# 14MZM5 - Mathematical Modeling and Process Optimization

Course specification
Course titleMathematical Modeling and Process Optimization
Acronym14MZM5
Study programmeChemical engineering
Module
Lecturer (for classes)
Lecturer/Associate (for practice)
Lecturer/Associate (for OTC)
ESPB5.0Status
ConditionNoneОблик условљености
The goalThe goal of the advanced course in mathematical modeling is to learn students to set-up, solve and analyze complex models of chemical engineering processes and systems. In this course, students also acquire essential knowledge of process optimization - the structure, methods and applications. Theoretical basis of modeling and optimization will be demonstrated through examples from various fields of chemical engineering, with the use of modern approaches and software packages.
The outcomeAfter completing and passing the exam, students will be able to: ; 1. Construct mathematical models for more complex problems in chemical engineering. ; 2. Choose an approach, method and software package for solving a model. ; 3. Set an optimization problem and optimize a system using software. ; 4. Perform model sensitivity and uncertainty analysis. ;
Contents
Contents of lectures1. Overview of approaches, numerical methods and software packages for solving complex chemical engineering problems. ; 2. Computational Fluid Dynamics (CFD) and Discrete Particle Modeling (DPM) - differences in the approaches and applications. ; 3. Neural networks models - the structure, adequacy and examples in chemical engineering. ; 4. Model sensitivity and uncertainty analysis, model order reduction. ; 5. Process optimization - the purpose, structure, applications in chemical engineering. ; 6. Optimization methods - linear (LP) and non-linear programming (NLP), stochastic programming, dynamic optimization. ;
Contents of exercisesPractical lessons are carried out in the computer lab. In the first part students learn to solve more complex examples from chemical engineering, using MATLAB software and the CFD simulator. Some of the examples include optimization (solved in MATLAB), demonstrating its capabilities and applications. In the second part students work independently on the project assignment.
Literature
1. Material from the lectures and practical exercises
2. S.C. Chapra, R.P. Canale, Numerical Methods for Engineers, McGraw Hill, 2010
3. K.J. Beers, Numerical Methods for Chem. Eng. Aplications in MATLAB, Oxford Uni, 2007
4. B.W. Bequette, Process Dynamics: Modeling, Analysis and Simulation, Prentice Hall, 1998
5. V.V. Ranade, Computational Flow Modeling for Chem. Reactor Eng, Academic Press, 2002
Number of hours per week during the semester/trimester/year
LecturesExercisesOTCStudy and ResearchOther classes
13
Methods of teachingLectures, practical classes in the computer laboratory, consultations
Knowledge score (maximum points 100)
Pre obligationsPointsFinal examPoints
Activites during lecturesTest paper
Practical lessonsOral examination
Projects50
Colloquia
Seminars20