6 CFU

Fundamentals of Mechanisms of Systems (block A) (since 2022-23)

Simona Ranieri 1st year, 6 CFU, a.a. 2022-23, a.a. 2023-24, a.a. 2024-25, Block A, I sem, Subjects ,
Fundamentals of Mechanisms of Systems (block A) (since 2022-23)
1 YEAR
 1 semester 6 CFU
Marco Ceccarelli A.Y. 2021-22 to 2024-25

A.Y. 2025-26 new name: 80300216 MECHANICS OF SYSTEMS FOR SIMULATIONS
Code: 803000062
SSD: ING-IND-13
(by Engineering Sciences)

OBJECTIVES

LEARNING OUTCOMES: The course aims to teach students the knowledge and tools that are needed to address the issues that are related to the identification, modeling, analysis, and design of multi-body planar systems in English language and terminology

KNOWLEDGE AND UNDERSTANDING: modeling and procedures to recognize the structure and characteristics of mechanisms and machines

APPLYING KNOWLEDGE AND UNDERSTANDING: acquisition of analysis procedures for the understanding of kinematic and dynamic characteristics of mechanisms and machines

MAKING JUDGEMENTS: possibility of judging the functionality of mechanisms and machines with their own qualitative and quantitative assessments

COMMUNICATION SKILLS: learning technical terminology and procedures for presenting the performance of mechanisms

LEARNING SKILLS: learning technical terminology and procedures for the presentation of the performance of mechanisms

PREREQUISITES: knowledge of basic mechanics of rigid bodies and computation skills

SYLLABUS

Structure and classification of planar mechanical systems, kinematic modeling, mobility analysis, graphical approaches of kinematics analysis, kinematic analysis with computer-oriented algorithms; dynamics and statics modeling, graphical approaches of dynamics analysis, dynamic analysis with computer-oriented algorithms, performance evaluation; elements of mechanical transmissions.

BOOKS:

Lopez-Cajùn C., Ceccarelli M., Mecanismos, Trillas, Città del Messico
Shigley J.E., Pennock G.R., Uicker J.J., “Theory of Machines and Mechanisms”, McGraw-Hill, New York
Handnotes and papers by the teachers

Digital Signal Processing 6cfu (block C1opt-C2-opt)

Simona Ranieri 1st year, 6 CFU, a.a. 2022-23, a.a. 2025-26, Block C, Block C1, Block C2, c-choice2, c1-choice31, c2-choice2, II semester, Subjects , , , , ,
Digital Signal Processing 6cfu (block C1opt-C2-opt)
1 YEAR II semester  6 CFU
ICT and Internet Engineering
Marina RUGGIERI (5cfu)

Tommaso ROSSI (1cfu)

 A.Y. 2023-24
A.Y. 2024-25
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

(Prof. M.RUGUERI)

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;
PART IV – Random sequences; processing of random sequences with digital filters; introduction to random sequence estimation; estimators of mean, variance and auto-covariance of random sequences with performance analysis; power spectrum estimation; periodogram and performance analysis; smoothed estimators of the power spectrum and performance analysis; use of FFT in power spectrum estimation.

(Dott. Tommaso ROSSI)

PART V – VLAB: applications with design examples and applications of IIR and FIR filters, Matlab-based lab and exercises; use of Matlab in the power spectrum estimation.

 

VERIFICATION CRITERIA

a) Combination of: design test (written); deepening on DSP System development (written); oral.
The design test is propedeutic to the oral one.
The course offers a verify in progress (with a related recovery date) that if passed exempts from the design test of the exam session.

b) The written exam includes design exercises.
The oral part envisages questions on the whole program and a discussion on the design test.

c) The written exam is scored from FAIL to EXCELLENT. The design test and the oral concur almost evenly to the final score (x/30).

d) The final score is based on the level of knowledge of the theoretical, design and algorithm elements and tools as well as on their effective use in design exercises; in particular, the final evaluation refers to 70% of the student’s knowledge level and for 30% to her/his capability of expressing the knowledge and providing an autonomous judgment in the design and oral exam phases.

