M E 406
(NUC E 406)
Introduction to Statistical Thermodynamics (3) Statistical description of systems composed of large numbers of particles in the context of classical and quantum mechanics; basic concepts of probability theory and thermodynamics as they relate to statistical mechanics.
M E (NUC E) 406 Introduction to Statistical Thermodynamics (3)
This course is an introduction to probabilistic and statistical concepts in the physical sciences, which we refer to as "statistical thermodynamics." In areas such as design and processing of electronic devices, materials engineering, chemical engineering, and combustion engineering, the science of statistical mechanics is a particularly necessary, powerful, and important tool for the engineer. The underlying foundation of statistical mechanics is developed by (1) reviewing the basic ideas from probability theory, (2) deriving the binomial, Poisson, and Gaussian probability distributions, and (3) using these models to analyze several examples taken from science and engineering. To make a connection between macroscopic quantities and the corresponding probabilistic representation, classical thermodynamics is reviewed using the internal energy, entropy, and free energy functions in the context of the first and second laws. Statistical mechanics for classical and quantum-mechanical systems is presented via the micro-canonical, canonical, and grand canonical ensembles using the associated partition functions. During the syntheses of ideas, applications from various branches of science are presented. Some examples of applications are the Einstein crystal, the Debye crystal, the ideal gas, and black body radiation.
This course covers the following program objectives:
1. Demonstrate knowledge of basic chemistry and physics.
2. Demonstrate a knowledge of atomic and nuclear physics.
3. Demonstrate a knowledge of thermodynamics, heat transfer, and fluid flow.
4. Understand and apply the basic concepts of particle transport.
5, Understand and apply thermodynamics and heat transfer principles to the analysis of nuclear power components and systems.
Note : Class size, frequency of offering, and evaluation methods will vary by location and instructor. For these details check the specific course syllabus.