Simulation with Entropy Thermodynamics
Material type:
- text
- computer
- online resource
- 9783036501147
- 9783036501154
- books978-3-0365-0115-4
- Research & information: general
- Altenkirch-Ioffe model
- colloids
- complex systems thermodynamics
- constant properties model
- CuNi
- Debye plasmas
- device modeling
- efficiency
- electrical conductivity
- electronic entropy
- energy harvesting
- entropy
- entropy production
- entropy pump mode
- FeRh
- figure of merit
- finite time thermodynamics
- Fourier heat
- generator mode
- irreversible thermodynamics
- Ising model
- Joule heat
- Kadanoff-Baym equation
- LaFeSi
- living systems
- machine learning
- maximum electrical power point
- non-equilibrium quantum field theory
- Ohm law
- optimization
- out of equilibrium thermodynamics
- polyelectrolytes
- power conversion
- power factor
- pressure-ionization
- pulsed heat
- quantum brain dynamics
- quantum phase transition
- reactor modelling
- Seebeck coefficient
- segmented thermoelectric generator
- super-radiance
- TEG performance
- temperature profile
- thermodynamics
- thermoelectric generator
- thermoelectric materials
- thermoelectrics
- Thomson heat
- transient
- transport
- variational autoencoder
- voltage-electrical current curve
- working point
- working points
Open Access Unrestricted online access star
Beyond its identification with the second law of thermodynamics, entropy is a formidable tool for describing systems in their relationship with their environment. This book proposes to go through some of these situations where the formulation of entropy, and more precisely, the production of entropy in out-of-equilibrium processes, makes it possible to forge an approach to the behavior of very different systems. Whether for dimensioning structures; influencing parameter variability; or optimizing power, efficiency, or waste heat reduction, simulations based on entropy production offer a tool that is both compact and reliable. In the case of systems marked by complexity, it appears to be the only way. In that sense, realistic optimization can be carried out, integrating within the same framework both the system and all the constraints and boundary conditions that define it. Simulations based on entropy give the researcher a powerful analytical framework that crosses the disciplines of physics and links them together.
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https://creativecommons.org/licenses/by/4.0/
English
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