Product Description

This book details the necessary numerical methods, the theoretical background and foundations and the techniques involved in creating computer particle models, including linked-cell method, SPME-method, tree codes, amd multipol technique. It illustrates modeling, discretization, algorithms and their parallel implementation with MPI on computer systems with distributed memory. The text offers step-by-step explanations of numerical simulation, providing illustrative code examples. With the description of the algorithms and the presentation of the results of various simulations from fields such as material science, nanotechnology, biochemistry and astrophysics, the reader of this book will learn how to write programs capable of running successful experiments for molecular dynamics.

Product Description

Engineering practice often has to deal with complex systems of multiple variable and multiple parameter models almost always with strong non-linear coupling. The conventional analytical techniques-based approaches for describing and predicting the behaviour of such systems in many cases are doomed to failure from the outset, even in the phase of the construction of a more or less appropriate mathematical model. These approaches normally are too categorical in the sense that in the name of “modelling accuracy” they try to describe all the structural details of the real physical system to be modelled. This can significantly increase the intricacy of the model and may result in a enormous computational burden without achieving considerable improvement of the solution. The best paradigm exemplifying this situation may be the classic perturbation theory: the less significant the achievable correction, the more work has to be invested to obtain it.

A further important component of machine intelligence is a kind of “structural uniformity” giving room and possibility to model arbitrary particular details a priori not specified and unknown. This idea is similar to the ready-to-wear industry, which introduced products, which can be slightly modified later on in contrast to tailor-made creations aiming at maximum accuracy from the beginning. These subsequent corrections can be carried out by machines automatically. This “learning ability” is a key element of machine intelligence.

The past decade confirmed that the view of typical components of the present soft computing as fuzzy logic, neural computing, evolutionary computation and probabilistic reasoning are of complementary nature and that the best results can be applied by their combined application.

Today, the two complementary branches of Machine Intelligence, that is, Artificial Intelligence and Computational Intelligence serve as the basis of Intelligent Engineering Systems. The huge number of scientific results published in Journal and conference proceedings worldwide substantiates this statement. The present book contains several articles taking different viewpoints in the field of intelligent systems.

Product Description
This book presents the full range of computational science and engineering -- the equations, numerical methods, and algorithms with MATLAB® codes.The author has taught this material to thousands of engineers and scientists.The book is solution-based and not formula-based: it covers applied linear algebra and fast solvers, differential equations with finite differences and finite elements, Fourier analysis, optimization, and more.

ContentsChapter 1: Applied Linear Algebra; Chapter 2: A Framework for Applied Mathematics; Chapter 3: Boundary Value Problems; Chapter 4: Fourier Series and Integrals; Chapter 5: Analytic Functions; Chapter 6: Initial Value Problems; Chapter 7: Solving Large Systems; Chapter 8: Optimization and Minimum Principles. ... Read more

Customer Reviews (6)

Not as good as his linear algebra book
Even though I love Prof. Strang for making his lectures available for people like me and even though I liked his linear algebra book, I can not say that this book is excellent.I think that he puts too many topics in one book without giving enough details or depth on any of them.The book is more like a collection of lecture notes rather than a book.If you like to study linear algebra, use his linear algebra book.If you study finite difference method for PDEs, Hoffman's is a much better choice.For numerical linear algebra, there is the book by Trefethen.

So, my suggestion for you is as follows.Pick up the book from a library.And go straight to a topic that you are somewhat familiar with.And try to see if Prof. Strang does an excellent job on that topic.I did that for a few of them, and I found that the book is not sufficient explaining those topics.

By the way, for CG method neither the book nor the video lectures are very useful.You will need the article by Jonathan Richard Shewchuk.You can find it online.This is the best for CG.

The best
This book has a modest amount of information on a whole range of topics in applied mathematics. The authors writing style makes it a lot easier on the eyes than other textbooks in the field. I recommend it to anyone who is interested in numerical methods.

Excellent for making connections, but not a text book
This books gives a unified view to topics which can seem unrelated.
For someone who has prior knowledge in CSE or applied mathematics, this book is good. Keep it in your shelf and read it to enjoy the beauty of the subject, not to learn from it.

This book is not any where close to Strang's linear algebra book.

absolutely recommended
This book is a must in bring all the main notions of scientific and engineering computation and establishing the links between them in a very comprehensive manner. Unmissable book for who is interested in the topic.

