The Role of Thermomechanical and Aeroelastic Optimization in FRP-Strengthened Structural Elements for High-Performance Aerospace and Civil Applications
DOI:
https://doi.org/10.32628/IJSRMME25144Keywords:
Fiber Reinforced Polymers, Thermomechanical Optimization, Aeroelastic Stability, Structural Reinforcement, High-Performance Aerospace, Civil Engineering ApplicationsAbstract
Fiber Reinforced Polymers (FRP) have revolutionized the field of structural engineering, particularly in aerospace and civil applications, by providing lightweight, high-strength, and corrosion-resistant solutions for structural enhancement. However, the structural efficiency of FRP-strengthened elements is often governed by thermomechanical and aeroelastic behavior, necessitating advanced optimization techniques to ensure performance under extreme loading conditions. This review explores the role of thermomechanical and aeroelastic optimization in improving the structural resilience and longevity of FRP-reinforced components in high-performance applications. The paper systematically examines the key parameters influencing FRP-enhanced structural members, including temperature-dependent mechanical degradation, interfacial debonding, and stress redistribution under fluctuating thermal and aerodynamic loads. Advanced computational models and experimental validation methods for optimizing FRP-strengthened structures are critically analyzed. Furthermore, the paper highlights emerging strategies such as multi-scale modeling, topology optimization, and adaptive hybrid reinforcement techniques to mitigate failure risks associated with thermal expansion mismatches, flutter instabilities, and fatigue-induced delamination. Case studies in aerospace and civil infrastructure applications are discussed to showcase the effectiveness of thermomechanical and aeroelastic optimization in enhancing load-bearing capacities, minimizing vibration-induced damage, and improving the energy absorption characteristics of FRP-reinforced structures. This review synthesizes state-of-the-art methodologies, identifies existing challenges, and outlines future research directions for optimizing FRP-strengthened structural elements, providing a comprehensive reference for engineers and researchers striving to advance the integration of FRP composites in next-generation aerospace and civil engineering applications.
References
Accueil, (2017). Understanding the Aerodynamic Forces in Flight. https://www.studyflight.com/understanding-the-aerodynamic-forces-in-flight/
Banks-Sills, L., Boniface, V., & Eliasi, R. (2003). Effect of residual stresses on delamination cracks in fiber reinforced composites. Interface Science, 11, 339-348.
Bayat, M., Dong, W., Thorborg, J., To, A. C., & Hattel, J. H. (2021). A review of multi-scale and multi-physics simulations of metal additive manufacturing processes with focus on modeling strategies. Additive Manufacturing, 47, 102278.
Bisagni, C. (2015). An overview of structural response of composite aerospace structures subjected to dynamic loading. Composite Structures, 129, 194-209. https://doi.org/10.1016/j.compstruct.2015.04.007
Chen, Y., Zhang, J., Li, Z., Zhang, H., Chen, J., Yang, W., ... & Li, Y. (2023). Intelligent methods for optimization design of lightweight fiber-reinforced composite structures: A review and the-state-of-the-art. Frontiers in Materials, 10, 1125328.
Chen, Y., Zhang, J., Li, Z., Zhang, H., Chen, J., Yang, W., ... & Li, Y. (2023). Intelligent methods for optimization design of lightweight fiber-reinforced composite structures: A review and the-state-of-the-art. Frontiers in Materials, 10, 1125328.
Christensen, R. M. (2019). Theory of viscoelasticity: An introduction. Academic Press.
D’Amore, A., Giorgio, M., & Grassia, L. (2015). Modeling the residual strength of carbon fiber reinforced composites subjected to cyclic loading. International Journal of Fatigue, 78, 31-37.
Ennis, B. L., Kelley, C. L., Naughton, B. T., Norris, R. E., Das, S., Lee, D., & Miller, D. (2019). Optimized carbon fiber composites in wind turbine blade design (No. SAND-2019-14173). Sandia National Lab.(SNL-NM), Albuquerque, NM (United States); Oak Ridge National Lab.(ORNL), Oak Ridge, TN (United States).
