Numerical Methods For Chemical Engineering

Applications of numerical mathematics and scientific computing to chemical engineering.

Master numerical methods using MATLAB, today's leading software for problem solving. This complete guide to numerical methods in chemical engineering is the first to take full advantage of MATLAB's powerful calculation environment. Every chapter contains several examples using general MATLAB functions that implement the method and can also be applied to many other problems in the same category. The authors begin by introducing the solution of nonlinear equations using several standard approaches, including methods of successive substitution and linear interpolation; the Wegstein method, the Newton-Raphson method; the Eigenvalue method; and synthetic division algorithms. With these fundamentals in hand, they move on to simultaneous linear algebraic equations, covering matrix and vector operations; Cramer's rule; Gauss methods; the Jacobi method; and the characteristic-value problem. Additional coverage includes: Finite difference methods, and interpolation of equally and unequally spaced points Numerical differentiation and integration, including differentiation by backward, forward, and central finite differences; Newton-Cotes formulas; and the Gauss Quadrature Two detailed chapters on ordinary and partial differential equations Linear and nonlinear regression analyses, including least squares, estimated vector of parameters, method of steepest descent, Gauss-Newton method, Marquardt Method, Newton Method, and multiple nonlinear regression The numerical methods covered here represent virtually all of those commonly used by practicing chemical engineers. The focus on MATLAB enables readers to accomplish more, with less complexity, than was possible with traditional FORTRAN. For those unfamiliar with MATLAB, a brief introduction is provided as an Appendix. Over 60+ MATLAB examples, methods, and function scripts are covered, and all of them are included on the book's CD

This undergraduate textbook integrates the teaching of numerical methods and programming with problems from core chemical engineering subjects.

This interdisciplinary book presents numerical techniques needed for chemical and biological engineers using Matlab. The book begins by exploring general cases, and moves on to specific ones. The text includes a large number of detailed illustrations, exercises and industrial examples. The book provides detailed mathematics and engineering background in the appendixes, including an introduction to Matlab. The text will be useful to undergraduate students in chemical/biological engineering, and in applied mathematics and numerical analysis.

In this second edition of An Introduction to Numerical Methods for Chemical Engineers the author has revised text, added new problems, and updated the accompanying computer programs. The result is a text that puts students on the cutting-edge of solving relevant chemical engineering problems.Designed explicitly for undergraduates, this book provides students with software and experience to solve a number of problems.Included in the text are: Numerical algorithms in explicit detail. Example problems from thermodynamic, fluid flow, heat transfer, mass transfer, kinetics, and process design. Equations developed specifically for the student from the example problems. An introduction to advanced numerical techniques, such as finite elements, singular value decomposition, and arc length homotopy. An introduction to optimization. A systematic approach to process modeling presented with advanced modeling examples. The software that accompanies the book is for IBM-compatible PCs. A solution manual is also available upon request.An Introduction to Numerical Methods for Chemical Engineers was first published in 1988 and has been taught in universities throughout the nation.

While teaching the Numerical Methods for Engineers course over the last 15 years, the author found a need for a new textbook, one that was less elementary, provided applications and problems better suited for chemical engineers, and contained instruction in Visual Basic® for Applications (VBA). This led to six years of developing teaching notes that have been enhanced to create the current textbook, Numerical Methods for Chemical Engineers Using Excel®, VBA, and MATLAB®. Focusing on Excel gives the advantage of it being generally available, since it is present on every computer—PC and Mac—that has Microsoft Office installed. The VBA programming environment comes with Excel and greatly enhances the capabilities of Excel spreadsheets. While there is no perfect programming system, teaching this combination offers knowledge in a widely available program that is commonly used (Excel) as well as a popular academic software package (MATLAB). Chapters cover nonlinear equations, Visual Basic, linear algebra, ordinary differential equations, regression analysis, partial differential equations, and mathematical programming methods. Each chapter contains examples that show in detail how a particular numerical method or programming methodology can be implemented in Excel and/or VBA (or MATLAB in chapter 10). Most of the examples and problems presented in the text are related to chemical and biomolecular engineering and cover a broad range of application areas including thermodynamics, fluid flow, heat transfer, mass transfer, reaction kinetics, reactor design, process design, and process control. The chapters feature "Did You Know" boxes, used to remind readers of Excel features. They also contain end-of-chapter exercises, with solutions provided.

