-PLQ). Le deuxième point concerne la modélisation de la variabilité spatiale du sol. Après une comparaison entre deux méthodes de génération de champs aléatoires nous avons retenu la méthode Circulant Embedding pour son efficience. Plusieurs études paramétriques ont été menées pour analyser les effets des hypothèses prises lors de la génération des champs aléatoires. Le troisième point concerne la mise en place d’une démarche mécano-fiabiliste permettant d’intégrer la variabilité spatiale du sol pour le cas des rideaux de palplanches. Le quatrième point est consacré à l’application de la démarche développée pour un cas d’étude à travers des analyses probabilistes et fiabilistes. L’influence des paramètres statistiques (e.g. les longueurs de corrélations, la corrélation croisée, …), mécanique et géométrique a été étudiée. / The geomechanical behaviour of geotechnical structures such as sheet pile walls is subjected to epistemic uncertainties due to geomechanical models’ assumptions and also the aleatory uncertainties which could be related to the soil spatial variability. The main objective of this thesis is to gain more insight into the effect of these uncertainties on the sheet pile behaviour. To this end, this thesis focuses on four main issues: The first one is related on the one hand to the analysis of the used geomechanical hypotheses for modelling of retaining walls. On the other hand, to extend the one-dimensional subgrade reaction method which is based on a beam relying on elastoplastic supports to a two-dimensional system that call to an orthotropic plate relying on the same supports (MISS-CR-PLQ). The second issue concerns the soil spatial variability modelling. After a key comparison between two random field generation methods, we selected the Circulating Embedding method for its efficiency. Several parametric studies have been conducted to analyse the effects of different assumptions of random field generation. The third issue is related to the implementation of the proposed mechanical-reliability approach taking into account the soil spatial variability. The last issue is devoted to the application of the developed approach to a case study through probabilistic and reliability analyses. The influence of statistical parameters (e.g. correlation lengths, cross-correlation,...), mechanical and geometrical has been examined.

It is believed that the extremely hot European summer in 2003, where tens of thousands died in buildings, will become the norm by the 2040s, and hence there is the urgent need to accurately assess the risk that buildings pose. Thermal simulations based on warmer than typical years will be key to this. Unfortunately, the existing warmer than typical years, such as probabilistic Design Summer Years (pDSYs) are not robust measures due to their simple selection method, and can even be cooler than typical years. This study developed two new summer reference years: one (pHSY-1) is suitable for assessing the occurrence and severity of overheating while the other (pHSY-2) is appropriate for evaluating the thermal stress. Both have been proven to be more robust than the pDSYs. In addition, this study investigated the spatial variation in overheating driven by variability in building characteristics and the local environment. This variation had been ignored by previous studies, as most of them either created thermal models using building archetypes with little or no concern about the influence of local shading, or assumed little variation in climate across a landscape. For the first time, approximately a thousand more accurate thermal models were created for a UK city based on the remote measurement including building characteristics and their local shading. By producing overheating and mortality maps this study found that spatial variation in the risk of overheating was considerably higher due to the variability of vernacular forms, contexts and climates than previously thought, and that the heat-related mortality will be tripled by the 2050s if no building and human thermal adaptations are taken. Such maps would be useful to Governments when making cost-effective adaptation strategies against a warming climate.

Fire is the primary natural disturbance vital to the ecological integrity of Quetico Provincial Park, Ontario, Canada. A new provincial park planning process (i.e., Class Environmental Assessment) has required the review of Quetico’s Fire Management Plan. To support this review, large and severe (stand-replacing) Quetico fires were studied using 1966 Ontario Ministry of Natural Resources (OMNR) forest resource inventory (FRI) mapping. A Geographic Information Systems (GIS) database of the FRI was created and updated with the OMNR digital fire atlas. This database was used as a time-since-fire and fire interval dataset to estimate fire frequency. It also served to archive the 1966 FRI for the largest protected area in the transition between the Boreal and Great Lakes-St. Lawrence forest regions. Non-parametric (Kaplan-Meier) survival analysis was used to estimate survival functions and mean fire intervals (i.e., the expected time between two consecutive stand-replacing fires for any location within the Park). Previous studies that have used Kaplan-Meier survival analysis methods have based fire frequency estimates solely on time-since-fire data. However, time-since-fire data cannot be equated with fire interval data when using non-parametric methods. At least one fire interval is required to obtain reliable results. The mean fire interval for the entire 475,782 ha Park between the years 1668 and 2007 was 230 years. Performing the analysis on various geographic and temporal partitions revealed fire frequency spatial and temporal variability. A constant (independent of time-since-fire) probability of burning was not observed for Quetico which is contrary to accepted conjecture for northwestern Ontario boreal/mixed-wood forests. A current fire cycle was also estimated for the Park (342 years) using the digital fire atlas. The results suggested that use of historical static fire frequency estimates as fire management prescriptions may not be justified given considerable fire frequency temporal variability. The observed fire frequency spatial variability suggests that studies should be undertaken at coarser scales than is the norm to characterise the regions fire regime in support of landscape level fire management planning.

