6 resultados para Minimization of open stack problem

em Digital Commons - Michigan Tech


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Interest in the study of magnetic/non-magnetic multilayered structures took a giant leap since Grünberg and his group established that the interlayer exchange coupling (IEC) is a function of the non-magnetic spacer width. This interest was further fuelled by the discovery of the phenomenal Giant Magnetoresistance (GMR) effect. In fact, in 2007 Albert Fert and Peter Grünberg were awarded the Nobel Prize in Physics for their contribution to the discovery of GMR. GMR is the key property that is being used in the read-head of the present day computer hard drive as it requires a high sensitivity in the detection of magnetic field. The recent increase in demand for device miniaturization encouraged researchers to look for GMR in nanoscale multilayered structures. In this context, one dimensional(1-D) multilayerd nanowire structure has shown tremendous promise as a viable candidate for ultra sensitive read head sensors. In fact, the phenomenal giant magnetoresistance(GMR) effect, which is the novel feature of the currently used multilayered thin film, has already been observed in multilayered nanowire systems at ambient temperature. Geometrical confinement of the supper lattice along the 2-dimensions (2-D) to construct the 1-D multilayered nanowire prohibits the minimization of magnetic interaction- offering a rich variety of magnetic properties in nanowire that can be exploited for novel functionality. In addition, introduction of non-magnetic spacer between the magnetic layers presents additional advantage in controlling magnetic properties via tuning the interlayer magnetic interaction. Despite of a large volume of theoretical works devoted towards the understanding of GMR and IEC in super lattice structures, limited theoretical calculations are reported in 1-D multilayered systems. Thus to gauge their potential application in new generation magneto-electronic devices, in this thesis, I have discussed the usage of first principles density functional theory (DFT) in predicting the equilibrium structure, stability as well as electronic and magnetic properties of one dimensional multilayered nanowires. Particularly, I have focused on the electronic and magnetic properties of Fe/Pt multilayered nanowire structures and the role of non-magnetic Pt spacer in modulating the magnetic properties of the wire. It is found that the average magnetic moment per atom in the nanowire increases monotonically with an ~1/(N(Fe)) dependance, where N(Fe) is the number of iron layers in the nanowire. A simple model based upon the interfacial structure is given to explain the 1/(N(Fe)) trend in magnetic moment obtained from the first principle calculations. A new mechanism, based upon spin flip with in the layer and multistep electron transfer between the layers, is proposed to elucidate the enhancement of magnetic moment of Iron atom at the Platinum interface. The calculated IEC in the Fe/Pt multilayered nanowire is found to switch sign as the width of the non-magnetic spacer varies. The competition among short and long range direct exchange and the super exchange has been found to play a key role for the non-monotonous sign in IEC depending upon the width of the Platinum spacer layer. The calculated magnetoresistance from Julliere's model also exhibit similar switching behavior as that of IEC. The universality of the behavior of exchange coupling has also been looked into by introducing different non-magnetic spacers like Palladium, Copper, Silver, and Gold in between magnetic Iron layers. The nature of hybridization between Fe and other non-magnetic spacer is found to dictate the inter layer magnetic interaction. For example, in Fe/Pd nanowire the d-p hybridization in two spacer layer case favors anti-ferromagnetic (AFM) configuration over ferromagnetic (FM) configuration. However, the hybridization between half-filled Fe(d) and filled Cu(p) state in Fe/Cu nanowire favors FM coupling in the 2-spacer system.

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Characterizing the spatial scaling and dynamics of convective precipitation in mountainous terrain and the development of downscaling methods to transfer precipitation fields from one scale to another is the overall motivation for this research. Substantial progress has been made on characterizing the space-time organization of Midwestern convective systems and tropical rainfall, which has led to the development of statistical/dynamical downscaling models. Space-time analysis and downscaling of orographic precipitation has received less attention due to the complexities of topographic influences. This study uses multiscale statistical analysis to investigate the spatial scaling of organized thunderstorms that produce heavy rainfall and flooding in mountainous regions. Focus is placed on the eastern and western slopes of the Appalachian region and the Front Range of the Rocky Mountains. Parameter estimates are analyzed over time and attention is given to linking changes in the multiscale parameters with meteorological forcings and orographic influences on the rainfall. Influences of geographic regions and predominant orographic controls on trends in multiscale properties of precipitation are investigated. Spatial resolutions from 1 km to 50 km are considered. This range of spatial scales is needed to bridge typical scale gaps between distributed hydrologic models and numerical weather prediction (NWP) forecasts and attempts to address the open research problem of scaling organized thunderstorms and convection in mountainous terrain down to 1-4 km scales.

