The significance and determination by image analysis of microcrack density in hard chromium plating

It is well known that the microcrack density is a fundamental parameter in hard chromium electroplating. The chemical and mechanical properties of this coating are widely dependent on its microcrack density. In this paper a simple image analysis procedure to determine microcrack density is presented in order to demonstrate it as a fundamental tool to estimate the fatigue, corrosion and wear behavior, as well as the residual stress field of a coated component. For this purpose, the image analysis procedure was carried out on two kinds of hard chromium plating - one called accelerated (high velocity of deposition and fluoride-free) and the other conventional (with fluoride). The coatings were applied on samples of AISI 4340 aeronautical steel, which is widely used in aircraft landing gear components. To characterize the practical significance of this study, the microcrack density results were related to the fatigue, wear and corrosion behavior from previous study and to the residual stress field in the coatings.

Investigação do potencial dos ensaios APULOT e pull-out para estimativa da resistência a compressão do concreto

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

A New Method for ECG Tracking of Persistent Atrial Fibrillation Termination during Stepwise Ablation

Stepwise radiofrequency catheter ablation (step-CA) has become the treatment of choice for the restoration of sinus rhythm (SR) in patients with long-standing persistent atrial fibrillation (pers-AF). Its success rate appears limited as the amount of ablation to achieve long term SR is unknown. Multiple organization indexes (OIs) have been previously developed to track the organization of AF during step-CA, however, with limited success. We report an adaptive method for tracking AF termination (AF-term) based on OIs characterizing the relationship between harmonic components of atrial activity from the surface ECG of AF activity. By computing their relative evolution during the last two steps preceding AF-term, we found that the performance of our OIs was superior to classical indices to track the efficiency of step-CA "en route" to AF-term. Our preliminary results suggest that the gradual synchronization between the fundamental and its first harmonic of AF activity appears as a promising parameter for predicting AF-term during step-CA.

Identifying quantitative operation principles in metabolic pathways: a systematic method for searching feasible enzyme activity patterns leading to cellular adaptive responses

Background: Optimization methods allow designing changes in a system so that specific goals are attained. These techniques are fundamental for metabolic engineering. However, they are not directly applicable for investigating the evolution of metabolic adaptation to environmental changes. Although biological systems have evolved by natural selection and result in well-adapted systems, we can hardly expect that actual metabolic processes are at the theoretical optimum that could result from an optimization analysis. More likely, natural systems are to be found in a feasible region compatible with global physiological requirements. Results: We first present a new method for globally optimizing nonlinear models of metabolic pathways that are based on the Generalized Mass Action (GMA) representation. The optimization task is posed as a nonconvex nonlinear programming (NLP) problem that is solved by an outer- approximation algorithm. This method relies on solving iteratively reduced NLP slave subproblems and mixed-integer linear programming (MILP) master problems that provide valid upper and lower bounds, respectively, on the global solution to the original NLP. The capabilities of this method are illustrated through its application to the anaerobic fermentation pathway in Saccharomyces cerevisiae. We next introduce a method to identify the feasibility parametric regions that allow a system to meet a set of physiological constraints that can be represented in mathematical terms through algebraic equations. This technique is based on applying the outer-approximation based algorithm iteratively over a reduced search space in order to identify regions that contain feasible solutions to the problem and discard others in which no feasible solution exists. As an example, we characterize the feasible enzyme activity changes that are compatible with an appropriate adaptive response of yeast Saccharomyces cerevisiae to heat shock Conclusion: Our results show the utility of the suggested approach for investigating the evolution of adaptive responses to environmental changes. The proposed method can be used in other important applications such as the evaluation of parameter changes that are compatible with health and disease states.

Parameter estimation using a particle method: inferring mixing coefficients from sea level observations

This paper presents a first attempt to estimate mixing parameters from sea level observations using a particle method based on importance sampling. The method is applied to an ensemble of 128 members of model simulations with a global ocean general circulation model of high complexity. Idealized twin experiments demonstrate that the method is able to accurately reconstruct mixing parameters from an observed mean sea level field when mixing is assumed to be spatially homogeneous. An experiment with inhomogeneous eddy coefficients fails because of the limited ensemble size. This is overcome by the introduction of local weighting, which is able to capture spatial variations in mixing qualitatively. As the sensitivity of sea level for variations in mixing is higher for low values of mixing coefficients, the method works relatively well in regions of low eddy activity.

A swarm pattern transformation method based on macroscopic parameter operations

The work reported in this paper is motivated by biomimetic inspiration - the transformation of patterns. The major issue addressed is the development of feasible methods for transformation based on a macroscopic tool. The general requirement for the feasibility of the transformation method is determined by classifying pattern formation approaches an their characteristics. A formal definition for pattern transformation is provided and four special cases namely, elementary and geometric transformation based on repositioning all and some robotic agents are introduced. A feasible method for transforming patterns geometrically, based on the macroscopic parameter operation of a swarm is considered. The transformation method is applied to a swarm model which lends itself to the transformation technique. Simulation studies are developed to validate the feasibility of the approach, and do indeed confirm the approach.

