Browsing by Subject "Cluster"
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Item Characterization of cluster/monomer ratio in pulsed supersonic gas jets(2012-12) Gao, Xiaohui, doctor of physics; Downer, Michael CoffinCluster mass fraction is an elusive quantity to measure, calculate or estimate accurately for pulsed supersonic gas jets typical of intense laser experiments. The optimization of this parameter is critical for transient phase-matched harmonic generation in an ionized cluster jet at high laser intensity. We present an in-depth study of a rapid, noninvasive, single-shot optical method of determining cluster mass fraction f_c(r,t) at specified positions r within, and at time t after opening the valve of, a high-pressure pulsed supersonic gas jet. A ∼ 2 mJ fs pump pulse ionizes the monomers, causing an immediate drop in the jet’s refractive index n_jet proportional to monomer density, while simultaneously initiating hydrodynamic expansion of the clusters. The latter leads to a second drop in n_jet that is proportional to cluster density and is delayed by ∼ 1 ps. A temporally stretched probe pulse measures the 2-step index evolution in a single shot by frequency domain holography, enabling recovery of f_c. We present the theory behind recovery of f_c in detail. We also present extensive measurements of spatio-temporal profiles f_c(r, t) of cluster mass fraction in a high-pressure supersonic argon jet for various values of backing pressure P, and reservoir temperature T.Item Fracture spatial arrangement in tight gas sandstone and shale reservoir rocks(2017-09-18) Li, John Zihong; Laubach, Stephen E; Gale, Julia F.W.A new statistical analytical method was applied to quantify the spatial arrangement of fractures in sandstones and shales. Results show that spatial arrangements of fractures in the subsurface have a wide range of patterns and that fracture clusters are prevalent. The Upper Cretaceous Frontier Formation is a naturally fractured gas-producing sandstone in Wyoming. East-west-striking regional fractures sampled using image logs and cores from three horizontal wells exhibit clustered patterns, whereas data collected from outcrop have patterns that are indistinguishable from random. Image log data analyzed with the correlation count method shows clusters ~35 m wide and spaced ~ 50 to 90 m apart as well as clusters up to 12 m wide with periodic inter-cluster spacings. A hierarchy of cluster sizes exists; arrangement within clusters is likely fractal. Regionally, random and statistically more clustered than random patterns exist in the same upper to lower shoreface depositional facies. These rocks have markedly different structural and burial histories, so regional differences in degree of clustering are unsurprising. Application to shale reservoirs further link fracture clusters and spatial arrangements with reservoir mechanical stratigraphy: Vaca Muerta Formation shale shows strong control of fracture cluster locality by reservoir mechanical properties; Middle Devonian shales in the Horn River Basin identify spatial arrangement and cluster dimensions associated with preferred wellbore intervals; Marcellus Formation shale shows spatial arrangement controlled by mechanical bed thickness. Our results show that quantifying and identifying patterns as statistically more or less clustered than random delineate differences in fracture patterns that are not otherwise apparent but that may influence petroleum and water production, and therefore may be economically important.Item Large-scale network analytics(2011-08) Song, Han Hee, 1978-; Zhang, Yin, doctor of computer scienceScalable and accurate analysis of networks is essential to a wide variety of existing and emerging network systems. Specifically, network measurement and analysis helps to understand networks, improve existing services, and enable new data-mining applications. To support various services and applications in large-scale networks, network analytics must address the following challenges: (i) how to conduct scalable analysis in networks with a large number of nodes and links, (ii) how to flexibly accommodate various objectives from different administrative tasks, (iii) and how to cope with the dynamic changes in the networks. This dissertation presents novel path analysis schemes that effectively address the above challenges in analyzing pair-wise relationships among networked entities. In doing so, we make the following three major contributions to large-scale IP networks, social networks, and application service networks. For IP networks, we propose an accurate and flexible framework for path property monitoring. Analyzing the performance side of paths between pairs of nodes, our framework incorporates approaches that perform exact reconstruction of path properties as well as approximate reconstruction. Our framework is highly scalable to design measurement experiments that span thousands of routers and end hosts. It is also flexible to accommodate a variety of design requirements. For social networks, we present scalable and accurate graph embedding schemes. Aimed