Introductory Course in Computational Physics/Engineering

[Astronuc]

Computational Physics:
http://farside.ph.utexas.edu/teaching/329/lectures/lectures.html

An introductory course

• Integration of ODEs
• The chaotic pendulum
• Poisson's equation
• The diffusion equation
• The wave equation
• Particle-in-cell codes
• Monte-Carlo methods

All very useful.

Computational physics/engineering (simulation, or predictive analysis) is widely used because it allows one to analyze a system or component without the time and expense of designing, building, and testing the system or component. Nevertheless, some experimentation, usually separate effects experiments, are necessary to fill in the holes in one's knowledge. Ultimately, an integrated test will be performed to verify that system or component performs as predicted in the simulation.

Simulations are based on accurate knowledge of thermophysical, thermomechanical, even electromagnetic behvaior of the constituent materials used to form the component or system one is simulating. Simuation is an important part of the design process.

 

[Astronuc]

An interesting perspective on Physics and a lot of useful information.

Worlds of physics are just clusters of suitable models.

The ten worlds of physics

1. The classical world
2. Thermal world
3. Nonequilibrium world
4. Continuum world
5. Electromagnetic world
6. Plasma world
7. The quantum world
8. High energy world
9. Relativistic world
10. Cosmological world

The tree of mathematical modeling in physics, with branches, leaves and buds as individual models

There are links between “worlds” invoking substructures with repeatable, reusable patterns

The author discusses computational physics (mathematical modeling, numerical analysis) in terms of the 10 worlds (or realms).

http://www5.in.tum.de/lehre/praktika/comp_mod/SS03/MathModeling03.pdf

Mathematical and Computer Modeling in Science and Engineering
Sergey Pankratov, Technische Universität München (TUM 2003)
http://www5.in.tum.de/lehre/praktika/comp_mod/SS03/questions_course

 

[sir-pinski]

It allows engineers to test different designs, materials, and parameters to optimize performance and reduce costs.

This course seems to cover a wide range of topics that are crucial for understanding computational physics and its applications in engineering. The integration of ODEs, chaotic pendulum, Poisson's equation, diffusion equation, and wave equation are all fundamental concepts that are essential for solving problems in physics and engineering. Additionally, the inclusion of particle-in-cell codes and Monte-Carlo methods shows the practical application of computational physics in real-world scenarios.

The use of simulations in engineering has become increasingly important in recent years, as it allows for quicker and more efficient analysis of systems and components. It also reduces the need for costly and time-consuming physical testing, making it a valuable tool in the design process.

Furthermore, the emphasis on accurate knowledge of material behavior highlights the importance of understanding the underlying physics behind computational simulations. This course not only teaches the technical skills needed for computational physics, but also stresses the importance of having a strong foundation in physics principles.

Overall, this introductory course in computational physics/engineering seems to be a comprehensive and valuable resource for anyone interested in this field. It covers a wide range of topics and provides practical applications, making it a great starting point for those looking to gain a deeper understanding of this important and rapidly growing field.