{"id":5683,"date":"2024-10-04T17:32:27","date_gmt":"2024-10-04T17:32:27","guid":{"rendered":"https:\/\/www.lasar.polimi.it\/?page_id=5683"},"modified":"2026-06-05T16:32:13","modified_gmt":"2026-06-05T16:32:13","slug":"reliability-safety-and-risk-analysis","status":"publish","type":"page","link":"https:\/\/www.lasar.polimi.it\/?page_id=5683","title":{"rendered":"RELIABILITY, SAFETY AND RISK ANALYSIS – notes"},"content":{"rendered":"\n

INSTRUCTOR: PIERO BARALDI<\/em><\/span><\/strong><\/p>\n\n\n\n

\n\n\n\n

LECTURE SLIDES<\/strong><\/p>\n\n\n\n

Lecture 1 – Introduction<\/a><\/p>\n\n\n\n

Lecture 2 – Interpretation of Probability in Reliability and Risk Analysis<\/a><\/p>\n\n\n\n

Lecture 4 – Continuous Probability Distribution<\/a><\/p>\n\n\n\n

Lecture 5 – Simple Systems<\/a><\/p>\n\n\n\n

Lecture 6 – Availability<\/a><\/p>\n\n\n\n

Lecture 7 – Markov Chain Discrete Time<\/a><\/p>\n\n\n\n

Lecture 8 – Markov Chain Continuous Time <\/a><\/p>\n\n\n\n

Lecture 9 – Monte Carlo<\/a><\/p>\n\n\n\n

Lecture 11 – Parameter Estimation<\/a><\/p>\n\n\n\n

Lecture 12 – Estimation of components failure rates from statistical data: Bayesian approach<\/a><\/p>\n\n\n\n

Lecture 13 – Maintenance Basic Concepts<\/a><\/p>\n\n\n\n

Lecture 16 – Fault Tree Analysis<\/a><\/p>\n\n\n\n

Lecture 17 – Event Tree Analysis<\/a><\/p>\n\n\n\n

Lecture 18 – Dependent Failures<\/a><\/p>\n\n\n\n

Lecture 19 – Artificial Intelligence (AI) and Machine Learning (ML) in Nuclear Engineering and Technology<\/a><\/p>\n\n\n\n

Lecture 20 – Importance Measures<\/a><\/p>\n\n\n\n

\n\n\n\n

EXERCISE SESSIONS<\/strong><\/p>\n\n\n\n

Exercise 1 – Probability<\/a><\/p>\n\n\n\n

Exercise 2 – Availability, Maintainability and Reliability<\/a><\/p>\n\n\n\n

Exercise 3 – Markov Chains<\/a><\/p>\n\n\n\n

Exercise 4 – Monte Carlo<\/a><\/p>\n\n\n\n

Exercise 5 – Estimation of components failure rates from statistical data: A Bayesian approach<\/a><\/p>\n\n\n\n

