"Numerical Methods in Civil Engineering, primarily meant for B.Tech (Civil Engineering) students of various Indian Technical Universities as well as National Institute of Technology, has been written according to the latest syllabi of Numerical /Methods. The attention is devoted to * Newmarl's Method (Chapter 8) * Collocation and Galerkin's Method (Chapter 4) * Solution to ODEs and PD Es by Finite Difference Technique (Chapters 5A, SB) * Initial and Boundary Value Problems: Implicit and Explicit methods. The subject matter has been well explained by providing counter examples. Moreover, the illustrative examples have been solved in an explanatory and methodological way so that even an ordinary student can know the numerical techniques to solve the mathematical and computational problems independently. Students are facing a gigantic number of problems in understanding and applying the concepts and techniques of Numerical Methods. This book, no doubt, will prove as BHAHIVISTHA in the quiver of the students."
Additional Info
  • Publisher: Laxmi Publications
  • Language: English
  • ISBN : 97-893-5138-298-0
  • Chapter 1

    Chapter 0 - An Overview of Basic Concepts Price 0.41  |  0.41 Rewards Points

    Chapter 0 - An Overview of Basic Concepts

  • Chapter 2

    Chapter 1 - Roots of Algebraic Transcendental Equations Price 0.41  |  0.41 Rewards Points


    1.1. Intermediate Value Property

    1.2. Bisection Method 

    1.3. Calculation of Number of Iterations 

    1.4. Order of Convergence of Iterative Methods 

    1.5. Order of Convergence of Bisection Method

    1.6. Rate of Convergence of a Sequence 

    1.7. Theorem I: Bisection Method Always Converges 

    1.8. Iteration Method (Successive Approximation Method) 

    1.8A. Theorem II: Sufficient Condition for Convergence of Iterations 

    1.9. Order of Convergence of Iteration Method

    1.10. Solution of Simultaneous Non-linear Equations 

    1.11. Sufficient Condition for the Convergence of Iteration Method for Two Unknowns

    1.12. Procedure to Solve Simultaneous Non-linear Equations in Two Variables by Iterative Method

    1.13. Method of False Position Or Regula-Falsi Method 

    1.14. Order of Convergence of Regula-Falsi Method 

    1.15. Newton-Raphson Method or Newton’s Method 

    1.16. Sufficient Condition for the Convergence of Newton-Raphson Method 

    1.17. Order of Convergence of Newton-Raphson Method 

    1.18. Geometrical Significance of Newton-Raphson Method

    1.19. Applications of Newton-Raphson’s or Newton’s Iterative Formulae

  • Chapter 3

    Chapter 2 - Linear Equations and Eigen Values Problems Price 0.41  |  0.41 Rewards Points

    Introduction to Linear Systems 

    2.2. Solution of Simultaneous Linear Equations by Matrix Method or Matrix Inversion Method

    2.3. Elementary Operations or Transformations on a Matrix 

    2.4 Gauss-Jordan Method (Inverse of a Matrix by Elementary Operations) 

    2.5. Gauss Elimination Method (Without Pivoting) to Solve Liner Equations 

    2.6. Failure of Gauss Elimination Method

    2.7. Gauss Elimination Method (with Partial Pivoting) to Solve Linear Equations

    2.8. Gauss Elimination Method (with Complete Pivoting) to Solve Linear Equations

    2.9. Gauss-Jordan Elimination Method to Solve Linear Equations

    2.10. Numerical Solution of Linear Systems: Iterative Methods or Indirect Methods

    2.11. Jacobi’s Iterative Method or Gauss-Jacobi Iterative Method or Method of Simultaneous Displacement

    2.12. Gauss-Seidel Iterative Method or Method of Successive Displacement 

    2.13. Eigen Values and Eigen Vectors of a Matrix 

    2.14. Elementary Properties of Eigen Values and Eigen Vectors

    2.15. Rayleigh’s Power Method

  • Chapter 4

    Chapter 3 - Interpolation with Equal and Unequal Intervals Price 0.41  |  0.41 Rewards Points


    3.1. Finite Differences 

    3.2. Some Other Difference Operators 

    3.3. Relation Between Difference Operators

    3.4. Differences of a Polynomial 

    3.5. Missing Term Technique

    3.6. Factorial Notation

    3.7. Differences of [x]n 

    3.8. Reciprocal Factorial 

    3.9. Method of Separation of Symbols 

    3.10. Interpolation with Equal Intervals 

    3.11. Assumptions for Interpolation 

    3.12. Newton’s Formulae for Interpolation 

    3.13. Error in Polynomial Interpolation

    3.14. Error in Newton-Gregory Forward Interpolation Formula 

    3.15. Central Difference Interpolation Formulae 

    3.16. Interpolation with Unequal Intervals 

    3.17. Inverse Interpolation 

    3.18. Divided Differences

    3.19. Properties of Divided Differences 

    3.20. Algebra of Divided Differences 

    3.21. Relation Between Divided Differences and Forward Differences 

    3.22. Merits and Demerits of Lagrange’s Interpolation Formula 

  • Chapter 5

    Chapter 4 - Solution of Initial and Boundary Value Problems Price 0.41  |  0.41 Rewards Points


