SELF-HEALING PRESTRESSED CONCRETE MATERIALS FOR LONG-TERM INFRASTRUCTURE
Keywords:
Self-healing concrete; Prestressed structures; Smart infrastructure; Shape memory alloys; Vascular networks; Structural health monitoring; Long-term durability; Machine learning; Digital twinsAbstract
Infrastructure degradation poses significant economic and safety challenges globally, with concrete structures requiring costly maintenance and premature replacement. Prestressed concrete, while offering enhanced performance, remains vulnerable to micro-crack formation and long-term deterioration. This paper examines the emerging paradigm of self-healing prestressed concrete materials, integrating autonomous crack repair mechanisms with prestressing technology to achieve unprecedented infrastructure longevity. A systematic review of recent literature (2015-2025) on self-healing mechanisms, prestressed systems, sensor integration, and machine learning applications for infrastructure health monitoring reveals three primary self-healing approaches demonstrating viability for prestressed systems: (1) Autogenous healing enhanced by crystalline admixtures (crack closure up to 0.8mm); (2) Vascular networks delivering healing agents (recovery efficiency 85-95%); (3) Shape memory alloy fibers enabling active crack closure (recovery up to 98%). Integration with piezoelectric sensors, fiber optic sensing, and IoT-enabled monitoring creates truly adaptive infrastructure systems. Self-healing prestressed concrete represents a transformative approach to infrastructure durability, potentially extending service life by 50-100% while reducing maintenance costs. Challenges remain in scalability, long-term validation, and standardization.
References
Aabid, A., Raheman, M. A., Badruddin, I. A., & Khan, A. A. (2021). A review of piezoelectric material-based structural control and health monitoring techniques. Actuators, 10(5), 101. https://doi.org/10.3390/act10050101
Allujami, H. M., Al-Khafaji, A. H., & Al-Mansori, N. N. (2022). Nanomaterials in recycled aggregates concrete applications. Cogent Engineering, 9(1), 2122885. https://doi.org/10.1080/23311916.2022.2122885
Argyroudis, S. A., Mitoulis, S. A., Hofer, L., Zanini, M. A., Tubaldi, E., & Frangopol, D. M. (2022). Digital technologies can enhance climate resilience of critical infrastructure. Climate Risk Management, 35, 100387. https://doi.org/10.1016/j.crm.2021.100387
Aslam, M., Shafigh, P., Jumaat, M. Z., & Shah, S. A. (2015). Strengthening of RC beams using prestressed fiber reinforced polymers. Construction and Building Materials, 82, 235-256. https://doi.org/10.1016/j.conbuildmat.2015.07.007
Azevedo, B. F., Paiva, A. P., Ferreira, J. R., & Soares, R. B. (2024). Hybrid approaches to optimization and machine learning methods. Machine Learning, 113(7), 4055-4097. https://doi.org/10.1007/s10994-023-06467-x
Bado, M. F., & Casas, J. R. (2021). A review of distributed optical fiber sensors applications for civil engineering SHM. Sensors, 21(5), 1818. https://doi.org/10.3390/s21051818
Berhane, T., Aydilek, A. H., & Aydilek, I. M. (2024). Performance evaluation of hybrid machine learning algorithms. Applied Artificial Intelligence, 38(1), 2358661. https://doi.org/10.1080/08839514.2024.2358661
Berglund, E. Z., Venigalla, M. M., & Soroushian, P. (2020). Smart infrastructure: A vision for civil engineering in smart cities. Journal of Infrastructure Systems, 26(2), 03120001. https://doi.org/10.1061/(ASCE)IS.1943-555X.0000526
Boubitsas, D., Olsson, L., & Stahl, F. (2021). Infrared thermography for detecting defects in concrete structures (Report No. 2021762). Energiforsk. https://energiforsk.se/media/29659/infrared-thermography-for-detecting-defects-in-concrete-structures-energiforskrapport-2021-762.pdf
Cha, Y. J., Choi, W., & Büyüköztürk, O. (2017). Deep learning-based crack damage detection using convolutional neural networks. Computer-Aided Civil and Infrastructure Engineering, 32(5), 361-378. https://doi.org/10.1111/mice.12263
Cuenca, E., Tejedor, A., & Ferrara, L. (2018). A methodology to assess crack-sealing effectiveness of crystalline admixtures under repeated cracking-healing cycles. Construction and Building Materials, 179, 619-632. https://doi.org/10.1016/j.conbuildmat.2018.05.261
Daousis, S., Khelifi, F., & Bouras, A. (2024). Overview of protocols for wireless sensor networks in critical infrastructures. Future Internet, 16(1), 33. https://doi.org/10.3390/fi16010033
De Belie, N., De Muynck, W., Van Tittelboom, K., & Verstraete, W. (2018). A review of self-healing concrete for damage management of structures. Advanced Materials Interfaces, 5(17), 1800074. https://doi.org/10.1002/admi.201800074
De Nardi, C., Ferrara, L., & Krelani, V. (2023). Mechanical response of vascular self-healing cementitious materials. Cement and Concrete Composites, 142, 105143. https://doi.org/10.1016/j.cemconcomp.2023.105143
Dehghani, A., & Aslani, F. (2024). Advanced shape memory alloy fibers for crack closure in cement-based composites. Construction and Building Materials, 415, 135095. https://doi.org/10.1016/j.conbuildmat.2024.135095
Escoffres, P., Desmettre, C., & Charron, J. P. (2018). Effect of a crystalline admixture on the self-healing capability of high-performance fiber reinforced concretes in service conditions. Construction and Building Materials, 173, 763-774. https://doi.org/10.1016/j.conbuildmat.2018.04.003
Firoozi, A. A., & Firoozi, A. A. (2023). Emerging trends in damage tolerance assessment. Structural Durability & Health Monitoring, 18(1), 1-18. https://doi.org/10.32604/sdhm.2023.044573
Fournier, B., Chevrier, R., Bilodeau, A., Nkinamubanzi, P. P. C., & Bouzoubaa, N. (2016). Comparative field and laboratory investigations on the use of supplementary cementing materials to control alkali-silica reaction in concrete. In Proceedings of the 15th International Conference on Alkali-Aggregate Reaction.
