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V. L. Manasa Mandalapu,
P. Venkatramana,
E. Baby Anitha,
S Vinayagapriya,
D. Suresh,
Bibhu Prasad Ganthia,
- Research Scholar, Department of Electronics and Communication Engineering., School of Engineering and Technology, Mohan Babu University, Andhra Pradesh, India
- Professor, Department of Electronics and Communication Engineering., School of Engineering and Technology, Mohan Babu University, Andhra Pradesh, India
- Assistant Professor, Department of Computer Science and Engineering, K.S.R College of Engineering, Tiruchengode, Namakkal Dt., Tamil Nadu, India
- Associate Professor, Department of Electronics and Communication Engineering., St. Joseph’s College of Engineering, Chennai, Tamil Nadu, India
- Assistant Professor, Department of Mechanical Engineering, Indra Ganesan college of engineering, Trichy- 12, Tamil Nadu, India
- Assistant Professor, Department of Electrical Engineering, Indira Gandhi Institute of Technology, Dhenkanal, Odisha, India
Abstract
Concurrently, lightweight, multifunctional, damage-tolerant materials which can be used for continuous monitoring of the structural integrity under complex mechanical and environmental conditions are required for aerospace structures. In this paper, a hybrid bio-polymer nanocomposite based Explainable Digital-Twin Guided Self-Healing (EDT-SH-BPN) approach for autonomous structural health monitoring (SHM) and recovery in aerospace applications is proposed. The proposed system comprises a bio-derived epoxy/epoxidized natural rubber (ENR) matrix, embedded electrical sensing and self-healing capabilities, a physics-based digital twin model and explainable artificial intelligence (XAI), within a closed-loop sense–diagnose–predict–heal–verify framework. The developed nanocomposite exhibits significant enhancement in comparison to neat bio-epoxy/ENR matrix with the following mechanical properties: tensile strength (91.4 MPa), Young’s modulus (3.26 GPa), flexural strength (126.8 MPa), interlaminar shear strength (51.7 MPa), and impact strength (34.5 kJ/m2). The composite has a glass-transition temperature of 118.7 °C, a storage modulus of 3.48 GPa, and a thermal conductivity of 1.84 W/m·K. It is found that the MXene–GNP conductive network has 42.6 S/m conductivity, a gauge factor of 6.84, crack-detection sensitivity of 85 μm and response time of 18.4 ms, with a high sensing repeatability of 96.1% for 1000 cycles. Self-healing can decrease the crack width from 420 to 58 μm after 6 h, which is 86.2% crack closure and 87.6% healing efficiency. The digital-twin/XAI framework can be accurate at 97.6% in damage classification, 97.0% in F1 score, 3.1% in damage severity MAE, 1.7 mm in localization error, 96.8% in healing decision accuracy and 93.6% in explanation consistency. The results clearly prove the capability of EDT-SH-BPN in lightweight, intelligent, predictive and autonomous aerospace structural systems.
Keywords: Biohybrid Nanocomposites; Digital Twin; Explainable AI; Self-Healing Materials; Structural Health Monitoring; Aerospace Structures.
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Journal of Polymer & Composites
| Volume | 14 | |
| 05 | ||
| Received | 11/08/2026 | |
| Accepted | 05/10/2026 | |
| Published | 21/10/2026 | |
| Publication Time | 71 Days |