Practical Numerical Methods for Chemical Engineers: Using Excel with VBA, 3rd Edition

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9781502527400: Practical Numerical Methods for Chemical Engineers: Using Excel with VBA, 3rd Edition

This latest edition expands Practical Numerical Methods with more VBA to boost Excel's power for modeling and analysis using the same numerical techniques found in more specialized math software. Visit the companion web site:

www.d.umn.edu/~rdavis/PNM/PNMExcelVBA3

to access all of the book's Excel and VBA files, and learn how to customize your own Excel workbooks with:

  1. A refined macro-enabled Excel workbook with a suite of over 170 VBA user-defined functions, macros and user-forms for learning VBA and implementing advanced numerical techniques in Excel.
  2. More than 200 example and animation workbook files from the book that demonstrate the power of numerical methods. Customize the example files and macros to tackle your own problems using VBA in Excel.
  3. Hundreds of practice problems for self-guided study to sharpen your Excel and VBA skills.

The first chapter sets the stage for problem solving with numerical methods. The next two chapters cover frequently overlooked features of Excel and VBA for implementing numerical methods in Excel, as well as documenting results. The remaining chapters present powerful numerical techniques using Excel and VBA to find roots to algebraic equations, approximate derivatives, optimize, model data by least-squares regression and interpolation, analyze risk and uncertainty, solve integrals & ordinary & partial differential equations:

  1. Numerical Methods & Mathematical Modeling: expert problem solving
  2. Excel: Documentation, Graphing, Worksheet Functions, Input Validation and Formatting, What-if Analysis
  3. VBA: Editor and objects, Function and Sub Procedures, Data Types, Structured Programming, Arithmetic and Worksheet Functions, Flow Control, Arrays, Communication, Message and Input Boxes, User Forms, Reading/Writing Files, Debugging, Unit Conversions
  4. Linear Equations: Matrix Algebra, Gaussian Elimination and Crout Reduction with Pivoting, Thomas, Cholesky, Power, Jacobi, and Interpolation Methods for Eigenvalues and Eigenvectors, Jacobi and Gauss-Seidel Iteration, Relaxation
  5. Taylor Series Analysis: Finite Difference Derivative Approximation, Richardson's Extrapolation, Ridder's algorithm, Sensitivity
  6. Nonlinear Equations Root Finding: Methods of Bisection, Regula Falsi, Newton, Secant, Pade, Wegstein, Quasi-Newton, Aitkin/Steffensen, Homotopy, Bairstow (for polynomial roots), Goal Seek and Solver
  7. Optimization: Solver, Luus-Jaakola, Quadratic, Golden Section, Powell, Downhill Simplex, Firefly, Constraints, Scaling and Sensitivity
  8. Uncertainty and Risk Analysis: Bootstrap, Confidence Intervals, Law of Propagation, Monte Carlo Simulations with Latin Hypercube Sampling
  9. Least-squares Regression: Linear, Nonlinear, LINEST, Gauss-Newton, Levenberg-Marquardt, Validation and Assessment, Uncertainty Analysis, Weighted Regression
  10. Interpolation: Linear, Newton Divided Difference and Lagrange Polynomials, Rational, Bulirsh-Stoer, Pade, Stineman, Cubic, B, Akima and Constrained Hermite Splines, Bivariate Interpolation
  11. Integration: Graphical, Trapezoidal, Midpoint and transformation for Improper Integrals, Romberg, Adaptive Simpson and Gauss-Kronrod, Multiple Integrals by Simpson, Kronrod and Monte Carlo
  12. Initial-value Problems: Single Step Euler and Backward Euler, Implicit Trapezoidal for Stiffness, Variable Step Runge-Kutta Cash-Karp, Dormand-Prince, Multi-step Adams-Bashforth-Moulton, Differential-Algebraic Systems
  13. Boundary-value Problems and Partial Differential Equations: Shooting, Finite Difference, Orthogonal Collocation, Quasilinearization, Method of Lines, Crank-Nicholson
  14. Review: Reference Tables of Excel and VBA Functions, User-defined Functions, Macros, User Forms
  15. Primer on chemical reaction engineering

Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.

