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Related Concept Videos

Thermodynamic Systems01:06

Thermodynamic Systems

5.0K
A thermodynamic system is a set of objects whose thermodynamic properties are of interest. The system is considered to be embedded in its surroundings or the environment. The system and its environment can exchange heat and do work on each other through a boundary that separates them. However, the immediate surroundings of the system interact with it directly and therefore have a much stronger influence on its behavior and properties.
Consider an example of  tea boiling in a kettle. The...
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Thermodynamic Potentials01:26

Thermodynamic Potentials

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Thermodynamic potentials are state functions that are extremely useful in analyzing a thermodynamic system. They have dimensions of energy. The four important thermodynamic potentials are internal energy, enthalpy, Helmholtz free energy, and Gibbs free energy. These thermodynamic potentials can be expressed using two of the following variables: pressure, volume, temperature, and entropy. These two variables are expressed as the rate of change of the thermodynamic potential with respect to other...
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Thermodynamics: Chemical Potential and Activity01:10

Thermodynamics: Chemical Potential and Activity

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The effective concentration of a species in a solution can be expressed precisely in terms of its activity. Activity considers the effect of electrolytes present in the vicinity of the species of interest and depends on the ionic strength of the solution. The activity of a species is expressed as the product of molar concentration and the activity coefficient of the species.
The thermodynamic equilibrium constant is more accurately defined in terms of activity rather than concentration.
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Path Between Thermodynamics States01:21

Path Between Thermodynamics States

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Consider the two thermodynamic processes involving an ideal gas that are represented by paths AC and ABC in Figure 1:
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Thermal Sigmatropic Reactions: Overview01:16

Thermal Sigmatropic Reactions: Overview

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Sigmatropic rearrangements are a class of pericyclic reactions in which a σ bond migrates from one part of a π system to another. These are intramolecular rearrangements where the total number of σ and π bonds remain unchanged.
Sigmatropic shifts are classified based on an order term [i, j ], where i and j indicate the number of atoms across which each end of the σ bond migrates. Below are examples of a [3,3] sigmatropic shift in...
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First Law Of Thermodynamics: Problem-Solving01:21

First Law Of Thermodynamics: Problem-Solving

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The first law of thermodynamics states that the change in internal energy of the system is equal to the net heat transfer into the system minus the net work done by the system. This equation is a generalized form of energy conservation and can be applied to any thermodynamic process.
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Author Spotlight: Simulation and Analysis of the Temperature Rise of Ring Main Unit Equipment
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KnowTD─An Actionable Knowledge Representation System for Thermodynamics.

Luisa Vollmer1, Sophie Fellenz1, Fabian Jirasek1

  • 1RPTU Kaiserslautern, 67663 Kaiserslautern, Germany.

Journal of Chemical Information and Modeling
|July 23, 2024
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Summary
This summary is machine-generated.

Human thermodynamic knowledge can now be transferred to computers using the KnowTD system. This enables machines to solve thermodynamic problems, providing correct and explainable solutions for introductory engineering thermodynamics.

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Area of Science:

  • Thermodynamics
  • Artificial Intelligence
  • Knowledge Representation

Background:

  • Human expertise in thermodynamics is difficult to transfer to computational systems.
  • Existing computational tools lack explainability and correctness guarantees for thermodynamic problem-solving.

Purpose of the Study:

  • To develop a system for transferring human thermodynamic knowledge to computers.
  • To enable machines to solve thermodynamic problems with explainable and correct solutions.

Main Methods:

  • Created KnowTD, a knowledge representation system based on a thermodynamics ontology.
  • Coupled the ontology with a reasoner to process user input, retrieve equations, and solve problems.
  • Developed a system for generating explainable solutions.

Main Results:

  • Demonstrated successful transfer of human thermodynamic knowledge to a computer system.
  • KnowTD can solve simple thermodynamic problems with guaranteed correctness and explanations.
  • The system is currently limited to introductory-level engineering thermodynamics problems.

Conclusions:

  • Human thermodynamic knowledge can be effectively encoded and utilized by computational systems.
  • KnowTD provides a foundation for explainable AI in thermodynamics.
  • The modular design allows for future expansion to more complex thermodynamic problems.