II semester

Electronic Interfaces (block B-opt) (since 2022-23)

Simona Ranieri 1st year, 6 CFU, a.a.2022-2023, b-choice2A, Block B, II semester, Subjects , ,
Electronic Interfaces (block B-opt) (since 2022-23)
1 YEAR II semester  6 CFU
Christian Falconi A.Y. 2022-23 (new)
Code: 80300103
SSD: ING-INF/01

FORMATIVE OBJECTIVES

LEARNING OUTCOMES:
The goal is to teach the fundamental principles and tools for designing electronic interfaces.
The contents of the course have general validity, but the focus will be on electronic interfaces for mechatronics.
The course is oriented toward design.

KNOWLEDGE AND UNDERSTANDING:
Students will need to know and understand the fundamental principles and tools for the analysis and design of electronic interfaces.

APPLYING KNOWLEDGE AND UNDERSTANDING:
Students will have to demonstrate that they are able to design electronic interfaces.

MAKING JUDGEMENTS:
Students will be able to evaluate the design of electronic interfaces.

COMMUNICATION SKILLS:
The students, in addition to illustrating the fundamental principles and tools for the design of electronic interfaces, must be able to explain each design choice.

LEARNING SKILLS:
Students must be able to read and understand scientific texts and articles (also in English) concerning electronic interfaces.

PREREQUISITES

Thévenin equivalent circuit.
Norton equivalent circuit.
Laplace transform
Fourier transform

Syllabus:

Fundamentals on electronic devices.
Equivalent circuits (mechanic systems, thermal systems,…).
Diode circuits.
Transistor circuits.
Nullors.
Operational amplifiers (op amps).
Universal active devices.
Non-idealities of op-amps and other universal active devices.
Op-amp circuits.
Simulations of electronic circuits (SPICE).
Electronic interfaces.
Circuits for mechatronics (design examples).

MEASUREMENT SYSTEMS FOR MECHATRONICS

Simona Ranieri 2nd year, 6 CFU, a.a.2022-2023, ALL blocks, Block A, Block B, Block C, II semester, Subjects , ,
MEASUREMENT SYSTEMS FOR MECHATRONICS
2 YEAR II semester  6 CFU
Arianna Mencattini A.Y. 2021-22

A.Y. 2022-23
A.Y. 2023-24

Computer Vision A.Y. 24-25
Code: 8039787
SSD: ING/INF/07

LEARNING OUTCOMES: Learning basic concepts in digital image processing and analysis as a novel measurement system in biomedical fields. The main algorithms will be illustrated particularly devoted to the image medical fields.

KNOWLEDGE AND UNDERSTANDING: The student acquires knowledge related to the possibility to use an image analysis platform to monitor the dynamics of a given phenomenon and to extract quantitative information from digital images such as object localization and tracking in digital videos.

APPLYING KNOWLEDGE AND UNDERSTANDING: The student acquires the capability to implement the algorithms in Matlab through dedicated lessons during the course with the aim of being able to autonomously develop new codes for the solution of specific problems in different application fields.

MAKING JUDGEMENTS: :
The student must be able to integrate the basic knowledge provided with those deriving from the other courses such as probability, signal theory, and pattern recognition. some fundamentals of measurement systems as well as basic metrological definitions will be provided in support of background knowledge.

COMMUNICATION SKILLS:
The student solves a written test and develops a project in Matlab that illustrates during the oral exam. The project can be done in a group to demonstrate working group capabilities.

LEARNING SKILLS:
Students will be able to read and understand scientific papers and books in English and also to deepen some topics. In some cases, students will develop also experimental tests with time-lapse microscopy acquisition in the department laboratory.

 

SYLLABUS:

Fundamentals of metrology. Basic definitions: resolution, accuracy, precision, reproducibility, and their impact over an image based measurement system. Image processing introduction. Image representation. Spatial and pixel resolution. Image restoration. Deconvolution. Deblurring. Image quality assessment. Image enhancement. Image filtering for smoothing and sharpening. Image segmentation: pixel based (otsu method), edge based, region based (region growing), model based (active contour, Hough transform), semantic segmentation. Morphological operators. Object recognition and image classification. Case study: defects detection, object tracking in biology, computer assisted diagnosis, facial expression in human computer interface.
Matlab exercises.