Exercise 6a – Bayesian Network Theory<\/a><\/p>\n\n\n\n

Exercise 6b – Bayesian Network Exercises & Solutions<\/a><\/p>\n\n\n\n

Exercise 6c – Bayesian Network Applications<\/a><\/p>\n\n\n\n

\n\n\n\n

EXAM PREPARATION<\/strong><\/p>\n\n\n\n

Exam Simulation Mock<\/a><\/p>\n\n\n\n

Topics & Material To be Studied<\/a><\/p>\n\n\n\n

FLIPPED CLASS<\/strong><\/p>\n\n\n\n

Flipped Classroom Guidelines<\/a><\/p>\n\n\n\n

Flipped Classroom Theory<\/a><\/p>\n\n\n\n

Flipped Exercise<\/a><\/p>\n\n\n\n

Flipped Exercises Solutions<\/a><\/p>\n\n\n\n

\n\n\n\n

ADDITIONAL MATERIAL<\/strong><\/p>\n\n\n\n

Exercise 1 – Additional Problems<\/a><\/p>\n\n\n\n

\n\n\n\n

LECTURE RECORDINGS<\/strong><\/p>\n\n\n\n

Lecture Recording 23\/02\/26<\/a><\/p>\n\n\n\n

Lecture Recording 25\/02\/26<\/a><\/p>\n\n\n\n

Lecture Recording 02\/03\/26<\/a><\/p>\n\n\n\n

Lecture Recording 06\/03\/26<\/a><\/p>\n\n\n\n

Lecture Recording 13\/03\/26<\/a><\/p>\n\n\n\n

Lecture Recording 16\/03\/26<\/a><\/p>\n\n\n\n

Lecture Recording 20\/03\/26<\/a><\/p>\n\n\n\n

Lecture Recording 23\/03\/26<\/a><\/p>\n\n\n\n

Lecture Recording 27\/03\/26<\/a><\/p>\n\n\n\n

Lecture Recording 08\/04\/26<\/a><\/p>\n\n\n\n

Lecture Recording 10\/04\/26<\/a><\/p>\n\n\n\n

Lecture Recording 13\/04\/26<\/a><\/p>\n\n\n\n

Lecture Recording 15\/04\/26<\/a><\/p>\n\n\n\n

Lecture Recording 17\/04\/26 (Monte Carlo Exercise Session)<\/a><\/p>\n\n\n\n

Lecture Recording 20\/04\/26<\/a><\/p>\n\n\n\n

Lecture Recording 22\/04\/26<\/a><\/p>\n\n\n\n

Lecture Recording 29\/04\/26<\/a><\/p>\n\n\n\n

Lecture Recording 13\/05\/26<\/a><\/p>\n\n\n\n

Lecture Recording 18\/05\/26<\/a><\/p>\n\n\n\n

Lecture Recording 20\/05\/26<\/a><\/p>\n\n\n\n

Lecture Recording 22\/05\/26<\/a><\/p>\n\n\n\n

Lecture Recording 27\/05\/26<\/a><\/p>\n\n\n\n

Lecture Recording 29\/05\/26<\/a><\/p>\n\n\n\n

Lecture Recording 03\/06\/26<\/a><\/p>\n\n\n\n

Lecture Recording 05\/06\/26 – Part I<\/a><\/p>\n\n\n\n

Lecture Recording 05\/06\/26 – Part II<\/a><\/p>\n\n\n\n

Lecture 4 – Continuous Probability Distribution (Video Link)<\/a><\/p>\n\n\n\n

<\/p>\n","protected":false},"excerpt":{"rendered":"

INSTRUCTOR: PIERO BARALDI LECTURE SLIDES Lecture 1 – Introduction Lecture 2 – Interpretation of Probability in Reliability and Risk Analysis Lecture 4 – Continuous Probability Distribution Lecture 5 – Simple Systems Lecture 6 – Availability Lecture 7 – Markov Chain Discrete Time Lecture 8 – Markov Chain Continuous Time Lecture […]<\/p>\n","protected":false},"author":1,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"inline_featured_image":false,"footnotes":""},"class_list":["post-5683","page","type-page","status-publish","hentry"],"a3_pvc":{"activated":false,"total_views":0,"today_views":0},"_links":{"self":[{"href":"https:\/\/www.lasar.polimi.it\/index.php?rest_route=\/wp\/v2\/pages\/5683","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.lasar.polimi.it\/index.php?rest_route=\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/www.lasar.polimi.it\/index.php?rest_route=\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/www.lasar.polimi.it\/index.php?rest_route=\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/www.lasar.polimi.it\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=5683"}],"version-history":[{"count":156,"href":"https:\/\/www.lasar.polimi.it\/index.php?rest_route=\/wp\/v2\/pages\/5683\/revisions"}],"predecessor-version":[{"id":7972,"href":"https:\/\/www.lasar.polimi.it\/index.php?rest_route=\/wp\/v2\/pages\/5683\/revisions\/7972"}],"wp:attachment":[{"href":"https:\/\/www.lasar.polimi.it\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=5683"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}