Numerical and statistical methods for Civil Engineering aims at providing students with fundamental knowledge on numerical and statistical methods for civil engineering problems, and at developing the competences required for designing and coding simple numerical and statistical models, also to learn how apply high level softwares for engineering analysis.
The course aims at providing in depth knowledge of 1) a technical/scientific programming language; 2) main numerical methods for the solution of ordinary and partial differential equations; 3) descriptive and inferential statistics.
Students shall be able of: 1) using a technical/scientific programming language to develop numerical models and to carry out statistical analyses; 2) designing, developing, validating and applying algorithms for the integration of ordinary and partial differential equations of interest for the civil engineering field; 3) carrying out statistical analysis on large datasets; 4) designing and carrying out statistical analyses; 5) finding and understanding scientific publications for specific problems of interest, also using scientific search engines/databases (Scopus, Web Of Science)
The course aims at providing in depth knowledge of 1) a technical/scientific programming language; 2) main numerical methods for the solution of ordinary and partial differential equations; 3) descriptive and inferential statistics.
Students shall be able of: 1) using a technical/scientific programming language to develop numerical models and to carry out statistical analyses; 2) designing, developing, validating and applying algorithms for the integration of ordinary and partial differential equations of interest for the civil engineering field; 3) carrying out statistical analysis on large datasets; 4) designing and carrying out statistical analyses; 5) finding and understanding scientific publications for specific problems of interest, also using scientific search engines/databases (Scopus, Web Of Science)
Curriculum
scheda docente
materiale didattico
Risk assessment and management: probabilistic methods of risk quantification, risk matrices, risk analysis as a tool to support land use planning and management.
Vulnerability analysis: natural hazard simulation models, techniques for identifying and characterizing natural hazards (Monte Carlo simulation), hazard maps, techniques for characterizing the response of systems, structures and infrastructure to natural stresses (fragility curves).
Lectures will be supported by examples related to risk and resilience analysis of civil systems, structures and infrastructure exposed to natural hazards, and by exercises.
Pinto, P.E., Giannini, R., and Franchin, P., 2004 - Seismic reliability. IUSS Press.
Mays, L.W., and Tung, T.-K., 1992 - Hydrosystems - McGrow-Hill
Zio, E., 2012 - Monte Carlo Simulation. Springer
Programma
Qualitative and quantitative definitions of hazard, vulnerability, fragility, risk and resilience.Risk assessment and management: probabilistic methods of risk quantification, risk matrices, risk analysis as a tool to support land use planning and management.
Vulnerability analysis: natural hazard simulation models, techniques for identifying and characterizing natural hazards (Monte Carlo simulation), hazard maps, techniques for characterizing the response of systems, structures and infrastructure to natural stresses (fragility curves).
Lectures will be supported by examples related to risk and resilience analysis of civil systems, structures and infrastructure exposed to natural hazards, and by exercises.
Testi Adottati
Kottegoda, N. T., and Rosso, R., 2nd Edition, 2008. Applied statistics for civil and environmental engineers. BlackwellPinto, P.E., Giannini, R., and Franchin, P., 2004 - Seismic reliability. IUSS Press.
Mays, L.W., and Tung, T.-K., 1992 - Hydrosystems - McGrow-Hill
Zio, E., 2012 - Monte Carlo Simulation. Springer
Modalità Frequenza
Attendance is not mandatory but strongly recommended.Modalità Valutazione
Exam: The test consists of an oral interview covering the practical exercises and the theory. The exercises are designed to assess students' understanding of the concepts and their ability to apply them in real-world contexts. Exam assessment: The final grade will take into account the following elements: - The level and quality of knowledge of the topics - The ability to analyse a topic critically - The logic of the arguments in support of a thesis - The ability to apply theories and concepts to contexts - The use of vocabulary appropriate to the discipline being studied
scheda docente
materiale didattico
Risk assessment and management: probabilistic methods of risk quantification, risk matrices, risk analysis as a tool to support land use planning and management.
Vulnerability analysis: natural hazard simulation models, techniques for identifying and characterizing natural hazards (Monte Carlo simulation), hazard maps, techniques for characterizing the response of systems, structures and infrastructure to natural stresses (fragility curves).
Lectures will be supported by examples related to risk and resilience analysis of civil systems, structures and infrastructure exposed to natural hazards, and by exercises.
Pinto, P.E., Giannini, R., and Franchin, P., 2004 - Seismic reliability. IUSS Press.
Mays, L.W., and Tung, T.-K., 1992 - Hydrosystems - McGrow-Hill
Zio, E., 2012 - Monte Carlo Simulation. Springer
Programma
Qualitative and quantitative definitions of hazard, vulnerability, fragility, risk and resilience.Risk assessment and management: probabilistic methods of risk quantification, risk matrices, risk analysis as a tool to support land use planning and management.
Vulnerability analysis: natural hazard simulation models, techniques for identifying and characterizing natural hazards (Monte Carlo simulation), hazard maps, techniques for characterizing the response of systems, structures and infrastructure to natural stresses (fragility curves).
Lectures will be supported by examples related to risk and resilience analysis of civil systems, structures and infrastructure exposed to natural hazards, and by exercises.
Testi Adottati
Kottegoda, N. T., and Rosso, R., 2nd Edition, 2008. Applied statistics for civil and environmental engineers. BlackwellPinto, P.E., Giannini, R., and Franchin, P., 2004 - Seismic reliability. IUSS Press.
Mays, L.W., and Tung, T.-K., 1992 - Hydrosystems - McGrow-Hill
Zio, E., 2012 - Monte Carlo Simulation. Springer
Modalità Frequenza
Attendance is not mandatory but strongly recommended.Modalità Valutazione
Exam: The test consists of an oral interview covering the practical exercises and the theory. The exercises are designed to assess students' understanding of the concepts and their ability to apply them in real-world contexts. Exam assessment: The final grade will take into account the following elements: - The level and quality of knowledge of the topics - The ability to analyse a topic critically - The logic of the arguments in support of a thesis - The ability to apply theories and concepts to contexts - The use of vocabulary appropriate to the discipline being studied