| computational science and engineering: Introduction to Computational Science Angela B. Shiflet, George W. Shiflet, 2014-03-30 The essential introduction to computational science—now fully updated and expanded Computational science is an exciting new field at the intersection of the sciences, computer science, and mathematics because much scientific investigation now involves computing as well as theory and experiment. This textbook provides students with a versatile and accessible introduction to the subject. It assumes only a background in high school algebra, enables instructors to follow tailored pathways through the material, and is the only textbook of its kind designed specifically for an introductory course in the computational science and engineering curriculum. While the text itself is generic, an accompanying website offers tutorials and files in a variety of software packages. This fully updated and expanded edition features two new chapters on agent-based simulations and modeling with matrices, ten new project modules, and an additional module on diffusion. Besides increased treatment of high-performance computing and its applications, the book also includes additional quick review questions with answers, exercises, and individual and team projects. The only introductory textbook of its kind—now fully updated and expanded Features two new chapters on agent-based simulations and modeling with matrices Increased coverage of high-performance computing and its applications Includes additional modules, review questions, exercises, and projects An online instructor's manual with exercise answers, selected project solutions, and a test bank and solutions (available only to professors) An online illustration package is available to professors |
| computational science and engineering: Elements of Scientific Computing Aslak Tveito, Hans Petter Langtangen, Bjørn Frederik Nielsen, Xing Cai, 2010-09-24 Science used to be experiments and theory, now it is experiments, theory and computations. The computational approach to understanding nature and technology is currently flowering in many fields such as physics, geophysics, astrophysics, chemistry, biology, and most engineering disciplines. This book is a gentle introduction to such computational methods where the techniques are explained through examples. It is our goal to teach principles and ideas that carry over from field to field. You will learn basic methods and how to implement them. In order to gain the most from this text, you will need prior knowledge of calculus, basic linear algebra and elementary programming. |
| computational science and engineering: Computational Science and Engineering Gilbert Strang, 2007-11-01 Encompasses the full range of computational science and engineering from modelling to solution, both analytical and numerical. It develops a framework for the equations and numerical methods of applied mathematics. Gilbert Strang has taught this material to thousands of engineers and scientists (and many more on MIT's OpenCourseWare 18.085-6). His experience is seen in his clear explanations, wide range of examples, and teaching method. The book is solution-based and not formula-based: it integrates analysis and algorithms and MATLAB codes to explain each topic as effectively as possible. The topics include applied linear algebra and fast solvers, differential equations with finite differences and finite elements, Fourier analysis and optimization. This book also serves as a reference for the whole community of computational scientists and engineers. Supporting resources, including MATLAB codes, problem solutions and video lectures from Gilbert Strang's 18.085 courses at MIT, are provided at math.mit.edu/cse. |
| computational science and engineering: Insight Through Computing Charles F. Van Loan, K.-Y. Daisy Fan, 2010-01-01 An introduction to computer-based problem-solving using the MATLAB® environment for undergraduates. |
| computational science and engineering: Software Engineering for Science Jeffrey C. Carver, Neil P. Chue Hong, George K. Thiruvathukal, 2016-11-03 Software Engineering for Science provides an in-depth collection of peer-reviewed chapters that describe experiences with applying software engineering practices to the development of scientific software. It provides a better understanding of how software engineering is and should be practiced, and which software engineering practices are effective for scientific software. The book starts with a detailed overview of the Scientific Software Lifecycle, and a general overview of the scientific software development process. It highlights key issues commonly arising during scientific software development, as well as solutions to these problems. The second part of the book provides examples of the use of testing in scientific software development, including key issues and challenges. The chapters then describe solutions and case studies aimed at applying testing to scientific software development efforts. The final part of the book provides examples of applying software engineering techniques to scientific software, including not only computational modeling, but also software for data management and analysis. The authors describe their experiences and lessons learned from developing complex scientific software in different domains. About the Editors Jeffrey Carver is an Associate Professor in the Department of Computer Science at the University of Alabama. He is one of the primary organizers of the workshop series on Software Engineering for Science (http://www.SE4Science.org/workshops). Neil P. Chue Hong is Director of the Software Sustainability Institute at the University of Edinburgh. His research interests include barriers and incentives in research software ecosystems and the role of software as a research object. George K. Thiruvathukal is Professor of Computer Science at Loyola University Chicago and Visiting Faculty at Argonne National Laboratory. His current research is focused on software metrics in open source mathematical and scientific software. |
