Publication | Journal of Engineering Design 2019
Physics-based simulation ontology
An ontology to support modelling and reuse of data for physics-based simulation
This paper describes how a formal ontology can be used to assist in modelling the physical phenomenon of interest in a veridical manner, while capturing the necessary and reusable information for physics-based simulation solvers. Such capabilities are important in the applications of CAE, generative design, and digital twins.
Download publicationAbstract
Physics-based simulation ontology: an ontology to support modelling and reuse of data for physics-based simulation
Hyunmin Cheong, Adrian Butscher
Journal of Engineering Design 2019
The current work presents an ontology developed for physics-based simulation in engineering design, called Physics-based Simulation Ontology (PSO). The purpose of the ontology is to assist in modelling the physical phenomenon of interest in a veridical manner, while capturing the necessary and reusable information for physics-based simulation solvers. The development involved extending an existing upper ontology, Basic Formal Ontology (BFO), to define lower-level terms of PSO. PSO has two parts – PSO-Physics, which consists of terms and relations used to model physical phenomena based on the perspective of classical mechanics involving partial differential equations, and PSO-Sim, which consists of terms used to represent the information artefacts that are about the physical phenomena modelled with PSO-Physics. The former terms are used to model the physical phenomenon of interest independent of solver- specific interpretations, which can be reused across different solvers, while the latter terms are used to instantiate solver-specific input data. A case study involving two simulation solvers was conducted to demonstrate this capability of PSO. Discussion around the benefits and limitations of using BFO for the current work is also provided, which should be valuable for any future work that extends an existing upper ontology to develop ontologies for engineering applications.
Associated Autodesk Researchers
Related Resources
2024
Performance-Aided DesignAn innovative product design process that integrates sensor-collected…
2024
Reduced-order modeling of unsteady fluid flow using neural network ensemblesA framework to enhance the accuracy of time-series predictions in…
2024
A hyperreduced reduced basis element method for reduced-order modeling of component-based nonlinear systemsThis method balances accuracy and computational speed through adaptive…
2021
COVID-19 Facility Planning and Analysis: Designing a Multi-Agent Occupant Simulation SystemThe COVID-19 pandemic changed our lives, forcing us to reconsider our…
Get in touch
Something pique your interest? Get in touch if you’d like to learn more about Autodesk Research, our projects, people, and potential collaboration opportunities.
Contact us