About the Author :

Richard Davis is a Jean G. Blehart Distinguished Professor of Chemical Engineering at the University of Minnesota Duluth. He earned Ph.D. and B.S. Chemical Engineering degrees from UCSB and BYU, respectively.

Professor Davis has over two decades experience teaching a variety of courses including computational methods, unit operations of momentum, heat and mass transfer, chemical reactor design, engineering economics, bioprocessing and green engineering.

His current teaching and research interests include process modeling and simulation applied to mineral processing, energy conversion, air pollution control, chemical process safety, and environmental management.

Professor Davis serves as the Executive Secretary for the National Chemical Engineering Honor Society Omega Chi Epsilon, and is active in AIChE and ASEE. He is the academic adviser to the local engineering student chapters of Tau Beta Pi, Omega Chi Epsilon, and the Society for Mining, Metallurgy, and Exploration.

He is the recipient of the University’s Outstanding Adviser and Exceptional Teaching awards.

Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.

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Description du livre Createspace Independent Publishing Platform, United States, 2014. Paperback. État : New. Language: English . Brand New Book ***** Print on Demand *****.This latest edition expands Practical Numerical Methods with more VBA to boost Excel s power for modeling and analysis using the same numerical techniques found in more specialized math software. Visit the companion web site: rdavis/PNM/PNMExcelVBA3 to access all of the book s Excel and VBA files, and learn how to customize your own Excel workbooks with: A refined macro-enabled Excel workbook with a suite of over 170 VBA user-defined functions, macros and user-forms for learning VBA and implementing advanced numerical techniques in Excel. More than 200 example and animation workbook files from the book that demonstrate the power of numerical methods. Customize the example files and macros to tackle your own problems using VBA in Excel. Hundreds of practice problems for self-guided study to sharpen your Excel and VBA skills. The first chapter sets the stage for problem solving with numerical methods. The next two chapters cover frequently overlooked features of Excel and VBA for implementing numerical methods in Excel, as well as documenting results. The remaining chapters present powerful numerical techniques using Excel and VBA to find roots to algebraic equations, approximate derivatives, optimize, model data by least-squares regression and interpolation, analyze risk and uncertainty, solve integrals ordinary partial differential equations: Numerical Methods Mathematical Modeling: expert problem solving Excel: Documentation, Graphing, Worksheet Functions, Input Validation and Formatting, What-if Analysis VBA: Editor and objects, Function and Sub Procedures, Data Types, Structured Programming, Arithmetic and Worksheet Functions, Flow Control, Arrays, Communication, Message and Input Boxes, User Forms, Reading/Writing Files, Debugging, Unit Conversions Linear Equations: Matrix Algebra, Gaussian Elimination and Crout Reduction with Pivoting, Thomas, Cholesky, Power, Jacobi, and Interpolation Methods for Eigenvalues and Eigenvectors, Jacobi and Gauss-Seidel Iteration, Relaxation Taylor Series Analysis: Finite Difference Derivative Approximation, Richardson s Extrapolation, Ridder s algorithm, Sensitivity Nonlinear Equations Root Finding: Methods of Bisection, Regula Falsi, Newton, Secant, Pade, Wegstein, Quasi-Newton, Aitkin/Steffensen, Homotopy, Bairstow (for polynomial roots), Goal Seek and Solver Optimization: Solver, Luus-Jaakola, Quadratic, Golden Section, Powell, Downhill Simplex, Firefly, Constraints, Scaling and Sensitivity Uncertainty and Risk Analysis: Bootstrap, Confidence Intervals, Law of Propagation, Monte Carlo Simulations with Latin Hypercube Sampling Least-squares Regression: Linear, Nonlinear, LINEST, Gauss-Newton, Levenberg-Marquardt, Validation and Assessment, Uncertainty Analysis, Weighted Regression Interpolation: Linear, Newton Divided Difference and Lagrange Polynomials, Rational, Bulirsh-Stoer, Pade, Stineman, Cubic, B, Akima and Constrained Hermite Splines, Bivariate Interpolation Integration: Graphical, Trapezoidal, Midpoint and transformation for Improper Integrals, Romberg, Adaptive Simpson and Gauss-Kronrod, Multiple Integrals by Simpson, Kronrod and Monte Carlo Initial-value Problems: Single Step Euler and 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 and Partial Differential Equations: Shooting, Finite Difference, Orthogonal Collocation, Quasilinearization, Method of Lines, Crank-Nicholson Review: Reference Tables of Excel and VBA Functions, User-defined Functions, Macros, User Forms Primer on chemical reaction engineering. N° de réf. du libraire APC9781502527400