| computational science and engineering: Scientific Computing with MATLAB and Octave Alfio Quarteroni, Fausto Saleri, Paola Gervasio, 2010-05-30 Preface to the First Edition This textbook is an introduction to Scienti?c Computing. We will illustrate several numerical methods for the computer solution of c- tain classes of mathematical problems that cannot be faced by paper and pencil. We will show how to compute the zeros or the integrals of continuous functions, solve linear systems, approximate functions by polynomials and construct accurate approximations for the solution of di?erential equations. With this aim, in Chapter 1 we will illustrate the rules of the game thatcomputersadoptwhenstoringandoperatingwith realandcomplex numbers, vectors and matrices. In order to make our presentation concrete and appealing we will 1 adopt the programming environment MATLAB as a faithful c- panion. We will gradually discover its principal commands, statements and constructs. We will show how to execute all the algorithms that we introduce throughout the book. This will enable us to furnish an - mediate quantitative assessment of their theoretical properties such as stability, accuracy and complexity. We will solve several problems that will be raisedthrough exercises and examples, often stemming from s- ci?c applications. |
| computational science and engineering: Handbook of Research on Computational Science and Engineering: Theory and Practice Leng, J., 2011-10-31 By using computer simulations in research and development, computational science and engineering (CSE) allows empirical inquiry where traditional experimentation and methods of inquiry are difficult, inefficient, or prohibitively expensive. The Handbook of Research on Computational Science and Engineering: Theory and Practice is a reference for interested researchers and decision-makers who want a timely introduction to the possibilities in CSE to advance their ongoing research and applications or to discover new resources and cutting edge developments. Rather than reporting results obtained using CSE models, this comprehensive survey captures the architecture of the cross-disciplinary field, explores the long term implications of technology choices, alerts readers to the hurdles facing CSE, and identifies trends in future development. |
| computational science and engineering: Computational Problems in Science and Engineering Nikos Mastorakis, Aida Bulucea, George Tsekouras, 2015-10-26 This book provides readers with modern computational techniques for solving variety of problems from electrical, mechanical, civil and chemical engineering. Mathematical methods are presented in a unified manner, so they can be applied consistently to problems in applied electromagnetics, strength of materials, fluid mechanics, heat and mass transfer, environmental engineering, biomedical engineering, signal processing, automatic control and more. |
| computational science and engineering: Python Scripting for Computational Science Hans Petter Langtangen, 2013-03-14 Scripting with Python makes you productive and increases the reliability of your scientific work. Here, the author teaches you how to develop tailored, flexible, and efficient working environments built from small programs (scripts) written in Python. The focus is on examples and applications of relevance to computational science: gluing existing applications and tools, e.g. for automating simulation, data analysis, and visualization; steering simulations and computational experiments; equipping programs with graphical user interfaces; making computational Web services; creating interactive interfaces with a Maple/Matlab-like syntax to numerical applications in C/C++ or Fortran; and building flexible object-oriented programming interfaces to existing C/C++ or Fortran libraries. |
| computational science and engineering: Fundamentals of Scientific Computing Bertil Gustafsson, 2011-06-11 The book of nature is written in the language of mathematics -- Galileo Galilei How is it possible to predict weather patterns for tomorrow, with access solely to today’s weather data? And how is it possible to predict the aerodynamic behavior of an aircraft that has yet to be built? The answer is computer simulations based on mathematical models – sets of equations – that describe the underlying physical properties. However, these equations are usually much too complicated to solve, either by the smartest mathematician or the largest supercomputer. This problem is overcome by constructing an approximation: a numerical model with a simpler structure can be translated into a program that tells the computer how to carry out the simulation. This book conveys the fundamentals of mathematical models, numerical methods and algorithms. Opening with a tutorial on mathematical models and analysis, it proceeds to introduce the most important classes of numerical methods, with finite element, finite difference and spectral methods as central tools. The concluding section describes applications in physics and engineering, including wave propagation, heat conduction and fluid dynamics. Also covered are the principles of computers and programming, including MATLAB®. |