Enyejo, J. O., Adeyemi, A. F., Olola, T. M., Igba, E., & Obani, O. Q. (2024). Resilience in supply chains: How technology is helping USA companies navigate disruptions. Magna Scientia Advanced Research and Reviews, 11(02), 261–277. https://doi.org/10.30574/msarr.2024.11.2.0129
Enyejo, J. O., Babalola, I. N. O., Owolabi, F. R. A., Adeyemi, A. F., Osam-Nunoo, G., & Ogwuche, A. O. (2024). Data-driven digital marketing and battery supply chain optimization in the battery-powered aircraft industry through case studies of Rolls-Royce’s ACCEL and Airbus's E-Fan X Projects. International Journal of Scholarly Research and Reviews, 5(2), 001–020. https://doi.org/10.56781/ijsrr.2024.5.2.0045
Enyejo, J. O., Balogun, T. K., Klu, E., Ahmadu, E. O., & Olola, T. M. (2024). The Intersection of Traumatic Brain Injury, Substance Abuse, and Mental Health Disorders in Incarcerated Women: Addressing Intergenerational Trauma through Neuropsychological Rehabilitation. American Journal of Human Psychology, 2(1).
Enyejo, J. O., Fajana, O. P., Jok, I. S., Ihejirika, C. J., Awotiwon, B. O., & Olola, T. M. (2024). Digital Twin Technology, Predictive Analytics, and Sustainable Project Management in Global Supply Chains for Risk Mitigation, Optimization, and Carbon Footprint Reduction through Green Initiatives. International Journal of Innovative Science and Research Technology, 9(11).
Enyejo, L. A., Adewoye, M. B., & Ugochukwu, U. N. (2024). Interpreting Federated Learning (FL) Models on Edge Devices by Enhancing Model Explainability with Computational Geometry and Advanced Database Architectures. International Journal of Scientific Research in Computer Science, Engineering and Information Technology, 10(6).
Farrar, C. R., & Worden, K. (2021). Structural health monitoring: A machine learning perspective. Annual Review of Control, Robotics, and Autonomous Systems, 4, 365–392. https://doi.org/10.1146/annurev-control-071819-060715
Fish, J., & Yuan, Z. (2019). Multiscale modeling of composite materials and structures. Applied Mechanics Reviews, 71(2), 021305. https://doi.org/10.1115/1.4044046
Friedrich, K. (2018). Wear performance of high temperature polymers and their composites. In Applications of High Temperature Polymers (pp. 221-246). CRC Press.
Gibson, R. F. (2012). Principles of composite material mechanics. CRC Press.
Gopalakrishnan, S., Ruzzene, M., & Buehler, M. J. (2020). Advances in smart sensor-based structural health monitoring for composite structures. Composites Science and Technology, 202, 108514. https://doi.org/10.1016/j.compscitech.2020.108514
Hamed, A., Milad, B., Esmaeil, P. N. & Asghar, V. O. (2017). The effect of mechanical and thermal properties of FRP bars on their tensile performance under elevated temperatures. https://www.sciencedirect.com/science/article/abs/pii/S0950061817319864
Henshaw, M. D. C., Badcock, K. J., Vio, G. A., Allen, C. B., Chamberlain, J., Kaynes, I., ... & Denley, C. J. (2007). Non-linear aeroelastic prediction for aircraft applications. Progress in Aerospace Sciences, 43(4-6), 65-137.
Hodges, D. H., & Pierce, G. A. (2011). Introduction to structural dynamics and aeroelasticity. Cambridge University Press.
Hollaway, L. C. (2019). A review of the present and future utilization of FRP composites in the civil infrastructure with reference to their important in-service properties. Construction and Building Materials, 208, 193-210. https://doi.org/10.1016/j.conbuildmat.2019.03.132
Holzapfel, G. A., & Gasser, T. C. (2001). A viscoelastic model for fiber-reinforced composites at finite strains: Continuum basis, computational aspects and applications. Computer methods in applied mechanics and engineering, 190(34), 4379-4403.
Ibokette, A. I., Aboi, E. J., Ijiga, A. C., Ugbane, S. I., Odeyemi, M. O., & Umama, E. E. (2024). The impacts of curbside feedback mechanisms on recycling performance of households in the United States. World Journal of Biology Pharmacy and Health Sciences, 17(2), 366-386.
Ibokette, A. I., Ogundare, T. O., Anyebe, A. P., Alao, F. O., Odeh, I. I., & Okafor, F. C. (2024). Mitigating maritime cybersecurity risks using AI-based intrusion detection systems and network automation during extreme environmental conditions. International Journal of Scientific Research and Modern Technology, 3(10).
