Muutke küpsiste eelistusi

Numerical Methods for Engineers 7th edition [Kõva köide]

  • Formaat: Hardback, 992 pages, kõrgus x laius x paksus: 239x218x36 mm, kaal: 1621 g, 582 Illustrations
  • Ilmumisaeg: 16-Feb-2014
  • Kirjastus: McGraw Hill Higher Education
  • ISBN-10: 007339792X
  • ISBN-13: 9780073397924
Teised raamatud teemal:
  • Kõva köide
  • Hind: 211,14 €*
  • * saadame teile pakkumise kasutatud raamatule, mille hind võib erineda kodulehel olevast hinnast
  • See raamat on trükist otsas, kuid me saadame teile pakkumise kasutatud raamatule.
  • Kogus:
  • Lisa ostukorvi
  • Tasuta tarne
  • Lisa soovinimekirja
  • Formaat: Hardback, 992 pages, kõrgus x laius x paksus: 239x218x36 mm, kaal: 1621 g, 582 Illustrations
  • Ilmumisaeg: 16-Feb-2014
  • Kirjastus: McGraw Hill Higher Education
  • ISBN-10: 007339792X
  • ISBN-13: 9780073397924
Teised raamatud teemal:
Numerical Methods for Engineers retains the instructional techniques that have made the text so successful. Chapra and Canale's unique approach opens each part of the text with sections called Motivation, Mathematical Background, and Orientation". Each part closes with an Epilogue containing Trade-Offs, Important Relationships and Formulas, and Advanced Methods and Additional References. Much more than a summary, the Epilogue deepens understanding of what has been learned and provides a peek into more advanced methods. Numerous new or revised problems are drawn from actual engineering practice. The expanded breadth of engineering disciplines covered is especially evident in these exercises, which now cover such areas as biotechnology and biomedical engineering. Excellent new examples and case studies span all areas of engineering giving students a broad exposure to various fields in engineering.

McGraw-Hill's Connect, is also available as an optional, add on item. Connect is the only integrated learning system that empowers students by continuously adapting to deliver precisely what they need, when they need it, how they need it, so that class time is more effective. Connect allows the professor to assign homework, quizzes, and tests easily and automatically grades and records the scores of the student's work. Problems are randomized to prevent sharing of answers an may also have a "multi-step solution" which helps move the students' learning along if they experience difficulty.
Preface xiv
About The Authors xvi
PART ONE MODELING, COMPUTERS, AND ERROR ANALYSIS
3(114)
Pt1.1 Motivation
3(2)
Pt1.2 Mathematical Background
5(3)
Pt1.3 Orientation
8(3)
Chapter 1 Mathematical Modeling and Engineering Problem Solving
11(16)
1.1 A Simple Mathematical Model
11(7)
1.2 Conservation Laws and Engineering
18(9)
Problems
21(6)
Chapter 2 Programming and Software
27(28)
2.1 Packages and Programming
27(1)
2.2 Structured Programming
28(9)
2.3 Modular Programming
37(2)
2.4 Excel
39(4)
2.5 MATLAB
43(4)
2.6 Mathcad
47(1)
2.7 Other Languages and Libraries
48(7)
Problems
49(6)
Chapter 3 Approximations and Round-Off Errors
55(26)
3.1 Significant Figures
56(2)
3.2 Accuracy and Precision
58(1)
3.3 Error Definitions
59(6)
3.4 Round-Off Errors
65(16)
Problems
79(2)
Chapter 4 Truncation Errors and the Taylor Series
81(36)
4.1 The Taylor Series
81(16)
4.2 Error Propagation
97(4)
4.3 Total Numerical Error
101(5)
4.4 Blunders, Formulation Errors, and Data Uncertainty
106(4)
Problems
108(2)
Epilogue: Part One
110(1)
Pt1.4 Trade-Offs
110(3)
Pt1.5 Important Relationships and Formulas
113(1)
Pt1.6 Advanced Methods and Additional References
113(4)
PART TWO ROOTS OF EQUATIONS
117(114)
Pt2.1 Motivation
117(2)
Pt2.2 Mathematical Background
119(1)
Pt2.3 Orientation
120(3)
Chapter 5 Bracketing Methods
123(22)
5.1 Graphical Methods
123(4)
5.2 The Bisection Method
127(8)
5.3 The False-Position Method
