Libros de Ing. Quim. Recursos para Ingenieria Quimica.

Optimization of chemical processes 2nd ed. – David M. Himmelblau

Publicado: 2010-04-28 14:04:09

Optimization of chemical processes 2nd ed.
Thomas F. Edgar, David M. Himmelblau, Leon S. Lasdon.

                                                                    

 »DOWNLOAD THIS BOOK / DESCARGAR LIBRO AQUI ---- (RAPIDSHARE)

 

                                                                    

 »DOWNLOAD THIS BOOK / DESCARGAR LIBRO AQUI ---- (MEGAUPLOAD)

 

PART I Problem Formulation
1 The Nature and Organization of Optimization Problems
1.1 What Optimization Is All About
l.2 Why Optimize?
1.3 Scope and Hierarchy of Optimization
1.4 Examples of Applications of Optimization
1.5 The Essential Features of Optimization Problems
1.6 General Procedure for Solving Optimization Problems
1.7 Obstacles to Optimization

2 Developing Models for Optimization
2.1 Classification of Models
2.2 How to Build a Model
2.3 Selecting Functions to Fit Empirical Data
2.3.1 How to Determine the Form of a Model / 2.3.2 Fitting Models by Least Squares
2.4 Factorial Experimental Designs
2.5 Degrees of Freedom
2.6 Examples of Inequality and Equality Constraints in Models

3 Formulation of the Objective Function
3.1 Economic Objective Functions
3.2 The Time Value of Money in Objective Functions
3.3 Measures of Profitability

Part II Optimization Theory and Methods
4 Basic Concepts of Optimization
4.1 Continuity of Functions
4.2 NLP Problem Statement
4.3 Convexity and Its Applications
4.4 Interpretation of the Objective Function in Terms of its Quadratic Approximation
4.5 Necessary and Sufficient Conditions for an Extremum of an Unconstrained Function

5 Optimization of Unconstrained Functions: One-Dimensional Search
5.1 Numerical Methods for Optimizing a Function of One Variable
5.2 Scanning and Bracketing Procedures
5.3 Newton and Quasi-Newton Methods of Unidimensional Search
5.3.1 Newton's Method / 5.3.2 Finite Difference approximations to Derivatives / 5.3.3 Quasi-Newton Method
5.4 Polynomial Approximation Methods
5.4.1 Quadratic Interpolation / 5.4.2 Cubic Interpolation
5.5 How One-Dimensional Search Is Applied in a Multidimensional Problem
5.6 Evaluation of Unidimensional Search Methods

6 Unconstrained Multivariable Optimization
6.1 Methods Using Function Values Only
6.1.1 Random Search / 6.1.2 Grid Search / 6.1.3 Univariate Search / 6.1.4 Simplex Search Method / 6.1.5 Conjugate Search Directions
6.2 Methods That Use First Derivatives
6.2.1 Steepest Descent / 6.2.2 Conjugate gradient methods
6.3 Newton's Method
6.3.1 Forcing the Hessian Matrix to Be Positive-Definite / 6.3.2 Movement in the Search Direction / 6.3.3 Termination / 6.3.4 Safeguarded Newton's Method / 6.3.5 Computation of Derivatives
6.4 Quasi-Newton Methods

7 Linear Programming (LP) and Applications
7.1 Geometry of Linear Programs
7.2 Basic Linear Programming Definitions and Results
7.3 Simplex Algorithm
7.4 Barrier Methods
7.5 Sensitivity Analysis
7.6 Linear Mixed Integer Programs
7.7 LP Software
7.8 A Transportation Problem Using the EXCEL Solver Spreadsheet Formulation
7.9 Network Flow and Assignment Problems

8 Nonlinear Programming with Constraints
8.1 Direct Substitution
8.2 First-Order Necessary Conditions for a Local Extremum
8.2.1 Problems Containing Only Equality Constraints / 8.2.2 Problems Containing Only Inequality Constraints / 8.2.3 Problems Containing both Equality and Inequality Constraints
8.3 Quadratic Programming
8.4 Penalty, Barrier, and Augmented Lagrangian Methods
8.5 Successive Linear Programming
8.5.1 Penalty Successive Linear Programming
8.6 Successive Quadratic Programming
8.7  The Generalized Reduced Gradient Method
8.8 Relative Advantages and Disadvantages of NLP Methods
8.9 Available NLP Software
8.9.1 Optimizers for Stand-Alone Operation or Embedded Applications / 8.9.2 Spreadsheet Optimizers / 8.9.3 Algebraic Modeling Systems
8.10 Using NLP Software
8.10.1 Evaluation of Derivatives: Issues and Problems / 8.10.2 What to Do When an NLP Algorithm Is Not "Working"