at analyzing the pair-wise relationships of social network users, we present three dimensionality reduction schemes leveraging matrix factorization, count-min sketch, and graph clustering paired with spectral graph embedding. As concrete applications showing the practical value of our schemes, we apply them to the important social analysis tasks of proximity estimation, missing link inference, and link prediction. The results clearly demonstrate the accuracy, scalability, and flexibility of our schemes for analyzing social networks with millions of nodes and tens of millions of links. For application service networks, we provide a proactive service quality assessment scheme. Analyzing the relationship between the satisfaction level of subscribers of an IPTV service and network performance indicators, our proposed scheme proactively (i.e., detect issues before IPTV subscribers complain) assesses user-perceived service quality using performance metrics collected from the network. From our evaluation using network data collected from a commercial IPTV service provider, we show that our scheme is able to predict 60% of the service problems that are complained by customers with only 0.1% of false positives.Item Old dog, new tricks : repurposing iron-carbide-carbonyl clusters as precursors for structural modeling of the nitrogenase cofactor(2020-05-08) Joseph, Christopher, Ph. D.; Rose, Michael J., Ph. D.; Humphrey, Simon M; Jones, Richard A; Anslyn, Eric V; Milliron, Delia JNitrogenases are the only known biological enzyme capable of catalyzing the transformation of dinitrogen (N₂) into ammonia (NH₃). The active site of nitrogenase is comprised of a double-cuboidal iron-sulfur cluster featuring an interstitial carbide as the shared vertex, three ‘belt’ sulfides bridging the cuboidal components, and either a homocitrate-bearing heterometal (Mo, V) or an Fe at one of the distal capping metal sites. Out of the three nitrogenases, the Mo-dependent variant demonstrates the highest activity for N₂ conversion. The active-site cofactor of Mo-dependent nitrogenase (FeMoco) was first isolated in 1977; however, after decades of kinetic, structural, and spectroscopic research, many questions surrounding the mechanism of substrate reduction and the electronic structure of reaction intermediates remain unanswered. In this regard, the synthetic modelling community has contributed significantly towards directing mechanistic discussions with N₂-reducing functional model compounds. Furthermore, structural model compounds have played a pivotal role in deciphering the structural and electronic properties of FeMoco, including the identification of the central carbide and assignment of metal-site valence and spin states. Despite this remarkable progress, a synthetic model featuring a paramagnetic iron cluster with sulfides, interstitial carbide, and heterometal Mo has yet to be reported. The work relayed in this dissertation outlines our efforts towards pursuing this synthetic goal. As such, we utilize a family of carbonyl-supported iron clusters — first reported in the 1960s — featuring iron-coordinated inorganic carbide. However, the highly symmetric packing structures have made heterometal-containing carbidocarbonyl iron clusters difficult to unambiguously characterize by X-ray crystallography. Moreover, the strongly π-acidic ligation sphere enforces low metal-valance states and overall diamagnetism, and ligand substitution of COs is difficult to control. Here, we demonstrate a strategy to disrupt the symmetry in molybdenum-containing heteroclusters to unambiguously characterize the Mo site in XRD. Additionally, CO→S ligand substitution is achieved with the utilization of electrophilic sulfur sources, leading to progressively higher oxidation state Fe sites. These synthetic approaches for heterometal incorporation and oxidative sulfur insertion will serve as fundamental stepping-stones towards future endeavors in utilizing and functionalizing carbidocarbonyl iron clusters as synthetic precursors and ultimately, in biomimetically modeling the nitrogenase active site cluster.Item Tropical theta functions and log Calabi-Yau surfaces(2014-05) Mandel, Travis Glenn; Keel, SeánWe describe combinatorial techniques for studying log Calabi-Yau surfaces. These can be viewed as generalizing the techniques for studying toric varieties in terms of their character and cocharacter lattices. These lattices are replaced by certain integral linear manifolds described in [GHK11], and monomials on toric varieties are replaced with the canonical theta functions defined in [GHK11] using ideas from mirror symmetry. We classify deformation classes of log Calabi-Yau surfaces in terms of the geometry of these integral linear manifolds. We then describe the tropicalizations of theta functions and use them to generalize the dual pairing between the character and cocharacter lattices. We use this to describe generalizations of dual cones, Newton and polar polytopes, Minkowski sums, and finite Fourier series expansions. We hope that these techniques will generalize to higher rank cluster varieties.