A Great Book for Mathematicians and Engineers
The following is the review I published in The UMAP Journal (Summer, 2009, Vol 30, no. 2) pp. 175-178.

My second review for this journal [1986] was of Gilbert Strang's Introduction to Applied Mathematics (hereafter IAM). I have never been too happy with that review, where I said that it is a "wonderful book." True enough; but more appropriately, it is an important book, as is the book reviewed here, Computational Science and Engineering (hereafter CSE).

CSE is--and is not--a second edition of IAM. Apparently, it is the result
of more than 20 years of Strang teaching his favorite course at MIT,
presumably out of IAM. Since CSE does not contain everything in IAM
and also contains topics not in IAM, it is a different text. CSE contains
Strang's further ruminations on the nature of applied mathematics, and
I view it as the superior text, but some individuals might prefer IAM. To
some extent, either book represents Strang's philosophy of teaching applied mathematics--that we need a new approach--but this conviction is much more explicit in CSE.

In particular, Strang believes that we should focus on both modeling and
computation. Many books are about one or the other, and he feels that applied mathematics is both. Furthermore, Strang believes that applied problems tend to have a common structure, and Chapter 2 is devoted to illustrating this principle through a wide variety of problems.

In my review of IAM, I tried to give an idea of the range of topics without enumerating the contents. CSE has the same difficulty: Enumerating the topics is tedious, but the titles of the chapters are informative (though listing them does not do justice to the sheer range of content):
1. Applied Linear Algebra
2. A Framework for Applied Mathematics
3. Boundary Value Problems
4. Fourier Series and Integrals
5. Analytic Functions
6. Initial Value Problems
7. Solving Large Systems
8. Optimization and Minimum Principles

Strang suggests that a course designed out of this text might follow the
structure that he uses (p. v):
* Applied linear algebra
* Applied differential equations
* Fourier series

I have long been a champion of Strang's books. I have reviewed different
editions of two texts on linear algebra, making clear that that I think he is the most influential author in linear algebra in the last 50 years. I have heaped high praise on his calculus text in my recent editorial on calculus [Cargal 2008]. I have done this for the exact reason that I have championed John Stillwell's books on geometry and algebra. These two authors, as well as a handful of others, write with authority leavened with the great enthusiasm of the born teacher. They are superb pedagogues.

What makes IAM and CSE so important is that they cover a great deal
of applied mathematics, and there is nothing in the literature that compares to them. Pedagogical works, as opposed to dry tomes, are simply
rarer in applied mathematics than they are in, say, calculus, linear algebra,geometry, and number theory. There are pedagogical works in differential equations and probability. But there is nothing that covers so much applied mathematics as these with comparative pedagogical skill and acumen.

Like IAM, CSE has a long first chapter that is a summary of applied linear
algebra (86 pp in IAM, 97 pp in CSE). Linear algebra is a key to applied
mathematics; it is the most important tool after calculus (this apparently is Strang's view). However, the first chapter is definitely a review. The reader needs to have had a course in linear algebra as well as the usual course in differential equations. These things are minimal. Courses in probability,numerical analysis, and so on certainly help. Knowledge of physics is a definite plus. These days, there are students of applied mathematics(computer science, statistics, operations research) who are physics-phobic. They would have problems with parts of the book. This necessity of a modicum of prior knowledge of applied mathematics means that the level of the book is for seniors and graduate students. The online comments about IAM are striking in their simplicity: Students who are not prepared despise the book, the others are enamored with it; there is no middle ground. The reader who is prepared should love this book. In particular, engineers and physicists should love this book.

People in industry, too, should love this book. Mathematicians and
engineers in industry benefit particularly froma book such as this for a very simple reason. Mathematicians in academia tend to specialize because of the need to publish. However, mathematicians in industry are motivated
to generalize. They don't have tenure; often they depend on contracts, so
that specializing can limit opportunities to get work. If a book like CSE (or AIM) had been available when I went into industry more than 30 years ago,it would have changed my life; it certainly would have made those first years easier. In fact, one topic that Strang covers very nicely in both books is the Kalman filter, a topic that is very big in industry and that occupied me in my first job.

The most important thing I tell my students is the need to study if they go into industry. This is particularly true if the student has stopped at the bachelor's degree, since a bachelor's degree is essentially a learner's permit.Few students go to work for national labs (those who do, do not need my advice--I need theirs), which means that on-the-job training is unlikely or superficial. Of people who have technical degrees, only a small portion maintain their technical skills; most simply travel along and forget much of what they learned. People tend to learn or they forget; nobody remains in stasis. In industry, you should take some of your time on the job to study.

