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Physics-informed machine learning for predicting the ballistic limit of whipple shields.

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Title: Physics-informed machine learning for predicting the ballistic limit of whipple shields.
Authors: Ryan, Shannon1 (AUTHOR) shannon.ryan@deakin.edu.au, Le, Hung1 (AUTHOR), Berk, Julian1 (AUTHOR), Kumar, AV Arun1 (AUTHOR), Venkatesh, Svetha1 (AUTHOR)
Source: International Journal of Impact Engineering. Sep2025, Vol. 203, pN.PAG-N.PAG. 1p.
Database: Academic Search Ultimate
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Header DbId: asn
DbLabel: Academic Search Ultimate
An: 184997639
AccessLevel: 2
PubType: Academic Journal
PubTypeId: academicJournal
PreciseRelevancyScore: 0
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  Data: <searchLink fieldCode="JN" term="%22International+Journal+of+Impact+Engineering%22">International Journal of Impact Engineering</searchLink>. Sep2025, Vol. 203, pN.PAG-N.PAG. 1p.
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=asn&AN=184997639
RecordInfo BibRecord:
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    Identifiers:
      – Type: doi
        Value: 10.1016/j.ijimpeng.2025.105364
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      – Code: eng
        Text: English
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        StartPage: N.PAG
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      – TitleFull: Physics-informed machine learning for predicting the ballistic limit of whipple shields.
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            NameFull: Ryan, Shannon
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            NameFull: Le, Hung
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            NameFull: Berk, Julian
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            NameFull: Kumar, AV Arun
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            – D: 01
              M: 09
              Text: Sep2025
              Type: published
              Y: 2025
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              Value: 0734743X
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              Value: 203
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