POWERTRAIN TECHNOLOGIES FOR FUTURE MOBILITY (ex Internal Combustion Engines)

Simona Ranieri 1st year, 2nd year, 9 CFU, a.a.2022-2023, ALL blocks, Block A, Block B, Block C, II semester, Subjects , , ,
POWERTRAIN TECHNOLOGIES FOR FUTURE MOBILITY (ex Internal Combustion Engines)
1 YEAR (Block C)

2 YEAR (Blocks A|B)

 II semester  9 CFU
Stefano CORDINER (6/9 cfu)
Lorenzo BARTOLUCCI (3/9 cfu)
 A.Y. 2021-22

Internal Combustion Engines
A.Y. 2022-23

POWERTRAIN TECHNOLOGIES FOR FUTURE MOBILITY
Code: 80300079
SSD: ING/IND/08
(by Mechanical Engineering)

 

LEARNING OUTCOMES:
The aim of the course is to provide students with in-depth scientific training to properly address the design, selection and management of internal combustion engines and their interaction with the environment, as well as to create the conditions for the development of innovative solutions. To this aim, students will develop in-depth knowledge of the principles of engine operation and learn simulation procedures for testing and sizing an alternative internal combustion engine and its main components. Special attention is also given to the latest technological development of internal combustion engine technology aimed at exceeding current limits in terms of emissions and efficiency and defining innovative scenarios of sustainable mobility.

KNOWLEDGE AND UNDERSTANDING:
The course aim is to provide the students with tools for the analysis of the performances and the evaluation of proper design solutions for internal combustion engines and their core components. At the end of the course, the student will be able to independently understand the functional link between design variables and the performance of internal combustion engines also in case of innovative design,

APPLYING KNOWLEDGE AND UNDERSTANDING:
The course, through the analysis of specific problems and quantitative data, is aimed at providing the tools for analysis and evaluation of the effects of different design choices. The theme of energy efficiency and pollution reduction are at the heart of the teaching organization. The student will be able to interpret and propose design solutions, even innovative ones, adapted to the specificity of the problems that are presented to him.

MAKING JUDGEMENTS:
By studying theoretical and practical aspects of engine design and critically assessing the influence of different design variables, the student will be able to improve his judgment and proposal in relation to design. and the management of internal combustion engines.

COMMUNICATION SKILLS:
The presentation of the theoretical and application profiles underlying the operation of internal combustion engines will be carried out to allow the knowledge of the technical language of the appropriate specialist terminology; The development of communication skills, both oral and written, will also be stimulated through classroom discussion, participation in seminary activities and through final tests.

LEARNING SKILLS:
The learning capacity, even individual, will be stimulated through numerical exercises, the drafting of papers on specialized topics, the discussion in the classroom, also aimed at verifying the actual understanding of the topics treated. The learning capacity will also be stimulated by integrative educational aids (journal articles and economic newspapers) in order to develop autonomous application capabilities.

SYLLABUS:

General information on internal combustion engines: Characteristics and Classification, thermodynamic and performance analysis. Experimental analysis of the performance of an internal combustion engine Air Supply for 4-stroke engines: volumetric efficiency and its evaluation, quasi-stationary effects; valve sizing; the influence of other engine parameters; Variable Valve Actuation systems; non-stationary phenomena in the intake and exhaust: inertia and wave propagation; variable valve geometry systems, computational models; 2-stroke engines: construction schemes; Supercharging; In cylinder charge motion: Turbulence; swirl, squish, tumble, stratified charge engines Traditional and alternative fuels; Fuels general properties: fuel, air stoichiometric; calorific value gaseous fuels: natural gas, hydrogen and mixtures thereof. bioethanol , bio-diesel and DME. Features and their use in engines: technical solutions, performance and emissions Fuel metering. Otto engines: carburetor; injection systems; lambda probe. Diesel engines: fuel injectors and injection systems, dimensioning. Experimental tests on a diesel injection system Common Rail Combustion: Fundamentals of analytical study of combustion, thermodynamics of combustion processes, calculation of the chemical composition and temperature in adiabatic equilibrium transport phenomena (notes), chemical kinetics (notes). Combustion in Otto and Diesel engines. Emissions and their control systems: emissions formation mechanisms, effects on health and environment, measurement of emissions; influence of engine parameters, test cycles and legislation; procedures and systems for the reduction of emissions in engines. Experimental tests. Cooling system: Heat flows, heat transfer in the engine cooling systems, liquid and air: structural layouts and sizing; thermal stress of the mechanical parts. Sustainable mobility. Principles of operation of hybrid vehicles: series and parallel solution; engines there and electrical workers, regenerative braking, lithium batteries, performance and prospects. Plug-in hybrid vehicles, engines c.i. ” Range extender “. Electric vehicles, characteristics and perspectives For all the topics of the course the numerical simulation tools will be presented