Is spending work time studying material that is not clearly work related
to the work unethical? Typically, doing so does not create a problem (as
long as one gets one's tasks done). However, if your supervisor sees you
reading a newspaper, that could create a problem. On the other hand, if
you are studying number theory, there is no problem; that number theory
has nothing to do with your current job tasks will almost certainly not
register. Moreover, the worker who studies number theory will tend to
retain competence in differential equations far better than a worker who
just lets technical skills dissipate. In fact, those few workers who develop good technical reputations almost always study widely while on the job. Their ability to quickly respond to new problems on the job is a result of having used work time not to do company tasks. I view this behavior as a survival skill. The fact is, if one "steals" company time to study mathematics and engineering--even topics that have nothing to do with the job--one is far more likely to be promoted because of it than to be reprimanded.

However, the young worker almost always would benefit not only from
learning more number theory but--more urgently--needs to learn a lot
more applied mathematics. The undergraduate curriculum can't cover it
all. Key core areas are not just physics and differential equations, but probability,numerical analysis, and programming. For a worker in industry, CSE would be invaluable, and yet experienced engineers and mathematicians will also be impressed by this book.

Computational Science and Engineering should be in the library of every
applied mathematician, not to mention engineers. As a textbook, it is well suited for a senior or graduate course in applied mathematics.

References
Cargal, J.M. 1986. Review of Strang [1986]. The UMAP Journal 7 (4): 364-
365.

Cargal, J.M. 2008. Calculus: Textbooks, aids, and infinitesimals. The UMAP
Journal 29 (4): 399-416.

Strang, Gilbert. 1986. Introduction to Applied Mathematics. Wellesley, MA:
Wellesley-Cambridge Press.

[...] ... Read more

Product Description
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 including a complete analysis of a computer code written in transportable Fortran 77. Each example also includes a discussion of the problem equations, the coding of the equations, and the computed numerical solution. The benefits of using quality general-purpose library routines to solve ODE/DAE/PDE problems are illustrated as well. This popular, classicbook is a valuable reference for methodologies in numerical mathematics applicable to a broad spectrum of problems encountered across many disciplines- virtually all fields of science and engineering. It also serves asan excellent text for senior undergraduates or beginning graduate students in computational science. ... Read more

Product Description
This book covers modern approaches to Verification andValidation of computer codes, and other topics related toQuantification of Uncertainty and code Quality Assurance. Especiallynoteworthy are the Method of Manufactured Solutions, a general methodfor obtaining exact solutions for use in code Verifications, and theGrid Convergene Index, a method for uniform reporting of gridconvergence tests. The methods and issues are applicable to commercialcodes as well as to in-house developed research codes, and to allproblems modeled by partial differential equations; examples includeComputational Fluid Dynamics, groundwater flow and transport modeling,electrodynamics, etc. The book provides useful formulas and practicalguidance for error estimation and for experimental Validation. ... Read more

Customer Reviews (1)

single reference to cover a broad range of V&V
This book looks great.

You will think "How incredible! How a book can give a set of well-balanced information to coverboth practical and engineering based point of view about verification and validation in a real world? ... Read more

Product Description
Numerical methods are playing an ever-increasing role in physics and engineering. This is especially true after the recent explosion of computing power on the desk-top. This text is aimed at helping the user make intelligent use of this power tool. Each method is introduced through realistic examples and actual computer programmes. The explanations provide the background for making a choice between similar approaches and the knowledge to explore the network for the appropriate existing codes. Tedious proofs and derivations, on the other hand, are delegated to references. Examples of unconventional methods are also given to stimulate readers in exploring new ways of solving problems. ... Read more

Customer Reviews (2)

A good book for starting out in computational Physics
I went thru this book when I first received it, but recently used it as a reference for a computational Physics course I took. I am glad I had it. The only reason for the 4 stars, is no solutions to the problems at the ends of the chapters. I am a firm believer in learning by doing, and this book, although it has some good examples, needs to add answers to the problems, for immediate feedback. Otherwise, it is a good first introduction, and provides an excellent reference.