Computational study of the step size parameter of the subgradient optimization method

The subgradient optimization method is a simple and flexible linear programming iterative algorithm. It is much simpler than Newton's method and can be applied to a wider variety of problems. It also converges when the objective function is non-differentiable. Since an efficient algorithm will not only produce a good solution but also take less computing time, we always prefer a simpler algorithm with high quality. In this study a series of step size parameters in the subgradient equation is studied. The performance is compared for a general piecewise function and a specific p-median problem. We examine how the quality of solution changes by setting five forms of step size parameter.

A hybrid method in combining treatment effects from matched and unmatched studies

In the biomedical studies, the general data structures have been the matched (paired) and unmatched designs. Recently, many researchers are interested in Meta-Analysis to obtain a better understanding from several clinical data of a medical treatment. The hybrid design, which is combined two data structures, may create the fundamental question for statistical methods and the challenges for statistical inferences. The applied methods are depending on the underlying distribution. If the outcomes are normally distributed, we would use the classic paired and two independent sample T-tests on the matched and unmatched cases. If not, we can apply Wilcoxon signed rank and rank sum test on each case. ^ To assess an overall treatment effect on a hybrid design, we can apply the inverse variance weight method used in Meta-Analysis. On the nonparametric case, we can use a test statistic which is combined on two Wilcoxon test statistics. However, these two test statistics are not in same scale. We propose the Hybrid Test Statistic based on the Hodges-Lehmann estimates of the treatment effects, which are medians in the same scale.^ To compare the proposed method, we use the classic meta-analysis T-test statistic on the combined the estimates of the treatment effects from two T-test statistics. Theoretically, the efficiency of two unbiased estimators of a parameter is the ratio of their variances. With the concept of Asymptotic Relative Efficiency (ARE) developed by Pitman, we show ARE of the hybrid test statistic relative to classic meta-analysis T-test statistic using the Hodges-Lemann estimators associated with two test statistics.^ From several simulation studies, we calculate the empirical type I error rate and power of the test statistics. The proposed statistic would provide effective tool to evaluate and understand the treatment effect in various public health studies as well as clinical trials.^

A stochastic model updating method for parameter variability quantification based on response surface models and Monte Carlo simulation

Stochastic model updating must be considered for quantifying uncertainties inherently existing in real-world engineering structures. By this means the statistical properties,instead of deterministic values, of structural parameters can be sought indicating the parameter variability. However, the implementation of stochastic model updating is much more complicated than that of deterministic methods particularly in the aspects of theoretical complexity and low computational efficiency. This study attempts to propose a simple and cost-efficient method by decomposing a stochastic updating process into a series of deterministic ones with the aid of response surface models and Monte Carlo simulation. The response surface models are used as surrogates for original FE models in the interest of programming simplification, fast response computation and easy inverse optimization. Monte Carlo simulation is adopted for generating samples from the assumed or measured probability distributions of responses. Each sample corresponds to an individual deterministic inverse process predicting the deterministic values of parameters. Then the parameter means and variances can be statistically estimated based on all the parameter predictions by running all the samples. Meanwhile, the analysis of variance approach is employed for the evaluation of parameter variability significance. The proposed method has been demonstrated firstly on a numerical beam and then a set of nominally identical steel plates tested in the laboratory. It is found that compared with the existing stochastic model updating methods, the proposed method presents similar accuracy while its primary merits consist in its simple implementation and cost efficiency in response computation and inverse optimization.

New method for analytical photovoltaic parameter extraction

Correct modeling of the equivalent circuits regarding solar cell and panels is today an essential tool for power optimization. However, the parameter extraction of those circuits is still a quite difficult task that normally requires both experimental data and calculation procedures, generally not available to the normal user. This paper presents a new analytical method that easily calculates the equivalent circuit parameters from the data that manufacturers usually provide. The analytical approximation is based on a new methodology, since methods developed until now to obtain the aforementioned equivalent circuit parameters from manufacturer's data have always been numerical or heuristic. Results from the present method are as accurate as the ones resulting from other more complex (numerical) existing methods in terms of calculation process and resources.

A methodology proposal to obtain operational parameter forecasts and operational risk assessment in container terminals

