Thermal Physics Tutorials with Python Simulations

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A01=Minjoon Kouh
A01=Taejoon Kouh
Adiabatic Process
Author_Minjoon Kouh
Author_Taejoon Kouh
Average Internal Energy
Average Kinetic Energy
Boltzmann Distribution
Category=PHH
Category=UMW
classical thermodynamics
Code Block
computational
computational thermal physics tutorials
dW
Electrical Potential Energy
Energy Conservation
Energy Conservation Principle
energy transfer modeling
engineering
entropy calculation
eq_bestseller
eq_computing
eq_isMigrated=1
eq_isMigrated=2
eq_nobargain
eq_non-fiction
eq_science
Gas Particles
Gravitational Potential Energy
Ideal Gas
Import Matplotlib
Import Numpy
Int
Integer Lattice Point
Internal Energy
Isothermal Process
kinetic theory
mathematical
Multiple Particles
Optional Input Argument
Partition Function
Positive Octant
python scientific programming
Quantum Number
scientific computing
simulations
statistical mechanics
statistical thermodynamics
Thermal Processes
Thermal System
undergraduate physics course
visualizations

Product details

  • ISBN 9781032257563
  • Weight: 460g
  • Dimensions: 156 x 234mm
  • Publication Date: 14 Mar 2023
  • Publisher: Taylor & Francis Ltd
  • Publication City/Country: GB
  • Product Form: Hardback
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This book provides an accessible introduction to thermal physics with computational approaches that complement the traditional mathematical treatments of classical thermodynamics and statistical mechanics. It guides readers through visualizations and simulations in the Python programming language, helping them to develop their own technical computing skills (including numerical and symbolic calculations, optimizations, recursive operations, and visualizations). Python is a highly readable and practical programming language, making this book appropriate for students without extensive programming experience.

This book may serve as a thermal physics textbook for a semester-long undergraduate thermal physics course or may be used as a tutorial on scientific computing with focused examples from thermal physics. This book will also appeal to engineering students studying intermediate-level thermodynamics as well as computer science students looking to understand how to apply their computer programming skills to science.

Key features

  • Major concepts in thermal physics are introduced cohesively through computational and mathematical treatments.
  • Computational examples in Python programming language guide students on how to simulate and visualize thermodynamic principles and processes for themselves.

Taejoon Kouh is a Professor of Nano and Electronic Physics at Kookmin University, Republic of Korea.

Minjoon Kouh is a Professor of Physics and Neuroscience at Drew University, USA.

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