| computational science and engineering: Cloud Computing for Science and Engineering Ian Foster, Dennis B. Gannon, 2017-09-29 A guide to cloud computing for students, scientists, and engineers, with advice and many hands-on examples. The emergence of powerful, always-on cloud utilities has transformed how consumers interact with information technology, enabling video streaming, intelligent personal assistants, and the sharing of content. Businesses, too, have benefited from the cloud, outsourcing much of their information technology to cloud services. Science, however, has not fully exploited the advantages of the cloud. Could scientific discovery be accelerated if mundane chores were automated and outsourced to the cloud? Leading computer scientists Ian Foster and Dennis Gannon argue that it can, and in this book offer a guide to cloud computing for students, scientists, and engineers, with advice and many hands-on examples. The book surveys the technology that underpins the cloud, new approaches to technical problems enabled by the cloud, and the concepts required to integrate cloud services into scientific work. It covers managing data in the cloud, and how to program these services; computing in the cloud, from deploying single virtual machines or containers to supporting basic interactive science experiments to gathering clusters of machines to do data analytics; using the cloud as a platform for automating analysis procedures, machine learning, and analyzing streaming data; building your own cloud with open source software; and cloud security. The book is accompanied by a website, Cloud4SciEng.org, that provides a variety of supplementary material, including exercises, lecture slides, and other resources helpful to readers and instructors. |
| computational science and engineering: A Primer on Scientific Programming with Python Hans Petter Langtangen, 2016-07-28 The book serves as a first introduction to computer programming of scientific applications, using the high-level Python language. The exposition is example and problem-oriented, where the applications are taken from mathematics, numerical calculus, statistics, physics, biology and finance. The book teaches Matlab-style and procedural programming as well as object-oriented programming. High school mathematics is a required background and it is advantageous to study classical and numerical one-variable calculus in parallel with reading this book. Besides learning how to program computers, the reader will also learn how to solve mathematical problems, arising in various branches of science and engineering, with the aid of numerical methods and programming. By blending programming, mathematics and scientific applications, the book lays a solid foundation for practicing computational science. From the reviews: Langtangen ... does an excellent job of introducing programming as a set of skills in problem solving. He guides the reader into thinking properly about producing program logic and data structures for modeling real-world problems using objects and functions and embracing the object-oriented paradigm. ... Summing Up: Highly recommended. F. H. Wild III, Choice, Vol. 47 (8), April 2010 Those of us who have learned scientific programming in Python ‘on the streets’ could be a little jealous of students who have the opportunity to take a course out of Langtangen’s Primer.” John D. Cook, The Mathematical Association of America, September 2011 This book goes through Python in particular, and programming in general, via tasks that scientists will likely perform. It contains valuable information for students new to scientific computing and would be the perfect bridge between an introduction to programming and an advanced course on numerical methods or computational science. Alex Small, IEEE, CiSE Vol. 14 (2), March /April 2012 “This fourth edition is a wonderful, inclusive textbook that covers pretty much everything one needs to know to go from zero to fairly sophisticated scientific programming in Python...” Joan Horvath, Computing Reviews, March 2015 |
| computational science and engineering: A Short Course in Computational Science and Engineering David Yevick, 2012-05-24 Building on his highly successful textbook on C++, David Yevick provides a concise yet comprehensive one-stop course in three key programming languages, C++, Java and Octave (a freeware alternative to MATLAB). Employing only public-domain software, this book presents a unique overview of numerical and programming techniques, including object-oriented programming, elementary and advanced topics in numerical analysis, physical system modelling, scientific graphics, software engineering and performance issues. Compact, transparent code in all three programming languages is applied to the fundamental equations of quantum mechanics, electromagnetics, mechanics and statistical mechanics. Uncommented versions of the code that can be immediately modified and adapted are provided online for the more involved programs. This compact, practical text is an invaluable introduction for students in all undergraduate- and graduate-level courses in the physical sciences or engineering that require numerical modelling, and also a key reference for instructors and scientific programmers. |
