Unit 1 Introduction

3 lecture hours

• Definition of Modelling
• Simulation and Optimization
• importance of modelling for simulation and optimization
• comparison of design and simulation
• scope and applications of modelling

Unit 2 Modelling Aspects

4 lecture hours

• Definition of model
• process model
• deterministic and stochastic process
• physical and mathematical modelling
• classification of models
• process to build a model
• degrees of freedom analysis for model
• empirical model
• selecting functions to fit empirical data
• Black-box model

Unit 3 Mathematical Modelling of Chemical Engineering Systems

• uses of mathematical models
• scope of coverage
• principles of 3 Subject Code: 3170513 w.e.f
• AY 2018-19 formulation
• fundamental laws
• continuity equations
• energy equations
• equation of motion
• transport equation
• equation of state

Unit 4 Examples of Mathematical Models of Chemical Engineering systems

6 lecture hours

• flow tank
• mixing tank
• two heated tanks, PFR, CSTR
• series of isothermal constant- hold up CSTR
• CSTR with variable holds up, gas-phase pressurized CSTR
• non- isothermal CSTR
• single-component vaporizer
• batch reactor
• reactor with mass transfer
• ideal binary distillation column
• batch distillation with holdup
• Solvent Extraction
• gas adsorption

Unit 5 Chemical Process Plant Simulation

5 lecture hours

• Steady state vs dynamic simulation
• lumped system-partitioning equation
• tearing equation
• simultaneous equation
• modular approaches & equation solving approaches
• decomposition of networks
• partition and tearing applied to process flow sheeting
• reachability matrix
• selection of property perdition method for simulation
• Introduction to Various Professional Simulators and Equation Solver Software

Unit 6 Basic Concepts of Optimization

4 lecture hours

• Scope and hierarchy of optimization
• examples of applications of optimization
• the essential features of optimization problems
• general procedure for solving optimization problems
• obstacles to optimization
• continuity of function
• convexity and its applications
• interpretation of the objective function in terms of its quadratic approximation
• necessary and sufficient conditions for an extremum of an unconstrained function

Unit 7 Optimization of Unconstrained Functions

6 lecture hours

• One dimensional search numerical methods for optimizing a function of one variable
• scanning and bracketing procedures
• Newton and Quasi-Newton methods of unidimensional search
• polynomial approximation methods
• how one-dimensional search is applied in a multidimensional problem
• evaluation of unidimensional search methods
• methods using function values only : Simplex search
• Hooke-Jeees and Powell’s method
• methods that use first derivatives : Newton’s method
• Marquardt’s method
• Quasi-Newton methods

Unit 8 Linear Programming (LP) and Applications

5 lecture hours

• Formulation of linear programming models
• LP in standard form
• principles of simplex method

Unit 9 Constrained Optimization

4 lecture hours

• Lagrange’s multiplier
• Kuhn-Tucker conditions
• transformation methods : penalty function
• constrained direct search method: complex method
• Quadratic approximation methods

Unit 10 Application of Optimizations

• Examples and case studies of optimization in chemical processes like optimizing recovery of waste heat
• optimal shell and tube heat exchanger design
• optimal design and operation of binary distillation column
• chemical reactor design and operation
• optimal location of coal-blending plant
• optimization of Glycol-Ethylene Oxide process 5 Subject Code: 3170513 w.e.f