Fairly good book on computational physics
This book is a fairly decent overview of computational physics. The author covers most of the topics that one would obtain in taking a senior level or first year graduate course in this subject. It could be used successfully in such a course as there are problem sets at the end of each chapter that can be solved most efficiently by writing programs. In addition, the author gives pseudocode throughout the book for the main algorithms. The most useful chapter to me was Chapter 7, which covered Monte Carlo techniques. The author is pretty thorough in his treatment of this subject, and does discuss how to apply this technique in calculating path integrals in quantum mechanics. Unfortunately, he limits his discussion to the harmonic oscillator and does not give any problem sets at the end of the chapter that will allow the reader to apply the techniques to other potentials in quantum mechanics (such as maybe the anharmonic oscillator or the double well potentials). The author also discusses finite difference methods and finite element methods in the last two chapters. The author unfortunately does not discuss the numerical solution of the Boltzmann transport equation, which is of interest to me.Overall though a pretty nice job, and will introduce the new comer to the field. ... Read more

Product Description

The increasing necessity to solve complex problems in Structural Dynamics and Earthquake Engineering requires the development of new ideas, innovative methods and numerical tools for providing accurate numerical solutions in affordable computing times.

This book presents the latest scientific developments in Computational Dynamics, Stochastic Dynamics, Structural Dynamics and Earthquake Engineering in thirty-five self-contained contributions. The selected state-of-the-art chapters are revised and extended versions of the papers which were presented as plenary, semi-plenary and keynote lectures at the thematic COMPDYN 2007 Conference.

This volume will benefit researchers and engineering professionals working on structural dynamics, earthquake engineering and computational mechanics. Readers will get acquainted with advanced computational methods and software tools, which can assist them in tackling complex problems in dynamic/seismic analysis and design. Moreover, it will raise the awareness of important application areas and the social impact of the scientific and technical fields involved.

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With a primary focus on examples and applications of relevance to computational scientists, this brilliantly useful book shows computational scientists how to develop tailored, flexible, and human-efficient working environments built from small scripts written in the easy-to-learn, high-level Python language. All the tools and examples in this book are open source codes. This third edition features lots of new material. It is also released after a comprehensive reorganization of the text. The author has inserted improved examples and tools and updated information, as well as correcting any errors that crept in to the first imprint.

Customer Reviews (10)

Excellent Text and Reference!
As an intermediate Python programmer, this excellent book has become my go to reference for useful intermediate and advanced techniques that I can locate and learn quickly. The writing is clear and not overly verbose. In addition to a wide array of numerical and scientific examples, the book is helpful for a wide range of programming issues, such as gluing together disparate legacy applications, interfacing to C++, regression testing numerical code, building GUI's, web programming, etc.

Outstanding introduction to Python and Numpy
I've bought what seems to (my wife) be every Python book out there and I can't tell you how sick I am of spam, spam, spam code! (trivial and obfuscated Python code examples with a common theme focused around one Monty Python skit or another...) Spam code seems to prevail in other Python books.

Here finally is a book with code examples that are very clear, are immediately useful to the serious programmer and filled with real life discourse on relative performance differences between Python and other languages that have a reputation for speed.There are clear examples of 'number crunching', producing images and even video animations, hooks into other scientific packages such as MathLab, etc.

If you are interested in really learning Python, want to come away from an hour or twos worth of coding experience with a module or two that you can use tomorrow and are not interested in code examples extolling Monty Python silliness, then this is the book for you.

While this book is about twice as expensive as many of my other Python books, I wish I had purchased this one first.Even though I've been using Python, seemingly every day, for two years, I kept finding nuggets in this book with what seemed to be every turn of the page.My focus right now is processing extremely large data sets of binary data but I'll soon be looking at image processing and I know I'll be reaching for this book over and over again.Don't hesitate!Just buy the book!

*The* reference for folks who work with Matlab
I'm giving this book five stars because it was basically written for me.I don't mean that literally, of course.I say that because the usual methods of googling for answers and reading the manual do not work when you are trying to push the limits of what a tool is capable of doing.I do numerical computations for a variety of things -- finding patterns in large data sets, automating data collection and analysis, converting raw serial output into convenient CSV, plotting multidimensional datasets etc.Over the years, I have collected a large number of productivity habits with Matlab, which allows me to do ridiculously convoluted things in a short period of time.You just have to read the introduction of any Python manual to understand why I am switching from Matlab to Python.The problem is -- what will replace all these productivity habits?They need to be replaced with "Pythonic" habits, something that can take years of practice.