The detailed final evaluation criteria are as follows:

Failed exam: deep lack and/or inaccuracy of knowledge and comprehension of topics and design techniques; limited capabilities in analysis and synthesis, critical ability and judgment; designs and topics are presented with a non-coherent and technically inadequate approach.
18-20: sufficient knowledge and comprehension of topics and design techniques with possible imperfections; sufficient capabilities in analysis, synthesis and autonomous judgment; designs and topics are presented with a not too much coherent and technically appropriate approach.
21-23: flat knowledge and comprehension of topics and design techniques; appropriate capabilities in analysis and synthesis with fair autonomous judgment; designs and topics are presented with sufficient coherency and technically appropriate approach.
24-26: more than fair knowledge and comprehension of topics and design techniques; good capabilities in analysis and synthesis with good autonomous judgment; designs and topics are presented with coherency and technically appropriate approach.
27-29: complete knowledge and very good comprehension of topics and design techniques; remarkable capabilities in analysis and synthesis with very good autonomous judgment; designs and topics are presented with a rigorous and technically very appropriate approach.
30-30L: excellent knowledge and complete comprehension of topics and design techniques; excellent capabilities in analysis and synthesis with excellent autonomous judgment and originality; designs and topics are presented with a rigorous and technically excellent approach.

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.

Thermodynamics and Heat Transfer (block A)

Simona Ranieri 1st year, 6 CFU, a.a. 2024-25, Block A, II semester, Subjects ,
Thermodynamics and Heat Transfer (block A)
1 YEAR II semester  6 CFU
Michela GELFUSA A.Y. 2021-22 (by Engineering Sciences)

A.Y. 2024-25 (last year)
Code: 80300063
SSD: ING-IND/10
(by Engineering Sciences)
  • Prerequisites: Knowledge of basic notions from physics courses, above all physical quantities, units of measurement, fundamental laws of mechanics, optics and electromagnetism.
  • Objectives:
  • LEARNING OUTCOMES: The course aims to provide students with the basic principles, physical laws, and applications of thermodynamics and heat transfer, with the dual purpose of preparing them to afford more applicative courses, and use the acquired knowledge for design and sizing simple components and thermal systems.
  • KNOWLEDGE AND UNDERSTANDING: Students will have to understand the laws of applied thermodynamics and heat transfer, and understand the structure and operation of simplest components and systems. They will also demonstrate that they have acquired the basic methodologies for verifying and designing the studied devices.
  • APPLYING KNOWLEDGE AND UNDERSTANDING: Students should be able to size and/or verify simple components and systems, such as, for example engine systems.
  • MAKING JUDGEMENTS: Students will have to acquire the autonomous ability to face subsequent studies for which this course is preparatory, and to draw up simple projects of thermal systems that use the components studied. They will also have to be able to evaluate projects drawn up by other parties, checking that the project specifications are respected. COMMUNICATION SKILLS: Students must be able to illustrate in a complete and exhaustive way the acquired information, the results of their study and of their project activity, also through the normally used means of communication (discussion of the results obtained, report on the performed activity, Power Point presentations, etc.).
  • LEARNING SKILLS: Students must be able to apply the physical laws underlying the studied phenomena, and to face further studies that use the acquired knowledge. They will have to be able to expand the already owned information through the analysis of technical-scientific literature, and to modify their curricula choosing future knowledge to be acquired on the base of their knowledge and tendency.