Idoko, D. O., Mbachu, O. E., Ololade, I. N., Erondu, O. F., Dada-Abidakun, O., & Alemoh, P. O. (2024). Exploring the impact of obesity and community health programs on enhancing endometrial cancer detection among low-income and Native American women through a public health lens. International Journal of Frontiers in Medicine and Surgery Research, 6(02), 001–018. https://doi.org/10.53294/ijfmsr.2024.6.2.0043
Idoko, I. P., David-Olusa, A., Badu, S. G., Okereke, E. K., Agaba, J. A., & Bashiru, O. (2024). The dual impact of AI and renewable energy in enhancing medicine for better diagnostics, drug discovery, and public health. Magna Scientia Advanced Biology and Pharmacy, 12(02), 099–127. https://magnascientiapub.com/journals/msabp/content/dual-impact-ai-and-renewable-energy-enhancing-medicine-better-diagnostics-drug-discovery-and
Idoko, I. P., Ijiga, O. M., Agbo, D. O., Abutu, E. P., Ezebuka, C. I., & Umama, E. E. (2024). Comparative analysis of Internet of Things (IoT) implementation: A case study of Ghana and the USA-vision, architectural elements, and future directions. World Journal of Advanced Engineering Technology and Sciences, 11(1), 180-199.
Idoko, I. P., Ijiga, O. M., Enyejo, L. A., Akoh, O., & Ileanaju, S. (2024). Harmonizing the voices of AI: Exploring generative music models, voice cloning, and voice transfer for creative expression.
Idoko, I. P., Ijiga, O. M., Enyejo, L. A., Akoh, O., & Isenyo, G. (2024). Integrating superhumans and synthetic humans into the Internet of Things (IoT) and ubiquitous computing: Emerging AI applications and their relevance in the US context. Global Journal of Engineering and Technology Advances, 19(01), 006-036.
Idoko, I. P., Ijiga, O. M., Enyejo, L. A., Akoh, O., & Odeyemi, M. O. (2024). Exploring the potential of Elon Musk's proposed quantum AI: A comprehensive analysis and implications. Global Journal of Engineering and Technology Advances, 18(3), 048-065.
Idoko, I. P., Ijiga, O. M., Harry, K. D., Ezebuka, C. C., Ukatu, I. E., & Peace, A. E. (2024). Renewable energy policies: A comparative analysis of Nigeria and the USA. World Journal of Advanced Research and Reviews, 23(3), 1407–1432.
Igba, E., Danquah, E. O., Ukpoju, E. A., Obasa, J., Olola, T. M., & Enyejo, J. O. (2024). Use of Building Information Modeling (BIM) to Improve Construction Management in the USA. World Journal of Advanced Research and Reviews, 23(03), 1799–1813. https://wjarr.com/content/use-building-information-modeling-bim-improve-construction-management-usa
Igba, E., Ihimoyan, M. K., Awotinwo, B., & Apampa, A. K. (2024). Integrating BERT, GPT, Prophet Algorithm, and Finance Investment Strategies for Enhanced Predictive Modeling and Trend Analysis in Blockchain Technology. International Journal of Scientific Research in Computer Science, Engineering, and Information Technology, 10(6), 1620-1645. https://doi.org/10.32628/CSEIT241061214
Ijiga, A. C., Aboi, E. J., Idoko, P. I., Enyejo, L. A., & Odeyemi, M. O. (2024). Collaborative innovations in Artificial Intelligence (AI): Partnering with leading U.S. tech firms to combat human trafficking. Global Journal of Engineering and Technology Advances, 18(03), 106-123. https://gjeta.com/sites/default/files/GJETA-2024-0046.pdf
Ijiga, A. C., Abutu, E. P., Idoko, P. I., Agbo, D. O., Harry, K. D., Ezebuka, C. I., & Umama, E. E. (2024). Ethical considerations in implementing generative AI for healthcare supply chain optimization: A cross-country analysis across India, the United Kingdom, and the United States of America. International Journal of Biological and Pharmaceutical Sciences Archive, 7(1), 048–063.
Ijiga, A. C., Balogun, T. K., Sariki, A. M., Klu, E., Ahmadu, E. O., & Olola, T. M. (2024). Investigating the Influence of Domestic and International Factors on Youth Mental Health and Suicide Prevention in Societies at Risk of Autocratization. IRE Journals, 8(5).
