Computational Nuclear Engineering And Radiological Science Using Python
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Computational Nuclear Engineering And Radiological Science Using Python
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Author : Ryan McClarren
language : en
Publisher: Academic Press
Release Date : 2017-10-19
Computational Nuclear Engineering And Radiological Science Using Python written by Ryan McClarren and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-10-19 with Technology & Engineering categories.
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
Internet Of Things
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Author : Pramod R. Gunjal
language : en
Publisher: CRC Press
Release Date : 2024-03-14
Internet Of Things written by Pramod R. Gunjal and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-03-14 with Computers categories.
This book addresses the fundamental technologies, architectures, application domains, and future research directions of the Internet of Things (IoT). It also discusses how to create your own IoT system according to applications requirements, and it presents a broader view of recent trends in the IoT domain and open research issues. This book encompasses various research areas such as wireless networking, advanced signal processing, IoT, and ubiquitous computing. Internet of Things: Theory to Practice discusses the basics and fundamentals of IoT and real-time applications, as well as the associated challenges and open research issues. The book includes several case studies about the use of IoT in day-to-day life. The authors review various advanced computing technologies—such as cloud computing, fog computing, edge computing, and Big Data analytics—that will play crucial roles in future IoT-based services. The book provides a detailed role of blockchain technology, Narrowband IoT (NB-IoT), wireless body area network (WBAN), LoRa (a longrange low power platform), and Industrial IoT (IIoT) in the 5G world. This book is intended for university/college students, as well as amateur electronic hobbyists and industry professionals who are looking to stay current in the IoT domain.
Government Reports Announcements Index
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Author :
language : en
Publisher:
Release Date : 1996
Government Reports Announcements Index written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1996 with Science categories.
Machine Learning For Engineers
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Author : Ryan G. McClarren
language : en
Publisher: Springer Nature
Release Date : 2021-09-21
Machine Learning For Engineers written by Ryan G. McClarren and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-09-21 with Technology & Engineering categories.
All engineers and applied scientists will need to harness the power of machine learning to solve the highly complex and data intensive problems now emerging. This text teaches state-of-the-art machine learning technologies to students and practicing engineers from the traditionally “analog” disciplines—mechanical, aerospace, chemical, nuclear, and civil. Dr. McClarren examines these technologies from an engineering perspective and illustrates their specific value to engineers by presenting concrete examples based on physical systems. The book proceeds from basic learning models to deep neural networks, gradually increasing readers’ ability to apply modern machine learning techniques to their current work and to prepare them for future, as yet unknown, problems. Rather than taking a black box approach, the author teaches a broad range of techniques while conveying the kinds of problems best addressed by each. Examples and case studies in controls, dynamics, heat transfer, and other engineering applications are implemented in Python and the libraries scikit-learn and tensorflow, demonstrating how readers can apply the most up-to-date methods to their own problems. The book equally benefits undergraduate engineering students who wish to acquire the skills required by future employers, and practicing engineers who wish to expand and update their problem-solving toolkit.
Uncertainty Quantification And Predictive Computational Science
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Author : Ryan G. McClarren
language : en
Publisher: Springer
Release Date : 2018-11-23
Uncertainty Quantification And Predictive Computational Science written by Ryan G. McClarren and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-11-23 with Science categories.
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.
99 Nuclear Engineering Algorithms Handbook With Python
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Author : Jamie Flux
language : en
Publisher: Independently Published
Release Date : 2024-11-22
99 Nuclear Engineering Algorithms Handbook With Python written by Jamie Flux and has been published by Independently Published this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-11-22 with Technology & Engineering categories.
