ECTS credits ECTS credits: 4.5
ECTS Hours Rules/Memories Student's work ECTS: 74.25 Hours of tutorials: 2.25 Expository Class: 18 Interactive Classroom: 18 Total: 112.5
Use languages Spanish, Galician
Type: Ordinary Degree Subject RD 1393/2007 - 822/2021
Departments: Chemistry Engineering
Areas: Chemical Engineering
Center Higher Technical Engineering School
Call: First Semester
Teaching: With teaching
Enrolment: Enrollable
The "Simulation and Optimization" course aims to train students in the mathematical optimization of chemical processes by learning and applying different methods and tools. It also highlights the use of mathematical models for structural analysis and strategic decomposition in order to simulation and optimization of chemical processes. This course also has some complementary aims, such as the use of software, simulators and spreadsheets. It is focused on practical use of the concepts and methods that serve not only for this course, but also for application in other degree disciplines and professional level.
a. Planning and creating models that represent real industrial processes.
b. Identifying systems structures. Simulation Strategies.
c. Formulation of the mathematical model corresponding to an optimization problem involving an objective function with one or more design variables, different constraints (equality and inequality) and resolution using a suitable algorithm (decision-making). The model must be mathematically consistent.
d. Learning of optimization algorithms fundamentals and practical application in industrial procedures.
e. Simulation and optimization with a steady-state chemical process simulator (HYSYS).
Lectures
SECTION I. Models (2 h)
Theme 1.- BASIS OF MODELIZATION (2 h). Introduction. System definition. Models types. Simulators. Variables. Freedom degrees.
SECTION II. Process optimization (12 h)
Theme 2.- INTRODUCTION TO PROCESS OPTIMIZATION (2 h). Target functions. Concavity and convexity. Analytical methods to search optimal points. Karush-Kunt-Tucker (KKT) conditions.
Theme 3.- OPTIMIZATION WITHOUT CONSTRAINTS (3 h). One-variable functions: Uniform and sequential methods. Direct (DSC-Powell) and indirect (Newton-Raphson) methods. Multivariable functions: Direct (Hooke-Jeeves and Nelder-Mead) and indirect (quasinewton - BFGS) methods.
Theme 4.- OPTIMIZATION WITH CONSTRAINTS (4 h). Linear programming: Simplex algorithm. Analysis of sensibility. Duality. Non-linear programming: GRG and complex methods.
Theme 5.- NETWORKS ANALYSIS (3 h). Graphs. Dijkstra algorithm. Ford-Fulkerson algorithm. Vogel method. Hungarian method for the assignation problem. CPM and PERT strategies.
SECTION III. Analysis and simulation of processes (7 h)
Theme 6.- SYSTEMS STRUCTURE (1 h). Systems and subsystems. Associated matrices. Cycles identification. Sparce systems. Simulation strategies.
Theme 7.-MODULAR SEQUENTIAL STRATEGY FOR STATIONARY PROCESSES SIMULATION (4 h). Partitioning and ordering algorithms. Algorithms for cycles tearing. Convergence algorithm. Nested cycles.
Theme 8.-EQUATIONS ORIENTED STRATEGY FOR STATIONARY PROCESSES SIMULATION (2 h). Algorithms for design variables selection. Output variables assignment algorithms. Singularity. Partitioning and ordering algorithms.
Themes 2 to 8 have associated an interactive class of seminary (7 for each of the 2 groups) for problems resolution (using spreadsheet) and doubts.
Interactive computer classes (10 h, 5 sessions).
SESSION 1: EXCEL. Linear programming. Analysis of sensibility, boundary and responses reports.
SESSION 2: EXCEL. Network problems. Analysis of sensibility, boundary and responses reports.
SESSION 3: EXCEL. CPM problems and non linear programming. Analysis of sensibility, boundary and responses reports.
SESSION 4: HYSYS. Structure, modules, convergence, process and logical units.
SESSION 5: HYSYS. Optimal operational conditions of a process with chemical reaction.
Basic bibliography:
SECTIONS I and III
N.J. Scenna (Editor). Modelado, Simulación y Optimización de procesos Químicos. 1999. E-book. http://www.edutecne.utn.edu.ar/modelado-proc-quim/modelado-proc-quim.pdf
SECTION II
R.W. Pike. Optimization for Engineering Systems, 1986. Van Nostrand Reinhold, New York. SIGNATURE: A 151 7
Complementary bibliography:
Matlab algorithms
1. J. Tornero, L. Armesto. Técnicas de Optimización, 2007. UPV, Valencia. SIGNATURE: IOP 107.
2. R.L. Rardin. Optimization in Operations Research, 1998. Prentice-Hall, Upper Saddle River. SIGNATURE: 90 708.
3. M.S. Bazaraa, H.D. Sherali, C.M. Shetty. Nonlinear Programming: Theory and Algorithms, 2006. Wiley, New York. SIGNATURE: 1209 067
Students can download all the material of the presentations used in lectures through the virtual campus.