Ijiga, A. C., Olola, T. M., Enyejo, L. A., Akpa, F. A., Olatunde, T. I., & Olajide, F. I. (2024). Advanced surveillance and detection systems using deep learning to combat human trafficking. Magna Scientia Advanced Research and Reviews, 11(01), 267–286. https://magnascientiapub.com/journals/msarr/sites/default/files/MSARR-2024-0091.pdf•
Kim, S., & Park, H. (2021). Structural optimization of composite aircraft fuselage: A computational approach for weight reduction. Composite Structures, 266, 113849. https://doi.org/10.1016/j.compstruct.2021.113849
Kossakowski, P. G., & Wciślik, W. (2022). Fiber-reinforced polymer composites in the construction of bridges: Opportunities, problems and challenges. Fibers, 10(4), 37.
Kumar, P., & Singh, R. (2023). Enhancing the resilience of offshore platforms with fiber-reinforced polymer composites: A review. Marine Structures, 89, 103546. https://doi.org/10.1016/j.marstruc.2023.103546
Kumar, R., & Singh, S. P. (2021). Influence of dynamic aerodynamic loading on fatigue crack growth in aerospace composite structures. International Journal of Fatigue, 147, 106162. https://doi.org/10.1016/j.ijfatigue.2021.106162
Lee, B. H. K. (2020). Flight dynamic response to buffeting and its implications for high-speed aircraft design. Journal of Aircraft, 57(2), 342-357. https://doi.org/10.2514/1.C035992
Li, X., Wang, Y., Zhang, Z., & Zhang, L. (2021). Mechanisms of interfacial delamination in fiber-reinforced polymer composites under thermal-mechanical loading. Composites Science and Technology, 206, 108-134. https://doi.org/10.1016/j.compscitech.2021.108134
Liu, G. R., & Quek, S. S. (2021). The finite element method: A practical course. Elsevier.
Liu, J., Gaynor, A. T., Chen, S., Kang, Z., Suresh, K., Takezawa, A., ... & To, A. (2018). Current and future trends in topology optimization for additive manufacturing. Structural and multidisciplinary optimization, 57(6), 2457-2483.
Livne, E. (2019). Aeroelasticity of nonconventional air vehicle configurations: State-of-the-art and future challenges. Journal of Aircraft, 55(4), 1407-1435. https://doi.org/10.2514/1.C034415
Luo, J., Meng, J., Yu, N., & Long, T. (2024). Configuration Optimization of a Skippable Anti-Ship Missile Considering Initial Kinematic Parameters. AIAA Journal, 62(3), 1094-1104.
Luo, J., Meng, J., Yu, N., & Long, T. (2024). Configuration Optimization of a Skippable Anti-Ship Missile Considering Initial Kinematic Parameters. AIAA Journal, 62(3), 1094-1104.
Manuel, H. N. N., Adeoye, T. O., Idoko, I. P., Akpa, F. A., Ijiga, O. M., & Igbede, M. A. (2024). Optimizing passive solar design in Texas green buildings by integrating sustainable architectural features for maximum energy efficiency. Magna Scientia Advanced Research and Reviews, 11(01), 235-261.
Parmar, V. (2022). Topology Optimization (For Structural Engineers). https://www.linkedin.com/pulse/topology-optimization-structural-engineers-vijay-parmar
Ramu, P., Thananjayan, P., Acar, E., Bayrak, G., Park, J. W., & Lee, I. (2022). A survey of machine learning techniques in structural and multidisciplinary optimization. Structural and Multidisciplinary Optimization, 65(9), 266.
Ricci, G., & Bernardini, G. (2022). Experimental methodologies for wind tunnel testing of fiber-reinforced polymer structures in aerospace applications. Aerospace Science and Technology, 122, 107382. https://doi.org/10.1016/j.ast.2022.107382
Ricciardi, G., & Ciavarella, M. (2021). Advances in computational fluid-structure interaction for aeroelastic modeling of composite airframes. Aerospace Science and Technology, 119, 106972. https://doi.org/10.1016/j.ast.2021.106972
Rouchon, J., & Hochard, C. (2020). Experimental and numerical investigation of fatigue and fracture behavior in fiber-reinforced polymer laminates under aerodynamic loads. Composite Structures, 240, 112083. https://doi.org/10.1016/j.compstruct.2020.112083
Schapery, R. A. (2020). Nonlinear thermoelastic and thermoviscoelastic behavior of composite materials. International Journal of Solids and Structures, 182, 1-19. https://doi.org/10.1016/j.ijsolstr.2020.03.022
Shahabaz, S. M., Sharma, S., Shetty, N., Shetty, S. D., & Gowrishankar, M. C. (2021). Influence of temperature on mechanical properties and machining of fibre reinforced polymer composites: a review. Engineered Science, 16(8), 26-46Wei, Z. G., Sandstrom, R., & Miyazaki, S. (1998). Shape memory materials and hybrid composites for smart systems: Part II Shape-memory hybrid composites. Journal of materials science, 33, 3763-3783.
