© 2002 – CRC Press
512 pages | 247 B/W Illus.
Engineering Analysis in Applied Mechanics is composed of two basic parts: the mathematical foundations in Chapters 1 through 3 and the final three chapters on specialized topics in engineering physics. Chapters 5 and 6 are devoted to solid mechanics and dynamics. The text surveys the mathematical foundations of applied mechanics. The sections on engineering mathematics includes treatments of simultaneous algebraic and differential equations, matrix algebra, the theory of optimization and the calculus of variations. The author pays considerable attention to engineering applications in theoretical thermodynamics, strength of materials and Langranian-Hamiltonian dynamics. This text is recommended for advanced undergraduate and graduate students and a familiarity with Matlab or Mathcad is suggested.
"'This is an excellent book for students in engineering physics and [for]…engineering science oriented students in the traditional engineering discipliens of mechanical, aeronautics and civil engineering.' bDr.Parvz Moin, Stanford University, Palo Alto, Calfornia, USA 'The structure of each of the parts of the book make it possible to study problems considered not only in an effective, but also pleasureable way. …Engineering Analysis in Applied Mechananics is a very useful book for both students and lecturers.' bT Krzyznski, Applied Mechanics Review, Volume 55 no.6, November 2002."
"'An authoritative treatment of the mathematics pertinent to applied engineering mechanics drives Brewer's book…The book is well written, complete, and peppered with examples. The author very appropriately endorses and provides assignments that use MATLAB software.' J. J. Miles, James Madison University, CHOICE, Current Reviews for Academic Libraries."
1.Theory of Equations 2.Theory of Extreme Values of Functions 3.The Calculus of Variations 4. The Extremum Principles of Thermodynamics 5.The Stationarity and Extremum Principles of Solid Mechanics 6. Equations of Motion and the Stationarity Principles of Lagrange and Hamilton Appendix A. Matrix Algebra and the Linear Independence of Vectors