135(6)
5.4 Incremental Searches and Determining Initial Guesses
141(4)
Problems
142(3)
Chapter 6 Open Methods
145(31)
6.1 Simple Fixed-Point Iteration
146(5)
6.2 The Newton-Raphson Method
151(6)
6.3 The Secant Method
157(5)
6.4 Brent's Method
162(4)
6.5 Multiple Roots
166(3)
6.6 Systems of Nonlinear Equations
169(7)
Problems
173(3)
Chapter 7 Roots of Polynomials
176(28)
7.1 Polynomials in Engineering and Science
176(3)
7.2 Computing with Polynomials
179(3)
7.3 Conventional Methods
182(1)
7.4 Muller's Method
183(4)
7.5 Bairstow's Method
187(5)
7.6 Other Methods
192(1)
7.7 Root Location with Software Packages
192(12)
Problems
202(2)
Chapter 8 Case Studies: Roots of Equations
204(27)
8.1 Ideal and Nonideal Gas Laws (Chemical/Bio Engineering)
204(3)
8.2 Greenhouse Gases and Rainwater (Civil/Environmental Engineering)
207(2)
8.3 Design of an Electric Circuit (Electrical Engineering)
209(3)
8.4 Pipe Friction (Mechanical/Aerospace Engineering)
212(14)
Problems
215(11)
Epilogue: Part Two
226(1)
Pt2.4 Trade-Offs
226(1)
Pt2.5 Important Relationships And Formulas
227(1)
Pt2.6 Advanced Methods And Additional References
227(4)
PART THREE LINEAR ALGEBRAIC EQUATIONS
231(114)
Pt3.1 Motivation
231(2)
Pt3.2 Mathematical Background
233(8)
Pt3.3 Orientation
241(4)
Chapter 9 Gauss Elimination
245(33)
9.1 Solving Small Numbers of Equations
245(7)
9.2 Naive Gauss Elimination
252(6)
9.3 Pitfalls of Elimination Methods
258(6)
9.4 Techniques for Improving Solutions
264(7)
9.5 Complex Systems
271(1)
9.6 Nonlinear Systems of Equations
271(2)
9.7 Gauss-Jordan
273(2)
9.8 Summary
275(3)
Problems
275(3)
Chapter 10 LU Decomposition and Matrix Inversion
278(22)
10.1 LU Decomposition
278(9)
10.2 The Matrix Inverse
287(4)
10.3 Error Analysis and System Condition
291(9)
Problems
297(3)
Chapter 11 Special Matrices and Gauss-Seidel
300(19)
11.1 Special Matrices
300(4)
11.2 Gauss-Seidel
304(7)
11.3 Linear Algebraic Equations with Software Packages
311(8)
Problems
316(3)
Chapter 12 Case Studies: Linear Algebraic Equations
319(26)
12.1 Steady-State Analysis of a System of Reactors (Chemical/Bio Engineering)
319(3)
12.2 Analysis of a Statically Determinate Truss (Civil/Environmental Engineering)
322(4)
12.3 Currents and Voltages in Resistor Circuits (Electrical Engineering)
326(2)
12.4 Spring-Mass Systems (Mechanical/Aerospace Engineering)
328(13)
Problems
331(10)
Epilogue: Part Three
341(1)
Pt3.4 Trade-Offs
341(1)
Pt3.5 Important Relationships and Formulas
342(1)
Pt3.6 Advanced Methods and Additional References
342(3)
PART FOUR OPTIMIZATION
345(96)
Pt4.1 Motivation
345(5)
Pt4.2 Mathematical Background
350(1)
Pt4.3 Orientation
351(4)
Chapter 13 One-Dimensional Unconstrained Optimization
355(15)
13.1 Golden-Section Search
356(7)
13.2 Parabolic Interpolation
363(2)
13.3 Newton's Method
365(1)
13.4 Brent's Method
366(4)
Problems
368(2)
Chapter 14 Multidimensional Unconstrained Optimization
370(20)
14.1 Direct Methods
371(4)
14.2 Gradient Methods
375(15)
Problems
388(2)
Chapter 15 Constrained Optimization
390(26)
15.1 Linear Programming
390(11)
15.2 Nonlinear Constrained Optimization
401(1)
15.3 Optimization with Software Packages
402(14)
Problems
413(3)
Chapter 16 Case Studies: Optimization
416(25)
16.1 Least-Cost Design of a Tank (Chemical/Bio Engineering)
416(5)
16.2 Least-Cost Treatment of Wastewater (Civil/Environmental Engineering)
421(4)
16.3 Maximum Power Transfer for a Circuit (Electrical Engineering)
425(4)
16.4 Equilibrium and Minimum Potential Energy (Mechanical/Aerospace Engineering)
429(9)
Problems
431(7)
Epilogue: Part Four
438(1)
Pt4.4 Trade-Offs
438(1)
Pt4.5 Additional References
439(2)
PART FIVE CURVE FITTING
441(146)
Pt5.1 Motivation
441(2)
Pt5.2 Mathematical Background
443(9)
Pt5.3 Orientation
452(4)
Chapter 17 Least-Squares Regression
