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Author: Glenn E Sjoden Publisher: World Scientific Publishing Company ISBN: 9814630950 Category : Science Languages : en Pages : 404
Book Description
Foundations in Applied Nuclear Engineering Analysis (2nd Edition) covers a fast-paced one semester course to address concepts of modeling in mathematics, engineering analysis, and computational problem solving needed in subjects such as radiation interactions, heat transfer, reactor physics, radiation transport, numerical modeling, etc., for success in a nuclear engineering/medical physics curriculum. While certain topics are covered tangentially, others are covered in depth to target on the appropriate amalgam of topics for success in navigating nuclear-related disciplines. Software examples and programming are used throughout the book, since computational capabilities are essential for new engineers. The book contains a array of topics that cover the essential subjects expected for students to successfully navigate into nuclear-related disciplines. The text assumes that students have familiarity with undergraduate mathematics and physics, and are ready to apply those skills to problems in nuclear engineering. Applications and problem sets are directed toward problems in nuclear science. Software examples using Mathematica software are used in the text. This text was developed as part of a very applied course in mathematical physics methods for nuclear engineers. The course in Nuclear Engineering Analysis that follows this text began at the University of Florida; the 2nd edition was released while at the Georgia Institute of Technology.
Author: Thomas M. Semkow Publisher: ISBN: Category : Science Languages : en Pages : 402
Book Description
This book will broach the topics of applied nuclear science in general, and nuclear chemistry in particular where there is usually a modeling or computational component. Typically one finds several modelers presenting their work in the course of almost every symposium. It's imperative to bring all such theoretical and computational work in applied nuclear science under one umbrella and thats what this book aims to do. The nuclear scientists interested in modeling are lacking a broader forum for their research, as well as a vehicle to enable those learning related techniques. The editors intend to include several topics: radiation risk assessment, radiation transport, contaminant transport, radiation dosimetry, modeling of experiments, detection limits, nuclear data analysis and statistical aspects.
Author: Glenn E Sjoden Publisher: World Scientific Publishing Company ISBN: 9814630950 Category : Science Languages : en Pages : 404
Book Description
Foundations in Applied Nuclear Engineering Analysis (2nd Edition) covers a fast-paced one semester course to address concepts of modeling in mathematics, engineering analysis, and computational problem solving needed in subjects such as radiation interactions, heat transfer, reactor physics, radiation transport, numerical modeling, etc., for success in a nuclear engineering/medical physics curriculum. While certain topics are covered tangentially, others are covered in depth to target on the appropriate amalgam of topics for success in navigating nuclear-related disciplines. Software examples and programming are used throughout the book, since computational capabilities are essential for new engineers. The book contains a array of topics that cover the essential subjects expected for students to successfully navigate into nuclear-related disciplines. The text assumes that students have familiarity with undergraduate mathematics and physics, and are ready to apply those skills to problems in nuclear engineering. Applications and problem sets are directed toward problems in nuclear science. Software examples using Mathematica software are used in the text. This text was developed as part of a very applied course in mathematical physics methods for nuclear engineers. The course in Nuclear Engineering Analysis that follows this text began at the University of Florida; the 2nd edition was released while at the Georgia Institute of Technology.
