1. EMSO Process Simulator: Software Presentation and Potentials
Speaker: Roymel Rodriguez Carpio
Local: Computing room of EPQB-EQ/UFRJ
Description: The EMSO simulator workshop aims to present students and engineering professionals with the capabilities and functionalities of the simulator. The EMSO is an open modeling environment that provides its users to develop mathematical models for representing any system whose phenomenon can be represented as algebraic-differential equations system (dynamic or stationary models). From these models, the simulation, control, parameters adjustment, and optimization processes are possible. The EMSO has been used in several studies especially in chemical-petrochemical processes simulation.
Download support material ?EMSO material
2. Introduction to Optimization Using GAMS Software
Speaker: Julia Coelho Lemos
Local: Room G-123
Description: The workshop will be divided into two parts, the first one will introduce some basic concepts of optimization and present some examples of use in the PSE area. In the second part, the GAMS software will be presented and formulations will be developed for optimization problems. These formulations will be implemented and solved using the GAMS software.
3. Aspen Plus applied to solve problems in Process Engineering
Speakers: Felipe Moura and Ariel Boveri Berti
Local: Room G-121
Description: Access to the NIST database. Analysis of pure components, binary and ternary mixtures. Estimates of physicochemical properties. Consistency of thermodynamic models. Regression of phenomenological models parameters. Flowsheet construction from available models. Simulation tools: Design Specs, Calculator Block, Sensitivity and Optimization.
4. Introduction to Python
Speaker: Nayher Andrés Clavijo Vallejo
Local: Computing Room of LADEQ-EQ/UFRJ
Description: The Python introductory workshop will aim to familiarize new users with the basic language features for solving typical PSE problems. Among the topics covered are: Import and export data, graphics generation with matplotlib, vectors and matrices definition, matrix operations, solution of (i) algebraic equations system, (ii) differential and algebraic-differential equations systems, and (iii) data adjustment problems.
5. Dynamic optimization with APMonitor + Python
Speaker: Ataíde Souza Andrade Neto
Local: Room G-121
Description: In the workshop of dynamic optimization with APMonitor will be approached the main platform tools for solving dynamic optimization problems. Among the topics covered are: consistent formulation of the optimization problem; nonlinear programming problems; optimal control; receding horizon estimation; and model predictive control.
6. Machine Learning with Python
Speaker: Afrânio José de Melo Jr.
Local: Room I-105A
Description: Data Science/Big Data: Application definitions and examples. Machine Learning: problem definition; supervised, unsupervised and reinforced approaches; classification methodologies, anomalies regression and detection. Importance for the Implementation of the Industry Paradigm 4.0. Presentation of the Data Science development environment in Python: the NumPy, pandas and scikit-learn libraries. Using the Jupyter notebook. Notions of artificial neural networks and deep learning. Applications in PSE: statistical control and process monitoring.
7. Introduction to Simulation and Process Optimization with the iiSE Simulator
Speaker: Rafael de Pelegrini Soares
Local: Room D-104
Description: Introduction to the basic concepts of process simulation. Typical equipment in a chemical processes simulation (material stream, mixers, separators, compressors, flash vessels, and reactors). System response and sensitivity analysis studies. Introduction to process optimization. Prerequisites: familiarity with chemical processes.