456(34)
17.1 Linear Regression
456(16)
17.2 Polynomial Regression
472(4)
17.3 Multiple Linear Regression
476(3)
17.4 General Linear Least Squares
479(4)
17.5 Nonlinear Regression
483(7)
Problems
487(3)
Chapter 18 Interpolation
490(36)
18.1 Newton's Divided-Difference Interpolating Polynomials
491(11)
18.2 Lagrange Interpolating Polynomials
502(5)
18.3 Coefficients of an Interpolating Polynomial
507(1)
18.4 Inverse Interpolation
507(1)
18.5 Additional Comments
508(3)
18.6 Spline Interpolation
511(10)
18.7 Multidimensional Interpolation
521(5)
Problems
524(2)
Chapter 19 Fourier Approximation
526(37)
19.1 Curve Fitting with Sinusoidal Functions
527(6)
19.2 Continuous Fourier Series
533(3)
19.3 Frequency and Time Domains
536(4)
19.4 Fourier Integral and Transform
540(2)
19.5 Discrete Fourier Transform (DFT)
542(2)
19.6 Fast Fourier Transform (FFT)
544(7)
19.7 The Power Spectrum
551(1)
19.8 Curve Fitting with Software Packages
552(11)
Problems
561(2)
Chapter 20 Case Studies: Curve Fitting
563(24)
20.1 Linear Regression and Population Models (Chemical/Bio Engineering)
563(4)
20.2 Use of Splines to Estimate Heat Transfer (Civil/Environmental Engineering)
567(2)
20.3 Fourier Analysis (Electrical Engineering)
569(1)
20.4 Analysis of Experimental Data (Mechanical/Aerospace Engineering)
570(12)
Problems
572(10)
Epilogue: Part Five
582(1)
Pt5.4 Trade-Offs
582(1)
Pt5.5 Important Relationships and Formulas
583(1)
Pt5.6 Advanced Methods and Additional References
584(3)
PART SIX NUMERICAL DIFFERENTATION AND INTEGRATION
587(112)
Pt6.1 Motivation
587(10)
Pt6.2 Mathematical Background
597(2)
Pt6.3 Orientation
599(4)
Chapter 21 Newton-Cotes Integration Formulas
603(30)
21.1 The Trapezoidal Rule
605(10)
21.2 Simpson's Rules
615(9)
21.3 Integration with Unequal Segments
624(3)
21.4 Open Integration Formulas
627(1)
21.5 Multiple Integrals
627(6)
Problems
629(4)
Chapter 22 Integration of Equations
633(22)
22.1 Newton-Cotes Algorithms for Equations
633(1)
22.2 Romberg Integration
634(6)
22.3 Adaptive Quadrature
640(2)
22.4 Gauss Quadrature
642(8)
22.5 Improper Integrals
650(5)
Problems
653(2)
Chapter 23 Numerical Differentiation
655(18)
23.1 High-Accuracy Differentiation Formulas
655(3)
23.2 Richardson Extrapolation
658(2)
23.3 Derivatives of Unequally Spaced Data
660(1)
23.4 Derivatives and Integrals for Data with Errors
661(1)
23.5 Partial Derivatives
662(1)
23.6 Numerical Integration/Differentiation with Software Packages
663(10)
Problems
670(3)
Chapter 24 Case Studies: Numerical Integration and Differentiation
673(26)
24.1 Integration to Determine the Total Quantity of Heat (Chemical/Bio Engineering)
673(2)
24.2 Effective Force on the Mast of a Racing Sailboat (Civil/Environmental Engineering)
675(2)
24.3 Root-Mean-Square Current by Numerical Integration (Electrical Engineering)
677(3)
24.4 Numerical Integration to Compute Work (Mechanical/Aerospace Engineering)
680(14)
Problems
684(10)
Epilogue: Part Six
694(1)
Pt6.4 Trade-Offs
694(1)
Pt6.5 Important Relationships and Formulas
695(1)
Pt6.6 Advanced Methods and Additional References
695(4)
PART SEVEN ORDINARY DIFFERENTIAL EQUATIONS
699(146)
Pt7.1 Motivation
699(4)
Pt7.2 Mathematical Background
703(2)
Pt7.3 Orientation
705(4)
Chapter 25 Runge-Kutta Methods
709(46)
25.1 Euler's Method
710(11)
25.2 Improvements of Euler's Method
721(8)
25.3 Runge-Kutta Methods
729(10)
25.4 Systems of Equations
739(5)
25.5 Adaptive Runge-Kutta Methods
744(11)
Problems
752(3)
Chapter 26 Stiffness and Multistep Methods
755(26)
26.1 Stiffness
755(4)
26.2 Multistep Methods
759(22)
Problems
779(2)
Chapter 27 Boundary-Value and Eigenvalue Problems
781(30)
27.1 General Methods for Boundary-Value Problems
782(7)
27.2 Eigenvalue Problems
789(12)
27.3 Odes and Eigenvalues with Software Packages
801(10)
Problems
808(3)