Author: Zafar Ullah Koreshi Publisher: Academic Press ISBN: 0323908314 Category : Science Languages : en Pages : 549
Book Description
Nuclear Engineering Mathematical Modeling and Simulation presents the mathematical modeling of neutron diffusion and transport. Aimed at students and early career engineers, this highly practical and visual resource guides the reader through computer simulations using the Monte Carlo Method which can be applied to a variety of applications, including power generation, criticality assemblies, nuclear detection systems, and nuclear medicine to name a few. The book covers optimization in both the traditional deterministic framework of variational methods and the stochastic framework of Monte Carlo methods. Specific sections cover the fundamentals of nuclear physics, computer codes used for neutron and photon radiation transport simulations, applications of analyses and simulations, optimization techniques for both fixed-source and multiplying systems, and various simulations in the medical area where radioisotopes are used in cancer treatment. Provides a highly visual and practical reference that includes mathematical modeling, formulations, models and methods throughout Includes all current major computer codes, such as ANISN, MCNP and MATLAB for user coding and analysis Guides the reader through simulations for the design optimization of both present-day and future nuclear systems
Author: Launey Kristina D Publisher: #N/A ISBN: 9813146060 Category : Science Languages : en Pages : 392
Book Description
This book is a unique collection of reviews that share a common topic, emergent phenomena in atomic nuclei, while revealing the multifaceted nature of the subject, from quarks to heavy nuclei. It tells an amazing story of a decades-long journey of trials and successes, up to present days, with the aim to understand the vast array of experimental data and the fundamentals of strongly interacting fermions. The emphasis is on discovering emergent orderly patterns amidst the overarching complexity of many-particle quantum-mechanical systems. Recent findings are discussed within an interesting framework: a combination of nuclear theory and experiment, of group theory and computational science, and of pivotal models of astonishing simplicity and state-of-the-art models empowered by supercomputers. A special theme resonates throughout the book: the important role of symmetries, exact and approximate, in exposing emergent features and guiding large-scale nuclear modeling. World-renowned experts offer their unique perspective on symmetries in the world of quarks and gluons, and that of protons and neurons — from chiral symmetry, through spin-isospin and quasi-spin symmetries, to symplectic symmetry, — as well as on the emergent nature of nuclear collectivity, clustering, and pairing, viewed from spectroscopy, microscopic considerations, and first principles. The book provides an excellent foundation that allows researchers and graduate students in physics and applied mathematics to review the current status of the subject, and to further explore the research literature through exhaustive sets of references that also point to studies underpinned by similar techniques in condensed matter and atomic physics along with quantum information.
Author: Dan Gabriel Cacuci Publisher: Springer ISBN: 366258395X Category : Technology & Engineering Languages : en Pages : 451
Book Description
This book addresses the experimental calibration of best-estimate numerical simulation models. The results of measurements and computations are never exact. Therefore, knowing only the nominal values of experimentally measured or computed quantities is insufficient for applications, particularly since the respective experimental and computed nominal values seldom coincide. In the author’s view, the objective of predictive modeling is to extract “best estimate” values for model parameters and predicted results, together with “best estimate” uncertainties for these parameters and results. To achieve this goal, predictive modeling combines imprecisely known experimental and computational data, which calls for reasoning on the basis of incomplete, error-rich, and occasionally discrepant information. The customary methods used for data assimilation combine experimental and computational information by minimizing an a priori, user-chosen, “cost functional” (usually a quadratic functional that represents the weighted errors between measured and computed responses). In contrast to these user-influenced methods, the BERRU (Best Estimate Results with Reduced Uncertainties) Predictive Modeling methodology developed by the author relies on the thermodynamics-based maximum entropy principle to eliminate the need for relying on minimizing user-chosen functionals, thus generalizing the “data adjustment” and/or the “4D-VAR” data assimilation procedures used in the geophysical sciences. The BERRU predictive modeling methodology also provides a “model validation metric” which quantifies the consistency (agreement/disagreement) between measurements and computations. This “model validation metric” (or “consistency indicator”) is constructed from parameter covariance matrices, response covariance matrices (measured and computed), and response sensitivities to model parameters. Traditional methods for computing response sensitivities are hampered by the “curse of dimensionality,” which makes them impractical for applications to large-scale systems that involve many imprecisely known parameters. Reducing the computational effort required for precisely calculating the response sensitivities is paramount, and the comprehensive adjoint sensitivity analysis methodology developed by the author shows great promise in this regard, as shown in this book. After discarding inconsistent data (if any) using the consistency indicator, the BERRU predictive modeling methodology provides best-estimate values for predicted parameters and responses along with best-estimate reduced uncertainties (i.e., smaller predicted standard deviations) for the predicted quantities. Applying the BERRU methodology yields optimal, experimentally validated, “best estimate” predictive modeling tools for designing new technologies and facilities, while also improving on existing ones.
Author: A.J Cole Publisher: CRC Press ISBN: 1420033476 Category : Science Languages : en Pages : 354
Book Description
Statistical Models for Nuclear Decay: From Evaporation to Vaporization describes statistical models that are applied to the decay of atomic nuclei, emphasizing highly excited nuclei usually produced using heavy ion collisions. The first two chapters present essential introductions to statistical mechanics and nuclear physics, followed by a descript
Author: Glenn E Sjoden
Author: Thomas M. Semkow
Author: Glenn E Sjoden
Author: Zafar Ullah Koreshi
Author: ComNSE Workshop
Author: 
Author: Yue Jin
Author: M. K. Mehta
Author: Launey Kristina D
Author: Dan Gabriel Cacuci
Author: A.J Cole