 

Mechanics of Materials and Structures – 6 CFU (block A-E)

Simona Ranieri 1st year, 6 CFU, a.a. 2022-23, a.a. 2023-24, a.a. 2024-25, a.a. 2025-26, Block A, Block E, II semester, Subjects ,
Mechanics of Materials and Structures – 6 CFU (block A-E)
1 YEAR II semester  6 CFU
Andrea Micheletti

Edoardo Artioli

 A.Y. 2021-22 (9 cfu)
Andrea Micheletti A.Y. 2022-23
A.Y. 2024-25 (6 cfu) – program 📑
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 – 9 CFU (block B-opt)

Simona Ranieri 1st year, 6 CFU, a.a. 2022-23, a.a. 2023-24, a.a. 2024-25, a.a. 2025-26, b-choice2A, Block B, Engineering Sciences, II semester, Subjects , ,
Analogue Electronics – 9 CFU (block B-opt)
1 YEAR II semester  6 CFU + 3 cfu extra
Rocco Giofre’ A.Y. 2021-22

A.Y. 2022-23
Paolo Colantonio A.Y. 2023-24 – program 📑
Code: 8037954 (9CFU)
80300060 (6CFU)
SSD: ING-INF/01
(by Engineering Sciences)

The students who include Analogue Electronics in their study plan are strongly advised to include it in its 9-CFU version, with the last 3 CFUs (out of 9) working as Extra Credits.

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.

NANOTECHNOLOGY – 6 CFU

Simona Ranieri 1st year, 6 CFU, a.a. 2022-23, a.a. 2023-24, a.a. 2024-25, a.a. 2025-26, ALL blocks, Block A, Block B, Block C, Block C1, Block C2, Block D, Block E, II semester, Subjects ,
NANOTECHNOLOGY – 6 CFU
1 YEAR II semester  6 CFU
Antonio Agresti (3cfu)
Francesca De Rossi (3cfu)		 A.Y. 2021-22
Antonio Agresti (3cfu)
Fabio Matteocci (3cfu)		 A.Y. 2022-23
A.Y. 2023-24
Antonio Agresti (5cfu)

Sara Pescetelli (1cfu)

 A.Y. 2024-25
A.Y. 2025-26 – program 📑
Code: 8039791
SSD: ING-INF/01

 

Feedback Control Systems (block B)

Simona Ranieri 1st year, 6 CFU, a.a. 2022-23, a.a. 2023-24, a.a. 2024-25, b-choice2B, II semester, Subjects , ,
Feedback Control Systems (block B)
1 YEAR II semester  6 CFU
Cristiano M. VERRELLI since 2017-18 (Engineering Sciences)
since 2022-23 to 2024-25 (block B)
(Mechatronics Engineering)

2025-26 (block E)
Code: 8039367
SSD: ING-INF/04
DidatticaWeb

FORMATIVE OBJECTIVES

LEARNING OUTCOMES:

The theory of differential equations is successfully used to gain profound insight into the fundamental mathematical control design techniques for linear and nonlinear dynamical systems.

KNOWLEDGE AND UNDERSTANDING:

Students should be able to deeply understand (and be able to use) the theory of differential equations and of systems theory, along with related mathematical control techniques.

APPLYING KNOWLEDGE AND UNDERSTANDING:

Students should be able to design feedback controllers for linear (and even nonlinear) dynamical systems.

MAKING JUDGEMENTS:

Students should be able to identify the specific design scenario and to apply the most suitable techniques. Students should be able to compare the effectiveness of different controls while analyzing theoretical/experimental advantages and drawbacks.

COMMUNICATION SKILLS: Students are expected to be able to read and capture the main results of a technical paper concerning the topics of the course, as well as to effectively communicate in a precise and clear way the content of the course. Tutor-guided individual projects (including Maple and Matlab-Simulink computer simulations as well as visits to labs) invite intensive participation and ideas exchange.

LEARNING SKILLS:

Being enough skilled in the specific field to undertake the following studies characterized by a high degree of autonomy.

SYLLABUS:

The matrix exponential; the variation of constants formula.

Computation of the matrix exponential via eigenvalues and eigenvectors and via residual matrices. Necessary and sufficient conditions for exponential stability: Routh-Hurwitz criterion. Invariant subspaces.

Impulse responses, step responses and steady state responses to sinusoidal inputs. Transient behaviours. Modal analysis: mode excitation by initial conditions and by impulsive inputs; modal observability from output measurements; modes which are both excitable and observable. Popov conditions for modal excitability and observability. Autoregressive moving average (ARMA) models and transfer functions.

