Browsing by Subject "Simulated annealing"
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Item Characterization of the Cana-Woodford Shale using fractal-based, stochastic inversion, Canadian County, Oklahoma(2016-05) Borgman, Barry Michael; Spikes, Kyle; Sen, Mrinal K; Wilson, Clark RThe past decade has seen a surge in unconventional hydrocarbon exploration and production, driven by advances in horizontal drilling and hydraulic fracturing. Even with such advances, reliable models of the subsurface are crucial in all phases of exploitation. This study focuses on the methods used for estimation of the elastic properties (density, velocity, and impedance), which play a key role in targeting reservoir zones ideal for hydraulic fracturing. Well-log data provides high-resolution vertical measurements of elastic properties, but a relatively shallow depth of investigation imposes spatial limitations. Seismic data provides broader horizontal coverage at lower cost, but sacrifices vertical resolution. Thin beds present in many unconventional reservoirs fall below seismic resolution. In addition, the band-limited nature of seismic data results in the absence of low-frequency content of the Earth model, as well as the high-frequency content present in well logs. Seismic inversion is a process that provides estimates of elastic properties given input seismic and well data. Stochastic inversion is a method that uses well-log data as a priori information, with an added aspect of randomness. The method generates many realizations using the same input model and takes an average of those realizations. We implement two separate stochastic inversion algorithms to estimate P-impedance in the Cana-Woodford Shale in west-central Oklahoma. First, we use a fractal-based, very fast simulated annealing algorithm that exploits the fractal characteristics found in well-log data to build a prior model. The method of very fast simulated annealing optimizes our elastic model by searching for the minimum misfit between observed and synthetic seismic traces. Next, we use a principal component analysis (PCA) based stochastic inversion algorithm to invert for impedance at all traces simultaneously. Comparison of the results with traditional deterministic inversion results shows improved vertical resolution while honoring the low-frequency content of the Earth model. The PCA-based inversion results also show improved lateral continuity of the elastic profile along our 2D line. The impedance profile from the PCA-based approach provides a better representation of the vertical and horizontal variability of the reservoir, allowing for improved targeting of frackable zones.Item Controlled self-assembly of charged particles(2010-05) Shestopalov, Nikolay Vladimirovic; Rodin, G. J. (Gregory J.); Henkelman, GraemeSelf-assembly is a process of non-intrusive transformation of a system from a disordered to an ordered state. For engineering purposes, self-assembly of microscopic objects can benefit significantly from macroscopic guidance and control. This dissertation is concerned with controlling self-assembly in binary monolayers of electrically charged particles that follow basic laws of statistical mechanics. First, a simple macroscopic model is used to determine an optimal thermal control for self-assembly. The model assumes that a single rate-controlling mechanism is responsible for the formation of spatially ordered structures and that its rate follows an Arrhenius form. The model parameters are obtained using molecular dynamics simulations. The optimal control is derived in an analytical form using classical optimization methods. Two major lessons were learned from that work: (i) isothermal control was almost as effective as optimal time-dependent thermal control, and (ii) neither electrostatic interactions nor thermal control were particularly effective in eliminating voids formed during self-assembly. Accordingly, at the next stage, the focus is on temperature-pressure control under isothermal-isobaric conditions. In identifying optimal temperature and pressure conditions, several assumptions, that allow one to relate the optimal conditions to the phase diagram, are proposed. Instead of verifying the individual assumptions, the entire approach is verified using molecular dynamics simulations. It is estimated that under optimal isothermal-isobaric conditions the rate of self-assembly is about five time faster than that under optimal temperature control conditions. It is argued that the proposed approach of relating optimal conditions to the phase diagram is applicable to other systems. Further, the work reveals numerous and useful parallels between self-assembly and crystal physics, which are important to exploit for developing robust engineering self-assembly processes.Item Dynamic and Robust Capacitated Facility Location in Time Varying Demand Environments(2010-07-14) Torres Soto, JoaquinThis dissertation studies models for locating facilities in time varying demand environments. We describe the characteristics of the time varying demand that motivate the analysis of our location models in terms of total demand and the change in value and location of the demand of each customer. The first part of the dissertation is devoted to the dynamic location