Specific skills
CQ.2.1. Capacity for analysis and design of processes and products.
CQ.2.2. Capacity for simulation and optimization of processes and products.
CQ.4.1 Ability to design, manage and operate simulation procedures for chemical processes.
CQ4.2 Control and instrumentation of chemical processes.
General skills
CG.3 Knowledge of fundamental and technological disciplines, to enable for
learning new methods and theories with versatility to adapt to new situations.
CG.4 Ability to solve problems with initiative, decision making, creativity, and critical reasoning, communicate and transmit knowledge, skills and abilities in the industrial engineering.
Transversal competences
CT.1 Capacity for analysis and synthesis
CT.4 Skills for the use and development of applications
CT.6 Troubleshooting
CT.8 Teamwork
CT.13 Capacity for applying knowledge in practice
The theoretical content will be taught based on lectures. Follow-up questions will be formulated for active participation by the student. Both slate and PowerPoint presentations will be used. These presentations will be also available to the student along with the program and problems bulletin on the Virtual Campus. (CG.3, CQ.2.1, CQ.2.2, CQ.4.1)
In interactive seminar classes proposed problems in the bulletin will be solved by the students. (CG4, CT1, CT4, CT6, CT13, CQ2.1, CQ2.2, CQ4.2)
Practice will be in a computer lab for solving optimization problem in spreadsheets and managing a chemical process simulator. A detailed instruction on the programs fundamentals will be delivered at the beginning; then an autonomous learning will be promoted to discover miscellaneous incomes. For practices students must deliver a report through the Virtual Campus. (CG4, CT1, CT4, CT6, CT13, CQ2.2, CQ4.1)
Small groups of students will work on the application of an advanced optimization algorithm applied to a practical case under the teacher supervision during group tutorials. (CG4, CT1, CT8, CT13, CQ2.1, CQ2.2)
Activities Timetable:
1st week
Lectures:
Course presentation
Theme 1.- BASIS OF MODELIZATION.
Introduction. System definition. Models types. Simulators. Variables. Freedom degrees.
Theme 2.- INTRODUCTION TO PROCESS OPTIMIZATION.
Target functions. Concavity and convexity.
2nd week
Lectures:
Theme 2.- INTRODUCTION TO PROCESS OPTIMIZATION (2 h).
Analytical methods to search optimal points. Karush-Kunt-Tucker (KKT) conditions.
Theme 3.- OPTIMIZATION WITHOUT CONSTRAINTS.
One-variable functions: Uniform and sequential methods. Direct (DSC-Powell) and indirect (Newton-Raphson) methods.
3rd week
Lectures:
Theme 3.- OPTIMIZATION WITHOUT CONSTRAINTS.
Multivariable functions: Direct (Hooke-Jeeves and Nelder-Mead) and indirect (Wegstein and BFGS) methods.
Seminary:
Case studies
4th week
Lectures:
Theme 4.- OPTIMIZATION WITH CONSTRAINTS.
Linear programming: Simplex algorithm.
5th week
Lectures:
Theme 4.- OPTIMIZATION WITH CONSTRAINTS
Analysis of sensibility. Duality.
6th week
Theme 4.- OPTIMIZATION WITH CONSTRAINTS
Non-linear programming: GRG and complex methods.
Seminary:
Case studies
7th week
Lectures:
Theme 5.- NETWORKS ANALYSIS
Graphs. Dijkstra algorithm. Ford-Fulkerson algorithm.
Seminary:
Case studies
8th week
Lectures:
Theme 5.- NETWORKS ANALYSIS
Vogel’s method. Hungarian methods for assignation problem-
9th week
Lectures:
Theme 5.- NETWORKS ANALYSIS
CPM and PERT strategies.
Seminary:
Case studies
Lab
Spreadsheet. Network problems. Analysis of sensibility, boundary and responses reports.
10th week
Theme 6.- SYSTEMS STRUCTURE
Systems and subsystems. Associated matrices. Cycles identification. Sparce systems. Simulation strategies.
Theme 7.-MODULAR SEQUENTIAL STRATEGY FOR STATIONARY PROCESSES SIMULATION
Partitioning and ordering algorithms.