 

Digital Signal Processing (block C-opt)

Simona Ranieri 1st year, 6 CFU, a.a.2022-2023, Block C, c-choice2, II semester, Subjects , ,
Digital Signal Processing (block C-opt)
1 YEAR II semester  6 CFU
ICT and Internet Engineering
Marina RUGGIERI

 

 A.Y. 2023-24
Code: 8039514
SSD: ING-INF/03

OBJECTIVES

LEARNING OUTCOMES: The course aims at providing to the students the theoretical and practical tools for the development of design capabilities and implementation awareness of Digital Signal Processing (DSP) systems and applications.

KNOWLEDGE AND UNDERSTANDING: Students are envisaged to understand the DSP theoretical, design and algorithm elements and to be able to apply them in design exercises.

APPLYING KNOWLEDGE AND UNDERSTANDING: Students are envisaged to apply broadly and to personalize the design techniques and algorithm approaches taught during the lessons.

MAKING JUDGEMENTS: Students are envisaged to provide a reasoned description of the design and algorithm techniques and tools, with proper integrations and links.

COMMUNICATION SKILLS: Students are envisaged to describe analytically the theoretical elements and to provide a description of the design techniques and the algorithm steps, also providing eventual examples.

LEARNING SKILLS: Students are envisaged to deal with design tools and manuals. The correlation of topics is important, particularly when design trade-offs are concerned.

BACKGROUND

A good mathematical background (in particular on complex numbers, series, functions of complex variable) is strongly recommended.

PROGRAMME

PART I – Discrete-time signals and systems; sampling process; Discrete-time Fourier transform (DTFT); Z-transform; Discrete Fourier Series (DFS).
PART II – Processing algorithms: introduction to processing; Discrete Fourier Transform (DFT); finite and long processing; DFT-based Processing; Fast Fourier Transform (FFT); processing with FFT.
PART III – Filter Design: introduction to digital filters: FIR and IIR classification; structures, design and implementation of IIR and FIR filters; analysis of finite word length effects; DSP system design and applications; VLAB and applications (Dr. Tommaso Rossi) with design examples and applications of IIR and FIR filters, Matlab-based lab and exercises (optional).

TEXTBOOKS

[1] “Digital Signal Processing Exercises and Applications”, Marina Ruggieri, Michele Luglio, Marco Pratesi. Aracne Editrice, ISBN: 88-7999-907-9.
[2] The River Publishers’ Series in Signal, Image & Speech Processing, “An Introduction to Digital Signal Processing: A Focus on Implementation”, Stanley Henry Mneney. River Publishers, ISBN: 978-87-92329-12-7.
[3] Slides (exercises are also included therein), published on the teaching website.

Mechanics of Materials and Structures (block A)

Simona Ranieri 1st year, 6 CFU, a.a.2022-2023, Block A, II semester, Subjects ,
Mechanics of Materials and Structures (block A)
1 YEAR II semester  6 CFU
Andrea Micheletti

Edoardo Artioli

 A.Y. 2021-22 (9 cfu)
Andrea Micheletti A.Y. 2022-23 (6 cfu)
Code: 80300064
SSD: ICAR/08
(by Engineering Sciences)

FORMATIVE OBJECTIVES

LEARNING OUTCOMES: The goal of this course, composed of two Modules, is to provide the student with basic knowledge of the mechanics of linearly elastic structures and of the strength of materials. By completing this class successfully, the student will be able to compute simple structural elements and reasonably complex structures.

KNOWLEDGE AND UNDERSTANDING: At the end of this course, the student will be able to:
– compute constraint reactions and internal actions in rigid-body systems and beams subjected to point/distributed forces and couples
– compute centroid position and central principal second-order moments of area distributions
– understand the formal structure of the theory of linear elasticity for beams and 3D bodies
– analyze strain and stress states in 3D bodies
– compute the stress state in beams subjected to uniaxial bending, biaxial bending, eccentric axial force
– understand the behaviour of beams subjected to shear with bending and torsion
– understand how to compute displacements/rotations in isostatic beam systems, how to solve statically underdetermined systems, how to apply yield criteria, and how to design beams against buckling

APPLYING KNOWLEDGE AND UNDERSTANDING: The student will apply the knowledge and understanding skills developed during the course to the analysis of practical problems. This includes the analysis of linearly elastic structures and structural members in terms of strength and stiffness.

