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  • 1
    Call number: ZSP-201-83/7
    In: CRREL Report, 83-7
    Description / Table of Contents: Peak power generation with hydropower creates tailwater flow conditions characterized by high and low flows with abrupt transitions between these states. Flows occurring in tailwaters typically form sharp-fronted, large-amplitude waves of relatively short period. An understanding of the mechanics of downstream propagation of these waves is important both for direct application in studies of the tailwater and because of the similarity of these waves to those following a dam break. An analysis of the dynamic equations of open channel flow is used to quantify the relative importance of flow wave convection, diffusion and dispersion in rivers. The relative importance of each process is re­lated to the relative magnitude of terms in the dynamic equations, providing a physical basis for model formulation. A one-dimensional diffusion wave flow routing model, modified for tailwaters, simulates the important physical pro­cesses affecting the flow and is straightforward to apply. The model is based upon a numerical solution of the kine­matic wave equation. The “modified equation,” Hirt, and von Neumann analyses are used to gain insight into the stability and dissipative and dispersive behavior of the numerical solution, and results of these analyses are compared. A set of linear routings is used to demonstrate the dissipative and dispersive behavior predicted by the analyses and to verify the accuracy of an expression that quantifies the numerical diffusion of the model. The analyses provide a basis for selection of numerical parameters for model applications. The capability and accuracy of the model are enhanced when physical wave diffusion is balanced by numerical diffusion in the model. Maintaining the diffusion balance re­quires that the time derivative weighting parameter 0 be variable and in some instances negative. Though some amount of phase error is introduced, negative 0 values have no adverse effect upon model stability. Field studies were con­ducted to demonstrate the benefits of careful model development and analysis, and to verify the diffusion wave model for rapidly varying tailwater flow. The bed slope and roughness characteristics of the field study reaches (below Apalachia and Norris Dams) differ greatly, spanning those of a large number of rivers of practical interest. The accurate simulation of flow in both of these tailwaters attests to the soundness of both the physical basis of the model and the numerical solution technique. The field studies confirm, for the extreme case of rapidly varying flow in a mildly sloped river, that inertia has a negligible effect upon unsteady flow waves at low Froude numbers. Additionally, these studies verify that diffusion of short-period waves in rivers is generally significant.
    Type of Medium: Series available for loan
    Pages: vi, 41 Seiten , Illustrationen
    Series Statement: CRREL Report 83-7
    Language: English
    Note: CONTENTS Abstract Preface Nomenclature Introduction Physical diffusion and dispersion in open channel flow Modeling approach Description of the diffusion wave flow routing model Analysis of the numerical model Modified equation and Hirt analyses of diffusion wave model von Neumann analysis of the diffusion wave model Linear case studies Accuracy considerations of the numerical solution Field studies Apalachia Dam tailwater Norris Dam tailwater Conclusions Literature cited
    Location: AWI Archive
    Branch Library: AWI Library
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  • 2
    Publication Date: 2016-06-16
    Description: Tandem mass spectrometry (MS/MS) is the dominant high throughput technology for identifying and quantifying proteins in complex biological samples. Analysis of the tens of thousands of fragmentation spectra produced by an MS/MS experiment begins by assigning to each observed spectrum the peptide that is hypothesized to be responsible for generating the spectrum. This assignment is typically done by searching each spectrum against a database of peptides. To our knowledge, all existing MS/MS search engines compute scores individually between a given observed spectrum and each possible candidate peptide from the database. In this work, we use a trellis , a data structure capable of jointly representing a large set of candidate peptides, to avoid redundantly recomputing common sub-computations among different candidates. We show how trellises may be used to significantly speed up existing scoring algorithms, and we theoretically quantify the expected speedup afforded by trellises. Furthermore, we demonstrate that compact trellis representations of whole sets of peptides enables efficient discriminative learning of a dynamic Bayesian network for spectrum identification, leading to greatly improved spectrum identification accuracy. Contact: bilmes@uw.edu or william-noble@uw.edu Supplementary information: Supplementary data are available at Bioinformatics online.
    Print ISSN: 1367-4803
    Electronic ISSN: 1460-2059
    Topics: Biology , Computer Science , Medicine
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  • 3
    Publication Date: 2013-01-20
    Description: The ENCODE Project has generated a wealth of experimental information mapping diverse chromatin properties in several human cell lines. Although each such data track is independently informative toward the annotation of regulatory elements, their interrelations contain much richer information for the systematic annotation of regulatory elements. To uncover these interrelations and to generate an interpretable summary of the massive datasets of the ENCODE Project, we apply unsupervised learning methodologies, converting dozens of chromatin datasets into discrete annotation maps of regulatory regions and other chromatin elements across the human genome. These methods rediscover and summarize diverse aspects of chromatin architecture, elucidate the interplay between chromatin activity and RNA transcription, and reveal that a large proportion of the genome lies in a quiescent state, even across multiple cell types. The resulting annotation of non-coding regulatory elements correlate strongly with mammalian evolutionary constraint, and provide an unbiased approach for evaluating metrics of evolutionary constraint in human. Lastly, we use the regulatory annotations to revisit previously uncharacterized disease-associated loci, resulting in focused, testable hypotheses through the lens of the chromatin landscape.
    Print ISSN: 0305-1048
    Electronic ISSN: 1362-4962
    Topics: Biology
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  • 4
    Publication Date: 2003-12-01
    Print ISSN: 1433-7541
    Electronic ISSN: 1433-755X
    Topics: Computer Science
    Published by Springer
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  • 5
    Publication Date: 2008-06-27
    Print ISSN: 1367-4803
    Electronic ISSN: 1460-2059
    Topics: Biology , Computer Science , Medicine
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