Many research groups are capable of performing impressive high-fidelity simulations of atomizing jets that lever- age advances to numerical methods and ever increasing computational resources. The simulations produce very large data-sets describing the flow and have the potential to advance our understanding of atomization. The challenge to making the results useful is extracting relevant physics from these large data-sets. In this work, we propose two physics extraction techniques that provide 1) the fundamental instabilities that exist on a jet’s liquid core that dictate the largest structures generated during atomization and 2) the ancestry of droplets created as the coherent liquid core breaks into droplets and ligaments which may continue to break into smaller droplets. Understanding these processes will allow for low-fidelity atomization models to be developed and tested that agree with the physics predicted by detailed simulations.
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Extraction and Analysis of Atomization Process from High-Fidelity Simulations
Understanding the process of primary and secondary atomization in liquid jets is crucial in describing spray distribution and droplet geometry for industrial applications and is essential in the development of physics-based low-fidelity atomization models. Significant advances in numerical modelling and computational resources allows research groups to conduct detailed numerical simulations of these flows. However, the large size of the datasets produced by highfidelity simulations limit researchers’ ability to analyze them. Consequently, the process of a coherent liquid core breaking into droplets has not been analyzed in simulation results even though a complete description of the jet dynamics exists. The present work applies a droplet physics extraction technique to high-fidelity simulations to track breakup events and data associated with the local flow. The data on the atomization process is stored in a Neo4j graphical database providing an easily accessible format. Results will provide a robust, quantitative description of the process of atomization and the details on the local flow field will be useful in the development of low-fidelity atomization models.
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- Award ID(s):
- 1749779
- PAR ID:
- 10324146
- Date Published:
- Journal Name:
- ICLASS 2021, 15th Triennial International Conference on Liquid Atomization and Spray Systems
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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