model, which determines the optimal time and location for establishing capacitated facilities when demand and cost parameters are time varying. This model minimizes the total cost over a discrete and finite time horizon for establishing, operating, and closing facilities, including the transportation costs for shipping demand from facilities to customers. The model is solved using Lagrangian relaxation and Benders? decomposition. Computational results from different time varying total demand structures demonstrate, empirically, the performance of these solution methods. The second part of the dissertation studies two location models where relocation of facilities is not allowed and the objective is to determine the optimal location of capacitated facilities that will have a good performance when demand and cost parameters are time varying. The first model minimizes the total cost for opening and operating facilities and the associated transportation costs when demand and cost parameters are time varying. The model is solved using Benders? decomposition. We show that in the presence of high relocation costs of facilities (opening and closing costs), this model can be solved as a special case by the dynamic location model. The second model minimizes the maximum regret or opportunity loss between a robust configuration of facilities and the optimal configuration for each time period. We implement local search and simulated annealing metaheuristics to efficiently obtain near optimal solutions for this model.Item Effects of intermetallic compound formation on reliability of Pb-free Sn-based solders for flip chip and three-dimensional interconnects(2013-12) Wang, Yiwei; Ho, P. S.The effects of intermetallic compound (IMC) formation on reliability of Pb-free Sn-based solders for flip chip and three-dimensional (3D) interconnects were studied. The dissertation is organized into four parts. In the first part, the effect of Sn grain orientation on electromigration (EM) reliability of Pb-free Sn-based flip chip solder joints was studied. The Sn grain microstructure in flip chip solder joints was characterized using the electron backscatter diffraction (EBSD) technique, and wa found to be closely related to the EM failure mechanims. The approach to grain structure optimization for improved EM reliability was also explored. In addition to the experimental work, a kinetic analysis was formulated to investigate the early EM degradation mechanism in Sn-based solder joints with Ni under-bump metallization (UMB). The aforementioned kinetic analysis, the intrinsic diffusion coefficients were not readily available in the literature. In the second part of the work, a Monte Carlo method known as simulated annealing was applied to estimate the unknown diffusion coefficients using a multi-parameter optimization method by fitting to experimental measurements. The intrinsic diffusion coefficients of Ni and Sn in Ni₃Sn₄ between 150 and 200°C, and those of Cu and Sn in Cu₃Sn and Cu₆Sn₅ between 120 and 200°C were estimatd. The activation energies for these diffusion coefficients were also determined. Together, this provides the diffusivity parameters to predict the intermetallic growth as a function of temperature. The third objective focused on the EM reliability of Sn-based microbump joints in 3D interconnects with through-silicon vias (TSVs). No EM-induced bump failure was observed, showing a robust EM reliability in microbumps. High temperature thermal annealing test was also performed on microbumps with three different metallizations in an effort to explore structural and process optimization. Finally, interfacial reaction induced stress in IMC microbumps was investigated. A numerial analysis was formulated to study the concurrent diffusion, phase transformation, and deformation in the process of IMC formation. Stress generation due to unbalanced diffusion rates and volumetric change upon phase transformation was considered. The coupled analysis was applied to investigate Ni₃Sn₄ growth in the Ni-Sn microbumping system. A simulation approach based on finite difference method with moving boundaries was employed to numerically solve stress evolution in Ni₃Sn₄. The equilibrium stress was also investigated using a modified model with a finite thickness of solder. Simulation predictions were found to be in good qualitative agreement with experimental observations.Item General-purpose optimization through information maximization(2012-05) Lockett, Alan Justin; Miikkulainen, Risto; Ghosh, Joydeep; Mooney, Raymond; Ravikumar, Pradeep; Zitkovic, GordanThe primary goal of artificial intelligence research is to develop a machine capable of learning to solve disparate real-world tasks autonomously, without relying on specialized problem-specific inputs. This dissertation suggests that such machines are realistic: If No Free Lunch theorems were to apply to all real-world problems, then the world would be utterly unpredictable. In response, the dissertation proposes the information-maximization principle, which claims that the optimal optimization methods make the best use of the information available to them. This principle results in a new algorithm, evolutionary annealing, which is shown to perform well especially in challenging problems with irregular structure.