AIMS AND CONTENT

LEARNING OUTCOMES

The teaching deals with the Theory of Statistics, the Theory of Estimates and the numerical methods in chemical engineering with the aim of training students in data analysis, in modelling chemical processes and in chemical process optimization.

AIMS AND LEARNING OUTCOMES

The participation to the training activities is instrumental to:

knowing the basics of the theory of development of chemical processes;

understanding the logical basis which a predictive model relies upon;

giving examples about the application of such models to the chemico-physical processes of the industrial production;

identifying and estimating the main parameters describing the kinetics of a chemical process;

developing process simulation algorithms with deterministic or statistic models (Monte Carlo);

choosing the most suitable algorithm for solving a problem of industrial optimization;

applying numerical discretization criteria to a model containing differential equations.

PREREQUISITES

A basic knowledge of  mathematics, chemistry and physics is required.

TEACHING METHODS

The course is structured in frontal lessons and exercises carried out by the teacher.

The students having certified disabilities or other specific handicaps are recommended to contact the teacher at the beginning of the course to decide the procedures of both exam and didactic activities, in order to take into account the specific individual necessities and to provide the relevant support in accordance with the didactic objectives.

SYLLABUS/CONTENT

Fundamentals of theory of applied statistics.

Simulation of stochastic processes. Monte Carlo methods for modelling aggregation, disaggregation, etching and corrosion of a solid phase.

Theory of estimates. Linear and non-linear regression.

Process optimization. Dynamic optimization.

Numerical methods for the solution of algebraic and ordinary differential equations.

Economic aspects of chemical engineering processes. Enterprise - Legal and technical-organizational structure.
Investment theory and profitability of a project. Design phases of a project/plant. Project Management - Techniques for monitoring results and budgets.

RECOMMENDED READING/BIBLIOGRAPHY

G. Vicario, R. Levi. Calcolo delle probabilità e statistica per ingegneri. Progetto Leonardo, Bologna 1997.

D.M. Himmelblau, K.B. Bischoff.  Process analysis and simulation : deterministic systems.

New York : Wiley, 1968

TEACHERS AND EXAM BOARD

Exam Board

ANDREA REVERBERI (President)

MARCO VOCCIANTE (President Substitute)

LESSONS

LESSONS START

https://corsi.unige.it/10375/p/studenti-orario

Class schedule

The timetable for this course is available here: Portale EasyAcademy

EXAMS

EXAM DESCRIPTION

The exam consists of an oral discussion.

The students having certified disabilities or other specific handicaps are recommended to contact the teacher at the beginning of the course to decide the procedures of both exam and didactic activities, in order to take into account the specific individual necessities and to provide the relevant support in accordance with the didactic objectives.

ASSESSMENT METHODS

The exam aims at checking:

• the learning level ;
• the skilfulness in applying the learned concepts to solve problems concerning the themes proposed.

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