| computational science and engineering: Verification of Computer Codes in Computational Science and Engineering Patrick Knupp, Kambiz Salari, 2002-10-29 How can one be assured that computer codes that solve differential equations are correct? Standard practice using benchmark testing no longer provides full coverage because today's production codes solve more complex equations using more powerful algorithms. By verifying the order-of-accuracy of the numerical algorithm implemented in the code, one can detect most any coding mistake that would prevent correct solutions from being computed. Verification of Computer Codes in Computational Science and Engineering sets forth a powerful alternative called OVMSP: Order-Verification via the Manufactured Solution Procedure. This procedure has two primary components: using the Method of Manufactured Exact Solutions to create analytic solutions to the fully-general differential equations solved by the code and using grid convergence studies to confirm the order-of-accuracy. The authors present a step-by-step procedural guide to OVMSP implementation and demonstrate its effectiveness. Properly implemented, OVMSP offers an exciting opportunity to identify virtually all coding 'bugs' that prevent correct solution of the governing partial differential equations. Verification of Computer Codes in Computational Science and Engineering shows you how this can be done. The treatment is clear, concise, and suitable both for developers of production quality simulation software and as a reference for computational science and engineering professionals. |
| computational science and engineering: Insight Through Computing Charles F. Van Loan, K.-Y. Daisy Fan, 2010-01-01 This introduction to computer-based problem-solving using the MATLAB environment is highly recommended for students wishing to learn the concepts and develop the programming skills that are fundamental to computational science and engineering (CSE). Through a 'teaching by examples' approach, the authors pose strategically chosen problems to help first-time programmers learn these necessary concepts and skills. Each section formulates a problem and then introduces those new MATLAB language features that are necessary to solve it. This approach puts problem-solving and algorithmic thinking first and syntactical details second. Each solution is followed by a 'talking point' that concerns some related, larger issue associated with CSE. Collectively, the worked examples, talking points, and 300+ homework problems build intuition for the process of discretization and an appreciation for dimension, inexactitude, visualization, randomness, and complexity. This sets the stage for further coursework in CSE areas. |
| computational science and engineering: Linear Algebra for Computational Sciences and Engineering Ferrante Neri, 2019-07-26 This book presents the main concepts of linear algebra from the viewpoint of applied scientists such as computer scientists and engineers, without compromising on mathematical rigor. Based on the idea that computational scientists and engineers need, in both research and professional life, an understanding of theoretical concepts of mathematics in order to be able to propose research advances and innovative solutions, every concept is thoroughly introduced and is accompanied by its informal interpretation. Furthermore, most of the theorems included are first rigorously proved and then shown in practice by a numerical example. When appropriate, topics are presented also by means of pseudocodes, thus highlighting the computer implementation of algebraic theory. It is structured to be accessible to everybody, from students of pure mathematics who are approaching algebra for the first time to researchers and graduate students in applied sciences who need a theoretical manual of algebra to successfully perform their research. Most importantly, this book is designed to be ideal for both theoretical and practical minds and to offer to both alternative and complementary perspectives to study and understand linear algebra. |
| computational science and engineering: Recent Progress in Computational Sciences and Engineering (2 vols) Theodore Simos, 2019-05-07 This volume brings together selected contributed papers presented at the International Conference of Computational Methods in Science and Engineering (ICCMSE 2006), held in Chania, Greece, October 2006. The conference aims to bring together computational scientists from several disciplines in order to share methods and ideas. The ICCMSE is unique in its kind. It regroups original contributions from all fields of the traditional Sciences, Mathematics, Physics, Chemistry, Biology, Medicine and all branches of Engineering. It would be perhaps more appropriate to define the ICCMSE as a conference on computational science and its applications to science and engineering. Topics of general interest are: Computational Mathematics, Theoretical Physics and Theoretical Chemistry. Computational Engineering and Mechanics, Computational Biology and Medicine, Computational Geosciences and Meteorology, Computational Economics and Finance, Scientific Computation. High Performance Computing, Parallel and Distributed Computing, Visualization, Problem Solving Environments, Numerical Algorithms, Modelling and Simulation of Complex System, Web-based Simulation and Computing, Grid-based Simulation and Computing, Fuzzy Logic, Hybrid Computational Methods, Data Mining, Information Retrieval and Virtual Reality, Reliable Computing, Image Processing, Computational Science and Education etc. More than 800 extended abstracts have been submitted for consideration for presentation in ICCMSE 2005. From these 500 have been selected after international peer review by at least two independent reviewers. |