This NEW 3rd edition builds on the popular success of prior editions to expand the breadth of Practical Numerical Methods with more VBA macros that boost Excel's power for modeling and analysis. Engineers & scientists will find enhanced coverage of computational tools applicable to a wider variety of problems in their own disciplines. Excel is the de facto computational tool used by practicing engineers & scientists. Use this book to become proficient with VBA programming & customize your workbooks with time saving enhancements & powerful numerical techniques. Topics include an introduction to modeling, Excel & VBA programming, root-finding for systems of linear & nonlinear equations, eigenproblems, derivative approximation, optimization, experimental uncertainty analysis, least-squares regression & model validation, interpolation, integration, ordinary & partial differential equations. A companion web site has digital files for downloading 200 illustrations, examples, & the refined PNM3Suite workbook with 100 VBA user-defined functions, macros, & user forms for advanced numerical techniques. End-of-chapter practice problems for self-study are also available at the site (www.d.umn.edu/~rdavis/PNM/PNMExcelVBA3). Example files & macros are ready to be modified by users for their own needs. The introduction includes a primer on chemical reaction engineering for problems involving mass & energy balances with reactions. The next two chapters cover frequently overlooked features of Excel & VBA to apply numerical methods in Excel, as well as document results. The remaining chapters present powerful numerical techniques using Excel & VBA. Introduction to Numerical Methods & Mathematical Modeling Introduction to Excel: Documentation, Graphing, Worksheet Functions, Validation & Formatting, What-if Analysis VBA: Editor, Functions & Sub Procedures, Data Types, Structured Programming, Arithmetic & Worksheet Functions, Flow Control, Arrays, Communication, Message & Input Boxes, User Forms, Reading/Writing Files, Debugging Linear Equations: Matrix Algebra, Gaussian Elimination & Crout Reduction with Pivoting, Thomas, Cholesky, Power, Jacobi, & Interpolation Method for Eigenvalues & Eigenvectors, Jacobi & Gauss-Seidel Iteration, Relaxation Taylor Series Analysis: Finite Difference Derivative Approximations, Richardson's Extrapolation Nonlinear Equations: Root Finding, Bisection, Regula Falsi, Newton & Secant Methods, Wegstein, Quasi-Newton, Aitkin & Steffensen, Homotopy, Goal Seek & Solver, Bairstow's Method for Polynomial Roots Optimization: Solver, Luus-Jaakola, Quadratic Interpolation, Golden Section, Powell, Constraints, Scaling Uncertainty Analysis: Law of Propagation, Monte Carlo Simulations with Latin Hypercube Sampling Least-squares Regression: Linear & Nonlinear, LINEST, Gauss-Newton, Levenberg-Marquardt, Model Validation & Assessment, Parameter & Model Uncertainty Analysis, Weighted Regression Interpolation: Linear, Newton Divided Difference & Lagrange Polynomials, Rational, Stineman, Cubic & Constrained Splines, Linear & Spline Bivariate Interpolation Integration: Graphical, Trapezoidal, Midpoint for Improper Integrals, Romberg, Adaptive Simpson & Gauss-Kronrod, Multiple Integrals by Simpson, Guass-Kronrod & Monte Carlo Initial-value Problems: Single Step Euler & Backward Euler, Implicit Trapezoidal for Stiffness, Variable Step Runge-Kutta Cash Karp, Dormand-Prince, Multi-step Adams-Bashforth-Moulton, Differential-Algebraic Systems Boundary-value Problems & Partial Differential Equations: Shooting, Finite Difference, Orthogonal Collocation, Quasilinearization, Method of Lines, Crank-Nicholson Review: Summary Tables of Excel & VBA Functions, User-defined Functions, Macros, User Forms

A practical, professional guide to MATLAB computational techniques and engineering applications MATLAB Numerical Methods with Chemical Engineering Applications shows you, step by step, how to use MATLAB® to model and simulate physical problems in the chemical engineering realm. Written for MATLAB 7.11, this hands-on resource contains concise explanations of essential MATLAB commands, as well as easy-to-follow instructions for using the programming features, graphical capabilities, and desktop interface. Every step needed toward the final solution is algorithmically explained via snapshots of the MATLAB platform in parallel with the text. End-of-chapter problems help you practice what you've learned. Master this powerful computational tool using this detailed, self-teaching guide. COVERAGE INCLUDES: MATLAB basics Matrices MATLAB scripting language: M-file Image and image analysis Curve-fitting Numerical integration Solving differential equations A system of algebraic equations Statistics Chemical engineering applications MATLAB Graphical User Interface Design Environment (GUIDE)