CODE 60459 ACADEMIC YEAR 2024/2025 CREDITS 6 cfu anno 2 INGEGNERIA MECCANICA - ENERGIA E AERONAUTICA 9270 (LM-33) - GENOVA 6 cfu anno 2 INGEGNERIA MECCANICA - ENERGIA E AERONAUTICA 9270 (LM-33) - GENOVA SCIENTIFIC DISCIPLINARY SECTOR ING-IND/08 LANGUAGE Italian TEACHING LOCATION GENOVA SEMESTER 1° Semester MODULES Questo insegnamento è un modulo di: EXPERIMENTAL AND NUMERICAL METHODS FOR FLUID MACHINERY AND ENERGY SYSTEMS TEACHING MATERIALS AULAWEB OVERVIEW The module provides the basic knowledge to perform experimental measurements on fluid machinery by means of advanced measurement techniques, it also provides the post processing tools for the analysis of the unsteady time-signals encountered in such applications. AIMS AND CONTENT LEARNING OUTCOMES The aim of the course is to present and discuss the main components of a measuring chain, and to provide students with post-processing tools for statistical moments and time (frequency) dependent analysis. The basic laws governing the main fluid dynamic instrumentations (such as Hot-wire anemometry, Laser Doppler Velocimetry and Particle Image Velocimetry) are provided and experiments are presented. The theory and development of post-processing routines will be introduced, jointly with real applications and implementations of data analysis tools in Matlab. AIMS AND LEARNING OUTCOMES The student should be able to: - identify the proper probe for velocity and pressure fields investigation to be used, based on the specific definition of the quantities to be measured and in relation to the constrains regarding the accuracy, sensibility, spatial resolution and frequency response; - employ the different measuring techniques, setting the acquisition parameters for the inspection and analysis of three-dimensional unsteady flows of practical and industrial interest; - provide a statistical analysis of an ensemble of data, as well as a detailed characterization of the dynamics of complex systems by means of advanced post-processing routines like the Fast Fourier Transform, the auto- and cross-correlation coefficients and phase-locked ensemble averaging; - acquire expertize in the treatment of voltage signals as well as in the development of regression and calibration curves of complex systems. The post-processing routines will be developed in Matlab. TEACHING METHODS Frontal lessons will be mainly employed in the course. The basic rules describing the theory of the measurement chains, of signal analysis and the basic operating principles of the different probes introduced into the course will be provided to the student. Experimental activities will be also carried out in the Aerodynamics and Turbomachinery laboratory in order to provide to the student expertize in the setting and operation of the different probes presented in the course. Post-processing routines will be also developed in Matlab. It is strongly suggested the participation of the student to the lessons, since the examination is driven by arguments discussed and presented during the lessons Students who have valid certification of physical or learning disabilities on file with the University and who wish to discuss possible accommodations or other circumstances regarding lectures, coursework and exams, should speak both with the instructor and with Professor Federico Scarpa (federico.scarpa@unige.it), the Polytechnic School's disability liaison. SYLLABUS/CONTENT Introduction to the main components of a measuring chain: transducers, filters, amplifiers and A/D conversion board. Nyquist’s theorem. Frequency response and dynamic calibration. Data statistics. Errors due to finite number of samples and samples dispersion. Mean, rms and higher order statistical moments. Probability density function. Introduction to the basic laws governing different kind of probes and possible applications. Pneumatic probes (1,3, and 5 hole probes): static pressure taps, pressure transducers and directional calibration; Fast response aerodynamic pressure probes (FRAPP): frequency response and dynamic calibration; Hot-wire anemometry (HWA): King’s and Jorgensen’s laws; Laser Doppler Velocimetry (LDV): introduction to the Doppler effect. Seeding particles and their dynamic; Particle Image Velocimetry (PIV): cross-correlation and magnification ratio; Advanced post-processing techniques: phase-locked analysis, Fourier’s transform, cross-correlation and autocorrelation functions. Applications with Matlab codes. RECOMMENDED READING/BIBLIOGRAPHY VKI lecture series, Measurement Thecniques in Fluid Dynamics TEACHERS AND EXAM BOARD DAVIDE LENGANI Ricevimento: Meetings by appointment, by sending an email to davide.lengani@edu.unige.it or via TEAMS chat DANIELE SIMONI Ricevimento: By appointment Exam Board CARLO CRAVERO (President) DARIO BARSI DAVIDE LENGANI (President Substitute) DANIELE SIMONI (President Substitute) ANDREA CATTANEI (Substitute) MATTEO DELLACASAGRANDE (Substitute) DAVIDE MARSANO (Substitute) FERRUCCIO PITTALUGA (Substitute) FRANCESCA SATTA (Substitute) LESSONS LESSONS START https://corsi.unige.it/en/corsi/9270/studenti-orario Class schedule The timetable for this course is available here: Portale EasyAcademy EXAMS EXAM DESCRIPTION The examination is composed of two parts. The first consists in the discussion of an exercise focused on the post-processing of different kind of data acquired by the research group of the professor, and provided to the student some days before the examination data. In the second part an oral discussion of theoretical topics treated in the lessons will conclude the examination. The examination data will be provided previous appointment. Students with SLD, disability or other regularly certified special educational needs are advised to contact the instructor at the beginning of the course to agree on teaching and examination methods that, in compliance with the course objectives, take into account the individual learning requirements. ASSESSMENT METHODS The oral examination will allow verifying the acquired knowledge of the student regarding the theory of the different measurement techniques, as well as the mathematical foundations of the different post processing algorithms. With the exercise the capability of the student in the development of a Matlab program aimed at the statistical and dynamical inspection of an ensemble of data will be verified. Exam schedule Data appello Orario Luogo Degree type Note 13/02/2025 10:00 GENOVA Esame su appuntamento 12/09/2025 10:00 GENOVA Esame su appuntamento