| computational science and engineering: Parallel Algorithms in Computational Science and Engineering Ananth Grama, Ahmed H. Sameh, 2020-07-06 This contributed volume highlights two areas of fundamental interest in high-performance computing: core algorithms for important kernels and computationally demanding applications. The first few chapters explore algorithms, numerical techniques, and their parallel formulations for a variety of kernels that arise in applications. The rest of the volume focuses on state-of-the-art applications from diverse domains. By structuring the volume around these two areas, it presents a comprehensive view of the application landscape for high-performance computing, while also enabling readers to develop new applications using the kernels. Readers will learn how to choose the most suitable parallel algorithms for any given application, ensuring that theory and practicality are clearly connected. Applications using these techniques are illustrated in detail, including: Computational materials science and engineering Computational cardiovascular analysis Multiscale analysis of wind turbines and turbomachinery Weather forecasting Machine learning techniques Parallel Algorithms in Computational Science and Engineering will be an ideal reference for applied mathematicians, engineers, computer scientists, and other researchers who utilize high-performance computing in their work. |
| computational science and engineering: Uncertainty Quantification and Predictive Computational Science Ryan G. McClarren, 2018-11-23 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. |
| computational science and engineering: Advanced Computational Methods in Science and Engineering Barry Koren, Kees Vuik, 2009-09-30 The aim of the present book is to show, in a broad and yet deep way, the state of the art in computational science and engineering. Examples of topics addressed are: fast and accurate numerical algorithms, model-order reduction, grid computing, immersed-boundary methods, and specific computational methods for simulating a wide variety of challenging problems, problems such as: fluid-structure interaction, turbulent flames, bone-fracture healing, micro-electro-mechanical systems, failure of composite materials, storm surges, particulate flows, and so on. The main benefit offered to readers of the book is a well-balanced, up-to-date overview over the field of computational science and engineering, through in-depth articles by specialists from the separate disciplines. |
| computational science and engineering: A First Course in Numerical Methods Uri M. Ascher, Chen Greif, 2011-07-14 Offers students a practical knowledge of modern techniques in scientific computing. |
| computational science and engineering: Data-Driven Science and Engineering Steven L. Brunton, J. Nathan Kutz, 2022-05-05 A textbook covering data-science and machine learning methods for modelling and control in engineering and science, with Python and MATLAB®. |
| computational science and engineering: Verification and Validation in Computational Science and Engineering Patrick J. Roache, 1998 |
| computational science and engineering: Computing the Electrical Activity in the Heart Joakim Sundnes, Glenn Terje Lines, Xing Cai, Bjørn Frederik Nielsen, Kent-Andre Mardal, Aslak Tveito, 2007-06-26 This book describes mathematical models and numerical techniques for simulating the electrical activity in the heart. It gives an introduction to the most important models, followed by a detailed description of numerical techniques. Particular focus is on efficient numerical methods for large scale simulations on both scalar and parallel computers. The results presented in the book will be of particular interest to researchers in bioengineering and computational biology. |
| computational science and engineering: Immersed Boundary Method Somnath Roy, Ashoke De, Elias Balaras, 2020-05-15 This volume presents the emerging applications of immersed boundary (IB) methods in computational mechanics and complex CFD calculations. It discusses formulations of different IB implementations and also demonstrates applications of these methods in a wide range of problems. It will be of special value to researchers and engineers as well as graduate students working on immersed boundary methods, specifically on recent developments and applications. The book can also be used as a supplementary textbook in advanced courses in computational fluid dynamics. |
| computational science and engineering: Computational Methods and Production Engineering J. Paulo Davim, J Paulo Davim, 2017-05-25 Computational Methods and Production Engineering: Research and Development is an original book publishing refereed, high quality articles with a special emphasis on research and development in production engineering and production organization for modern industry. Innovation and the relationship between computational methods and production engineering are presented. Contents include: Finite Element method (FEM) modeling/simulation; Artificial neural networks (ANNs); Genetic algorithms; Evolutionary computation; Fuzzy logic; neuro-fuzzy systems; Particle swarm optimization (PSO); Tabu search and simulation annealing; and optimization techniques for complex systems. As computational methods currently have several applications, including modeling manufacturing processes, monitoring and control, parameters optimization and computer-aided process planning, this book is an ideal resource for practitioners. - Presents cutting-edge computational methods for production engineering - Explores the relationship between applied computational methods and production engineering - Presents new innovations in the field - Edited by a key researcher in the field |
