Course content

The course is part of the skill strands in numerical and experimental work in physics.

The uniqueness of physics and the role of physics in society. Scientific method. SI units. Examples of the use of physics within natural science and technology.

Multidimensional kinematics, with vector description. The concept of force and Newton's laws. Centripetal force. Newton's law of gravitation . Work and mechanical energy. Friction. Conservation of energy.

Current, resistance, electromotive force and direct current circuits. Capacitance and capacitors. Magnetic field and flux. Lenz 's law. Faraday's law of induction .

Experimental working methods, methods for measuring physical quantities, data processing, interpretation and documentation. Basic introduction to digital measurement systems. Basic error analysis.

The numerical activities in this subject require knowledge acquired in the subject FY1008 - Introduction to Numerical Physics, as joint projects are compulsory in both subjects.

Learning outcome

Knowledge

After completing the course, the student has:

• Insight into the nature of physics and the scientific method.
• Basic knowledge of Newton's laws.
• Basic knowledge of the energy concept and conservation law of energy.
• Basic knowledge of the terms electric current, voltage, potential and energy.
• Basic knowledge of electric and magnetic fields.
• Understanding of the concept of magnetic flux and how changing it results in induced voltage.
• Basic knowledge of digital measurement systems.

Skills

After completing the course, the student can:

• Analyze forces and use force diagrams.
• Use the conservation law of energy to solve problems.
• Analyze simple electrical circuits and calculate current and voltage.
• Use basic numerical methods to model motion.
• Plan and carry out experiments to answer a physics problem.
• Use experimental tools for recording and analyzing data and perform basic error analysis.
• Use digital measurement systems at a basic level.
• Classify, quantify and analyze various sources of error in data.
• Document experimental work through laboratory records and make simple uncertainty calculations.
• Calculate units in the SI system and carry out simple dimensional analysis.

General competence

After completing the course, the student can:

• Use known analytical models in problem solving.
• Use mathematical methods to solve theoretical and practical problems.
• Combine theory, experiment and numerical methods to investigate relationships.
• Draw conclusions based on theory, data and error analysis.

Learning methods and activities

• Theory lessons
• Arithmetic work with compulsory attendance
• Laboratory work
• Project in experimental work

Expected workload in the course is 225 hours.

Compulsory activities

• Exercises, which must be approved for admission to the written exam.

Compulsory assignments

• Calculation exercises

Specific conditions

Recommended previous knowledge

The course requires knowledge corresponding to Physics 1 and Mathematics R2 from upper secondary school. Knowledge equivalent to Physics 2 from upper secondary school is also recommended.

Course materials

Stated at the start of the semester.

Credit reductions