    4.1. Collocation Method 

    4.2. Galerkin’s Method of Least Squares 

    4.3. Runge-Kutta Methods 

    4.4. First order Runge-Kutta Method 

    4.5. Second Order Runge-Kutta Method 

    4.6. Third Order Runge-Kutta Method or Runge’s Method 

    4.7. Fourth Order Runge-Kutta Method

    4.8. Runge-Kutta Method for Simultaneous Initial Value Problems 

    4.9. Runge-Kutta Method for Second Order Initial Value Problem

  • Chapter 6

    Chapter 5a - Finite Difference Method for Ordinary Differential Equations Price 0.41  |  0.41 Rewards Points


    5.1A. Finite-difference Method for Ordinary Differential Equation

  • Chapter 7

    Chapter 5b - Finite Difference Method for Partial Differential Equations Price 0.41  |  0.41 Rewards Points


    5.1B. Classification of Linear Partial Differential Equation of Second Order 

    5.2B. Derive Finite Difference Approximation to Partial Derivatives 

    5.3B. Grid Lines and Grid Points

    5.4B. Solution of Laplace’s Equation by Finite Difference Method 

    5.5B. Procedure for ADI Method 

    5.6B. Solution of Poisson’s Equation by Finite Difference Method 

    5.7B. Parabolic Partial Differential Equations 

    5.8B. Explicit and Implicit Methods

    5.9B. Hyperbolic Partial Differential Equation 

    5.10B. Finite Difference Method of Solving one Dimensional Wave Equation

  • Chapter 8

    Chapter 6 - Correlation and Regression Analysis Price 0.41  |  0.41 Rewards Points

    Univariate Distributions 

    6.2. Bivariate Distributions

    6.3. Correlation

    6.4. Positive or Negative Correlation 

    6.5. Linear and Non-linear Correlation 

    6.6. Methods of Measuring Correlation

    6.7. Scatter or Dot Diagram Method

    6.8. Karl Pearson’s Coefficient of Correlation 

    6.9. Alternative Formula of Correlation Coefficient 

    6.10. Characteristics of Karl Pearson’s Coefficient of Correlation

    6.11. Degree of Karl Pearson’s Coefficient of Correlation 

    6.12. Probable Error 

    6.13. Standard Error 

    6.14. Limits of Correlation 

    6.15. Calculation of Coefficient of Correlation for a Bivariate Frequency Distribution 

    6.16. Spearman’s Rank Correlation 

    6.17. Repeated Ranks or Tied Ranks 

    6.18. Regression Analysis

    6.19. Curve of Regression and Regression Equation 

    6.20. Linear Regression 

    6.21. Lines of Regression 

    6.22. Derivation of Lines of Regression

    6.23. Regression Coefficients 

    6.24. Uses of Regression Analysis 

    6.25. Comparison of Correlation and Regression Analysis

    6.26. Properties of Regression Coefficients

    6.27. Angle Between Two Lines of Regression 

  • Chapter 9

    Chapter 7 - Fitting a Polynomial Price 0.41  |  0.41 Rewards Points


    7.1. Importance of Fitting a Polynomial 

    7.2. Method of Least Squares

    7.3. Fitting a Straight Line 

    7.4. Fitting of an Exponential Curve y = aebx 

    7.5. Fitting of the Curve y = axb 

    7.6. Fitting of the Curve y = abx 

    7.7. Fitting of the Curve pvr = k 

    7.8. Fitting of the Curve xy = b + ax

    7.9. Fitting of the Curve y = ax2 +bx

    7.10. Fitting of the Curve y = ax + bx2 

    7.11. Fitting of the Curve y = ax +bx

    7.12. Fitting of the Curve y = a +bx+cx2 

    7.13. Fitting of the Curve y =cx0 + c1 x 

    7.14. Fitting of the Curve 2x = ax2 + bx + c 

    7.15. Fitting of the Curve y = ae–k1x + be–k2x 

    7.16. Most Plausible Solution of a System of Linear Equations 

    7.17. Polynomial Fit: Non-linear Regression

  • Chapter 10

    Chapter 8 - Numerical Integration in Time Implicit and Explicit Method Price 0.41  |  0.41 Rewards Points


    8.1. Stability of Explicit Methods 

    8.2. Stability of Implicit Methods 

    8.3. Single-degree-of-Freedom (SDOF) Systems 

    8.4. Fundamental Equation of Motion for a SDOF System

    8.5. Derivation of Newmark’s Method 

    8.6. Stability of Newmark’s Method

    8.7. Newmark’s Algorithm for a SDOF System

    8.8. Numerical Integration in Time by Explicit Method

    8.9. Central Difference Method Algorithm to Find Displacement, Velocity and Acceleration of a SDOF System.

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