KnowTD-An Actionable Knowledge Representation System for Thermodynamics

Fuente: arXiv
Enregistré dans:
Détails bibliographiques
Auteurs principaux: Vollmer, Luisa, Fellenz, Sophie, Jirasek, Fabian, Leitte, Heike, Hasse, Hans
Format: Preprint
Publié: 2024
Sujets:
Accès en ligne:
Tags: Ajouter un tag
Pas de tags, Soyez le premier à ajouter un tag!
_version_ 1866911965673160704
author Vollmer, Luisa
Fellenz, Sophie
Jirasek, Fabian
Leitte, Heike
Hasse, Hans
author_facet Vollmer, Luisa
Fellenz, Sophie
Jirasek, Fabian
Leitte, Heike
Hasse, Hans
contents We demonstrate that thermodynamic knowledge acquired by humans can be transferred to computers so that the machine can use it to solve thermodynamic problems and produce explainable solutions with a guarantee of correctness. The actionable knowledge representation system that we have created for this purpose is called KnowTD. It is based on an ontology of thermodynamics that represents knowledge of thermodynamic theory, material properties, and thermodynamic problems. The ontology is coupled with a reasoner that sets up the problem to be solved based on user input, extracts the correct, pertinent equations from the ontology, solves the resulting mathematical problem, and returns the solution to the user, together with an explanation of how it was obtained. KnowTD is presently limited to simple thermodynamic problems, similar to those discussed in an introductory course in Engineering Thermodynamics. This covers the basic theory and working principles of thermodynamics. KnowTD is designed in a modular way and is easily extendable.
format Preprint
id arxiv_https___arxiv_org_abs_2407_17169
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle KnowTD-An Actionable Knowledge Representation System for Thermodynamics
Vollmer, Luisa
Fellenz, Sophie
Jirasek, Fabian
Leitte, Heike
Hasse, Hans
Computational Engineering, Finance, and Science
We demonstrate that thermodynamic knowledge acquired by humans can be transferred to computers so that the machine can use it to solve thermodynamic problems and produce explainable solutions with a guarantee of correctness. The actionable knowledge representation system that we have created for this purpose is called KnowTD. It is based on an ontology of thermodynamics that represents knowledge of thermodynamic theory, material properties, and thermodynamic problems. The ontology is coupled with a reasoner that sets up the problem to be solved based on user input, extracts the correct, pertinent equations from the ontology, solves the resulting mathematical problem, and returns the solution to the user, together with an explanation of how it was obtained. KnowTD is presently limited to simple thermodynamic problems, similar to those discussed in an introductory course in Engineering Thermodynamics. This covers the basic theory and working principles of thermodynamics. KnowTD is designed in a modular way and is easily extendable.
title KnowTD-An Actionable Knowledge Representation System for Thermodynamics
topic Computational Engineering, Finance, and Science
url https://arxiv.org/abs/2407.17169