The beauty about Langtangen's book is that it runs through every one of those techniques.Instead of giving a basic example (what your google search would have provided) or a complete list of, ahem, useless techniques (what the manual would have provided), you get exactly what a seasoned data analyst needs to know to get moving with state-of-the-art commands.The author also discusses optimizations and alternatives in each chapter.

The book is also the best source for explaining *why* NumPy should be used by people working with large datasets.Folks love to create toolkits for Python, but some of these are a list of non-intuitive shortcuts that don't provide a substantial improvement over basic Python.Langtangen goes through the pain of explaining the benefits of the package (chapter 4.1.4), so that you can decide for yourself if NumPy is useful for your application.

I will not comment on the parts of the book that deal with C and FORTRAN integration because I leave that to more able programmers.I also will not comment on the extensive GUI building chapters because I do not build GUIs.I will point out, though, that I have derived full value out of this book simply by reading, and re-reading chapters 2, 3, 4 and 8.Some will argue that there is too much "basic Python" in these chapters for the whole to be considered advanced computational science -- my opinion is that even when the author describes "basic Python", his examples and intuition make it so that even one who has read a couple of reference books cover-to-cover will learn something about using "basic Python" to perform numerical analysis in a more efficient way.In fact, the book is a testament to doing really convoluted things in a really compact and elegant manner!

Absolutly Outstanding
Python Scripting for Computational Science is both an introduction to the Python language and an excellent reference for the intermediate developer.The approach taken by the author is to present the language in the form of tasks to be solved accompanied by example code.As expected for a book on scientific computing the modules covered in the examples emphasize numerical packages but this in no way detracts from the applicability to general Python enthusiast.

What really makes this book more than just another Python introduction is that the author bridges the gap between complied and interpreted code.He demonstrates how the speed of execution of compiled code can be tied to the rapid pace at which scripts can be developed.Examples are provided for interfacing C, C++ and FORTRAN code with Python.Calls to precompiled applications are also covered and the examples were easily adapted to my favorite computational tools.One of the risks with doing numerical work in a scripting language is the possibility of straying into computationally intensive tasks to which interpreted code is not well suited .Latter chapters discuss how to identify these portions of your code and how to migrating these tasks to a compiled language.

good book
If you want to learn Python, you should get it. Author do not build some "big" application (like "internet store software" or "bookstore software") from beginning to end, but rather give you a lot of practical examples of using python.

It is not like in others book that examples include only learned functions/methods, but use topics from the rest of book (you have example on page 25 and note that explanation of this and that function you found on page 543). By that you have interesting examples to use in real-world problems, not only examples to explain freshly learned topic.
In other books interesting examples of use python you found on page 3234, because only when author introduce all useful functions. In this book nice examples is even on first pages.


You learn how to use numerical packages (numpy) in python, using some useful tricks on lists and arrays, introduce to using graphical interface in Tk. ... Read more

Product Description
This textbook teaches students to create computer codes used to engineer antennas, microwave circuits, and other critical technologies for wireless communications and other applications of electromagnetic fields and waves. Worked code examples are provided for MATLAB technical computing software. It is the only textbook on numerical methods that begins at the undergraduate engineering student level but bring students to the state-of-the-art by the end of the book. It focuses on the most important and popular numerical methods, going into depth with examples and problem sets of escalating complexity. This book requires only one core course of electromagnetics, allowing it to be useful both at the senior and beginning graduate levels. Developing and using numerical methods in a powerful tool for students to learn the principles of intermediate and advanced electromagnetics. This book fills the missing space of current textbooks that either lack depth on key topics (particularly integral equations and the method of moments) and where the treatment is not accessible to students without an advanced theory course. Important topics include: Method of Moments; Finite Difference Time Domain Method; Finite Element Method; Finite Element Method-Boundary Element Method; Numerical Optimization; and Inverse Scattering. ... Read more

Product Description
Computational Materials Engineering is an advanced introduction to the computer-aided modeling of essential material properties and behavior, including the physical, thermal and chemical parameters, as well as the mathematical tools used to perform simulations. Its emphasis will be on crystalline materials, which includes all metals. The basis of Computational Materials Engineering allows scientists and engineers to create virtual simulations of material behavior and properties, to better understand how a particular material works and performs and then use that knowledge to design improvements for particular material applications.The text displays knowledge of software designers, materials scientists and engineers, and those involved in materials applications like mechanical engineers, civil engineers, electrical engineers, and chemical engineers.