| computational science and engineering: An Introduction to Computational Science Allen Holder, Joseph Eichholz, 2019-06-18 This textbook provides an introduction to the growing interdisciplinary field of computational science. It combines a foundational development of numerical methods with a variety of illustrative applications spread across numerous areas of science and engineering. The intended audience is the undergraduate who has completed introductory coursework in mathematics and computer science. Students gain computational acuity by authoring their own numerical routines and by practicing with numerical methods as they solve computational models. This education encourages students to learn the importance of answering: How expensive is a calculation, how trustworthy is a calculation, and how might we model a problem to apply a desired numerical method? The text is written in two parts. Part I provides a succinct, one-term inauguration into the primary routines on which a further study of computational science rests. The material is organized so that the transition to computational science from coursework in calculus, differential equations, and linear algebra is natural. Beyond the mathematical and computational content of Part I, students gain proficiency with elemental programming constructs and visualization, which are presented in MATLAB syntax. The focus of Part II is modeling, wherein students build computational models, compute solutions, and report their findings. The models purposely intersect numerous areas of science and engineering to demonstrate the pervasive role played by computational science. |
| computational science and engineering: The Finite Element Method: Theory, Implementation, and Applications Mats G. Larson, Fredrik Bengzon, 2013-01-13 This book gives an introduction to the finite element method as a general computational method for solving partial differential equations approximately. Our approach is mathematical in nature with a strong focus on the underlying mathematical principles, such as approximation properties of piecewise polynomial spaces, and variational formulations of partial differential equations, but with a minimum level of advanced mathematical machinery from functional analysis and partial differential equations. In principle, the material should be accessible to students with only knowledge of calculus of several variables, basic partial differential equations, and linear algebra, as the necessary concepts from more advanced analysis are introduced when needed. Throughout the text we emphasize implementation of the involved algorithms, and have therefore mixed mathematical theory with concrete computer code using the numerical software MATLAB is and its PDE-Toolbox. We have also had the ambition to cover some of the most important applications of finite elements and the basic finite element methods developed for those applications, including diffusion and transport phenomena, solid and fluid mechanics, and also electromagnetics. |
| computational science and engineering: High Performance Computing in Science and Engineering ' 18 Wolfgang E. Nagel, Dietmar H. Kröner, Michael M. Resch, 2019-06-07 This book presents the state-of-the-art in supercomputer simulation. It includes the latest findings from leading researchers using systems from the High Performance Computing Center Stuttgart (HLRS) in 2018. The reports cover all fields of computational science and engineering ranging from CFD to computational physics and from chemistry to computer science with a special emphasis on industrially relevant applications. Presenting findings of one of Europe’s leading systems, this volume covers a wide variety of applications that deliver a high level of sustained performance. The book covers the main methods in high-performance computing. Its outstanding results in achieving the best performance for production codes are of particular interest for both scientists and engineers. The book comes with a wealth of color illustrations and tables of results. |
| computational science and engineering: High Performance Computing in Science and Engineering ‘14 Wolfgang E. Nagel, Dietmar H. Kröner, Michael M. Resch, 2015-02-14 This book presents the state-of-the-art in supercomputer simulation. It includes the latest findings from leading researchers using systems from the High Performance Computing Center Stuttgart (HLRS). The reports cover all fields of computational science and engineering ranging from CFD to computational physics and from chemistry to computer science with a special emphasis on industrially relevant applications. Presenting findings of one of Europe’s leading systems, this volume covers a wide variety of applications that deliver a high level of sustained performance. The book covers the main methods in high-performance computing. Its outstanding results in achieving the best performance for production codes are of particular interest for both scientists and engineers. The book comes with a wealth of color illustrations and tables of results. |
