3 resultados para Elastic And Statistically Brittle (Esb) Model

em Bucknell University Digital Commons - Pensilvania - USA


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The Gaussian-2, Gaussian-3, Complete Basis Set-QB3, and Complete Basis Set-APNO methods have been used to calculate geometries of neutral clusters of water, (H2O)n, where n = 2–6. The structures are in excellent agreement with those determined from experiment and those predicted from previous high-level calculations. These methods also provide excellent thermochemical predictions for water clusters, and thus can be used with confidence in evaluating the structures and thermochemistry of water clusters.

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Solid oxide fuel cells (SOFCs) provide a potentially clean way of using energy sources. One important aspect of a functioning fuel cell is the anode and its characteristics (e.g. conductivity). Using infiltration of conductor particles has been shown to be a method for production at lower cost with comparable functionality. While these methods have been demonstrated experimentally, there is a vast range of variables to consider. Because of the long time for manufacture, a model is desired to aid in the development of the desired anode formulation. This thesis aims to (1) use an idealized system to determine the appropriate size and aspect ratio to determine the percolation threshold and effective conductivity as well as to (2) simulate the infiltrated fabrication method to determine the effective conductivity and percolation threshold as a function of ceramic and pore former particle size, particle fraction and the cell¿s final porosity. The idealized system found that the aspect ratio of the cell does not affect the cells functionality and that an aspect ratio of 1 is the most efficient computationally to use. Additionally, at cell sizes greater than 50x50, the conductivity asymptotes to a constant value. Through the infiltrated model simulations, it was found that by increasing the size of the ceramic (YSZ) and pore former particles, the percolation threshold can be decreased and the effective conductivity at low loadings can be increased. Furthermore, by decreasing the porosity of the cell, the percolation threshold and effective conductivity at low loadings can also be increased

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This is the second part of a study investigating a model-based transient calibration process for diesel engines. The first part addressed the data requirements and data processing required for empirical transient emission and torque models. The current work focuses on modelling and optimization. The unexpected result of this investigation is that when trained on transient data, simple regression models perform better than more powerful methods such as neural networks or localized regression. This result has been attributed to extrapolation over data that have estimated rather than measured transient air-handling parameters. The challenges of detecting and preventing extrapolation using statistical methods that work well with steady-state data have been explained. The concept of constraining the distribution of statistical leverage relative to the distribution of the starting solution to prevent extrapolation during the optimization process has been proposed and demonstrated. Separate from the issue of extrapolation is preventing the search from being quasi-static. Second-order linear dynamic constraint models have been proposed to prevent the search from returning solutions that are feasible if each point were run at steady state, but which are unrealistic in a transient sense. Dynamic constraint models translate commanded parameters to actually achieved parameters that then feed into the transient emission and torque models. Combined model inaccuracies have been used to adjust the optimized solutions. To frame the optimization problem within reasonable dimensionality, the coefficients of commanded surfaces that approximate engine tables are adjusted during search iterations, each of which involves simulating the entire transient cycle. The resulting strategy, different from the corresponding manual calibration strategy and resulting in lower emissions and efficiency, is intended to improve rather than replace the manual calibration process.