Readers from students to practicing engineers to materials research scientists will find in this book a single source of the major elements that make up contemporary computer modeling of materials characteristics and behavior. The reader will gain an understanding of the underlying statistical and analytical tools that are the basis for modeling complex material interactions, including an understanding of computational thermodynamics and molecular kinetics; as well as various modeling systems. Finally, the book will offer the reader a variety of algorithms to use in solving typical modeling problems so that the theory presented herein can be put to real-world use.

.Balanced coverage of fundamentals of materials modeling, as well as more advanced aspects of modeling, such as modeling at all scales from the atomic to the molecular to the macro-material
.Concise, yet rigorous mathematical coverage of such analytical tools as the Potts type Monte Carlo method, cellular automata, phase field, dislocation dynamics and Finite Element Analysis in statistical and analytical modeling
.Companion web site will offer ample workable programs, along with suggested projects, resources for further reading, and useful classroom exercises ... Read more

Product Description

Computational Intelligence: Principles, Techniques and Applications presents both theories and applications of computational intelligence in a clear, precise and highly comprehensive style. The textbook addresses the fundamental aspects of fuzzy sets and logic, neural networks, evolutionary computing and belief networks. The application areas include fuzzy databases, fuzzy control, image understanding, expert systems, object recognition, criminal investigation, telecommunication networks, and intelligent robots. The book contains many numerical examples and homework problems with sufficient hints so that the students can solve them on their own. A CD-ROM containing the simulations is supplied with the book, to enable interested readers to develop their own application programs with the supplied C/ C++ toolbox.

Customer Reviews (1)

Computational Intelligence: Principles, Techniques and Applications
Excellent book. I highly recommend it. Although Computational Intelligence could include almost any subject, this book is a comprehensive review of the most agreed-upon paradigms in CI. Haven't checked out the CD that comes with the book, so I cannot comment about it. ... Read more

Product Description
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.

The interplay between programming and mathematics throughout the text reinforces the student s ability to reason numerically and geometrically.

Audience: Undergraduate students whose mathematical maturity is at the level of Calculus I will find this book extremely useful, especially as preparation for further courses in computing and mathematics. It can also be used as a MATLAB reference at any level.

Contents: Preface; MATLAB Glossary; Programming Topics; Software; Chapter 1: From Formula to Program; Chapter 2: Limits and Error; Chapter 3: Approximation with Fractions; Chapter 4: The Discrete versus the Continuous; Chapter 5: Abstraction; Chapter 6: Randomness; Chapter 7: The Second Dimension; Chapter 8: Reordering; Chapter 9: Search; Chapter 10: Points, Polygons, and Circles; Chapter 11: Text File Processing; Chapter 12: The Matrix: Part II; Chapter 13: Acoustic File Processing; Chapter 14: Divide and Conquer; Chapter 15: Optimization; Appendix A: Refined Graphics; Appendix B: Mathematical Facts; Appendix C: MATLAB, Java, and C; Appendix D: Exit Interview; Index ... Read more

Customer Reviews (2)

Excellent Book..great problems
Excellent book. The problems are completely worked out in detail. Unlike other books from high end publishing houses, this book really provides a great educational insight to students on the power of computing for all engineering fields. The authors seem to have worked out most of the problems and examples in their own course at Cornell and they are flawless

Useless
The textbook was useless. Only used it for practice problems, but even then, those were not much help ... Read more

Product Description
Although there are a number of satisfactory advanced thermodynamics texts on the market, virtually all of them take a rigorous theoretical and mathematical approach to the subject. Engineering students need a more practical approach-one that offers physical explanations along with the mathematical relation and equations-so they can readily apply them to real world problems.Advanced Thermodynamics Engineering fills that need. The authors take a down-to-earth approach that lays a strong conceptual foundation and provides simple, physical explanations for thermodynamic processes and the practical evaluation of thermodynamic systems. They employ a phenomenological approach throughout the book and include more than 150 engineering examples.The authors stress applications throughout the book, illustrate availability concepts,and emphasize the use of two conservation and two balance equations. They include an abundance of figures, exercises, and tables, plus a summary of important formulae and a summary of each chapter, ideal for quick reference or review. The authors have also developed spreadsheet software that covers many of the applications presented.This text eliminates the need for students to wade through the abstract generalized concepts and mathematical relations that govern thermodynamics. You can now offer them the perfect text for understanding the physics of thermodynamic concepts and apply that knowledge in the field: Advanced Thermodynamics Engineering. ... Read more

Customer Reviews (2)

Clear concepts and in depth analysis
I have taken the advanced level thermodynamics course under Dr. Annamalai and enjoyed learning from this textbook. I like the approach used in this book because it directly goes into concepts and the discussions are focused. The example problems are very good in helping students understand the theory. If you don't bother much about how information is put in the book and if you are more interested in gaining good knowledge in thermodynamics, you will be happy to use this book as a reference or textbook.

