Recent advancements in morphing applications: Architecture, artificial intelligence integration, challenges, and future trends-a comprehensive survey

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dc.authoridDurhasan, Tahir/0000-0001-5212-9170
dc.authoridAmoozgar, mohammaeza/0000-0003-1670-9762
dc.authoridMowla, Najmul/0000-0003-0613-9858
dc.contributor.authorMowla, Md. Najmul
dc.contributor.authorAsadi, Davood
dc.contributor.authorDurhasan, Tahir
dc.contributor.authorJafari, Javad Rashid
dc.contributor.authorAmoozgar, Mohammadreza
dc.date.accessioned2026-02-27T07:33:00Z
dc.date.available2026-02-27T07:33:00Z
dc.date.issued2025
dc.description.abstractThis study provides a comprehensive review of recent advancements in aerospace morphing technologies, focusing on integrating artificial intelligence (AI) into morphing architectures. It emphasizes AI's pivotal role in optimizing these systems, particularly through machine learning (ML), deep learning (DL), and reinforcement learning (RL), to enhance real-time adaptability, performance, and efficiency. The review categorizes developments in smart materials, compliant mechanisms, and adaptive structures, offering a detailed analysis of their architectural foundations. It further examines AI-driven aerodynamic optimization and control systems, highlighting recent solutions to structural integrity, energy efficiency, and scalability challenges. Key contributions since 2020 are synthesized through a year-by-year analysis, offering a clear overview of the research landscape. The paper also addresses emerging challenges in aerospace morphing and proposes strategies to alleviate them. Recommendations for future advancements emphasize the integration of state-of-the-art technologies. By critically evaluating current capabilities and limitations, this review provides valuable insights for researchers and practitioners, identifying AI's transformative potential in morphing systems and outlining the technical challenges that must be addressed for future morphing aerospace applications.
dc.description.sponsorshipScientific and Technological Research Council of Turkey (TUEBIdot;TAK) [223M340]
dc.description.sponsorshipThis research is supported by the Scientific and Technological Research Council of Turkey (TUEB & Idot;TAK) under the TUEB & Idot;TAK 1001 program, with project number 223M340.
dc.identifier.doi10.1016/j.ast.2025.110102
dc.identifier.issn1270-9638
dc.identifier.issn1626-3219
dc.identifier.urihttp://dx.doi.org/10.1016/j.ast.2025.110102
dc.identifier.urihttps://hdl.handle.net/20.500.14669/4417
dc.identifier.volume161
dc.identifier.wosWOS:001439966500001
dc.indekslendigikaynakWeb of Science
dc.language.isoen
dc.publisherElsevier France-Editions Scientifiques Medicales Elsevier
dc.relation.ispartofAerospace Science and Technology
dc.relation.publicationcategoryMakale - Uluslararas� Hakemli Dergi - Kurum ��retim Eleman�
dc.rightsinfo:eu-repo/semantics/openAccess
dc.snmzKA_20260302
dc.subjectStructure of morphing
dc.subjectAerodynamics modeling
dc.subjectControl systems
dc.subjectAI for morphing
dc.subjectPrivacy & challenges
dc.subjectFuture trends
dc.titleRecent advancements in morphing applications: Architecture, artificial intelligence integration, challenges, and future trends-a comprehensive survey
dc.typeReview

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