| computational science and engineering: Computational Methods in Engineering S. P. Venkateshan, Prasanna Swaminathan, 2023-05-31 The book is designed to serve as a textbook for courses offered to graduate and upper-undergraduate students enrolled in mechanical engineering. The book attempts to make students with mathematical backgrounds comfortable with numerical methods. The book also serves as a handy reference for practicing engineers who are interested in applications. The book is written in an easy-to-understand manner, with the essence of each numerical method clearly stated. This makes it easy for professional engineers, students, and early career researchers to follow the material presented in the book. The structure of the book has been modeled accordingly. It is divided into four modules: i) solution of a system of equations and eigenvalues which includes linear equations, determining eigenvalues, and solution of nonlinear equations; ii) function approximations: interpolation, data fit, numerical differentiation, and numerical integration; iii) solution of ordinary differential equations—initial value problems and boundary value problems; and iv) solution of partial differential equations—parabolic, elliptic, and hyperbolic PDEs. Each section of the book includes exercises to reinforce the concepts, and problems have been added at the end of each chapter. Exercise problems may be solved by using computational tools such as scientific calculators, spreadsheet programs, and MATLAB codes. The detailed coverage and pedagogical tools make this an ideal textbook for students, early career researchers, and professionals. |
| computational science and engineering: Computational Partial Differential Equations Hans Petter Langtangen, 2013-04-17 Targeted at students and researchers in computational sciences who need to develop computer codes for solving PDEs, the exposition here is focused on numerics and software related to mathematical models in solid and fluid mechanics. The book teaches finite element methods, and basic finite difference methods from a computational point of view, with the main emphasis on developing flexible computer programs, using the numerical library Diffpack. Diffpack is explained in detail for problems including model equations in applied mathematics, heat transfer, elasticity, and viscous fluid flow. All the program examples, as well as Diffpack for use with this book, are available on the Internet. XXXXXXX NEUER TEXT This book is for researchers who need to develop computer code for solving PDEs. Numerical methods and the application of Diffpack are explained in detail. Diffpack is a modern C++ development environment that is widely used by industrial scientists and engineers working in areas such as oil exploration, groundwater modeling, and materials testing. All the program examples, as well as a test version of Diffpack, are available for free over the Internet. |
| computational science and engineering: High Performance Computing in Science and Engineering '20 Wolfgang E. Nagel, Dietmar H. Kröner, Michael M. Resch, 2022-01-01 This book presents the state-of-the-art in supercomputer simulation. It includes the latest findings from leading researchers using systems from the High Performance Computing Center Stuttgart (HLRS) in 2020. The reports cover all fields of computational science and engineering ranging from CFD to computational physics and from chemistry to computer science with a special emphasis on industrially relevant applications. Presenting findings of one of Europe’s leading systems, this volume covers a wide variety of applications that deliver a high level of sustained performance. The book covers the main methods in high-performance computing. Its outstanding results in achieving the best performance for production codes are of particular interest for both scientists and engineers. The book comes with a wealth of color illustrations and tables of results. |
| computational science and engineering: Computational Mathematics in Engineering and Applied Science W.E. Schiesser, 2014-07-22 Computational Mathematics in Engineering and Applied Science provides numerical algorithms and associated software for solving a spectrum of problems in ordinary differential equations (ODEs), differential algebraic equations (DAEs), and partial differential equations (PDEs) that occur in science and engineering. It presents detailed examples, each |
| computational science and engineering: Computational Nuclear Engineering and Radiological Science Using Python Ryan McClarren, 2017-10-19 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 |
| computational science and engineering: Mathematics in Computational Science and Engineering Ramakant Bhardwaj, Jyoti Mishra, Satyendra Narayan, Gopalakrishnan Suseendran, 2022-06-01 MATHEMATICS IN COMPUTATIONAL SCIENCE AND ENGINEERING This groundbreaking new volume, written by industry experts, is a must-have for engineers, scientists, and students across all engineering disciplines working in mathematics and computational science who want to stay abreast with the most current and provocative new trends in the industry. Applied science and engineering is the application of fundamental concepts and knowledge to design, build and maintain a product or a process, which provides a solution to a problem and fulfills a need. This book contains advanced topics in computational techniques across all the major engineering disciplines for undergraduate, postgraduate, doctoral and postdoctoral students. This will also be found useful for professionals in an industrial setting. It covers the most recent trends and issues in computational techniques and methodologies for applied sciences and engineering, production planning, and manufacturing systems. More importantly, it explores the application of computational techniques and simulations through mathematics in the field of engineering and the sciences. Whether for the veteran engineer, scientist, student, or other industry professional, this volume is a must-have for any library. Useful across all engineering disciplines, it is a multifactional tool that can be put to use immediately in practical applications. This groundbreaking new volume: Includes detailed theory with illustrations Uses an algorithmic approach for a unique learning experience Presents a brief summary consisting of concepts and formulae Is pedagogically designed to make learning highly effective and productive Is comprised of peer-reviewed articles written by leading scholars, researchers and professors AUDIENCE: Engineers, scientists, students, researchers, and other professionals working in the field of computational science and mathematics across multiple disciplines |