Siddika, A., Al Mamun, M. A., Ferdous, W., & Alyousef, R. (2020). Performances, challenges and opportunities in strengthening reinforced concrete structures by using FRPs–A state-of-the-art review. Engineering Failure Analysis, 111, 104480.
Sun, Q., Zhou, G., Meng, Z., Jain, M., & Su, X. (2021). An integrated computational materials engineering framework to analyze the failure behaviors of carbon fiber reinforced polymer composites for lightweight vehicle applications. Composites science and technology, 202, 108560.
Teng, J. G., Chen, J. F., Smith, S. T., & Lam, L. (2002). FRP-strengthened RC structures. Progress in Structural Engineering and Materials, 4(1), 1-18. https://doi.org/10.1002/pse.120
Teng, J. G., Yu, T., & Fernando, D. (2012). Strengthening of steel structures with fiber-reinforced polymer composites. Journal of Constructional Steel Research, 78, 131-143. https://doi.org/10.1016/j.jcsr.2012.06.011
Ugbane, S. I., Umeaku, C., Idoko, I. P., Enyejo, L. A., Michael, C. I., & Efe, F. (2024). Optimization of Quadcopter Propeller Aerodynamics Using Blade Element and Vortex Theory. International Journal of Innovative Science and Research Technology, 9(10).
Uniprism Market Research (2025). Future of Infrastructure: How FRP Bridges Are Transforming Construction, https://www.linkedin.com/pulse/future-infrastructure-how-frp-bridges-transforming-pqcff
Wang, X., Cui, F., Cui, L., & Jiang, D. (2023). Research on a Multi-Objective Optimization Design for the Durability of High-Performance Fiber-Reinforced Concrete Based on a Hybrid Algorithm. Coatings, 13(12), 2054.
Wang, Y., & Chen, H. (2021). Strengthening high-rise buildings using carbon fiber-reinforced polymers: A structural analysis approach. Engineering Structures, 244, 112743. https://doi.org/10.1016/j.engstruct.2021.112743
Wang, Y., & Chen, X. (2022). Integrating experimental data with numerical simulations for enhanced predictive modeling in composite materials. Engineering Structures, 259, 114179. https://doi.org/10.1016/j.engstruct.2022.114179
Wright, J. R., & Cooper, J. E. (2015). Introduction to aircraft aeroelasticity and loads. John Wiley & Sons.
Yang, Y., & Zhang, X. (2021). Thermal chamber testing for composite materials under extreme conditions: A review of methods and applications. Composites Part B: Engineering, 210, 108672. https://doi.org/10.1016/j.compositesb.2021.108672
Zhang, T., & Li, J. (2022). Structural reinforcement with hybrid composites: The role of nanomaterials in fiber-reinforced polymers. Materials Today, 52(3), 89-102. https://doi.org/10.1016/j.mattod.2022.04.005
Zhou, C., & Wang, L. (2022). Comparative study on topology optimization and artificial intelligence-based reinforcement strategies for structural materials. Composite Structures, 301, 116117. https://doi.org/10.1016/j.compstruct.2022.116117
Zhu, J. Z. (2013). The finite element method: its basis and fundamentals. Elsevier.
Zhu, J., Zhang, W., & Xia, L. (2021). Topology optimization in aerospace and mechanical structures: A review of recent advances. Structural and Multidisciplinary Optimization, 64(5), 1033-1058. https://doi.org/10.1007/s00158-021-02944-9
Zienkiewicz, O. C., Taylor, R. L., & Zhu, J. Z. (2020). The finite element method: Itsbasis and fundamentals. Butterworth-Heinemann.
Zou, P. X. W., Kim, H., & Owen, J. R. (2017). Optimization in civil and structural engineering. Journal of Structural Engineering, 143(9), 1-11. https://doi.org/10.1061/(ASCE)ST.1943-541X.0001803