Kalman reachability conditions, gramian reachability matrices and the computation of input signals to drive the system between two given states. Kalman observability conditions, gramian observability matrices and the computation of initial conditions given input and output signals. Equivalence between Kalman and Popov conditions.

Kalman decomposition for non-reachable and non-observable systems.

Eigenvalues assignment by state feedback for reachable systems. Design of asymptotic observers and Kalman filters for state estimation of observable systems. Design of dynamic compensators to stabilize any reachable and observable system. Design of regulators to reject disturbances generated by linear exosystems.

Bode plots. Static gain, system gain and high-frequency gain.

Zero-pole cancellation.

STATISTICS:

A.Y.  Mechatronics students Other courses Students Mechatronics average Other courses average
2019/2020 10 62 24 23
2020/2021 19 25 23 24
2021/2022 13 44 21 22

Innovative Materials with Laboratory (blocks B-C-C1-E)

Simona Ranieri 1st year, 2021, 6 CFU, a.a. 2022-23, a.a. 2023-24, a.a. 2024-25, Block B, Block C, Block C1, Block E, I sem, Subjects , ,
Innovative Materials with Laboratory (blocks B-C-C1-E)
1 YEAR 1 semester 6 CFU
TATA MARIA ELISA (1cfu)
COSTANZA GIROLAMO (1cfu)
VARONE ALESSANDRA (4cfu)		 A.Y. 2020-21 to
A.Y. 2024-25 (B-C1-E)
COSTANZA GIROLAMO (4cfu)

TATA MARIA ELISA (2cfu)

 A.Y. 2025-26 (C1-E)
Code: 8039786
SSD: ING-IND/21

LEARNING OUTCOMES:
The aim of the course is to provide an overview of novel materials recently developed and investigated for applications in mechanics, electronics, and mechatronics. Different types of materials are considered and described with particular attention on the preparation route, specific characteristics, and applications. Some of them are of basic importance for new technologies gaining increasing attention in industrial practice. The knowledge of innovative materials is strictly connected to the possibility and capability of designing new products.

KNOWLEDGE AND UNDERSTANDING:
Deep knowledge of the metallic structure and their mechanical behavior; in particular knowledge of innovative materials for mechatronics applications; selection of conventional material or not as a function of application, structure and properties.

APPLYING KNOWLEDGE AND UNDERSTANDING:
Ability to define materials properties and the most suitable production technologies for the components realization; Ability to perform tests in laboratory; Ability to define appropriate treatments in order to obtain the suitable mechanical properties as a function of service conditions. Ability to select innovative materials; ability to evaluate innovative materials properties.

MAKING JUDGEMENTS:
Ability to investigate, select and choose metallic materials as a function of the application.

COMMUNICATION SKILLS:
Clear and correct expression, in English language, skills on the topics covered in the course.

LEARNING SKILLS:

Ability to face a new problem, know how to manage it and find functional and correct solutions. learning ability will be evaluated by exam tests and laboratory activities.

SYLLABUS:

Metallurgy Fundamentals: crystal structure, defects, plastic deformation. Mechanical tests.

Amorphous alloys: production and applications of metallic glasses as mechatronic devices. Alloys with mixed structure (nanocrystalline and amorphous).

Ultrafine grained (UFG) materials: microstructural features and production routes.

Nanoporous and mesoporous materials: structural characterization and properties. Their applications for energy and gas storage.

Powder metallurgy, Additive Manufacturing Technologies.

Advanced composite materials: properties, applications and production routes.

Porous materials: metal foams, Open and closed porosity (micro and macro). Classification according to size and shape of the pores. Properties (sound, energy and vibration absorption, crash

behavior) and production methods. Functional and structural

applications: lightweight construction, automotive. Metal sandwich structures.

Functional and Smart Materials. Property change as a response of external stimulus: shape memory alloy (one-way and two-way shape memory), thermochromic, photomechanical. Energy conversion: piezoelectric, thermoelectric. Phase change materials. 

Applications: mechatronic, energy. Functionally graded materials.