9 Mixed-Integer Programming
9.1 Problem Formulation
9.2 Branch-and-Bound Methods Using LP Relaxations
9.3 Solving MINLP Problems Using Branch-and-Bound Methods
9.4 Solving MINLPs Using Outer Approximation
9.5 Other Decomposition Approaches for MINLP
9.6 Disjunctive Programming

10 Global Optimization for Problems with Continuous and Discrete Variables
10.1 Methods for Global Optimization
10.2 Smoothing Optimization Problems
10.3 Branch-and-Bound Methods
10.4 Multistart Methods
10.5 Heuristic Search Methods
10.5.1 Heuristic Search / 10.5.2 Tabu Search / 10.5.3 Simulated Annealing / 10.5.4 Genetic and Evolutionary Algorithms / 10.5.5 Using the Evolutionary Algorithm in the Premium Excel Solver / 10.5.6 Scatter Search
10.6 Other Software for Global Optimization

Part III Applications of Optimization
11 Heat Transfer and Energy Conservation
Example 11.1 Optimizing Recovery of Waste Heat
Example 11.2 Optimal Shell-and-Tube Heat Exchanger Design
Example 11.3 Optimization of a Multi-Effect Evaporator
Example 11.4 Boiler/Turbo-Generator System Optimization

12 Separation Processes
Example 12.1 Optimal Design and Operation of a Conventional Staged-Distillation Column
Example 12.2 Optimization of Flow Rates in a Liquid-Liquid Extraction Column
Example 12.3 Fitting Vapor-Liquid Equilibrium Data Via Nonlinear Regression
Example 12.4 Determination of the Optimal Reflux Ratio for a Staged-Distillation Column

13 Fluid Flow Systems
Example 13.1 Optimal Pipe Diameter
Example 13.2 Minimum Work of Compression
Example 13.3 Economic Operation of a Fixed-Bed Filter
Example 13.4 Optimal Design of a Gas Transmission Network

14 Chemical Reactor Design and Operation
Example 14.1 Optimization of a Thermal Cracker Via Linear Programming
Example 14.2 Optimal Design of an Ammonia Reactor
Example 14.3 Solution of an Alkylation Process by Sequential Quadratic Programming
Example 14.4 Predicting Protein Folding
Example 14.5 Optimization of Low-Pressure Chemical Vapor Deposition Reactor for the Deposition of Thin Films
Example 14.6 Reaction Synthesis Via MINLP

15 Optimization in Large-Scale Plant Design and Operations
15.1 Process Simulators and Optimization Codes
15.2 Optimization Using Equation-Based Process Simulators
15.3 Optimization Using Modular-Based Simulators
15.3.1 Sequential Modular Methods / 15.3.2 Simultaneous Modular Methods / 15.3.3 Calculation of Derivatives
15.4 Summary 546

16 Integrated Planning, Scheduling, and Control in the Process Industries
16.1 Plant Optimization Hierarchy
16.2 Planning and Scheduling
16.2.1 Planning / 16.2.2 Scheduling
16.3 Plantwide Management and Optimization
16.4 Unit Management and Control
16.4.1 Formulating the MPC Optimization Problem
16.5 Process Monitoring and Analysis

Appendixes
A Mathematical Summary
A.1 Definitions / A.2 Basic Matrix Operations / A.3 Linear Independence and Row Operations / A.4 Solution of Linear Equations / A.5 Eigenvalues, Eigenvectors
B Cost Estimation
B.1 Capital Costs / B.2 Operating Costs / B.3 Taking Account of Infation / B.4 Predicting Revenues in an Economic-Based Objective Function / B.5 Project Evaluation

                                                                    

 »DOWNLOAD THIS BOOK / DESCARGAR LIBRO AQUI ---- (RAPIDSHARE)

 

                                                                    

 »DOWNLOAD THIS BOOK / DESCARGAR LIBRO AQUI ---- (MEGAUPLOAD)