Introduction to Process Systems Engineering: Basic Principles and Calculations with MATLAB and Python comprehensively approaches how to master core chemical engineering concepts through computational methods. The book bridges the gap between theory and practice by integrating numerical computations from the outset, enabling students and professionals to develop practical skills alongside foundational knowledge. Covering essential topics such as mass and energy balances, property calculations, vapor-liquid equilibria, and process optimization, the book emphasizes realistic problem-solving using accessible MATLAB and Python programs. Each chapter features real-world examples, progressively increasing in complexity to build confidence and competence.
The material is tailored to current chemical engineering practice, making it an invaluable resource for students, researchers, and industry practitioners seeking to enhance their computational and analytical capabilities in process systems engineering. This book empowers readers to learn by doing, fostering a deeper understanding of both theoretical principles and their practical applications.
1. 1. Introduction to chemical and process systems engineering - p. 1 2. 2. Introduction and basic definitions - p. 17 3. 2.1 Measurements in science and the systems of units - p. 17 4. 2.2 Systems of units - p. 17 5. 2.3 Uncertainty in measurements and uncertainty propagation - p. 17 6. 2.4 Significant figures - p. 17 7. 2.5 Organizing multiple experimental measurements - p. 17 8. 2.6 Dimensional homogeneity - p. 17 9. 2.7 Important process variables - p. 17 10. 2.8 Energy, work, and heat - p. 17 11. 2.9 System definition, processes and the ideal gas law - p. 17 12. 2.10 MATLAB and Python - p. 17 13. Chapter summary - p. 17 14. Problems - p. 17 15. 3. General balance equations - p. 115 16. 3.1 The general balance equation - p. 115 17. 3.2 Total mass balance - p. 126 18. 3.3 Analytic solution of first order differential equations - p. 135 19. 3.4 Numerical solution of first order differential equations - p. 140 20. 3.5 MATLAB and Python for solving ordinary differential equations - p. 144 21. Chapter summary - p. 153 22. Problems - p. 154 23. 4. Component mass and mole balances - p. 165 24. 4.1 Review of the general balance equation - p. 165 25. 4.2 The component mass and mole balance equations - p. 166 26. 4.3 The component balance equations without chemical reactions - p. 167 27. 4.4 The component balance equations with chemical reactions - p. 181 28. 4.5 MATLAB and Python for solving systems of ordinary differential equations - p. 191 29. Chapter summary - p. 201 30. Problems - p. 203 31. 5. Energy balance equation - p. 215 32. 5.1 The general energy balance equation - p. 215 33. 5.2 The energy balance equation for process systems - p. 215 34. 5.3 Enthalpy of pure compounds - p. 217 35. 5.4 Enthalpy of reaction - p. 238 36. 5.5 Solution of nonlinear algebraic equations - p. 243 37. 5.6 Adiabatic flame temperature - p. 250 38. 5.7 MATLAB and Python for solving nonlinear algebraic equations - p. 256 39. Chapter summary - p. 260 40. Problems - p. 261 41. 6. Mass balances at steady state - p. 277 42. 6.1 Introduction - p. 277 43. 6.2 Steady state mass balances without chemical reactions - p. 280 44. 6.3 Steady state mass balances without chemical reactions in multiple-unit processes - p. 302 45. 6.4 Steady state mass balances with chemical reactions - p. 313 46. 6.5 Purge streams - p. 321 47. Chapter summary - p. 331 48. Problems - p. 331 49. 7. Properties of single component systems - p. 341 50. 7.1 Introduction - p. 341 51. 7.2 Phase diagram of CO2 - p. 343 52. 7.3 The van der Waals equation of state - p. 347 53. 7.4 The Peng-Robinson equation of state - p. 371 54. 7.5 Predicting properties of pure components using group contribution methods - p. 379 55. 