Fire is the primary natural disturbance vital to the ecological integrity of Quetico Provincial Park, Ontario, Canada. A new provincial park planning process (i.e., Class Environmental Assessment) has required the review of Quetico’s Fire Management Plan. To support this review, large and severe (stand-replacing) Quetico fires were studied using 1966 Ontario Ministry of Natural Resources (OMNR) forest resource inventory (FRI) mapping. A Geographic Information Systems (GIS) database of the FRI was created and updated with the OMNR digital fire atlas. This database was used as a time-since-fire and fire interval dataset to estimate fire frequency. It also served to archive the 1966 FRI for the largest protected area in the transition between the Boreal and Great Lakes-St. Lawrence forest regions. Non-parametric (Kaplan-Meier) survival analysis was used to estimate survival functions and mean fire intervals (i.e., the expected time between two consecutive stand-replacing fires for any location within the Park). Previous studies that have used Kaplan-Meier survival analysis methods have based fire frequency estimates solely on time-since-fire data. However, time-since-fire data cannot be equated with fire interval data when using non-parametric methods. At least one fire interval is required to obtain reliable results. The mean fire interval for the entire 475,782 ha Park between the years 1668 and 2007 was 230 years. Performing the analysis on various geographic and temporal partitions revealed fire frequency spatial and temporal variability. A constant (independent of time-since-fire) probability of burning was not observed for Quetico which is contrary to accepted conjecture for northwestern Ontario boreal/mixed-wood forests. A current fire cycle was also estimated for the Park (342 years) using the digital fire atlas. The results suggested that use of historical static fire frequency estimates as fire management prescriptions may not be justified given considerable fire frequency temporal variability. The observed fire frequency spatial variability suggests that studies should be undertaken at coarser scales than is the norm to characterise the regions fire regime in support of landscape level fire management planning.