Gao, W., Zhang, Y., Ramanujan, D., Ramani, K., Chen, Y., Williams, C. B., ... & Zavattieri, P. D. (2015). The status, challenges, and future of additive manufacturing in engineering. Computer-Aided Design, 69, 65-89. https://doi.org/10.1016/j.cad.2015.04.001
Ghosh, A., Biswas, S., Chatterjee, P., & Chakraborty, A. K. (2021). Real-time structural health monitoring using piezo sensors. International Journal of Building Pathology and Adaptation, 39(2), 283-311. https://doi.org/10.1108/IJBPA-12-2019-0111
Golovastikov, N. V., Kazanskiy, N. L., & Khonina, S. N. (2025). Optical fiber-based structural health monitoring. Photonics, 12(6), 615. https://doi.org/10.3390/photonics12060615
Gordan, B., Aydilek, A. H., & Gordan, B. (2024). Structural health monitoring of concrete bridges through artificial intelligence: A narrative review. Applied Sciences, 15(9), 4855. https://doi.org/10.3390/app15094855
Gul, S., & Shaheen, N. (2026). Influence of Bacillus subtilis-instigated calcite precipitation on damage progression and ionic transport. Materials, 19(6), 1153. https://doi.org/10.3390/ma19061153
Han, B., Zhang, L., & Ou, J. (2015). Smart concretes and structures: A review. Journal of Intelligent Material Systems and Structures, 26(11), 1303-1345. https://doi.org/10.1177/1045389X15586452
Han, B., Zhang, L., & Ou, J. (2017). Smart and multifunctional concrete toward sustainable infrastructures. https://link.springer.com/book/10.1007/978-981-10-4349-9
Huang, H., Ye, G., Qian, C., & Schlangen, E. (2016). Self-healing in cementitious materials: Materials, methods and service conditions. Materials & Design, 92, 499-511. https://doi.org/10.1016/j.matdes.2015.12.091
Javadian, A., Khani Sarbangholi, M. M., Ebrahimpour Bozorg, A., Rahmani, H., & Vatin, N. I. (2025). Assessment of biogenic healing capability, mechanical properties, and freeze–thaw durability of bacterial-based concrete using Bacillus subtilis, Bacillus sphaericus, and Bacillus megaterium. Buildings, 15(6), 943. https://doi.org/10.3390/buildings15060943
Jebelli, H. (2025). Digital twins in civil infrastructure. Civil Engineering Source. https://www.asce.org/publications-and-news/civil-engineering-source/article/2025/11/10/digital-twins-show-great-promise-in-civil-engineering-but-whats-next
Jonkers, H. M., Thijssen, A., Muyzer, G., Copuroglu, O., & Schlangen, E. (2010). Application of bacteria as self-healing agent for the development of sustainable concrete. Ecological Engineering, 36(2), 230-235. https://doi.org/10.1016/j.ecoleng.2008.12.036
Keo, S. A., Brachelet, F., Defer, D., & others. (2023). Defect detection in CFRP concrete reinforcement using the microwave infrared thermography (MIRT) method—A feasibility study. Applied Sciences, 13(14), 8393. https://doi.org/10.3390/app13148393
Kishida, K., Nishida, Y., & Takeda, N. (2022). Field application of distributed fiber optic sensing on elevated railway bridge. Structural Control and Health Monitoring, 29(3), e2876. https://doi.org/10.1002/stc.2876
Li, X., Jiang, H., & Wang, R. (2024). Deep convolutional neural network based crack detection technique for concrete structures. Automation in Construction, 158, 105312. https://doi.org/10.1016/j.autcon.2020.103199
Lorenzi, A., Somensi, L., Reginato, L. A., Covatti, L., & da Silva Filho, L. C. P. (2024). Application of ultrasonic tomography to detect defects in concrete structures. e-Journal of Nondestructive Testing, 29(3), 1435-4934.
