A direction-encoded machine learning approach for peak overpressure prediction in urban environments

Dennis, A.A. orcid.org/0000-0002-3347-2747 (2024) A direction-encoded machine learning approach for peak overpressure prediction in urban environments. In: Proceedings of The 19th International Symposium on Interaction of the Effects of Munitions with Structures (ISIEMS). 19th International Symposium on Interaction of the Effects of Munitions with Structures (ISIEMS), 09-13 Dec 2024, Bonn, Germany. International Symposium on Interaction of the Effects of Munitions with Structures (ISIEMS)

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Item Type: Proceedings Paper
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© 2024 ISIEMS. This is an author-produced version of a paper subsequently published in Proceedings of The 19th International Symposium on Interaction of the Effects of Munitions with Structures (ISIEMS). Uploaded with permission from the copyright holder.

Dates:
  • Published: 9 December 2024
Institution: The University of Sheffield
Academic Units: The University of Sheffield > Faculty of Engineering (Sheffield) > School of Mechanical, Aerospace and Civil Engineering
Depositing User: Symplectic Sheffield
Date Deposited: 03 Jan 2025 17:13
Last Modified: 06 Jan 2025 12:02
Published Version: https://www.bundeswehr.de/en/organization/infrastr...
Status: Published
Publisher: International Symposium on Interaction of the Effects of Munitions with Structures (ISIEMS)
Refereed: Yes
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