Lab
Spreadsheet: Network problems. Analysis of sensibility, boundary and responses reports.
11th week
Lectures:
Theme 7.-MODULAR SEQUENTIAL STRATEGY FOR STATIONARY PROCESSES SIMULATION
Algorithms for cycles tearing.
Seminary:
Case studies
Lab
Spreadsheet: CPM problems. Analysis of sensibility, boundary and responses reports.
12th week
Lectures:
Theme 7.-MODULAR SEQUENTIAL STRATEGY FOR STATIONARY PROCESSES SIMULATION
Convergence algorithm. Nested cycles.
Seminary:
Case studies
Lab
HYSYS. Structure, modules, convergence, process and logical units
13th week
Lectures:
Theme 8.-EQUATIONS ORIENTED STRATEGY FOR STATIONARY PROCESSES SIMULATION
Algorithms for design variables selection.
14th week
Lectures:
Theme 8.-EQUATIONS ORIENTED STRATEGY FOR STATIONARY PROCESSES SIMULATION
Output variables assignment algorithms. Singularity. Partitioning and ordering algorithms.
Seminary:
Case studies
Lab
HYSYS. Optimal operational conditions of a process with chemical reaction.
Scenario 1 (no restrictions on physical presence)- Expository classes: face-to-face master classes in the classroom, encouraging student intervention.- Interactive classes: - Seminars: mainly face-to-face; dedicated to the work of the student under the tutelage of the professor, to study in detail important aspects of the subject, and for the resolution of practical cases, problems and questions. - Practices in computer room: fundamentally of face-to-face character; dedicated to the work of the student under the tutelage of the professor, to study in detail important aspects of the subject, and for the resolution of practical cases, problems and questions. - Tutorials: for the follow-up of the works in group realized by the students and personalized follow-up of the student; of a compulsory nature, they will be face-to-face in the classroom or online, using the virtual platforms available at USC and e-mail.Scenario 2: distancing.The exhibition activities will be developed electronically synchronously through Microsoft Teams and the Moodle platform. Seminars and practices in the computer room will be developed in person in the classroom. The tutorials will preferably be virtual, synchronous and asynchronous, using the virtual platforms available at USC and e-mail.Scenario 3: closure of the facilities.The teaching will be completely virtual. Microsoft Teams will be used for the synchronous sessions and the Moodle platform for asynchronous teaching, making available to students presentations in pdf or recorded Power Point documents, documents for reading, web links, questionnaires and videos. The tutorials will be carried out through synchronous meetings through Teams and asynchronous through Moodle forums, as well as through consultation with teachers by e-mail.
Learning will be tracked by performing exercises as individual and group troubleshooting. Also, an exam based on the problems resolution for the theoretical part and one practical for the lab will be used to obtain final mark.
Score distribution
Exam 60% (45% theory; 15% practice)
Jobs / activities 25%
Tutoring 10% (oral presentation of teamwork).
Report professor 5%
It is necessary at least 5 points and 3/10 (excepting in practice exam) in each of the parts of the evaluation to pass.
Attendance at practical classes and the presentation of the teamwork, by their characteristics, are compulsory to pass the course in the ordinary and retest opportunity.
The accumulated score of the continuous evaluation corresponding to work/activities is maintained for the second oprtunity exam. When the minimum mark was not reached, some activities will be planned by the teacher for the student, and after pass, to have the chance to pass the course.
Skills assessment (Exam (E); Work (T), Practices (P), Tutorials (TU).
CG.3: E, T
CG.4: E, T, P, TU
CT.1: E, T, TU
CT.4: T, P
CT.6: E, T, P, TU
CT.8: TU
CT.13: T, P
CQ2.1: E, T, P
CQ2.2: E, T, P, TU
CQ4.1: E, P
CQ4.2: E, P
In scenario 1 the final exam and the presentation of works will be face-to-face. In scenario 2, the final exam and homework assignment will be done virtually, using the Moodle platform, although if possible the final exam will be done in person. In scenario 3, the final exam and homework assignments will be done virtually, using the Moodle platform.For cases of fraudulent performance of exercises or tests, the provisions of the Regulations for the evaluation of students' academic performance and the review of grades will apply.
Hours: 38
Home work: 74.5
Total: 112.5
Students must know mathematics, balances of property and design, fluid and heat transfer, chemical reactors, mass transfer and process engineering.
It is advisable that student domain English and spreadsheet tools for solving optimization problems. Finally, it is recommend the use of tutorial office for clarification of doubts and concepts.
