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)
teacher profile teaching materials
2-Ordinary differential equations
3-Partial differential equations
4-Descriptive statistics
5-Inferential statistics
-Chapra S., 2018. Applied Numerical Methods with MATLAB for Engineers and Scientists, 4th Edition, McGrawHill Education.
-Chapra S., Canale R., 2015. Numerical Methods for Engineers 7th Edition, McGrawHill Education.
-Ross S. M., 2015. Probabilità e statistica per l'Ingegneria e le scienze, Apogeo Education.
-Navidi W., 2006. Probabilità e statistica per l'Ingegneria e le scienze, Apogeo McGraw-Hill.
Mutuazione: 20810101 METODI NUMERICI E STATISTICI PER L'INGEGNERIA CIVILE in Ingegneria civile per la protezione dai rischi naturali LM-23 BELLOTTI GIORGIO
Programme
1-Introduction to programming in Matlab2-Ordinary differential equations
3-Partial differential equations
4-Descriptive statistics
5-Inferential statistics
Core Documentation
-Lecture notes-Chapra S., 2018. Applied Numerical Methods with MATLAB for Engineers and Scientists, 4th Edition, McGrawHill Education.
-Chapra S., Canale R., 2015. Numerical Methods for Engineers 7th Edition, McGrawHill Education.
-Ross S. M., 2015. Probabilità e statistica per l'Ingegneria e le scienze, Apogeo Education.
-Navidi W., 2006. Probabilità e statistica per l'Ingegneria e le scienze, Apogeo McGraw-Hill.
Type of delivery of the course
Theoretical and applied lectures. About two lectures will take place in the computational laboratory. Students should develop the exercises using Matlab, for which the University offers a campus license.Type of evaluation
The exam consists in the development of about 10 numerical and statistical exercises, to be completed in two hours. The students work directly at the pc. During the COVID-19 emergency the exam is carried out according to the art. 1 of the Decreto rettorale n. 703 (May 5th 2020). The students will share the screen of their PC and will show how to develop, in about 30 minutes, the solution of 2-3 exercises.