7.6 An advanced application: Filling an hydrogen Tank1 - p. 385 56. Chapter summary - p. 394 57. Problems - p. 395 58. 8. Vapor-liquid equilibrium calculations - p. 405 59. 8.1 Introduction - p. 405 60. 8.2 The Gibbs phase rule - p. 406 61. 8.3 Txy diagrams for ideal binary mixtures - p. 407 62. 8.4 Raoult’s law for VLE of ideal solutions - p. 411 63. 8.5 BUBBLE- and DEW-point calculations using Raoult’s law - p. 413 64. 8.6 Flash calculations using Raoult’s law - p. 426 65. 8.7 The modified Raoult’s law for nonideal liquid phase - p. 434 66. Chapter summary - p. 451 67. Problems - p. 451 68. 9. Process flowsheeting - p. 457 69. 10. Graphical design techniques - p. 493 70. 10.1 Introduction - p. 493 71. 10.2 Graphical design of ideal reactors - p. 494 72. 10.3 Graphical design of equilibrium-stage separation operations - p. 506 73. Summary - p. 526 74. Problems - p. 527 75. 11. Psychrometry - p. 537 76. 12. Process optimization - p. 573 77. 12.1 Introduction - p. 573 78. 12.2 A motivating example - p. 574 79. 12.3 Optimality conditions for unconstrained problems - p. 583 80. 12.4 Optimality conditions for equality-constrained problems - p. 596 81. 12.5 Parameter estimation using least squares - p. 606 82. Summary - p. 618 83. Problems - p. 618 84. 13. Dimensional analysis and scale-up - p. 627 85. 13.1 Introduction - p. 627 86. 13.2 Nondimensionalization of equations - p. 629 87. 13.3 Dimensional similarity and the Buckingham π theorem - p. 636 88. 13.3.1 Similarity - p. 636 89. 13.3.2 The Buckingham π theorem - p. 638 90. 13.3.3 Two interesting applications of the Buckingham π theorem - p. 651 91. 13.4 Process scale-up - p. 660 92. 13.4.1 The 50 Foot Woman—A challenging scale-up problem - p. 660 93. 13.4.2 The power requirements for mixing nonaerated fluids - p. 663 94. 13.4.3 Scale up of agitated, baffled, and jacketed tanks - p. 668 95. Chapter summary - p. 675 96. Problems - p. 675 97. Index - p. 681
Introduction to Process Systems Engineering: Basic Principles and Calculations with MATLAB and Python comprehensively approaches how to master core chemical engineering concepts through computational methods. The book bridges the gap between theory and practice by integrating numerical computations from the outset, enabling students and professionals to develop practical skills alongside foundational knowledge. Covering essential topics such as mass and energy balances, property calculations, vapor-liquid equilibria, and process optimization, the book emphasizes realistic problem-solving using accessible MATLAB and Python programs. Each chapter features real-world examples, progressively increasing in complexity to build confidence and competence.
The material is tailored to current chemical engineering practice, making it an invaluable resource for students, researchers, and industry practitioners seeking to enhance their computational and analytical capabilities in process systems engineering. This book empowers readers to learn by doing, fostering a deeper understanding of both theoretical principles and their practical applications.
1. 1. Introduction to chemical and process systems engineering - p. 1 2. 2. Introduction and basic definitions - p. 17 3. 2.1 Measurements in science and the systems of units - p. 17 4. 2.2 Systems of units - p. 17 5. 2.3 Uncertainty in measurements and uncertainty propagation - p. 17 6. 2.4 Significant figures - p. 17 7. 2.5 Organizing multiple experimental measurements - p. 17 8. 2.6 Dimensional homogeneity - p. 17 9. 2.7 Important process variables - p. 17 10. 2.8 Energy, work, and heat - p. 17 11. 2.9 System definition, processes and the ideal gas law - p. 17 12. 2.10 MATLAB and Python - p. 17 13. Chapter summary - p. 17 14. Problems - p. 17 15. 3. General balance equations - p. 115 16. 3.1 The general balance equation - p. 115 17. 3.2 Total mass balance - p. 126 18. 