Classes will be in Spanish language.
“Campus Virtual” will be used.
Excel, HYSYS and VensimPLE will be used as software.
Contingency planFollowing the Guidelines for the development of a safe face-to-face teaching, course 2020-2021, all the teaching activities to be developed in the subject are adapted to the different probable scenarios.Scenario 1 (no restrictions on physical presence)Teaching of expository and interactive face-to-face activities in the classroom; face-to-face assessment in the classroom through final examination and presentation of works.Scenario 2: distancing.The exhibition activities will be developed electronically synchronously through Microsoft Teams and the Moodle platform. The seminars and practices in the computer room will be developed in person in the classroom. The tutorials will preferably be virtual, synchronous and asynchronous, using the virtual platforms available at USC and e-mail. The final exam and presentation of works will be done virtually, using the Moodle platform and Microsoft Teams, although if possible the final exam will be done in person.Scenario 3: closure of the facilities.The teaching will be completely virtual. Microsoft Teams will be used for the synchronous sessions and the Moodle platform for asynchronous teaching, making available to students presentations in pdf or recorded Power Point documents, documents for reading, web links, questionnaires and videos. The tutorials will be carried out through synchronous meetings through Teams and asynchronous through Moodle forums, as well as through consultation with teachers by e-mail. The final exam and presentation of works will be done virtually, using the Moodle platform and Microsoft Teams.
Pastora Maria Bello Bugallo
Coordinador/a- Department
- Chemistry Engineering
- Area
- Chemical Engineering
- Phone
- 881816789
- pastora.bello.bugallo [at] usc.es
- Category
- Professor: Temporary PhD professor
| Monday | |||
|---|---|---|---|
| 16:00-17:00 | Grupo /CLIS_01 | Spanish | Classroom A2 |
| Tuesday | |||
| 16:00-17:00 | Grupo /CLIS_01 | Spanish | Classroom A2 |
| Wednesday | |||
| 16:00-17:00 | Grupo /CLE_01 | Spanish | Classroom A2 |
| Thursday | |||
| 16:00-17:00 | Grupo /CLE_01 | Spanish | Classroom A2 |
| 01.11.2021 16:00-20:45 | Grupo /CLIS_01 | Classroom A3 |
| 01.11.2021 16:00-20:45 | Grupo /CLIS_02 | Classroom A3 |
| 01.11.2021 16:00-20:45 | Grupo /CLIS_03 | Classroom A3 |
| 01.11.2021 16:00-20:45 | Grupo /CLIL_01 | Classroom A3 |
| 01.11.2021 16:00-20:45 | Grupo /CLIL_02 | Classroom A3 |
| 01.11.2021 16:00-20:45 | Grupo /CLIL_03 | Classroom A3 |
| 01.11.2021 16:00-20:45 | Grupo /CLIL_04 | Classroom A3 |
| 01.11.2021 16:00-20:45 | Grupo /CLE_01 | Classroom A3 |
| 01.11.2021 16:00-20:45 | Grupo /CLIS_01 | Classroom A4 |
| 01.11.2021 16:00-20:45 | Grupo /CLIS_02 | Classroom A4 |
| 01.11.2021 16:00-20:45 | Grupo /CLIS_03 | Classroom A4 |
| 01.11.2021 16:00-20:45 | Grupo /CLIL_01 | Classroom A4 |
| 01.11.2021 16:00-20:45 | Grupo /CLIL_02 | Classroom A4 |
| 01.11.2021 16:00-20:45 | Grupo /CLIL_03 | Classroom A4 |
| 01.11.2021 16:00-20:45 | Grupo /CLIL_04 | Classroom A4 |
| 01.11.2021 16:00-20:45 | Grupo /CLE_01 | Classroom A4 |
| 06.29.2021 09:15-14:00 | Grupo /CLE_01 | Classroom A2 |
| 06.29.2021 09:15-14:00 | Grupo /CLIS_01 | Classroom A2 |
| 06.29.2021 09:15-14:00 | Grupo /CLIS_02 | Classroom A2 |
| 06.29.2021 09:15-14:00 | Grupo /CLIS_03 | Classroom A2 |
| 06.29.2021 09:15-14:00 | Grupo /CLIL_01 | Classroom A2 |
| 06.29.2021 09:15-14:00 | Grupo /CLIL_02 | Classroom A2 |
| 06.29.2021 09:15-14:00 | Grupo /CLIL_03 | Classroom A2 |
| 06.29.2021 09:15-14:00 | Grupo /CLIL_04 | Classroom A2 |