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ISBN 10 : 1502527405 ISBN 13 : 9781502527400
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Description du livre Createspace Independent Publishing Platform, United States, 2014. Paperback. État : New. Language: English . Brand New Book ***** Print on Demand *****. This latest edition expands Practical Numerical Methods with more VBA to boost Excel s power for modeling and analysis using the same numerical techniques found in more specialized math software. Visit the companion web site: rdavis/PNM/PNMExcelVBA3 to access all of the book s Excel and VBA files, and learn how to customize your own Excel workbooks with: A refined macro-enabled Excel workbook with a suite of over 170 VBA user-defined functions, macros and user-forms for learning VBA and implementing advanced numerical techniques in Excel. More than 200 example and animation workbook files from the book that demonstrate the power of numerical methods. Customize the example files and macros to tackle your own problems using VBA in Excel. Hundreds of practice problems for self-guided study to sharpen your Excel and VBA skills. The first chapter sets the stage for problem solving with numerical methods. The next two chapters cover frequently overlooked features of Excel and VBA for implementing numerical methods in Excel, as well as documenting results. The remaining chapters present powerful numerical techniques using Excel and VBA to find roots to algebraic equations, approximate derivatives, optimize, model data by least-squares regression and interpolation, analyze risk and uncertainty, solve integrals ordinary partial differential equations: Numerical Methods Mathematical Modeling: expert problem solving Excel: Documentation, Graphing, Worksheet Functions, Input Validation and Formatting, What-if Analysis VBA: Editor and objects, Function and Sub Procedures, Data Types, Structured Programming, Arithmetic and Worksheet Functions, Flow Control, Arrays, Communication, Message and Input Boxes, User Forms, Reading/Writing Files, Debugging, Unit Conversions Linear Equations: Matrix Algebra, Gaussian Elimination and Crout Reduction with Pivoting, Thomas, Cholesky, Power, Jacobi, and Interpolation Methods for Eigenvalues and Eigenvectors, Jacobi and Gauss-Seidel Iteration, Relaxation Taylor Series Analysis: Finite Difference Derivative Approximation, Richardson s Extrapolation, Ridder s algorithm, Sensitivity Nonlinear Equations Root Finding: Methods of Bisection, Regula Falsi, Newton, Secant, Pade, Wegstein, Quasi-Newton, Aitkin/Steffensen, Homotopy, Bairstow (for polynomial roots), Goal Seek and Solver Optimization: Solver, Luus-Jaakola, Quadratic, Golden Section, Powell, Downhill Simplex, Firefly, Constraints, Scaling and Sensitivity Uncertainty and Risk Analysis: Bootstrap, Confidence Intervals, Law of Propagation, Monte Carlo Simulations with Latin Hypercube Sampling Least-squares Regression: Linear, Nonlinear, LINEST, Gauss-Newton, Levenberg-Marquardt, Validation and Assessment, Uncertainty Analysis, Weighted Regression Interpolation: Linear, Newton Divided Difference and Lagrange Polynomials, Rational, Bulirsh-Stoer, Pade, Stineman, Cubic, B, Akima and Constrained Hermite Splines, Bivariate Interpolation Integration: Graphical, Trapezoidal, Midpoint and transformation for Improper Integrals, Romberg, Adaptive Simpson and Gauss-Kronrod, Multiple Integrals by Simpson, Kronrod and Monte Carlo Initial-value Problems: Single Step Euler and 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 and Partial Differential Equations: Shooting, Finite Difference, Orthogonal Collocation, Quasilinearization, Method of Lines, Crank-Nicholson Review: Reference Tables of Excel and VBA Functions, User-defined Functions, Macros, User Forms Primer on chemical reaction engineering. N° de réf. du libraire APC9781502527400

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