Author: Pablo Philippe Ducru
Publisher:
ISBN:
Category :
Languages : en
Pages : 343

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Book Description
These contributions are documented in nine peer-reviewed journal articles (eight published and one under review) and seven conference articles (six published and one under review), constituting the core of this thesis.

Author: Maria Piarulli
Publisher: Frontiers Media SA
ISBN: 2832532098
Category : Science
Languages : en
Pages : 233

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Author: Harry J. Reilly
Publisher:
ISBN:
Category :
Languages : en
Pages : 40

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Author: Yousry Azmy
Publisher: Springer Science & Business Media
ISBN: 9048134110
Category : Technology & Engineering
Languages : en
Pages : 476

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Book Description
Nuclear engineering has undergone extensive progress over the years. In the past century, colossal developments have been made and with specific reference to the mathematical theory and computational science underlying this discipline, advances in areas such as high-order discretization methods, Krylov Methods and Iteration Acceleration have steadily grown. Nuclear Computational Science: A Century in Review addresses these topics and many more; topics which hold special ties to the first half of the century, and topics focused around the unique combination of nuclear engineering, computational science and mathematical theory. Comprising eight chapters, Nuclear Computational Science: A Century in Review incorporates a number of carefully selected issues representing a variety of problems, providing the reader with a wealth of information in both a clear and concise manner. The comprehensive nature of the coverage and the stature of the contributing authors combine to make this a unique landmark publication. Targeting the medium to advanced level academic, this book will appeal to researchers and students with an interest in the progression of mathematical theory and its application to nuclear computational science.

Author:
Publisher:
ISBN:
Category :
Languages : en
Pages : 6

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Book Description
Here we present a methodology to propagate nuclear data covariance information in neutron source calculations from ([alpha], n) reactions. The approach is applied to estimate the uncertainty in the neutron generation rates for uranium oxide fuel types due to uncertainties on 1) 17,18O([alpha], n) reaction cross sections and 2) uranium and oxygen stopping power cross sections. The procedure to generate reaction cross section covariance information is based on the Bayesian fitting method implemented in the R-matrix SAMMY code. The evaluation methodology uses the Reich-Moore approximation to fit the 17,18O([alpha], n) reaction cross-sections in order to derive a set of resonance parameters and a related covariance matrix that is then used to calculate the energydependent cross section covariance matrix. The stopping power cross sections and related covariance information for uranium and oxygen were obtained by the fit of stopping power data in the -energy range of 1 keV up to 12 MeV. Cross section perturbation factors based on the covariance information relative to the evaluated 17,18O([alpha], n) reaction cross sections, as well as uranium and oxygen stopping power cross sections, were used to generate a varied set of nuclear data libraries used in SOURCES4C and ORIGEN for inventory and source term calculations. The set of randomly perturbed output ([alpha], n) source responses, provide the mean values and standard deviations of the calculated responses reflecting the uncertainties in nuclear data used in the calculations. Lastly, the results and related uncertainties are compared with experiment thick target ([alpha], n) yields for uranium oxide.

Author: National Research Council
Publisher: National Academies Press
ISBN: 0309178460
Category : Political Science
Languages : en
Pages : 93

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Book Description
Maintaining the capabilities of the nuclear weapons stockpile and performing the annual assessment for the stockpile's certification involves a wide range of processes, technologies, and expertise. An important and valuable framework helping to link those components is the quantification of margins and uncertainties (QMU) methodology. In this book, the National Research Council evaluates: how the national security labs were using QMU, including any significant differences among the three labs its use in the annual assessment whether the applications of QMU to assess the proposed reliable replacement warhead (RRW) could reduce the likelihood of resuming underground nuclear testing This book presents an assessment of each of these issues and includes findings and recommendations to help guide laboratory and NNSA implementation and development of the QMU framework. It also serves as a guide for congressional oversight of those activities.

Author: Ryan G. McClarren
Publisher: Springer
ISBN: 3319995251
Category : Science
Languages : en
Pages : 345

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Book Description
This textbook teaches the essential background and skills for understanding and quantifying uncertainties in a computational simulation, and for predicting the behavior of a system under those uncertainties. It addresses a critical knowledge gap in the widespread adoption of simulation in high-consequence decision-making throughout the engineering and physical sciences. Constructing sophisticated techniques for prediction from basic building blocks, the book first reviews the fundamentals that underpin later topics of the book including probability, sampling, and Bayesian statistics. Part II focuses on applying Local Sensitivity Analysis to apportion uncertainty in the model outputs to sources of uncertainty in its inputs. Part III demonstrates techniques for quantifying the impact of parametric uncertainties on a problem, specifically how input uncertainties affect outputs. The final section covers techniques for applying uncertainty quantification to make predictions under uncertainty, including treatment of epistemic uncertainties. It presents the theory and practice of predicting the behavior of a system based on the aggregation of data from simulation, theory, and experiment. The text focuses on simulations based on the solution of systems of partial differential equations and includes in-depth coverage of Monte Carlo methods, basic design of computer experiments, as well as regularized statistical techniques. Code references, in python, appear throughout the text and online as executable code, enabling readers to perform the analysis under discussion. Worked examples from realistic, model problems help readers understand the mechanics of applying the methods. Each chapter ends with several assignable problems. Uncertainty Quantification and Predictive Computational Science fills the growing need for a classroom text for senior undergraduate and early-career graduate students in the engineering and physical sciences and supports independent study by researchers and professionals who must include uncertainty quantification and predictive science in the simulations they develop and/or perform.

Author:
Publisher:
ISBN:
Category :
Languages : en
Pages :

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Book Description
The numerical technique of Lattice QCD holds the promise of connecting the nuclear forces, nuclei, the spectrum and structure of hadrons, and the properties of matter under extreme conditions with the underlying theory of the strong interactions, quantum chromodynamics. A distinguishing, and thus far unique, feature of this formulation is that all of the associated uncertainties, both statistical and systematic can, in principle, be systematically reduced to any desired precision with sufficient computational and human resources. As a result, we review the sources of uncertainty inherent in Lattice QCD calculations for nuclear physics, and discuss how each is quantified in current efforts.

Author: Jeffery Lewins
Publisher: Pergamon
ISBN:
Category : Mathematics
Languages : en
Pages : 202

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Author: Rudi J. J. Stamm'ler
Publisher:
ISBN: 9780126633207
Category : Technology & Engineering
Languages : en
Pages : 506

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Book Description