| Code |
A005513 |
| CFU |
9 |
| Teacher |
Caterina Petrillo |
| Teachers |
|
| Hours |
- 72 ore - Caterina Petrillo
|
| Learning activities |
Base |
| Area |
Fisica e chimica |
| Sector |
FIS/01 |
| Type of study-unit |
Obbligatorio (Required) |
| Language of instruction |
Italian |
| Contents |
Dimensions, errors and statistical analysis. Simple physical models, approximations and validity limits. Classical mechanics and dynamics. Statics. Force fields. Energy and work. Harmonic oscillator. Gravitation. Gauss law. Conservation principles. |
| Reference texts |
Elementi di Fisica - Meccanica Termodinamica, Mazzoldi, Nigro, Voci |
| Educational objectives |
At the end of the course the student should have acquired (descriptor Dublin 1) the main basic knowledge of the mechanics of the point, of particle systems and rigid body, and have assimilated the fundamentals of universal gravitation. The student must have a thorough knowledge of the principles of conservation in physics, the force fields and their specific properties and the elementary models for the treatment of complex mechanical systems. The main skills acquired (ability to apply their knowledge, descriptor Dublin 2, and to adopt the appropriate approach under independent judgment, Dublin descriptor 3) will consist of the ability to model physical phenomena, together with the skills to solve exercises and problems and the ability to individually develop simple demonstrations based on the extension and application of the knowledge acquired. |
| Prerequisites |
To successfully address the study of the Physics Course and to more easily understand the topics covered, a solid knowledge of basic mathematics ( equations of various degrees , inequalities , systems of equations), trigonometry , elementary geometry and analytical geometry (study of functions, etc.) is mandatory. It is also required the knowledge of vectors and vector operations. For a deeper understanding of the initial topics of kinematics covered in the course, the knowledge of the basic techniques of differentiation and integration is useful. This knowledge becomes mandatory with progressing of the course even though the parallel treatment of these topics in the course Analysis I should help the student. Knowledge of all the mathematical techniques listed and the ability to apply them effectively to solve problems are prerequisites essential to follow the course with profit. |
| Teaching methods |
The course is organized in face-to-face lectures. There are 72 hours of lectures. Each lesson is typically a 30-minute explanation and 15 minutes of training with solution of problems and questions and discussion of applications. At the end of each cycle of thematically consistent lessons there are scheduled classroom exercises conducted by the teacher and consisting in solving problems. The hours dedicated to tutorials and practical training are in addition to those dedicated to lectures. The students are also offered to participate to three written tests with open answers for evaluation and self-assessment. |
| Other information |
Attendance is optional but strongly advised. |
| Learning verification modality |
The assessment of the level of student knowledge and ability achieved by the student is carried out consistently throughout the course. In fact, students are given "in progress" written tests at the end of major specific blocks of lectures thematically consistent. The purpose is in progress verification of the level of knowledge achieved by the student on the subjects of the specific block, offering, at the same time, the student a tool for self-assessment with respect to her/his level of understanding and her/his ability to solve problems. The student can apply to all written tests, regardless of the result achieved in each, or any number she/he wishes to. Each in progress test, although limited as to the specific content of the thematic block, simulates the structure of the written exam and contains problems with open answer questions to be solved in no more than 30 minutes each. Students who have obtained a positive assessment (> 18/30) in more than half of the in progress tests may, if they wish, be exempted from carrying out the final written exam. The learning assessment (exam) involves passing a mandatory written test, which requires solving problems with open answer questions.The student who, as a result of the in-progress evaluation has been exempted from the final written test, can apply to it again if she/he so wishes. The exam tests are designed to ensure: i) the ability to understand the problems proposed during the course, ii) the ability to correctly apply the theoretical knowledge (descriptor Dublin 2), iii) the ability to independently express judgment and appropriate comments on possible alternative models (descriptor Dublin 3), iv) the ability to communicate effectively in writing (descriptor Dublin 4). Information on support services to students with learning disability can be found at http://www.unipg.it/disabilita-e-dsa |
