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Scheda Riassuntiva
Anno Accademico 2016/2017
Tipo incarico Dottorato
Insegnamento 098565 - MONTE CARLO SIMULATION METHODS: THEORY AND APPLICATIONS TO STOCHASTIC AND UNCERTAIN SYSTEM, STRUCTURES AND COMPONENTS
Docente Baraldi Piero
Cfu 5.00 Tipo insegnamento Monodisciplinare

Corso di Dottorato Da (compreso) A (escluso) Insegnamento
MI (1300) - SCUOLA DI DOTTORATOAZZZZ098565 - MONTE CARLO SIMULATION METHODS: THEORY AND APPLICATIONS TO STOCHASTIC AND UNCERTAIN SYSTEM, STRUCTURES AND COMPONENTS

Programma dettagliato e risultati di apprendimento attesi

Programme of the course:

Basic concepts of uncertain and stochastic systems

Introduction to Monte Carlo Simulation

Sampling Random Numbers from Generic Distributions

Sampling by the Inverse Transform Method

Sampling by the Rejection Method

Evaluation of definite integrals by Monte Carlo Simulation

Analog Simulation

Forced (Biased) Simulation

Efficient methods of sampling uncertain variables:

Basic Principles of System Reliability Analysis

The Transport Process of a Stochastic System

System Reliability Analysis by Monte Carlo Simulation (Indirect Simulation Method, Direct Simulation Method)

Transport Theory for System Reliability

Dynamic reliability methods: accidental scenarios simulation and processing

  • Markov Chain Monte Carlo for model and parameter identification
  • Monte Carlo and possibilistic methods for Uncertainty and Sensitivity analysis
  • Particle Filtering for diagnosis, prognosis and on condition maintenance

 

COURSE GOALS

Students will learn the most advanced methods of Monte Carlo (MC) simulation to quantitatively model the behavior of stochastic engineering systems and perform uncertainty and sensitivity analyses, e.g. those typical of the energy, nuclear, aerospace, chemical, structural, hydraulic, environmental, electrical and mechanical fields.

 


Note Sulla Modalità di valutazione

Final exam consisting in a group project.


Intervallo di svolgimento dell'attività didattica
Data inizio
Data termine

Calendario testuale dell'attività didattica

Rooms of all lectures to be defined. They will be in CAMPUS BOVISA

 

LECTURE 1

Lecturer: Enrico Zio

December 2nd , 2016, 10:15-13:15

Introduction to Monte Carlo Simulation

 

LECTURE 2

Lecturer: Enrico Zio

December 5th, 2016, 10:15-12:15

Monte Carlo Simulation for reliability and availability analysis in complex systems

 

LECTURE 3

Lecturer: Piero Baraldi

December 12th, 9:15-13:15

Examples and Exercises on Monte Carlo Simulations

 

LECTURE 4

Lecturer: FrancescoCadini

December 14th, 10:15-13:15

Particle Filtering for diagnosis, prognosis and on condition maintenance

 

LECTURE 5

Lecturer: FrancescoCadini

December 16th, 10:15-13:15

Exercises on particle filtering for diagnosis, prognosis and on condition maintenance

 

LECTURE 6

Lecturer: Francesco Di Maio

December 19th, 2016, 10:15-13:15

Dynamic reliability methods: accidental scenarios simulation and processing (Part 1)

 

LECTURE 7

Lecturer: Francesco Di Maio

December 21th, 2016, 10:15-13:15

Dynamic reliability methods: accidental scenarios simulation and processing (Part 2)

 

LECTURE 8 (to be confirmed)

Lecturer: Nicola Pedroni (Ecole Centrale, Paris)

January 9th, 2017, 10:15-13:15

Markov Chain Monte Carlo for model and parameter identification

 

LECTURE 9

Lecturer: Piero Baraldi

January 11th, 2017, 10:15-13:15

Monte Carlo and possibilistic methods for uncertainty analysis

 

LECTURE 10

Lecturer: Piero Baraldi

January 13th, 2017, 10:15-13:15

Examples and exrcises on Monte Carlo and possibilistic methods for uncertainty analysis

 

EXAM

February 1st, 2017; 10:15-13:15

Discussion of the projects


Bibliografia
Risorsa bibliografica facoltativaE. Zio, The Monte Carlo Simulation Method for System Reliability and Risk Analysis, ISBN: 978-1-4471-4588-2
Risorsa bibliografica facoltativaTerje Aven, Enrico Zio, Piero Baraldi, Roger Flage, Uncertainty in Risk Assessment: The Representation and Treatment of Uncertainties by Probabilistic and Non-Probabilistic Methods, ISBN: 978-1-118-48958-1

Software utilizzato
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Mix Forme Didattiche
Tipo Forma Didattica Ore didattiche
lezione
25.0
esercitazione
0.0
laboratorio informatico
0.0
laboratorio sperimentale
0.0
progetto
4.0
laboratorio di progetto
0.0

Informazioni in lingua inglese a supporto dell'internazionalizzazione
Insegnamento erogato in lingua Inglese
Disponibilità di materiale didattico/slides in lingua inglese

Note Docente
schedaincarico v. 1.6.9 / 1.6.9
Area Servizi ICT
21/01/2022