Nuclear Computational Science - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Nuclear Computational Science write by Yousry Azmy. This book was released on 2010-04-15. Nuclear Computational Science available in PDF, EPUB and Kindle. 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.
Computational Nuclear Engineering and Radiological Science Using Python
Computational Nuclear Engineering and Radiological Science Using Python - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Computational Nuclear Engineering and Radiological Science Using Python write by Ryan McClarren. This book was released on 2017-10-19. Computational Nuclear Engineering and Radiological Science Using Python available in PDF, EPUB and Kindle. Computational Nuclear Engineering and Radiological Science Using Python provides the necessary knowledge users need to embed more modern computing techniques into current practices, while also helping practitioners replace Fortran-based implementations with higher level languages. The book is especially unique in the market with its implementation of Python into nuclear engineering methods, seeking to do so by first teaching the basics of Python, then going through different techniques to solve systems of equations, and finally applying that knowledge to solve problems specific to nuclear engineering. Along with examples of code and end-of-chapter problems, the book is an asset to novice programmers in nuclear engineering and radiological sciences, teaching them how to analyze complex systems using modern computational techniques. For decades, the paradigm in engineering education, in particular, nuclear engineering, has been to teach Fortran along with numerical methods for solving engineering problems. This has been slowly changing as new codes have been written utilizing modern languages, such as Python, thus resulting in a greater need for the development of more modern computational skills and techniques in nuclear engineering. - Offers numerical methods as a tool to solve specific problems in nuclear engineering - Provides examples on how to simulate different problems and produce graphs using Python - Supplies accompanying codes and data on a companion website, along with solutions to end-of-chapter problems
An Advanced Course in Computational Nuclear Physics
An Advanced Course in Computational Nuclear Physics - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook An Advanced Course in Computational Nuclear Physics write by Morten Hjorth-Jensen. This book was released on 2017-05-09. An Advanced Course in Computational Nuclear Physics available in PDF, EPUB and Kindle. This graduate-level text collects and synthesizes a series of ten lectures on the nuclear quantum many-body problem. Starting from our current understanding of the underlying forces, it presents recent advances within the field of lattice quantum chromodynamics before going on to discuss effective field theories, central many-body methods like Monte Carlo methods, coupled cluster theories, the similarity renormalization group approach, Green’s function methods and large-scale diagonalization approaches. Algorithmic and computational advances show particular promise for breakthroughs in predictive power, including proper error estimates, a better understanding of the underlying effective degrees of freedom and of the respective forces at play. Enabled by recent improvements in theoretical, experimental and numerical techniques, the state-of-the art applications considered in this volume span the entire range, from our smallest components – quarks and gluons as the mediators of the strong force – to the computation of the equation of state for neutron star matter. The lectures presented provide an in-depth exposition of the underlying theoretical and algorithmic approaches as well details of the numerical implementation of the methods discussed. Several also include links to numerical software and benchmark calculations, which readers can use to develop their own programs for tackling challenging nuclear many-body problems.
Uncertainty Quantification and Predictive Computational Science
Uncertainty Quantification and Predictive Computational Science - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Uncertainty Quantification and Predictive Computational Science write by Ryan G. McClarren. This book was released on 2018-11-23. Uncertainty Quantification and Predictive Computational Science available in PDF, EPUB and Kindle. 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.
Advances of Computational Fluid Dynamics in Nuclear Reactor Design and Safety Assessment
Advances of Computational Fluid Dynamics in Nuclear Reactor Design and Safety Assessment - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Advances of Computational Fluid Dynamics in Nuclear Reactor Design and Safety Assessment write by Jyeshtharaj Joshi. This book was released on 2019-06-11. Advances of Computational Fluid Dynamics in Nuclear Reactor Design and Safety Assessment available in PDF, EPUB and Kindle. Advances of Computational Fluid Dynamics in Nuclear Reactor Design and Safety Assessment presents the latest computational fluid dynamic technologies. It includes an evaluation of safety systems for reactors using CFD and their design, the modeling of Severe Accident Phenomena Using CFD, Model Development for Two-phase Flows, and Applications for Sodium and Molten Salt Reactor Designs. Editors Joshi and Nayak have an invaluable wealth of experience that enables them to comment on the development of CFD models, the technologies currently in practice, and the future of CFD in nuclear reactors. Readers will find a thematic discussion on each aspect of CFD applications for the design and safety assessment of Gen II to Gen IV reactor concepts that will help them develop cost reduction strategies for nuclear power plants.
