Applications of plasticity theory to selected problems in soil mechanics

Two topics in plane strain perfect plasticity are studied using the method of characteristics. The first is the steady-state indentation of an infinite medium by either a rigid wedge having a triangular cross section or a smooth plate inclined to the direction of motion. Solutions are exact and results include deformation patterns and forces of resistance; the latter are also applicable for the case of incipient failure. Experiments on sharp wedges in clay, where forces and deformations are recorded, showed a good agreement with the mechanism of cutting assumed by the theory; on the other hand the indentation process for blunt wedges transforms into that of compression with a rigid part of clay moving with the wedge. Finite element solutions, for a bilinear material model, were obtained to establish a correspondence between the response of the plane strain wedge and its axi-symmetric counterpart, the cone. Results of the study afford a better understanding of the process of indentation of soils by penetrometers and piles as well as the mechanism of failure of deep foundations (piles and anchor plates).

The second topic concerns the plane strain steady-state free rolling of a rigid roller on clays. The problem is solved approximately for small loads by getting the exact solution of two problems that encompass the one of interest; the first is a steady-state with a geometry that approximates the one of the roller and the second is an instantaneous solution of the rolling process but is not a steady-state. Deformations and rolling resistance are derived. When compared with existing empirical formulae the latter was found to agree closely.

Estimation of catalyst activity profiles and deactivation parameters from reactor operating data with applications to naphtha reforming

Techniques are developed for estimating activity profiles in fixed bed reactors and catalyst deactivation parameters from operating reactor data. These techniques are applicable, in general, to most industrial catalytic processes. The catalytic reforming of naphthas is taken as a broad example to illustrate the estimation schemes and to signify the physical meaning of the kinetic parameters of the estimation equations. The work is described in two parts. Part I deals with the modeling of kinetic rate expressions and the derivation of the working equations for estimation. Part II concentrates on developing various estimation techniques.

Part I: The reactions used to describe naphtha reforming are dehydrogenation and dehydroisomerization of cycloparaffins; isomerization, dehydrocyclization and hydrocracking of paraffins; and the catalyst deactivation reactions, namely coking on alumina sites and sintering of platinum crystallites. The rate expressions for the above reactions are formulated, and the effects of transport limitations on the overall reaction rates are discussed in the appendices. Moreover, various types of interaction between the metallic and acidic active centers of reforming catalysts are discussed as characterizing the different types of reforming reactions.

Part II: In catalytic reactor operation, the activity distribution along the reactor determines the kinetics of the main reaction and is needed for predicting the effect of changes in the feed state and the operating conditions on the reactor output. In the case of a monofunctional catalyst and of bifunctional catalysts in limiting conditions, the cumulative activity is sufficient for predicting steady reactor output. The estimation of this cumulative activity can be carried out easily from measurements at the reactor exit. For a general bifunctional catalytic system, the detailed activity distribution is needed for describing the reactor operation, and some approximation must be made to obtain practicable estimation schemes. This is accomplished by parametrization techniques using measurements at a few points along the reactor. Such parametrization techniques are illustrated numerically with a simplified model of naphtha reforming.

To determine long term catalyst utilization and regeneration policies, it is necessary to estimate catalyst deactivation parameters from the the current operating data. For a first order deactivation model with a monofunctional catalyst or with a bifunctional catalyst in special limiting circumstances, analytical techniques are presented to transform the partial differential equations to ordinary differential equations which admit more feasible estimation schemes. Numerical examples include the catalytic oxidation of butene to butadiene and a simplified model of naphtha reforming. For a general bifunctional system or in the case of a monofunctional catalyst subject to general power law deactivation, the estimation can only be accomplished approximately. The basic feature of an appropriate estimation scheme involves approximating the activity profile by certain polynomials and then estimating the deactivation parameters from the integrated form of the deactivation equation by regression techniques. Different bifunctional systems must be treated by different estimation algorithms, which are illustrated by several cases of naphtha reforming with different feed or catalyst composition.

Isotope shift studies in the rare earths and lead

Isotope shifts of K_α1 x-ray transitions were measured for the Neodymium isotopes Nd 142, 143, 144, 145, 146, 148 and 150, the Samarium isotopes Sm 147, 148, 149, 150, 152 and 154, the Gadolinium isotopes Gd 154, 155, 156, 157, 158 and 160, the Dysprosium isotopes Dy 162 and 164, the Erbium isotopes Er 166, 168 and 170, the Hafnium isotopes Hf 178 and 180 and the Lead isotopes Pb 204, 206, 207 and 208. A curved crystal Cauchois spectrometer was used. The analysis of the measurement furnished the variation of the mean square charge radius of the nucleus, δ˂r²˃, for 23 isotope pairs. The experimental results were compared with theoretical values from nuclear models. Combining the x-ray shifts and the optical shifts in Nd and Sm yielded the optical mass shifts. An anomaly was observed in the odd-even shifts when the optical and the x-ray shifts were plotted against each other.