The properties of natural soil are inherently variable and influence design decisions in geotechnical engineering. Apart from the inherent variability of the soil, the variability may arise due to measurement of soil properties in the field or laboratory tests and model errors. These wide ranges of variability in soil are expressed in terms of mean, variance and autocorrelation function using probability/reliability based models. The most common term used in reliability based design is the reliability index, which is a probabilistic measure of assurance of performance of structure. The main objective of the reliability based design is to quantify probability of failure/reliability of a geotechnical system considering variability in the design parameters and associated safety. In foundation design, reliability based design is useful compared to deterministic factor of safety approach. Several design codes of practice recommend the use of limit state design concept based on probabilistic models, and suggest that, development of reliability based design methodologies for practical use are of immense value. The objective of the present study is to propose reliability based design methodologies for pile foundations under static and seismic loads. The work presented in this dissertation is subdivided into two parts, namely design of pile foundations under static vertical and lateral loading; and design of piles under seismic loading, embedded in non-liquefiable and liquefiable soil. The significance of consideration of variability in soil parameters in the design of pile foundation is highlighted. A brief review of literature is presented in Chapter 2 on current pile design methods under vertical, lateral and seismic loads. It also identifies the scope of the work. Chapter 3 discusses the methods of analysis which are subsequently used for the present study. Chapter 4 presents the reliability based design methodology for vertically and laterally loaded piles based on cone penetration test data for cohesive soil. CPT data from Konaseema area in India is used for analysis. Ultimate limit sate and serviceability limit state are considered for reliability based design using CPT data and load displacement curves. Chapter 5 presents the load resistance factor design (LRFD) of vertically and laterally loaded piles based on load test data. Reliability based code calibrated partial factors are determined considering bias in failure criteria, model bias and variability in load and resistance. Chapter 6 illustrates a comprehensive study on the effect of soil spatial variability on response of vertically and laterally loaded pile foundations in undrained clay. Two-dimensional finite difference program, FLAC2D (Itasca 2005) is used to model the soil and pile. The response of pile foundations due to the effect of variance and spatial correlation of undrained shear strength is studied using Monte Carlo simulation. The influence of spatial variability on the propagation and formation of failure near the pile foundation is also examined. Chapter 7 describes reliability based design methodology of piles in non-liquefiable soil. The seismic load on pile foundation is determined from code specified elastic design response spectrum using pseudo-static approach. Variability in seismic load and soil undrained shear strength are incorporated. The effects of soil relative densities, pile diameters, earthquake predominant frequencies and peak acceleration values on the two plausible failure mechanisms; bending and buckling are examined in Chapter 8. The two-dimensional finite difference analysis is used for dynamic analysis. A probabilistic approach is proposed to identify governing failure modes of piles in liquefiable soil in Chapter 9. The variability in the soil parameters namely SPT-N value, friction angle, shear modulus, bulk modulus, permeability and shear strain at 50% of modulus ratio is considered. Monte Carlo simulation is used to determine the probability of failure. A well documented case of the failed pile of Showa Bridge in 1964 Niigata earthquake is considered as case example. Based on the studies reported in this dissertation, it can be concluded that the reliability based design of pile foundations considering variability and spatial correlation of soil enables a rational choice of design loads. The variability in the seismic design load and soil shear strength can quantify the risk involved for pile design in a rational basis. The identification of depth of liquefiable soil layer is found to be most important to identify failure mechanisms of piles in liquefiable soil. Considerations of soil type, earthquake intensity, predominant frequency of earthquake, pile material, variability of soil are also significant.

Submitted by Johnny Rodrigues (johnnyrodrigues@ufcg.edu.br) on 2018-11-10T13:49:36Z No. of bitstreams: 1 CÍCERO AURÉLIO GRANGEIRO LIMA - DISSERTAÇÃO PPGECA 1992..pdf: 25126677 bytes, checksum: 344ec8cc3722c36124b4e9b1b88b50b3 (MD5) / Made available in DSpace on 2018-11-10T13:49:36Z (GMT). No. of bitstreams: 1 CÍCERO AURÉLIO GRANGEIRO LIMA - DISSERTAÇÃO PPGECA 1992..pdf: 25126677 bytes, checksum: 344ec8cc3722c36124b4e9b1b88b50b3 (MD5) Previous issue date: 1992-11-12 / Testes de infiltração com infiltrômetro duplo anel de nível constante foram efetuados em 32 pontos de uma malha retangular de uma parcela agrícola da Fazenda Experimental da EMEPA - Pb. Ajustamentos as Leis de Philip e de Green e Ampt foram efetuados. Medições da granulometria, densidade aparente seca do solo e umidade volumétrica antes e depois dos testes foram também efetuadas. Utilizou-se a seguir técnicas de análises estatística clássica e geoestatística para caracterizar a variabilidade espacial dos parâmetros de infiltração obtidos pelos ajustamentos. Nenhum dos parâmetros estudados apresentou estrutura espacial definida. Correlações simples e múltiplas evidenciaram dependência da percentagem de Argila + Silte com o espaço físico, e independência entro os parâmetros de infiltração. Ilustrações sobre o efeito da variabilidade espacial sobro o ponto de vista agronômico o hidrológico são mostradas. / Infiltration tests with double-ring infiltrometers were performed in a 33 paint reiangular regular]y spaced grid of an agri cultural site. Fitting of the infiltration curve obtained by Philip and Green and Ampt laws allowed to obtain the sorptivity, the infiltration rate at steady state and the suction parameters of Green and Ampt,for each point. Measurements of pre- and post-humidi ty, granulometry and dry density were also performed. Classical statistical and geo-statistical techniques were used to characterize spatial variability. None of the parameters studied showed a defined spatial structure. Single and muitiple correlations showed a dependence between Cclay + siltD percentage with space but no correlation between parameters was obtained. I11ustrative considerations about spatial variability were ma de with agronomic and hydrologic applications.