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Moisture induced distresses have been the prevalent distress type affecting the deterioration of both asphalt and concrete pavement sections. While various surface techniques have been employed over the years to minimize the ingress of moisture into the pavement structural sections, subsurface drainage components like open-graded base courses remain the best alternative in minimizing the time the pavement structural sections are exposed to saturated conditions. This research therefore focuses on assessing the performance and cost-effectiveness of pavement sections containing both treated and untreated open-graded aggregate base materials. Three common roadway aggregates comprising of two virgin aggregates and one recycled aggregate were investigated using four open-ended gradations and two binder types. Laboratory tests were conducted to determine the hydraulic, mechanical and durability characteristics of treated and untreated open-graded mixes made from these three aggregate types. Results of the experimental program show that for the same gradation and mix design types, limestone samples have the greatest drainage capacity, stability to traffic loads and resistance to degradation from environmental conditions like freeze-thaw. However, depending on the gradation and mix design used, all three aggregate types namely limestone, natural gravel and recycled concrete can meet the minimum coefficient of hydraulic conductivity required for good drainage in most pavements. Tests results for both asphalt and cement treated open-graded samples indicate that a percent air void content within the range of 15-25 will produce a treated open-graded base course with sufficient drainage capacity and also long term stability under both traffic and environmental loads. Using the new Mechanistic and Empirical Design Guide software, computer simulations of pavement performance were conducted on pavement sections containing these open-graded base aggregate base materials to determine how the MEPDG predicted pavement performance is sensitive to drainage. Using three truck traffic levels and four climatic regions, results of the computer simulations indicate that the predicted performance was not sensitive to the drainage characteristics of the open-graded base course. Based on the result of the MEPDG predicted pavement performance, the cost-effectiveness of the pavement sections with open-graded base was computed on the assumption that the increase service life experienced by these sections was attributed to the positive effects of subsurface drainage. The two cost analyses used gave two contrasting results with the one indicating that the inclusion of open-graded base courses can lead to substantial savings.

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This thesis presents a methodology for measuring thermal properties in situ, with a special focus on obtaining properties of layered stack-ups commonly used in armored vehicle components. The technique involves attaching a thermal source to the surface of a component, measuring the heat flux transferred between the source and the component, and measuring the surface temperature response. The material properties of the component can subsequently be determined from measurement of the transient heat flux and temperature response at the surface alone. Experiments involving multilayered specimens show that the surface temperature response to a sinusoidal heat flux forcing function is also sinusoidal. A frequency domain analysis shows that sinusoidal thermal excitation produces a gain and phase shift behavior typical of linear systems. Additionally, this analysis shows that the material properties of sub-surface layers affect the frequency response function at the surface of a particular stack-up. The methodology involves coupling a thermal simulation tool with an optimization algorithm to determine the material properties from temperature and heat flux measurement data. Use of a sinusoidal forcing function not only provides a mechanism to perform the frequency domain analysis described above, but sinusoids also have the practical benefit of reducing the need for instrumentation of the backside of the component. Heat losses can be minimized by alternately injecting and extracting heat on the front surface, as long as sufficiently high frequencies are used.

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The main goal of the research presented in this work is to provide some important insights about computational modeling of open-shell species. Such projects are: the investigation of the size-extensivity error in Equation-of-Motion Coupled Cluster methods, the analysis of the Long-Range corrected scheme in predicting UV-Vis spectra of Cu(II) complexes with the 4-imidazole acetate and its ethylated derivative, and the exploration of the importance of choosing a proper basis set for the description of systems such as the lithium monoxide anion. The most significant findings of this research are: (i) The contribution of the left operator to the size-extensivity error of the CR-EOMCC(2,3) approach, (ii) The cause of d-d shifts when varying the range-separation parameter and the amount of the exact exchange arising from the imbalanced treatment of localized vs. delocalized orbitals via the "tuned" CAM-B3LYP* functional, (iii) The proper acidity trend of the first-row hydrides and their lithiated analogs that may be reversed if the basis sets are not correctly selected.

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Planning, navigation, and search are fundamental human cognitive abilities central to spatial problem solving in search and rescue, law enforcement, and military operations. Despite a wealth of literature concerning naturalistic spatial problem solving in animals, literature on naturalistic spatial problem solving in humans is comparatively lacking and generally conducted by separate camps among which there is little crosstalk. Addressing this deficiency will allow us to predict spatial decision making in operational environments, and understand the factors leading to those decisions. The present dissertation is comprised of two related efforts, (1) a set of empirical research studies intended to identify characteristics of planning, execution, and memory in naturalistic spatial problem solving tasks, and (2) a computational modeling effort to develop a model of naturalistic spatial problem solving. The results of the behavioral studies indicate that problem space hierarchical representations are linear in shape, and that human solutions are produced according to multiple optimization criteria. The Mixed Criteria Model presented in this dissertation accounts for global and local human performance in a traditional and naturalistic Traveling Salesman Problem. The results of the empirical and modeling efforts hold implications for basic and applied science in domains such as problem solving, operations research, human-computer interaction, and artificial intelligence.