DEVELOPMENT AND APPLICATIONS OF TIME-DEPENDENT DENSITY MATRIX FUNCTIONAL THEORY

En esta tesis estudiamos las teorías sobre la Matriz Densidad Reducida (MDR) como un marco prometedor. Nos enfocamos sobre esta teorías desde dos aspectos: Primero, usamos algunos modelos sencillos hechos con dos partículas las cuales estan armónicamente confinadas como una base para ilustrar la utilidad de la matriz densidad. Para tales sistemas, usamos la MDR de un cuerpo para calcular algunas cantidades de interés tales como densidad de momentum. Posteriormente obtenemos los orbitales naturales y su número de ocupación para algunos de los modelos, y en uno de los casos expresamos la MDR de dos cuerpos de manera exacta en términos de la MDR de un cuerpo. También usamos el teorema diferencial del virial para establecer una descripción unificada de la familia entera de estos sistemas modelo en términos de la densidad. En la seguna parte cambiamos a casos fuera del equilibrio y analizamos la así llamada jerarquía BBGKY de ecuaciones para describir la evolución temporal de un sistema de muchos cuerpos en términos de sus MDRs (a todos los órdenes). Proveemos un exhaustivo estudio de los desafíos y problemas abiertos ligados a la truncación de tales jerarquías de ecuaciones para hacerlas aplicables. Restringimos nuestro análisis a la evolución acoplada de la MDR de uno y dos cuerpos, donde los efectos de correlación de alto orden estan embebidos dentro de la aproximación usada para cerrar las ecuaciones. Probamos que dentro de esta aproximación, el número de electrones y la energía total se conservan, sin importar la aproximación usada. Luego, demostramos que aplicando los esquemas de truncación de estado base para llevar los electrones a comportamientos indeseables y no físicos, tales como la violación e incluso la divergencia en la densidad electrónica local, tanto en regímenes correlacionados débiles y fuertes.

Strong visible up-conversion emissions and thermometric applications of Er3+-Yb3+ codoped Al2O3 prepared by the sol-gel method

The Er3+-Yb3+ codoped Al2O3 has been prepared by the sol-gel method using the aluminium isopropoxide [Al(OC3H7)(3)]-derived Al2O3 sols with addition of the erbium nitrate [Er(NO3)(3) center dot 5H(2)O] and ytterbium nitrate [Yb(NO3)(3) center dot 5H(2)O]. The phase structure, including only two crystalline types of doped Al2O3 phases, theta and gamma, was obtained for the 1 mol% Er3+ and 5 mol% Yb3+ codoped Al2O3 at the sintering temperature of 1,273 K. By a 978 nm semiconductor laser diodes excitation, the visible up-conversion emissions centered at about 523, 545, and 660 nm were obtained. The temperature dependence of the green up-conversion emissions was studied over a wide temperature range of 300-825 K, and the reasonable agreement between the calculated temperature by the fluorescence intensity ratio (FIR) theory and the measured temperature proved that Er3+-Yb3+ codoped Al2O3 plays an important role in the application of high temperature sensor.

Properties of convergence of a class of iterative processes generated by sequences of self-mappings with applications to switched dynamic systems

This article investigates the convergence properties of iterative processes involving sequences of self-mappings of metric or Banach spaces. Such sequences are built from a set of primary self-mappings which are either expansive or non-expansive self-mappings and some of the non-expansive ones can be contractive including the case of strict contractions. The sequences are built subject to switching laws which select each active self-mapping on a certain activation interval in such a way that essential properties of boundedness and convergence of distances and iterated sequences are guaranteed. Applications to the important problem of stability of dynamic switched systems are also given.

Deep learning review and its applications

Deep neural networks have recently gained popularity for improv- ing state-of-the-art machine learning algorithms in diverse areas such as speech recognition, computer vision and bioinformatics. Convolutional networks especially have shown prowess in visual recognition tasks such as object recognition and detection in which this work is focused on. Mod- ern award-winning architectures have systematically surpassed previous attempts at tackling computer vision problems and keep winning most current competitions. After a brief study of deep learning architectures and readily available frameworks and libraries, the LeNet handwriting digit recognition network study case is developed, and lastly a deep learn- ing network for playing simple videogames is reviewed.