Chapter 28 Case Studies: Ordinary Differential Equations
811(34)
28.1 Using ODEs to Analyze the Transient Response of a Reactor (Chemical/Bio Engineering)
811(7)
28.2 Predator-Prey Models and Chaos (Civil/Environmental Engineering)
818(4)
28.3 Simulating Transient Current for an Electric Circuit (Electrical Engineering)
822(5)
28.4 The Swinging Pendulum (Mechanical/Aerospace Engineering)
827(14)
Problems
831(10)
Epilogue: Part Seven
841(1)
Pt7.4 Trade-Offs
841(1)
Pt7.5 Important Relationships and Formulas
842(1)
Pt7.6 Advanced Methods and Additional References
842(3)
PART EIGHT PARTIAL DIFFERENTIAL EQUATIONS
845(88)
Pt8.1 Motivation
845(3)
Pt8.2 Orientation
848(4)
Chapter 29 Finite Difference: Elliptic Equations
852(21)
29.1 The Laplace Equation
852(2)
29.2 Solution Technique
854(6)
29.3 Boundary Conditions
860(6)
29.4 The Control-Volume Approach
866(3)
29.5 Software to Solve Elliptic Equations
869(4)
Problems
870(3)
Chapter 30 Finite Difference: Parabolic Equations
873(17)
30.1 The Heat-Conduction Equation
873(1)
30.2 Explicit Methods
874(4)
30.3 A Simple Implicit Method
878(4)
30.4 The Crank-Nicolson Method
882(3)
30.5 Parabolic Equations in Two Spatial Dimensions
885(5)
Problems
888(2)
Chapter 31 Finite-Element Method
890(25)
31.1 The General Approach
891(4)
31.2 Finite-Element Application in One Dimension
895(9)
31.3 Two-Dimensional Problems
904(4)
31.4 Solving PDEs with Software Packages
908(7)
Problems
912(3)
Chapter 32 Case Studies: Partial Differential Equations
915(18)
32.1 One-Dimensional Mass Balance of a Reactor (Chemical/Bio Engineering)
915(4)
32.2 Deflections of a Plate (Civil/Environmental Engineering)
919(2)
32.3 Two-Dimensional Electrostatic Field Problems (Electrical Engineering)
921(3)
32.4 Finite-Element Solution of a Series of Springs (Mechanical/Aerospace Engineering)
924(7)
Problems
928(3)
Epilogue: Part Eight
931(1)
Pt8.3 Trade-Offs
931(1)
Pt8.4 Important Relationships And Formulas
931(1)
Pt8.5 Advanced Methods And Additional References
932(1)
Appendix A The Fourier Series 933(2)
Appendix B Getting Started With Matlab 935(8)
Appendix C Getting Started With Mathcad 943(11)
Bibliography 954(3)
Index 957
Steve Chapra is the Emeritus Professor and Emeritus Berger Chair in the Civil and Environmental Engineering Department at Tufts University. His other books include Surface Water-Quality Modeling, Numerical Methods for Engineers, and Applied Numerical Methods with Python. Dr. Chapra received engineering degrees from Manhattan College and the University of Michigan. Before joining Tufts, he worked for the U.S. Environmental Protection Agency and the National Oceanic and Atmospheric Administration, and taught at Texas A&M University, the University of Colorado, and Imperial College London. His general research interests focus on surface water-quality modeling and advanced computer applications in environmental engineering. He is a Fellow and Life Member of the American Society of Civil Engineering (ASCE) and has received many awards for his scholarly and academic contributions, including the Rudolph Hering Medal (ASCE) for his research, and the Meriam-Wiley Distinguished Author Award (American Society for Engineering Education). He has also been recognized as an outstanding teacher and advisor among the engineering faculties at Texas A&M University, the University of Colorado, and Tufts University. As a strong proponent of continuing education, he has also taught over 90 workshops for professionals on numerical methods, computer programming, and environmental modeling.Beyond his professional interests, he enjoys art, music (especially classical music, jazz, and bluegrass), and reading history. Despite unfounded rumors to the contrary, he never has, and never will, voluntarily bungee jump or sky dive.