| Extended program |
Units, dimensions, measurements, errors and statistical analysis. Dimensional Analysis - Motion: reference systems, approximations. Motion in one dimension: displacement, velocity, acceleration. Motion with constant velocity. Motion with constant acceleration. Free-fall under gravity. Vectors and their components. Adding and multiplying vectors. Motion in two and three dimensions: position, displacement, average velocity, velocity, average acceleration, acceleration. Projectile motion. Uniform circular motion. Forces: motion and equilibrium. Mass. Newton's first, second and third law. Some specific forces: weight, normal component of the reaction, friction, elastic forces. Dynamics of the circular motion. Linear momentum. Work. Calculation of the work in elementary cases. Fields. Conservative fields. Potential energy. Calculation of the potential energy in elementary cases. Spring potential energy. Kinetic energy. Work-energy theorem. Non-conservative fields. The harmonic oscillators. Systems of particles. Center of mass. Newton's second law for a system of particles. Linear momentum of a system of particles. Conservation of linear momentum. Collisions: elastic and inelastic. Torque. Angular momentum. Conservation of angular momentum. Dynamics of the rigid bodies. Rotations, rigid translations and rolling. Inertial momentum. Huygens-Steiner theorem. Equilibrium of rigid bodies. Static laws. Gravitation: Kepler's laws, Newton's law of gravitation, examples. Gauss' theorem. |
| Obiettivi Agenda 2030 per lo sviluppo sostenibile |
High quality education |
| Code |
A005512 |
| CFU |
3 |
| Teacher |
Caterina Petrillo |
| Teachers |
|
| Hours |
- 24 ore - Caterina Petrillo
|
| Learning activities |
Base |
| Area |
Fisica e chimica |
| Sector |
FIS/01 |
| Type of study-unit |
Obbligatorio (Required) |
| Language of instruction |
Italian |
| Contents |
Measurement of a physical quantity and the concept of uncertainty. Representation of measurement errors. Error propagation. Statistical analysis of experimental errors. Normal (Gaussian) distribution. Weighted means. Least squares method. Binomial and Poisson distributions. Chi-squared test. |
| Reference texts |
J.R. Taylor Introduzione all'analisi degli errori. |
| Educational objectives |
This course provides an introduction to the fundamental concepts of measurement in physics, with particular focus on uncertainty analysis and the statistical treatment of experimental data. Students will gain practical skills in representing, analyzing, and interpreting measurement errors through examples and graphical methods. By the end of the course, students will be able to: understand and quantify the uncertainty associated with physical measurements; apply statistical tools to analyze experimental data; distinguish between different types of errors and manage their impact on results; use probabilistic distributions to model physical processes; evaluate the goodness-of-fit of data using statistical tests. |
| Prerequisites |
Knowledge of the basics of mathematics. |
| Teaching methods |
The course is organized in face-to-face lectures. There are 24 hours of lectures. Each lesson is typically a 30-minute explanation and 15 minutes of training with solution of problems and questions and discussion of applications. At the end of each cycle of thematically consistent lessons there are scheduled classroom exercises conducted by the teacher and consisting in solving problems and applications. The hours dedicated to tutorials and practical training are in addition to those dedicated to lectures. |
| Learning verification modality |
Written exam on data analysis for a given experiment. |
| Extended program |
The concept of measurement uncertainty. Examples: reading an instrument, counting events, repeated measurements yielding different values. Graphical representation and analysis. Significant figures. Relative error. Propagation of uncertainties: general formula. Statistical analysis of random errors: random and systematic errors; mean and standard deviation; standard deviation of the mean; systematic errors. The normal distribution. Weighted average. Least squares method: introduction and examples. Binomial and Poisson distributions: definitions, properties, and examples. Chi-squared test: introduction, definition, and examples. |
| Obiettivi Agenda 2030 per lo sviluppo sostenibile |
High level education and training |