| computational science and engineering: Computing the Future National Research Council, Computer Science and Telecommunications Board, Committee to Assess the Scope and Direction of Computer Science and Technology, 1992-02-01 Computers are increasingly the enabling devices of the information revolution, and computing is becoming ubiquitous in every corner of society, from manufacturing to telecommunications to pharmaceuticals to entertainment. Even more importantly, the face of computing is changing rapidly, as even traditional rivals such as IBM and Apple Computer begin to cooperate and new modes of computing are developed. Computing the Future presents a timely assessment of academic computer science and engineering (CS&E), examining what should be done to ensure continuing progress in making discoveries that will carry computing into the twenty-first century. Most importantly, it advocates a broader research and educational agenda that builds on the field's impressive accomplishments. The volume outlines a framework of priorities for CS&E, along with detailed recommendations for education, funding, and leadership. A core research agenda is outlined for these areas: processors and multiple-processor systems, data communications and networking, software engineering, information storage and retrieval, reliability, and user interfaces. This highly readable volume examines: Computer science and engineering as a discipline-how computer scientists and engineers are pushing back the frontiers of their field. How CS&E must change to meet the challenges of the future. The influence of strategic investment by federal agencies in CS&E research. Recent structural changes that affect the interaction of academic CS&E and the business environment. Specific examples of interdisciplinary and applications research in four areas: earth sciences and the environment, computational biology, commercial computing, and the long-term goal of a national electronic library. The volume provides a detailed look at undergraduate CS&E education, highlighting the limitations of four-year programs, and discusses the emerging importance of a master's degree in CS&E and the prospects for broadening the scope of the Ph.D. It also includes a brief look at continuing education. |
| computational science and engineering: Current Problems in Experimental and Computational Engineering Nenad Mitrovic, Goran Mladenovic, Aleksandra Mitrovic, 2021-11-18 The book is a collection of high-quality peer-reviewed research papers presented at the International Conference of Experimental and Numerical Investigations and New Technologies (CNNTech2021) held at Zlatibor, Serbia, from June 29 to July 2, 2021. The book discusses a wide variety of industrial, engineering, and scientific applications of the engineering techniques. Researchers from academia and industry present their original work and exchange ideas, experiences, information, techniques, applications, and innovations in the field of mechanical engineering, materials science, chemical and process engineering, experimental techniques, numerical methods, and new technologies. |
| computational science and engineering: Computational Sciences and Artificial Intelligence in Industry Tero Tuovinen, Jacques Periaux, Pekka Neittaanmäki, 2021-08-19 This book is addressed to young researchers and engineers in the fields of Computational Science and Artificial Intelligence, ranging from innovative computational methods to digital machine learning tools and their coupling used for solving challenging industrial and societal problems.This book provides the latest knowledge from jointly academic and industries experts in Computational Science and Artificial Intelligence fields for exploring possibilities and identifying challenges of applying Computational Sciences and AI methods and tools in industrial and societal sectors. |
| computational science and engineering: Recent Trends in Computational Science and Engineering Serdar Celebi, 2018-05-30 Computational science and engineering (CSE) is a broad multidisciplinary and integrative area including a variety of applications in science, engineering, numerical methods, applied mathematics, and computer science disciplines. The book covers a collection of different types of applications and visions to various disciplinary key aspects, which comprises both problem-driven and methodology-driven approaches at the same time. These selected applications are: Computational and information technologies for numerical models and large unstructured data processing Evolution of matrix computations and new concepts in computing Inverse problems covering both classical and newer approaches Integro-differential scheme (IDS) that combines finite volume and finite difference methods Smart city wireless networks Signal processing methods |
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