Las terminales de contenedores son sistemas complejos en los que un elevado número de actores económicos interactúan para ofrecer servicios de alta calidad bajo una estricta planificación y objetivos económicos. Las conocidas como "terminales de nueva generación" están diseñadas para prestar servicio a los mega-buques, que requieren tasas de productividad que alcanzan los 300 movimientos/ hora. Estas terminales han de satisfacer altos estándares dado que la competitividad entre terminales es elevada. Asegurar la fiabilidad de las planificaciones del atraque es clave para atraer clientes, así como reducir al mínimo el tiempo que el buque permanece en el puerto. La planificación de las operaciones es más compleja que antaño, y las tolerancias para posibles errores, menores. En este contexto, las interrupciones operativas deben reducirse al mínimo. Las principales causas de dichas perturbaciones operacionales, y por lo tanto de incertidumbre, se identifican y caracterizan en esta investigación. Existen una serie de factores que al interactuar con la infraestructura y/o las operaciones desencadenan modos de fallo o parada operativa. Los primeros pueden derivar no solo en retrasos en el servicio sino que además puede tener efectos colaterales sobre la reputación de la terminal, o incluso gasto de tiempo de gestión, todo lo cual supone un impacto para la terminal. En el futuro inmediato, la monitorización de las variables operativas presenta gran potencial de cara a mejorar cualitativamente la gestión de las operaciones y los modelos de planificación de las terminales, cuyo nivel de automatización va en aumento. La combinación del criterio experto con instrumentos que proporcionen datos a corto y largo plazo es fundamental para el desarrollo de herramientas que ayuden en la toma de decisiones, ya que de este modo estarán adaptadas a las auténticas condiciones climáticas y operativas que existen en cada emplazamiento. Para el corto plazo se propone una metodología con la que obtener predicciones de parámetros operativos en terminales de contenedores. Adicionalmente se ha desarrollado un caso de estudio en el que se aplica el modelo propuesto para obtener predicciones de la productividad del buque. Este trabajo se ha basado íntegramente en datos proporcionados por una terminal semi-automatizada española. Por otro lado, se analiza cómo gestionar, evaluar y mitigar el efecto de las interrupciones operativas a largo plazo a través de la evaluación del riesgo, una forma interesante de evaluar el effecto que eventos inciertos pero probables pueden generar sobre la productividad a largo plazo de la terminal. Además se propone una definición de riesgo operativo junto con una discusión de los términos que representan con mayor fidelidad la naturaleza de las actividades y finalmente, se proporcionan directrices para gestionar los resultados obtenidos. Container terminals are complex systems where a large number of factors and stakeholders interact to provide high-quality services under rigid planning schedules and economic objectives. The socalled next generation terminals are conceived to serve the new mega-vessels, which are demanding productivity rates up to 300 moves/hour. These terminals need to satisfy high standards because competition among terminals is fierce. Ensuring reliability in berth scheduling is key to attract clients, as well as to reduce at a minimum the time that vessels stay the port. Because of the aforementioned, operations planning is becoming more complex, and the tolerances for errors are smaller. In this context, operational disturbances must be reduced at a minimum. The main sources of operational disruptions and thus, of uncertainty, are identified and characterized in this study. External drivers interact with the infrastructure and/or the activities resulting in failure or stoppage modes. The later may derive not only in operational delays but in collateral and reputation damage or loss of time (especially management times), all what implies an impact for the terminal. In the near future, the monitoring of operational variables has great potential to make a qualitative improvement in the operations management and planning models of terminals that use increasing levels of automation. The combination of expert criteria with instruments that provide short- and long-run data is fundamental for the development of tools to guide decision-making, since they will be adapted to the real climatic and operational conditions that exist on site. For the short-term a method to obtain operational parameter forecasts in container terminals. To this end, a case study is presented, in which forecasts of vessel performance are obtained. This research has been entirely been based on data gathered from a semi-automated container terminal from Spain. In the other hand it is analyzed how to manage, evaluate and mitigate disruptions in the long-term by means of the risk assessment, an interesting approach to evaluate the effect of uncertain but likely events on the long-term throughput of the terminal. In addition, a definition for operational risk evaluation in port facilities is proposed along with a discussion of the terms that better represent the nature of the activities involved and finally, guidelines to manage the results obtained are provided.

3D numerical modelling of acoustic horns using the method of fundamental solutions

In the present work, a three-dimensional (3D) formulation based on the method of fundamental solutions (MFS) is applied to the study of acoustic horns. The implemented model follows and extends previous works that only considered two-dimensional and axisymmetric horn configurations. The more realistic case of 3D acoustic horns with symmetry regarding two orthogonal planes is addressed. The use of the domain decomposition technique with two interconnected sub-regions along a continuity boundary is proposed, allowing for the computation of the sound pressure generated by an acoustic horn installed on a rigid screen. In order to reduce the model discretization requirements for these cases, Green’s functions derived with the image source methodology are adopted, automatically accounting for the presence of symmetry conditions. A strategy for the calculation of an optimal position of the virtual sources used by the MFS to define the solution is also used, leading to improved reliability and flexibility of the proposed method. The responses obtained by the developed model are compared to reference solutions, computed by well-established models based on the boundary element method. Additionally, numerically calculated acoustic parameters, such as directivity and beamwidth, are compared with those evaluated experimentally.

Stresses in reinforced nozzle-cylinder attachments under external moment loadings analyzed by the finite-element method : a parameter study /

"ORNL/NUREG-52."

Development and Application of Improvements to the Tile-based Fisher Ratio Method and Fundamental Instrument Considerations for Non-targeted Analysis using Two-dimensional Gas Chromatography

Thesis (Ph.D.)--University of Washington, 2016-06