OVERVIEW

The Theory of Chemical Process Development concerns the application of mathematical tools to the description of industrial chemical processes, with special reference to the simulation and optimization of these processes for the proper design of industrial chemical plants. The relevant mathematical tools refer to the setting of equations and their resolution by analytical or numerical methods.

AIMS AND CONTENT

LEARNING OUTCOMES

The training objectives refer to the student's acquisition of mastery in the use of a mathematical tool applied to industrial chemical processes. In particular, the teaching aims at the formulation of the process model, the adoption of appropriate simplifying hypotheses, the analytical or numerical resolution of the model and the critical analysis of the model itself. At the end of the course, the student will be able to perform a rational statistical analysis of experimental data, to select the most appropriate algorithm for solving problems in industrial chemistry and to choose the best process optimisation strategy in order to match production targets with the criteria of eco-sustainability and environmental protection.

AIMS AND LEARNING OUTCOMES

The global purposes refer to the acquisition of a mastery in the use of a mathematical tool applied to industrial chemical processes. In particular, the teaching is intended to formulate a mathematical model, to adopt the proper simplifications, to obtain a numerical solution of the model and finally to propose a critical analysis of the model itself.

At the end of teaching, the student will be able to perform a rigorous data analysis, a correct model identification, a reliable process optimization and a choice of the most suitable algorithm to solve problems pertaining to industrial chemistry.

TEACHING METHODS

Oral lessons and exercises on the blackboard. The exercises are carried out by the teacher himself.

Additionally, *.pdf files containing the topics covered and the exercises carried out during the lessons are provided.

SYLLABUS/CONTENT

Part 1

Elements of stochastic calculus. Measures of central tendency and dispersion. Application to the unit operations of industrial chemical processes.

Residence time distribution functions for reagent and non-reagent systems. Ideal and real chemical reactors. Choice of the optimal reactor setup in a chemical process.

Theory of sample variables. Test of hypothesis applied to quality control of a chemical product and to pollution data analysis.  

Part 2

Introduction to matrix algebra. Operations with vectors, matrices and determinants. Numerical solution of a linear algebraic system.

Experimental data fitting with linear and non-linear models. Least squares estimation.

Determination of the local singular points of an objective function in the technical-economical optimization of an industrial chemical process.

Numerical methods for non-linear algebraic equations. Application to chemical equilibria.

Computational molecules for derivative operators and their uses in finite difference methods for the solution of ordinary differential equations. Applications to diffusive processes.

Introduction to elements of scale-up. Application of scale-up concepts to mixing and heat transfer in batch and continuous processes.

RECOMMENDED READING/BIBLIOGRAPHY

Recommended bibliography:

R. Bird, “Transport Phenomena”, John Wiley & Sons

N. Piskunov, “Calcolo Differenziale e Integrale”, vol. 1 e 2, Editori Riuniti

D.Himmelblau, “Process Analysis by Statistical Methods”, John Wiley & Sons

Scheid, “Analisi numerica”, Schaum

D.Himmelblau, “Applied Nonlinear Programming”, Glen Head NY

R. Felder, “Elementary Principles of Chemical Processes”, John Wiley & Sons

Supplementary material is provided on request by working students or by students affected by disabilities in order to meet specific needs.

TEACHERS AND EXAM BOARD

Exam Board

ANDREA REVERBERI (President)

ALBERTO SERVIDA

MARCO VOCCIANTE (President Substitute)

ANTONIO COMITE (Substitute)

PAOLO MORETTI (Substitute)

LESSONS

LESSONS START

Classes will be held in the period 24/02/2025 - 13/06/2025 with the relevant interruptions according to the academic calendar.

See the link: 

https://servizionline.unige.it/unige/stampa_manifesto/MF/2024/11767.html

Class schedule

The timetable for this course is available here: Portale EasyAcademy

EXAMS

EXAM DESCRIPTION

The examination consists of an oral session, which includes three questions. The first of them concerns topics relating to the Theory of Applied Statistics, while the subsequent ones relate to the theory of estimates, process optimization and mathematical methods for solving problems concerning these disciplines.

For those students affected by disabilities, the format of examination is subject to the regulations of the University of Genoa (https://unige.it/disabilita-dsa).

In case of emergency and only according to specific indications by the University of Genoa, the assessment method for the exam might be changed, including the possibility of an online procedure.

ASSESSMENT METHODS

The oral examination will cover the topics treated during the lectures and it will aim to assess not only whether the student has achieved an adequate level of knowledge, but whether she/he has acquired the ability to critically analyze the problems that will be posed during the examination. In particular, the ability to make a rational statistical analysis of experimental data, to identify relevant models, to select the best process optimization strategy and to choose the most appropriate algorithm for solving problems pertaining to industrial chemistry will be assessed.

The assessment standards concern the ability to stay on topic, the quality of expression, the logic pattern of the reasoning and the critical reasoning skills.

Exam schedule

FURTHER INFORMATION

Students who have valid certification of physical or learning disabilities on file with the University and who wish to discuss possible accommodations or other circumstances regarding lectures, coursework and exams, should speak both with the instructor and with Professor Sergio Di Domizio (sergio.didomizio@unige.it), the Department’s disability liaison.