Where is the "0 star" option?
This book is horrible.I took a class with the professor who wrote it and he admits there are numerous errors in it, and even the tables in the back of the book are incorrect.If you take his class, he will provide notes to "correct" the book, but his notes are as equally horribly written.Do not waste your money on this book, unless you want something that the author admits is full of errors.I can't imagine how this book got published and seemed to completely bypass the editor phase.I would feel guilty giving this book away. ... Read more

Product Description
Designed for the fluid mechanics course for mechanical engineers or as a reference for professional engineers, this up to date text uses computer algorithms and applications to solve modern problems related to fluid flow, aerodynamics, and thermodynamics. Algorithms for numerical solutions of fluid problems (which can be implemented in programming environments such as MATLAB) will be used throughout the book, and it also includes an introduction to Computational Fluid Dynamics, a well-established method in the design of heat transfer and cooling applications. A DVD accompanies the book with source code, MATLAB files, third-party simulations, color figures, and other resources. ... Read more

Customer Reviews (1)

For the undergrad college student and interested researcher
This book is designed to be the standard undergraduate text for a traditional course in engineering. A one semester course would likely use chapters 1-5. For classes with an emphasis on aerospace engineering, aerodynamics is covered in Chapter six.

This book, more than most, includes a lot of commentary on real world situations that both keep interest level up and which indicate some of the types of applications which the student may find himself studying in post-college life. This includes some quite interesting commentary on fluid flow in biological systems including the human lung and wings of insects and birds, studies on the air flow around large trucks, and numerous photos and comments on strangely shaped aircraft studied by NASA and others.

At this time the photo of the book cover on the Amazon description is not correct. Perhaps they used a photo of an earlier edition. Also the publication date of the current edition is given by the publisher as 2011. ... Read more

Product Description
The book "Computational Error and Complexity in Science and Engineering" pervades all the science and engineering disciplines where computation occurs. Scientific and engineering computation happens to be the interface between the mathematical model/problem and the real world application. One needs to obtain good quality numerical values for any real-world implementation. Just mathematical quantities symbols are of no use to engineers/technologists. Computational complexity of the numerical method to solve the mathematical model, also computed along with the solution, on the other hand, will tell us how much computation/computational effort has been spent to achieve that quality of result. Anyone who wants the specified physical problem to be solved has every right to know the quality of the solution as well as the resources spent for the solution. The computed error as well as the complexity provide the scientific convincing answer to these questions.
Specifically some of the disciplines in which the book will be readily useful are (i) Computational Mathematics, (ii) Applied Mathematics/Computational Engineering, Numerical and Computational Physics, Simulation and Modelling. Operations Research (both deterministic and stochastic), Computing Methodologies, Computer Applications, and Numerical Methods in Engineering.

Key Features:

- Describes precisely ready-to-use computational error and complexity
- Includes simple easy-to-grasp examples wherever necessary.
- Presents error and complexity in error-free, parallel, and probabilistic methods.
- Discusses deterministic and probabilistic methods with error and complexity.
- Points out the scope and limitation of mathematical error-bounds.
- Provides a comprehensive up-to-date bibliography after each chapter.

· Describes precisely ready-to-use computational error and complexity
· Includes simple easy-to-grasp examples wherever necessary.
· Presents error and complexity in error-free, parallel, and probabilistic methods.
· Discusses deterministic and probabilistic methods with error and complexity.
· Points out the scope and limitation of mathematical error-bounds.
· Provides a comprehensive up-to-date bibliography after each chapter. ... Read more

Product Description
The subject of computational plasticity encapsulates the numerical methods used for the finite element simulation of the behaviour of a wide range of engineering materials considered to be plastic – i.e. those that undergo a permanent change of shape in response to an applied force. Computational Methods for Plasticity: Theory and Applications describes the theory of the associated numerical methods for the simulation of a wide range of plastic engineering materials; from the simplest infinitesimal plasticity theory to more complex damage mechanics and finite strain crystal plasticity models. It is split into three parts - basic concepts, small strains and large strains. Beginning with elementary theory and progressing to advanced, complex theory and computer implementation, it is suitable for use at both introductory and advanced levels. The book:

• Offers a self-contained text that allows the reader to learn computational plasticity theory and its implementation from one volume.
• Includes many numerical examples that illustrate the application of the methodologies described.
• Provides introductory material on related disciplines and procedures such as tensor analysis, continuum mechanics and finite elements for non-linear solid mechanics.
• Is accompanied by purpose-developed finite element software that illustrates many of the techniques discussed in the text, downloadable from the book’s companion website.