MAKING JUDGEMENTS: The student will have to demonstrate his awareness of the modeling assumptions useful to describe and calculate structural elements, as well as his critical judgement on the static response of elastic structures under loads, in terms of stresses, strains, and displacements.

COMMUNICATION SKILLS: The student will demonstrate, mostly during the oral test, his capacity of analyzing and computing the static response of linearly elastic structures, as well as his knowledge of the underlying theoretical models.

LEARNING SKILLS: The student will get familiar with the modeling of structures and structural elements in practical problems, mostly during the development of his skills for the written test. This mainly concerns beams and three-dimensional bodies.

PREREQUISITES: The student should have already attended the basic courses of calculus, geometry, and physics.
It is required that the student has good skills with regard to differential and integral calculus, linear algebra and matrix calculations.

SYLLABUS:

Together with the other Module of this course, the following topics are covered.

Review of basic notions of vector and tensor algebra and calculus.
Kinematics and statics of rigid-body systems.
Geometry of area distributions.
Strain and stress in 3D continuous bodies and beam-like bodies.
Virtual power and virtual work equation for beams and 3D bodies.
One-dimensional beam models: Bernoulli-Navier model, Timoshenko model, constitutive equations, governing differential equations.
Constitutive equation for linearly elastic and isotropic bodies, material moduli.
Hypothesis in linear elasticity, equilibrium problem for linearly elastic beams and 3D bodies.
Three-dimensional beam model: the Saint-Venant problem, uniaxial and biaxial bending, eccentric axial force, shear and bending, torsion.
Elastic energy of beams and 3D bodies, work-energy theorem, Betti’s reciprocal theorem, Castigliano’s theorem.
Yield criteria (maximum normal stress, maximum tangential stress, maximum elastic energy, maximum distortion energy).
Buckling instability, bifurcation diagrams, load and geometry imperfections, Euler buckling load, design against buckling.
Basic notions on the finite element method and structural analysis software.

Analogue Electronics (block B-opt)

Simona Ranieri 1st year, 6 CFU, a.a.2022-2023, b-choice2A, Block B, Engineering Sciences, II semester, Subjects , ,
Analogue Electronics (block B-opt)
1 YEAR II semester  6 CFU
Rocco Giofre’ A.Y. 2021-22

A.Y. 2022-23
Paolo Colantonio A.Y. 2023-24
Code: 80300060
SSD: ING-INF/01
(by Engineering Sciences)

LEARNING OUTCOMES:
Learning the basic concept of analogue electronic systems and circuits and developing the competencies to design electronic circuits.
The educational objectives are pursued through lectures and exercises.

KNOWLEDGE AND UNDERSTANDING:
The student acquires the basic conceptual and analytical knowledge, both theoretical and applied, of the main basic electronic components. Subsequently, it acquires knowledge related to the integration of basic electronic components for the development of more complex electronic systems, such as amplifiers, oscillators, rectifiers, etc.

APPLYING KNOWLEDGE AND UNDERSTANDING:
The student will demonstrate to have acquired the methodologies for the analysis and synthesis (design) of simple electronic circuits.

MAKING JUDGEMENTS:
The student must be able to integrate the basic knowledge provided with those deriving from physics, mathematics, and electrical engineering courses, in order to correctly select the most appropriate analytical and circuit synthesis options.

COMMUNICATION SKILLS:
Students must be able to illustrate the basic themes of the course synthetically and analytically, linking together the different concepts that are integrated into more complex electronic systems.

Prerequisite: Knowledge of network analysis in general.

SYLLABUS:

Diode semiconductor devices and circuit applications: clipper, clamper, peak detector, etc. Bipolar Junction and Field Effect Transistors. Biasing techniques for Transistors. Amplifiers classification, analysis, and circuit design. Frequency response of single and cascaded amplifiers. Differential amplifiers and Cascode. Current mirrors. Feedback amplifiers and stability issues. Power amplifiers. Operational amplifiers and related applications. Oscillator circuits. Integrated circuits and voltage waveform generators.

Books for references
“Electronics: a systems approach”, Neil Storey, Prentice Hall
“Elettronica di Millman”, J. Millman, A. Grabel, P. Terreni, McGraw-Hill

HOW TO ATTEND LESSONS:

Although attendance is optional, given the complexity of the topics covered, it is strongly recommended to follow the lessons.