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دانلود کتاب Multi-Objective Optimization in Chemical Engineering: Developments and Applications

دانلود کتاب بهینه سازی چند هدفه در مهندسی شیمی: تحولات و کاربردها

Multi-Objective Optimization in Chemical Engineering: Developments and Applications

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Multi-Objective Optimization in Chemical Engineering: Developments and Applications

دسته بندی: علم شیمی
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تعداد صفحات: 515 
زبان: English 
فرمت فایل : PDF (درصورت درخواست کاربر به PDF، EPUB یا AZW3 تبدیل می شود) 
حجم فایل: 6 مگابایت 

قیمت کتاب (تومان) : 29,000



کلمات کلیدی مربوط به کتاب بهینه سازی چند هدفه در مهندسی شیمی: تحولات و کاربردها: شیمی و صنایع شیمیایی، روش های ریاضی و مدل سازی در شیمی



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توضیحاتی درمورد کتاب به خارجی

Wiley; 1 edition (May 28, 2013). — 528 p
For reasons both financial and environmental, there is a perpetual need to optimize the design and operating conditions of industrial process systems in order to improve their performance, energy efficiency, profitability, safety and reliability. However, with most chemical engineering application problems having many variables with complex inter-relationships, meeting these optimization objectives can be challenging. This is where Multi-Objective Optimization (MOO) is useful to find the optimal trade-offs among two or more conflicting objectives
This book provides an overview of the recent developments and applications of MOO for modeling, design and operation of chemical, petrochemical, pharmaceutical, energy and related processes. It then covers important theoretical and computational developments as well as specific applications such as metabolic reaction networks, chromatographic systems, CO2 emissions targeting for petroleum refining units, ecodesign of chemical processes, ethanol purification and cumene process design
Multi-Objective Optimization in Chemical Engineering: Developments and Applications is an invaluable resource for researchers and graduate students in chemical engineering as well as industrial practitioners and engineers involved in process design, modeling and optimization
Table of Contents
Preface
Overview
Introduction
Adrian Bonilla-Petriciolet and Gade Pandu Rangaiah
Optimization and Chemical Engineering
Basic Definitions and Concepts of Multi-Objective Optimization
Multi-Objective Optimization in Chemical Engineering
Scope and Organization of the Book
Optimization of Pooling Problems for Two Objectives Using the ε-Constraint Method
Haibo Zhang and Gade Pandu Rangaiah
Introduction
Pooling Problem Description and Formulations
ε-Constraint Method and IDE Algorithm
Application to Pooling Problems
Results and Discussion
Conclusions
Multi-objective Optimization Applications in Chemical Engineering
Shivom Sharma and Gade Pandu Rangaiah
Introduction
Multi-Objective Optimization Applications in Process Design and Operation
Multi-Objective Optimization Applications in Petroleum Refining, Petrochemicals, and Polymerization
Multi-Objective Optimization Applications in the Food Industry, Biotechnology, and Pharmaceuticals
Multi-Objective Optimization Applications in Power Generation and Carbon Dioxide Emissions
Multi-Objective Optimization Applications in Renewable Energy
MOO Applications in Hydrogen Production and Fuel Cells
Conclusions
II Multi-Objective Optimization Developments
Performance Comparison of Jumping-Gene Adaptations of the Elitist Nondominated Sorting Genetic Algorithm
Shivom Sharma, Seyed Reza Nabavi and Gade Pandu Rangaiah
Introduction
Jumping-Gene Adaptations
Termination Criterion
Constraints Handling and Implementation of Programs
Performance Comparison
Conclusions
Improved Constraint Handling Technique for Multi-objective Optimization with Application to Two Fermentation Processes
Shivom Sharma and Gade Pandu Rangaiah
Introduction
Constraint Handling Approaches in Chemical Engineering