3.3 Analytic solution of first order differential equations - p. 135 19. 3.4 Numerical solution of first order differential equations - p. 140 20. 3.5 MATLAB and Python for solving ordinary differential equations - p. 144 21. Chapter summary - p. 153 22. Problems - p. 154 23. 4. Component mass and mole balances - p. 165 24. 4.1 Review of the general balance equation - p. 165 25. 4.2 The component mass and mole balance equations - p. 166 26. 4.3 The component balance equations without chemical reactions - p. 167 27. 4.4 The component balance equations with chemical reactions - p. 181 28. 4.5 MATLAB and Python for solving systems of ordinary differential equations - p. 191 29. Chapter summary - p. 201 30. Problems - p. 203 31. 5. Energy balance equation - p. 215 32. 5.1 The general energy balance equation - p. 215 33. 5.2 The energy balance equation for process systems - p. 215 34. 5.3 Enthalpy of pure compounds - p. 217 35. 5.4 Enthalpy of reaction - p. 238 36. 5.5 Solution of nonlinear algebraic equations - p. 243 37. 5.6 Adiabatic flame temperature - p. 250 38. 5.7 MATLAB and Python for solving nonlinear algebraic equations - p. 256 39. Chapter summary - p. 260 40. Problems - p. 261 41. 6. Mass balances at steady state - p. 277 42. 6.1 Introduction - p. 277 43. 6.2 Steady state mass balances without chemical reactions - p. 280 44. 6.3 Steady state mass balances without chemical reactions in multiple-unit processes - p. 302 45. 6.4 Steady state mass balances with chemical reactions - p. 313 46. 6.5 Purge streams - p. 321 47. Chapter summary - p. 331 48. Problems - p. 331 49. 7. Properties of single component systems - p. 341 50. 7.1 Introduction - p. 341 51. 7.2 Phase diagram of CO2 - p. 343 52. 7.3 The van der Waals equation of state - p. 347 53. 7.4 The Peng-Robinson equation of state - p. 371 54. 7.5 Predicting properties of pure components using group contribution methods - p. 379 55. 7.6 An advanced application: Filling an hydrogen Tank1 - p. 385 56. Chapter summary - p. 394 57. Problems - p. 395 58. 8. Vapor-liquid equilibrium calculations - p. 405 59. 8.1 Introduction - p. 405 60. 8.2 The Gibbs phase rule - p. 406 61. 8.3 Txy diagrams for ideal binary mixtures - p. 407 62. 8.4 Raoult’s law for VLE of ideal solutions - p. 411 63. 8.5 BUBBLE- and DEW-point calculations using Raoult’s law - p. 413 64. 8.6 Flash calculations using Raoult’s law - p. 426 65. 8.7 The modified Raoult’s law for nonideal liquid phase - p. 434 66. Chapter summary - p. 451 67. Problems - p. 451 68. 9. Process flowsheeting - p. 457 69. 10. Graphical design techniques - p. 493 70. 10.1 Introduction - p. 493 71. 10.2 Graphical design of ideal reactors - p. 494 72. 10.3 Graphical design of equilibrium-stage separation operations - p. 506 73. Summary - p. 526 74. Problems - p. 527 75. 11. Psychrometry - p. 537 76. 12. Process optimization - p. 573 77. 12.1 Introduction - p. 573 78. 12.2 A motivating example - p. 574 79. 12.3 Optimality conditions for unconstrained problems - p. 583 80. 12.4 Optimality conditions for equality-constrained problems - p. 596 81. 12.5 Parameter estimation using least squares - p. 606 82. Summary - p. 618 83. Problems - p. 618 84. 13. Dimensional analysis and scale-up - p. 627 85. 13.1 Introduction - p. 627 86. 13.2 Nondimensionalization of equations - p. 629 87. 13.3 Dimensional similarity and the Buckingham π theorem - p. 636 88. 13.3.1 Similarity - p. 636 89. 13.3.2 The Buckingham π theorem - p. 638 90. 13.3.3 Two interesting applications of the Buckingham π theorem - p. 651 91. 13.4 Process scale-up - p. 660 92. 13.4.1 The 50 Foot Woman—A challenging scale-up problem - p. 660 93. 13.4.2 The power requirements for mixing nonaerated fluids - p. 663 94. 13.4.3 Scale up of agitated, baffled, and jacketed tanks - p. 668 95. Chapter summary - p. 675 96. Problems - p. 675 97. Index - p. 681
