Instructor : Dr. Anand Bharti
Tuesday :- 2:30 PM - 3:20 PM (Room No. FIII, LH-3/4)
Thursday :- 2:30 PM - 3:20 PM (Room No. FIII, LH-3/4)
Friday :- 11:00 AM - 11:50 AM (Room No. FIII, LH-3/4)
CL 407 PROCESS MODELING, SIMULATION AND OPTIMIZATION
Credits L:3, T:1, P:0
Class per week 3 hrs
Branch Chemical Engineering
COURSE OUTCOMES
After the completion of this course, students will be able to:
Develop mathematical models for chemical engineering systems.
Formulate optimization problem.
Solve unconstrained Single Variable Optimization problems.
Solve unconstrained Multivariable Optimization problems.
Solve Linear Programming Problems.
SYLLABUS
Module I:
Mathematical Modeling and Simulation of Chemical Engineering Systems: Introduction, Uses of Mathematical Models, Principles of Formulation, Lumped and distributed parameter systems, Fundamental Laws: Continuity Equations & Energy Equations, Modeling of Separation Processes, Modeling of Reactors, Modeling of Heat Transfer Equipment such as Series of Isothermal constant- holdup CSTRs, CSTRs with variable holdups, Two heated tanks, Gas-phase Pressurized CSTR, Non-isothermal CSTR, Single Component Vaporizer, Multicomponent Flash drum, Batch Reactor, Reactor with mass transfer, Ideal binary distillation column, Multicomponent non-ideal distillation column etc. Computer Simulation of above modelled chemical engineering systems.
Module II:
Introduction to Optimization: Statement of optimization problems, Classification of optimization problems, Optimization problem formulation, Continuity of functions, Unimodal and Multimodal functions, concave and convex functions, Optimality criteria for unconstrained single variable and multivariable functions.
Module III:
Unconstrained Single Variable Optimization: Methods and Applications, Bracketing Method, Region elimination methods (Dichotomous search method, Interval Halving method, Fibonacci Search Method, Golden Section Search Method), Methods requiring derivatives: Newton-Raphson method, Bisection method, Secant method.
Module IV:
Unconstrained Multivariable Optimization: Direct Search Methods (Simplex method, Hooke-Jeeves pattern search method, Powell’s conjugate direction method), Unconstrained Multivariable Optimization: Gradient Based Methods (Cauchy’s method, Newton’s method, Marquardt Method).
Module V:
Linear Programming: Graphical Method and The Simplex Method. Basics of Global Optimization Algorithms, Introduction to Genetic Algorithm.
Text books:
Process Modeling, Simulation and Control for Chemical Engineers, Willian L. Luyben, Second Edition, McGraw-Hill Chemical Engineering Series.
Modeling and Simulation of Chemical Process Systems, Nayef Ghasem, CRC Press, Taylor &Fraccis Group.
Process Modeling and Simulation for Chemical Engineers – Theory and Practice, Simant Ranjan Upreti, John Wiley & Sons Ltd.
Optimization of Chemical Processes, Edgar, Himmelblau and Lasdon, 2nd edition, McGraw-Hill Chemical Engineering Series.
Engineering Optimization: Theory and Practice, S S Rao, John Wiley & Sons.
Optimization for Engineering Design - Algorithms and Examples, K Deb, PHI Learning Private Limited.
ASSESSMENT
First Quiz 10 Marks
Mid Semester Examination 25 Marks
Second Quiz 10 Marks
Teacher’s Assessment 05 Marks
End Semester Examination 50 Marks
Course Delivery methods:
• Lecture by use of boards.
• Self- learning such as use of NPTEL materials and internets.
Midterms and Final:
There will be one mid semester (25 % weightage) and one end semester (50% weightage) exam. Exams will be closed book and closed notes. However, I will provide relevant equations during the exams. The exams will consist of conceptual problems and traditional problems. My intention is to help you develop your problem-solving skills as well as your conceptual understanding of the subject. Material can and will be drawn from the lecture notes.
Module-1: Lecture Notes - 1 Lecture Notes - 2 MCQs
Module-2: Lecture Notes additional_problems
Module-3: Lecture Notes
Module-4: Lecture Notes additional_notes
Module-5: Lecture Notes additional_problems