A Comprehensive Guide to Advanced Programming Algorithms in Nuclear Engineering Delve deep into the computational backbone of nuclear engineering with this exhaustive compendium of advanced programming algorithms. This authoritative resource presents a meticulously curated collection of 99 sophisticated algorithms, each dedicated to solving complex problems in nuclear science and engineering. Key Features: In-Depth Algorithm Exploration: Each chapter focuses on a specific algorithm, providing detailed explanations, mathematical formulations, and practical implementation strategies. Wide-Ranging Applications: Covers a spectrum of topics including Monte Carlo neutron transport, discrete ordinates methods, thermal hydraulics, reactor kinetics, fuel cycle optimization, and multiphysics coupling. Practical Implementation: Emphasizes real-world applications with code snippets, pseudocode, and step-by-step guides to facilitate understanding and implementation. Advanced Computational Techniques: Explores high-performance computing, parallel processing, adaptive mesh refinement, and machine learning applications tailored for nuclear engineering challenges. Cutting-Edge Topics: Includes contemporary methods such as hybrid deterministic-stochastic simulations, uncertainty quantification, adjoint methods, and reduced-order modeling. Who Should Read This Book: Nuclear Engineers and Scientists: Professionals seeking advanced computational tools to address complex nuclear systems and reactor designs. Computational Physicists and Engineers: Those interested in the application of numerical methods and algorithms in the nuclear domain. Graduate Students and Researchers: An invaluable reference for advanced studies and research in nuclear engineering and computational methods. Software Developers in Scientific Computing: Programmers developing simulation software for nuclear applications who require a deep understanding of underlying algorithms. Benefits: Enhance Computational Skills: Develop proficiency in implementing advanced algorithms crucial for modern nuclear engineering tasks. Stay Ahead in the Field: Keep abreast of the latest computational techniques and methodologies driving innovation in nuclear science. Problem-Solving Resource: A go-to reference for tackling computational challenges in reactor physics, thermal analysis, fuel management, and safety assessments. About the Content: Structured to provide both breadth and depth, the book allows readers to: Understand Fundamental Concepts: Begin with foundational algorithms before progressing to more complex methods. Apply Algorithms Practically: Each chapter includes practical examples, facilitating the transition from theory to application. Adapt and Innovate: Gain insights into how algorithms can be adapted to specific problems or used as a foundation for developing new methods. Elevate your computational capabilities in nuclear engineering with this definitive guide to advanced programming algorithms.
Computational Methods In Nuclear Engineering
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Author : American Nuclear Society
language : en
Publisher:
Release Date : 1975*
Computational Methods In Nuclear Engineering written by American Nuclear Society and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1975* with Nuclear engineering categories.
Computational Methods In Nuclear Engineering
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Author :
language : en
Publisher:
Release Date : 1979
Computational Methods In Nuclear Engineering written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1979 with Nuclear engineering categories.
Intelligent Techniques And Soft Computing For Nuclear Science And Engineering
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Author : Da Ruan
language : en
Publisher: World Scientific
Release Date : 2000
Intelligent Techniques And Soft Computing For Nuclear Science And Engineering written by Da Ruan and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 2000 with Technology & Engineering categories.
This book is divided into three parts. The first part, ?Mathematical Tools and New Developments?, provides basic tools to treat fuzzy set theory, rough set theory, fuzzy control, fuzzy modelling, decision support systems, and related applications. The second part, ?Intelligent Engineering Applications?, reports on engineering problems such as man-machine interface, risk analysis, image processing, robotics, knowledge-based engineering, expert systems, process control integration, diagnosis, measurements and interpretation by intelligent techniques and soft computing used for general engineering applications. The third part, ?Nuclear Engineering Applications?, concentrates on nuclear applications and covers several topics such as nuclear energy, nuclear safety assessment, radioactive waste management, nuclear measurements, nuclear safeguards, nuclear reactor operation, reactor controller design, fuel reload pattern design, signal validation, nuclear power plants, and optimizations in nuclear applications.
Topical Meeting On Computational Methods In Nuclear Engineering
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Author : Lawrence L. Barinka
language : en
Publisher:
Release Date : 1979
Topical Meeting On Computational Methods In Nuclear Engineering written by Lawrence L. Barinka and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1979 with categories.