Adaptive Constraint Relaxation and Feasibility Approach for SOO
Adaptive Relaxation of Constraints and Feasibility Approach for MOO
Testing of MODE-ACRFA
Multi-Objective Optimization of the Fermentation Process
Conclusions
Robust Multi-Objective Genetic Algorithm (RMOGA) with Online Approximation under Interval Uncertainty
Weiwei Hu, Adeel Butt, Ali Almansoori, Shapour Azarm and Ali Elkamel
Introduction
Background and Definition
Robust Multi-Objective Genetic Algorithm (RMOGA)
Online Approximation-Assisted RMOGA
Case Studies
Conclusion
Chance Constrained Programming to Handle Uncertainty in Nonlinear Process Models
Kishalay Mitra
Introduction
Uncertainty Handling Techniques
Chance-Constrained Programming: Fundamentals
Industrial Case Study: Grinding
Conclusion
Fuzzy Multi-objective Optimization for Metabolic Reaction Networks by Mixed-Integer Hybrid Differential Evolution
Feng-Sheng Wang and Wu-Hsiung Wu
Introduction
Problem Formulation
Optimality
Mixed-Integer Hybrid Differential Evolution
Examples
Summary
III Chemical Engineering Applications
Parameter Estimation in Phase Equilibria Calculations using Multi-Objective Evolutionary Algorithms
Sameer Punnapala, Francisco M. Vargas and Ali Elkamel
Introduction
icle Swarm Optimization (PSO)
Parameter Estimation in Phase Equilibria Calculations
Model Description
Multi-Objective Optimization Results and Discussions
Conclusions
Phase Equilibrium Data Reconciliation using Multi-Objective Differential Evolution with Tabu List
A. Bonilla-Petriciolet, Shivom Sharma and Gade Pandu Rangaiah
Introduction
Formulation of the Data-Reconciliation Problem for Phase Equilibrium Modeling
Multi-Objective Optimization using Differential Evolution with Tabu List
Data Reconciliation of Vapor-Liquid Equilibrium by MOO
Conclusions
CO2 Emissions Targeting for Petroleum Refinery Optimization
Mohmmad A. Al-Mayyahi, Andrew F.A. Hoadley and Gade Pandu Rangaiah
Introduction
MOO-Pinch Analysis Framework to Target CO2 Emissions
Case Studies
Case Studies
Conclusions
Ecodesign of Chemical Processes with Multi-Objective Genetic Algorithms
Catherine Azzaro-Pantel and Luc Pibouleau
Introduction
Numerical Tools
Williams–Otto Process (WOP) Optimization for Multiple Economic and Environmental Objectives
Revisiting the HDA Process
Conclusions and Perspectives
Modeling and Multi-objective Optimization of a Chromatographic System
Abhijit Tarafder
Introduction
Chromatography—Some Facts
Modeling Chromatographic Systems
Solving the Model Equations
Steps for Model Characterization
Description of the Optimization Routine—NSGA-II
Optimization of a Binary Separation in Chromatography
An Example Study
Conclusion
Estimation of Crystal Size Distribution: Image Thresholding based on Multi-Objective Optimization
Karthik Raja Periasamy and S. Lakshminarayanan
Introduction
Methodology
Image Simulation
Image Preprocessing
Image Segmentation
Feature Extraction
Future Work
Conclusions
Multi-Objective Optimization of a Hybrid Steam Stripper-Membrane Process for Continuous Bioethanol Purification
Krishna Gudena, Gade Pandu Rangaiah and S Lakshminarayanan
Introduction
Description and Design of a Hybrid Stripper-Membrane System
Mathematical Formulation and Optimization
Results and Discussion
Conclusions
Exercises
Process Design for Economic, Environmental and Safety Objectives with an Application to the Cumene Process
Shivom Sharma, Zi Chao Lim and Gade Pandu Rangaiah
Introduction
Review and Calculation of Safety Indices
Cumene Process, its Simulation and Costing
I2SI Calculation for Cumene Process
Optimization using EMOO Program
Optimization for Two Objectives
Optimization for EES Objectives
Conclusions
New PI Controller Tuning Methods Using Multi-Objective Optimization
Allan Vandervoort, Jules Thibault and Yash Gupta
Introduction
PI Controller Model
Optimization Problem
Pareto Domain
Optimization Results
Controller Tuning
Application of the Tuning Methods
Conclusions
Index




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