{"id":3457,"date":"2025-06-03T10:48:17","date_gmt":"2025-06-03T07:48:17","guid":{"rendered":"https:\/\/fti.dp.ua\/conf\/?p=3457"},"modified":"2025-09-23T10:50:29","modified_gmt":"2025-09-23T07:50:29","slug":"cims-313","status":"publish","type":"post","link":"https:\/\/fti.dp.ua\/conf\/2025\/cims-313\/","title":{"rendered":"Physics-Informed Neural Networks in Aerospace: A Structured Taxonomy with Literature Review"},"content":{"rendered":"\n

Physics-Informed Neural Networks in Aerospace: A Structured Taxonomy with Literature Review<\/h1>\n\n\n\n
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Yurii Tkachov<\/strong><\/strong><\/strong><\/strong><\/strong><\/strong><\/strong><\/strong><\/strong><\/strong><\/strong><\/strong><\/strong><\/strong><\/strong><\/strong><\/strong><\/strong><\/strong><\/strong><\/strong><\/strong><\/strong><\/strong><\/strong><\/strong><\/strong><\/strong><\/strong><\/strong><\/strong><\/strong><\/strong><\/strong><\/strong><\/strong><\/strong><\/strong><\/strong><\/strong><\/strong><\/strong><\/strong><\/strong><\/strong><\/strong><\/strong><\/strong><\/strong><\/strong><\/strong><\/strong><\/strong><\/strong><\/strong><\/strong><\/strong><\/strong><\/strong><\/strong><\/strong><\/strong><\/strong><\/strong><\/strong><\/h5>\n\n\n\n

ORCID: https:\/\/orcid.org\/0000-0003-1556-2463<\/a><\/em><\/p>\n\n\n\n

Oles Honchar Dnipro National University<\/em><\/p>\n<\/div><\/div>\n\n\n\n

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Oleh Murashko<\/strong><\/strong><\/strong><\/strong><\/strong><\/strong><\/strong><\/strong><\/strong><\/strong><\/strong><\/strong><\/strong><\/strong><\/strong><\/strong><\/strong><\/strong><\/strong><\/strong><\/strong><\/strong><\/strong><\/strong><\/strong><\/strong><\/strong><\/strong><\/strong><\/strong><\/strong><\/strong><\/strong><\/strong><\/strong><\/strong><\/strong><\/strong><\/strong><\/strong><\/strong><\/strong><\/strong><\/strong><\/strong><\/strong><\/strong><\/strong><\/strong><\/strong><\/strong><\/strong><\/strong><\/strong><\/strong><\/strong><\/strong><\/strong><\/strong><\/strong><\/strong><\/strong><\/strong><\/strong><\/strong><\/strong><\/h5>\n\n\n\n

ORCID: https:\/\/orcid.org\/0009-0006-3643-1576<\/a><\/em><\/p>\n\n\n\n

Oles Honchar Dnipro National University<\/em><\/p>\n<\/div><\/div>\n\n\n\n

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Purpose.<\/strong>\u00a0This study aims to develop a structured four-tier taxonomy that systematically organizes aerospace engineering tasks suitable for the application of Physics-Informed Neural Networks (PINNs), while validating this classification through a literature review and identifying opportunities for future research.\u00a0Design \/ Method \/ Approach.<\/strong>\u00a0The methodology involves grouping tasks into four distinct tiers\u2014Physical Modeling, Dynamic Analysis, Functional Assessment, and System-Level Assessment\u2014based on their physical, operational, and systemic characteristics. This framework is subsequently populated with real-world examples derived from the analysis of 145 peer-reviewed studies.\u00a0Findings.<\/strong>\u00a0The reviewed literature confirms a balanced distribution of PINNs applications across all tiers. Contrary to initial assumptions, studies were identified even in areas previously presumed underrepresented, such as acoustic modeling, optical simulations, and environmental impact assessment. This outcome reveals the broader applicability of PINNs and calls for a reassessment of current assumptions regarding underexplored domains.\u00a0Theoretical Implications.<\/strong>\u00a0The proposed taxonomy offers a coherent framework for structuring interdisciplinary PINNs applications by integrating physics-based modeling with machine learning across aerospace engineering contexts.\u00a0Practical Implications.<\/strong>\u00a0It provides engineers and researchers with a practical roadmap for selecting PINNs methods tailored to specific problem types, potentially improving computational efficiency and enhancing predictive accuracy in aerospace design and analysis.\u00a0Originality \/ Value.<\/strong>\u00a0The study\u2019s originality lies in its empirically validated, four-tier taxonomy that synthesizes the fragmented body of literature on PINNs in aerospace, offering a unified perspective for researchers and practitioners.\u00a0Research Limitations \/ Future Research.<\/strong>\u00a0While the taxonomy covers a wide range of existing applications, future studies should consider extending it with new tiers\u2014particularly related to manufacturing-aware modeling\u2014and pursue methodological standardization to ensure reproducibility and scalability.\u00a0Article Type.<\/strong>\u00a0Review.<\/p>\n\n\n\n

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ACCESS ARTICLE<\/a><\/div>\n<\/div>\n\n\n\n
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CIMS 2025 The Awakening of Nature<\/a><\/div>\n\n
Aerospace vehicles<\/a><\/div><\/div>\n\n\n\n
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Physics-Informed Neural Networks in Aerospace: A Structured Taxonomy with Literature Review Yurii Tkachov ORCID: https:\/\/orcid.org\/0000-0003-1556-2463 Oles Honchar Dnipro National University Oleh Murashko ORCID: https:\/\/orcid.org\/0009-0006-3643-1576 Oles Honchar Dnipro National University Purpose.\u00a0This study aims to develop a structured four-tier taxonomy that systematically organizes aerospace engineering tasks suitable for the application of Physics-Informed Neural Networks (PINNs), while validating this classification through a literature review and identifying opportunities for future research.\u00a0Design \/ Method \/ Approach.\u00a0The methodology involves grouping tasks into four distinct tiers\u2014Physical Modeling, … <\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[15],"tags":[39],"class_list":["post-3457","post","type-post","status-publish","format-standard","hentry","category-aerospace","tag-cims-2025-the-awakening-of-nature"],"_links":{"self":[{"href":"https:\/\/fti.dp.ua\/conf\/wp-json\/wp\/v2\/posts\/3457","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/fti.dp.ua\/conf\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/fti.dp.ua\/conf\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/fti.dp.ua\/conf\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/fti.dp.ua\/conf\/wp-json\/wp\/v2\/comments?post=3457"}],"version-history":[{"count":1,"href":"https:\/\/fti.dp.ua\/conf\/wp-json\/wp\/v2\/posts\/3457\/revisions"}],"predecessor-version":[{"id":3458,"href":"https:\/\/fti.dp.ua\/conf\/wp-json\/wp\/v2\/posts\/3457\/revisions\/3458"}],"wp:attachment":[{"href":"https:\/\/fti.dp.ua\/conf\/wp-json\/wp\/v2\/media?parent=3457"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/fti.dp.ua\/conf\/wp-json\/wp\/v2\/categories?post=3457"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/fti.dp.ua\/conf\/wp-json\/wp\/v2\/tags?post=3457"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}