Author: Simona Ranieri

Digital Electronics

Simona Ranieri 1 semester, 3 Year, 9 credits, Subjects
Digital Electronics
3 YEAR 1 semester 9 CREDITS
Prof. Marco Re

since 2019-20 to
  2024-25
 

marco.re@uniroma2.it

Code: 8037956
SSD: ING-INF/01

OBJECTIVES

LEARNING OUTCOMES

This course aims at providing the fundamentals of DIGITAL ELECTRONICS. More in detail, it deals with the characterization and design of combinational circuits starting from gates. The target technology is CMOS. Starting from the study of the CMOS circuits and the implementation of memory cells the course will face the design and characterization of sequential circuits.

KNOWLEDGE AND UNDERSTANDING

The student will be able to analyze and design combinational and sequential circuits.
Starting from these blocks the student will be able to write a high-level description of a complex digital system based on a computational unit and a control unit.

APPLYING KNOWLEDGE AND UNDERSTANDING

The student will apply the knowledge and understanding developed to the analysis of practical problems. This would imply critical knowledge in terms of silicon real estate and speed for both combinational and sequential systems.
MAKING JUDGEMENTS: The student will have to prove his critical awareness with respect to the simplifying assumptions useful to describe and analyze combinational and sequential systems as well as his critical awareness of the correct order of magnitude of performance parameters while dealing or designing digital circuits.

COMMUNICATION SKILLS

The student will prove, mostly during the oral test, his capacity of describing the operation and functioning of digital systems.

LEARNING SKILLS

The student will get familiar with the schematization of practical problems, mostly during the development of his skills for the written test. This mainly concerns combinational systems and sequential systems

COURSE SYLLABUS

  • This course constitutes an introduction to the engineering of digital systems.
  • Starting with data representation in digital form, it goes on to provide students with the ability to design a circuit for a given algorithmic information processing task. For this purpose, Boolean functions and combinational design are covered, followed by sequential logic design through Finite State Machines. Moreover standard MSI blocks (sequential and combinational are illustrated) up the description of algorithmic state machines.
  • The student should be able to understand the structure of a complex digital system and able to design the architecture and the internal blocks of the system. In the course, a brief introduction to the electrical measurements for digital systems is given (oscilloscope, Logic State Analyzer, Pattern Generator).

Thermodynamics and Heat Transfer

Simona Ranieri 2 semester, 2 Year, 9 credits, Subjects
Thermodynamics and Heat Transfer
2 YEAR 2 semester 9 CREDITS
Prof. Paolo Coppa 2019-20
BOVESECCHI GIANLUIGI 2020-21
Michela Gefulsa – gelfusa@ing.uniroma2.it 

2021-22 to 2023-24
  Code: 8039146
SSD: ING-IND/10

OBJECTIVES

LEARNING OUTCOMES: The course aims to provide students with the basic principles, physical laws, and applications of thermodynamics, thermo-fluid dynamics, and heat transfer, with the dual purpose of preparing them to afford more applicative courses and using the acquired knowledge for design and sizing simple components and thermal systems.

KNOWLEDGE AND UNDERSTANDING

Students will have to understand the physical laws of applied thermodynamics and heat transfer, and understand the structure and operation of the 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 must be able to afford courses for which this course is preparatory (for example Thermotechnique, or Machines) and to size or verify simple components and systems, topics covered by the course, such as air conditioning systems, engine systems, fins and heat exchangers.

MAKING JUDGEMENTS

Students must assume the autonomous capacity to face the subsequent studies for which this course is preparatory and to draw up simple projects of thermal systems that use the studied components. They will also need to be able to evaluate projects written by other parties, checking that the project requirements are satisfied.

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, PowerPoint 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.

COURSE SYLLABUS

  • Fundamental laws of thermodynamics: zeroth law, first law for open and closed systems, second law, entropy definition and Clausius integral, Maxwell equations, Claperyron equation
  • Thermodynamic diagrams: P-v, T-s, H-s, P-h
  • Thermodynamic cycles for close and open systems: engine cycles: Otto Cycle, Diesel cycle, Joule Brighton cycle, Rankine and Hirn cycle, refrigeration cycle
  • Air and steam mixtures, design of conditioning air systems
  • Basic laws of fluid dynamics: Bernoulli equation, the motion of fluids in ducts, major and minor pressure drops, dimensional analysis for turbulent flow friction factor.
  • Heat transfer mechanisms. Conduction: Fourier law, basic conduction heat transfer equation, solution for simple geometries with and without heat generation, lumped parameter problems, cooling fins. Convection: dimension analysis for forced and free convection. Radiation heat transfer: basic laws of radiation, radiation exchanges between black bodies and grey bodies, configuration factors, electric analogy. Heat exchangers: types, size problem and rate problem.

Mechanics of Materials and Structures

Simona Ranieri 2 semester, 2 Year, 9 credits, Subjects
Mechanics of Materials and Structures
2 YEAR 2 semester 9 CREDITS
Prof. Micheletti Andrea
Prof. Artioli Edoardo

2019-20 to 2022-23
MICHELETTI ANDREA – micheletti@ing.uniroma2.it  2023-24
  Code: 8037955
SSD: ICAR/08

OBJECTIVES

LEARNING OUTCOMES: The goal of this course 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 both discrete and continuous systems (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 behavior 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 judgment 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 discrete systems, beams, and three-dimensional bodies.

COURSE SYLLABUS

  • Review of basic notions of vector and tensor algebra and calculus.
  • Kinematics and statics of rigid-body systems.
  • Geometry of area distributions.
  • Discrete linearly elastic systems, static-kinematic duality, solution methods.
  • Strain and stress in 3D continuous bodies and beam-like bodies.
  • Virtual power and virtual work equation for discrete systems, 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 discrete systems, 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.

Feedback Control Systems

Simona Ranieri 2 semester, 2 Year, 9 credits, Subjects
Feedback Control Systems
2 YEAR 2 semester 9 CREDITS
Prof. Cristiano Maria VERRELLI Since 2019-20 to
  2024-25
  Code: 8037953
SSD: ING-INF/04

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 understand and use the theory of differential equations and 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 skilled enough in the specific field to undertake following studies characterized by a high degree of autonomy.

COURSE SYLLABUS

Linear systems
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 behaviors. 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.
Introduction to adaptive control. Introduction to tracking control. Minimum phase systems and Proportional Integral Derivative (PID) control.
Bode plots. Static gain, system gain and high-frequency gain. Zero-pole cancellation. Nyquist plot and Nyquist criterion. Root locus analysis. Stability margins. Frequency domain design. Realization theory.

Introduction to nonlinear systems Nonlinear models and nonlinear phenomena. Fundamental properties. Lyapunov stability. Linear systems and linearization. Center manifold theorem. Stabilization by linearization.

Analogue Electronics

Simona Ranieri 2 semester, 2 Year, 9 credits, Subjects
Analogue Electronics
2 YEAR 2 semester 9 CREDITS
Prof. Rocco GIOFRE’

Since 2019-20 to 2022-23

Prof. Paolo COLANTONIO

2023-24
2024-25
 

paolo.colantonio@uniroma2.it

Code: 8037954
SSD: ING-INF/01

OBJECTIVES

 

COURSE SYLLABUS

  • Classification of electrical systems and requirements.
  • Analysis of transitory and frequency behavior.
  • Distortion in electronic systems and Bode diagrams.
  • 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.