Gianpiero PATARO | MATHEMATICAL MODELING OF PROCESSES IN FOOD INDUSTRIES
Gianpiero PATARO MATHEMATICAL MODELING OF PROCESSES IN FOOD INDUSTRIES
cod. 0622800009
MATHEMATICAL MODELING OF PROCESSES IN FOOD INDUSTRIES
| 0622800009 | |
| DIPARTIMENTO DI INGEGNERIA INDUSTRIALE | |
| FOOD ENGINEERING | |
| 2014/2015 |
| OBBLIGATORIO | |
| YEAR OF COURSE 2 | |
| YEAR OF DIDACTIC SYSTEM 2012 | |
| PRIMO SEMESTRE |
| SSD | CFU | HOURS | ACTIVITY | |
|---|---|---|---|---|
| ING-IND/26 | 6 | 60 | LESSONS |
| Objectives | |
|---|---|
| TO PROVIDE THE BASIC KNOWLEDGE, METHODS AND SOFTWARE INSTRUMENTS IN ORDER TO: 1) DISCRIMINATE THE COMPLEXITY OF THE SYSTEMS OF PROCESS ENGINEERING AND MEET THE POSSIBILITIES OF ABSTRACT REPRESENTATION; 2) CLASSIFY THE MODELS, PARTICULARLY THE ONES RELATED TO PROCESSES; 3) NUMERICALLY SOLVE THE PARABOLIC PARTIAL DIFFERENTIAL EQUATIONS; 4) UNDERSTAND THE MAIN ISSUES OF ENGINEERING OPTIMIZATION AND KNOW LINEAR PROGRAMMING (LP) METHODS; 5) HANDLE THE MATLAB® SOFTWARE TO DEVELOP OR OBTAIN SOME CLASSES OF MODELS, AND TO SOLVE LP PROBLEMS. |
| Prerequisites | |
|---|---|
| GENERAL KNOWLEDGE OF DIFFERENTIAL CALCULUS, MASS AND ENERGY BALANCES, TRANSPORT PHENOMENA |
| Contents | |
|---|---|
| INTRODUCTION TO MATLAB® LANGUAGE AND TECHNICAL USES. THE VARIOUS CLASSIFICATIONS OF MATHEMATICAL MODELS. FIRST-PRINCIPLE MODELS. MODELS BASED ON THE POPULATION BALANCE APPROACH. EMPIRICAL MODELS AND DATA FITTING. DYNAMICAL MODELS. TIME SERIES. NUMERICAL METHODS FOR PARABOLIC PDES. USE OF MUC 1.0 - PARABOLIC PDE SOLVER CODE IN LABVIEW®. INTRODUCTION TO OPTIMIZATION. LINEAR PROGRAMMING: THE GRAPHICAL METHOD AND THE SIMPLEX ALGORITHM. |
| Teaching Methods | |
|---|---|
| THE COURSE COVERS LECTURES, CLASSROOM EXERCISES CONDUCTED BY THE TEACHER ON THE BLACKBOARD AND EXERCISES IN THE COMPUTER LAB CONDUCTED BY THE TEACHER WITH THE STUDENTS IN AN INTERACTIVE MANNER, THROUGH THE USE OF APPROPRIATE EDUCATIONAL SOFTWARE. EACH STUDENT IS ASSIGNED A USER NAME AND A PASSWORD, AND THEN ALLOWED TO ENTER THE CLASSROOM WITH A PC LICENSE FOR MATLAB ®¸ WITH ITS CURVE FITTING TOOLBOX, AND THE EXECUTABLE MUC ®. |
| Verification of learning | |
|---|---|
| THE OF THE ACHIEVEMENT OF THE OBJECTIVES WILL BE DONE THROUGH: 1) A PRACTICAL TEST AIMED AT SOLVING TWO PROBLEMS DESCRIBED IN THE ENGLISH LANGUAGE, ONE OF LINEAR PROGRAMMING, THE OTHER ALTERNATELY CONSISTING IN THE RESOLUTION OF PDE OR IN BUILDING A DATA FITTING MODEL. THE SOFTWARE-BASED TEST REQUIRES PREPARATION OF AN ELABORATE DIRECTLY ON PC, IN MS WORD ®, WITH THE RESULTS OBTAINED FROM THE MATLAB ® AND / OR MUC ®, WHILE HAVING ALL COURSE MATERIALS AVAILABLE; 2) A SUBSEQUENT ORAL COLLOQUIUM DEALING WITH MATHEMATICAL MODELING. THE PRACTICAL TEST IS PASSED WITH THE MINIMUM SCORE (18/30) IF THE STUDENT HAS FULLY CARRIED OUT ONLY ONE OF THE TWO ASSIGNED PROBLEMS OR PROVIDED VALID RESPONSES TO 60% OF THE QUESTIONS. |
| Texts | |
|---|---|
| 1.HIMMELBLAU D.M. AND BISCHOFF K.B., “PROCESS ANALYSIS AND SIMULATION”, JOHN WILEY & SONS INC., 1967 2.SNIEDER R., “A GUIDED TOUR OF MATHEMATICAL METHODS FOR THE PHYSICAL SCIENCES”, 2ND EDITION, CAMBRIDGE UNIVERSITY PRESS, ISBN-13: 9780521834926, ISBN-10: 0521834929, 2004 3.TEACHING AIDS PROVIDED BY THE LECTURERS |
| More Information | |
|---|---|
| •REFERENCE WEB SITE FOR PERSONAL STUDY AND EXAM MATTERS: HTTP://COMET.ENG.UNIPR.IT/~MICCIO •FURTHER INFORMATION CAN BE REQUESTED VIA E-MAIL: MMICCIO@UNISA.IT OR GPATARO@UNISA.IT |
BETA VERSION Data source ESSE3 [Ultima Sincronizzazione: 2016-09-30]