This comprehensive text will appeal to postgraduate and graduate students of civil, mechanical, aerospace and materials engineering as well as applied mathematics and courses with computational mechanics components. It will also be of interest to research engineers, scientists and software developers working in the field of computational solid mechanics. ... Read more

Customer Reviews (1)

Excellent, comprehensive book on plasticity
A very good book on plasticity for researchers, engineers and students. It deals with fundamentals of plasticity as well as with numerical implementations and contains examples with computer program listings. Ideal as a reference book for anybody in the field of FE simulations for forming processes. ... Read more

Product Description
Students embarking on their studies in chemical, mechanical, aerospace, energy, and environmental engineering will face continually changing combustion problems, such as pollution control and energy efficiency, throughout their careers. Approaching these challenges requires a deep familiarity with the fundamental theory, mathematics, and physical concepts of combustion. Based on more than two decades of teaching experience, Combustion Science and Engineering lays the necessary groundwork while using an illustrative, hands-on approach.

Taking a down-to-earth perspective, the book avoids heavy mathematics in the first seven chapters and in Chapter 17 (pollutants formation and destruction), but considers molecular concepts and delves into engineering details. It begins with an outline of thermodynamics; basics of thermochemistry and chemical equilibrium; descriptions of solid, liquid, and gaseous fuels; chemical kinetics and mass transfer; and applications of theory to practical systems. Beginning in chapter 8, the authors provide a detailed treatment of differential forms of conservation equations; analyses of fuel combustion including jet combustion and boundary layer problems; ignition; flame propagation; interactive and group combustion; pollutant formation and control; and turbulent combustion.

In addition, this textbook includes abundant examples, illustrations, and exercises, as well as spreadsheet software in combustion available for download. This software allows students to work out the examples found in the text. Combustion Science and Engineering imparts the skills and foundational knowledge necessary for students to successfully approach and solve new problems. ... Read more

Product Description

All over the world sport plays a prominent role in society: as a leisure activity for many, as an ingredient of culture, as a business and as a matter of national prestige in such major events as the World Cup in soccer or the Olympic Games. Hence, it is not surprising that science has entered the realm of sports, and, in particular, that computer simulation has become highly relevant in recent years. This is explored in this book by choosing five different sports as examples, demonstrating that computational science and engineering (CSE) can make essential contributions to research on sports topics on both the fundamental level and, eventually, by supporting athletes’ performance.

Product Description
Presents discretization methods on non-matching triangulations and iterative solvers with emphasis on mortar fine elements, Schwartz methods, and multigrid techniques. Also emphasizes the role of trace theorems, dual norms and weak interface conditions. Softcover. ... Read more

Product Description
This book introduces the concepts and methodologies related to the modelling of the complex phenomena occurring in materials processing. After a short reminder of conservation laws and constitutive relationships, the authors introduce the main numerical methods: finite differences, finite volumes and finite elements. These techniques are developed in three main chapters of the book that tackle more specific problems: phase transformation, solid mechanics and fluid flow. The two last chapters treat inverse methods to obtain the boundary conditions or the material properties and stochastic methods for microstructural simulation. This book is intended for undergraduate and graduate students in materials science and engineering, mechanical engineering and physics and for engineering professionals or researchers who want to get acquainted with numerical simulation to model and compute materials processing. ... Read more

Customer Reviews (1)

Modelling at the continuum scale
With the increased power and availability of computers, computer aided modeling is becoming more prevalent in various fields of engineering.One important example is modelling of stress, strain, and flow (plastic solid and liquid) at the continuum level.Examples of this are finite element analysis, finite difference analysis, Monte Carlo simulations, and the random walk. This book covers all of these topics and generally serves as a good introductory textbook to learn about modelling at the continuum scale.The mathematical treatment is very brisk though, and requires prior knowledge of linear and partial differential equations, linear algebra, and basic computing. ... Read more