Process Modeling and Supervision

Recommended Prerequisites

Chemical Thermodynamics; Fluid Dynamics; Mass and Energy Balances; Programming and Numerical Methods; Heat Transfer; Introduction to Reaction Engineering; Chemical Reactors; Solid-Liquid Operations; Mass Transfer; Modeling, Simulation and Optimization; Separation Processes; Instrumentation and Control; Data Processing

Teaching Methods

Classes are used to present the basic concepts, definitions, formulations and illustrative examples. These concepts are later practiced by the students during the solution of a set of tasks, in groups of 2 students.

The final grade involves two components: a) solution of a number of tasks during the semester (25-35%); b) final exam (65-75%). Students need to obtain a minimal classification of 8/20 in the final exam. The final exam will involve questions that require the demonstration of theoretical and practical skills and competences acquired during the semester.

Learning Outcomes

This curricular unit will help the students acquire capabilities of developing mathematical models of physico-chemical systems. Systematic methodologies of model building are addressed, supported in experimental data treatment. The students will acquire the capability of evaluating the dominant physical phenomena that occur and simplify the models produced, together with the capability of knowledge integration in the domains of transfer, transformation and separation processes. The use of these models as the support for process supervion activitiez is also considered. This course aims at developing the capabilities of the students in the area of solution, manipulation and analysis of complex models, together with the capabilities of solving problems that require the integration of knowledge from various other curricular units.

Work Placement(s)

No

Syllabus

Mathematical modeling of mechanistic nature. Principle of conservation of extensities. Constitutive relations.

Extensity balances (macro and microscopic). Systems of lumped and distributed parameters. Analogies between different system types. Typical applications in chemical processes.

Dynamic simulation of chemical and biological systems. Numerical solution strategies. Computational fluid dynamics simulators.

Parameter estimation and inference. Confidence intervals and prediction errors. System identification.

Multivariable supervision in chemical processes. Multilayer supervision. Predictive controlo and real time optimization of chemical processes. 

Head Lecturer(s)

Nuno Manuel Clemente de Oliveira

Assessment Methods

Assessment
Resolution Problems: 30.0%
Exam: 70.0%

Bibliography

- Aris, R. Vectors, Tensors, and the Basic Equations of Fluid Mechanics, Dover Publications, New York, 1989.

- Bird, R. B.; Stewart, W. E; Lightfoot, E. N. Transport Phenomena, 2ª ed., John Wiley & Sons, New York, 2002.

- Hangos, K. M.; Cameron, I. T. Process Modeling and Model Analysis, Academic Press, New York, 2001.

- Roffel, B.; Betlem, B. Process Dynamics and Control: Modeling for Control and Prediction, John Wiley & Sons, New York, 2006.

- Himmelblau, D. M.; Bischoff, K. B.Process Analysis and Simulation - Deterministic Systems, John Wiley & Sons, New York, 1967.

- Fogler, H. S. Elements of Chemical Reaction Engineering, 5ª ed., Prentice-Hall Inc., Englewood Cliffs, 2016.

- Finlayson, B. A. Introduction to Chemical Engineering Computing,2ª ed. John Wiley & Sons, New York, 2014.

- Montegomery, D. C.; Peck, E. A.; Vining, G. G. Introduction to Linear Regression Analysis, 5ª ed., John Wiley & Sons, New York, 2014.