Maierhofer, C., Arndt, R., & Rollig, M. (2007). Influence of concrete properties on the detection of voids with impulse-thermography. Infrared Physics & Technology, 49(3), 213-217. https://doi.org/10.1016/j.infrared.2006.06.007
Mostella, P. (2025). Digital twins show great promise in civil engineering. But what's next? Civil Engineering Source. https://www.asce.org/publications-and-news/civil-engineering-source/article/2025/11/10/digital-twins-show-great-promise-in-civil-engineering-but-whats-next
Nasser, A. A., Sorour, N. M., Saafan, M. A., & Abbas, R. N. (2022). Microbially-induced-calcite-precipitation (MICP): A biotechnological approach to enhance the durability of concrete using Bacillus pasteurii and Bacillus sphaericus. Heliyon, 8(7), e09879. https://doi.org/10.1016/j.heliyon.2022.e09879
Park, B., & Choi, Y. C. (2018). Self-healing capability of cementitious materials with crystalline admixtures and super absorbent polymers (SAPs). Construction and Building Materials, 189, 1054-1066. https://doi.org/10.1016/j.conbuildmat.2018.09.061
Rahman, M. M., Haque, M. A., & others. (2026). Toward durable infrastructure: A review of self-healing geopolymer concrete for sustainable construction. Applied Sciences, 16(3), 1571. https://doi.org/10.3390/app16031571
Sah, A. K., & Hong, Y. M. (2024). Performance comparison of machine learning models for concrete compressive strength prediction. Materials, 17(9), 2075. https://doi.org/10.3390/ma17092075
Sarbangholi, M. M. K., Bahari, A., Ebrahimpour Bozorg, A., Rahmani, H., Vatin, N. I., Gholamian, E., & Kordlou, M. (2025). Bacterial self-healing and mechanical strength enhancement in concrete: A comparative study of Bacillus subtilis, Bacillus sphaericus, and Escherichia coli. Innovative Infrastructure Solutions, 10, 278. https://doi.org/10.1007/s41062-025-02278-2
Shahzad, A., Rehman, S. U., & Lee, S. (2024). Use of carbon nanotubes for the functionalization of self-sensing concrete. Journal of Building Engineering, 89, 109245.
Shiri, M., Bahari, A., Ebrahimpour Bozorg, A., Khani Sarbangholi, M. M., Rahmani, H., Vatin, N. I., Gholamian, E., & Kordlou, M. (2025). Microbial-induced calcite precipitation by indigenous bacteria for self-healing concrete. Scientific Reports, 15, 12345.
Sun, Y., Dong, Z., Zhu, H., Wu, G., Sun, Z., Sun, X., & Ghafoori, E. (2025). Investigation on effective prestress in Fe-SMA bars and flexural behavior of damaged T-shaped RC beams strengthened by NSM method. Structures, 72, 108289. https://doi.org/10.1016/j.istruc.2025.108289
Ta, Q. T., Mac, V. H., Huh, J., & Yim, H. J. (2023). Nondestructive detection of delamination in painted concrete structures through square pulse thermography. Journal of Building Engineering, 73, 106700. https://doi.org/10.1016/j.jobe.2023.106700
Subhan, F.; Noreen, M.; Imran, M.; Tariq, M.; Khan, A.; Shoaib, M. Impact of Node Deployment and Routing for Protection of Critical Infrastructures. IEEE Access 2019, 7, 11502–11514. [Google Scholar] [CrossRef]
Valdivia, L.J.; Del-Valle-Soto, C.; Rosas-Caro, J.C. Wireless communication for railway applications: Reactive and proactive protocols. In Proceedings of the 2019 International Conference on Electronics, Communications and Computers (CONIELECOMP), Cholula, Mexico, 27 February 2018–1 March 2019; pp. 21–26. [Google Scholar]
Yang, H. A practical method for connectivity and coverage reliability analysis for linear wireless sensor networks. Ad. Hoc. Netw. 2023, 146, 103183. [Google Scholar] [CrossRef]
Thomas, M. D. A. (2011). The effect of supplementary cementing materials on alkali-silica reaction: A review. Cement and Concrete Research, 41(12), 1224-1231. https://doi.org/10.1016/j.cemconres.2010.11.003
Wiktor, V., & Jonkers, H. M. (2011). Quantification of crack-healing in novel bacteria-based self-healing concrete. Cement and Concrete Composites, 33(7), 763-770. https://doi.org/10.1016/j.cemconcomp.2011.03.012
Zhang, Y. (2022). Nondestructive evaluation of sub-surface defect in concrete structures based on high-resolution aerial infrared thermography [Doctoral dissertation, University of Nebraska-Lincoln]. Digital Commons @ University of Nebraska-Lincoln. https://digitalcommons.unl.edu/dissertations/AAI28085882/
Downloads
How to Cite
Issue
Section
License
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
