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Rheology-Guided Spray-Applied Engineered Cementitious Composites for Lightweight Structural Repair

Authors

  • Dabin Yang

    Faculty of Engineering, University of New South Wales, Sydney, Australia
    Author

  • Allan Charles

    Faculty of Engineering, University of New South Wales, Sydney, Australia
    Author

  • Ben Daphne

    Faculty of Engineering, University of New South Wales, Sydney, Australia
    Author

DOI:

https://doi.org/10.71465/jgs50

Keywords:

Rheology, Engineered Cementitious Composites, Spray Application, Structural Repair

Abstract

The rapid deterioration of aging civil infrastructure globally has necessitated the development of advanced structural repair materials and application techniques. Conventional concrete repair materials often suffer from premature failure due to poor dimensional compatibility, high brittleness, and inadequate bonding with the substrate. Engineered Cementitious Composites have emerged as a promising alternative due to their extraordinary tensile ductility and tight crack width control. However, the application of Engineered Cementitious Composites in large-scale structural repair, particularly for overhead and vertical surfaces, is severely hindered by the lack of optimized spray application methodologies. This paper presents a comprehensive investigation into the development of a rheology-guided, spray-applied lightweight Engineered Cementitious Composite. By integrating lightweight aggregates, specifically fly ash cenospheres and hollow glass microspheres, the dead load of the repair layer is significantly reduced, addressing critical structural constraints. The core of this research revolves around tailoring the fresh state properties of the composite to meet the paradoxical requirements of pumpability and shootability. Through rigorous rheological modification using specific combinations of polycarboxylate ether superplasticizers and viscosity modifying agents, an optimal rheological window is established. The resulting material demonstrates exceptional thixotropic behavior, enabling low pumping pressure while ensuring structural build-up immediately upon substrate impact, effectively minimizing rebound and sagging. Furthermore, the micromechanical design principles are maintained, ensuring that the spray process induces favorable fiber alignment, thereby preserving the signature strain-hardening behavior of the composite.

References

1. Gao, L., Wang, Y., Wang, J., Yuan, J., Chen, B., & Bai, L. (2025). Experimental and numerical investigation on global-stability of welded BS700 high-strength steel beams. Journal of Constructional Steel Research, 227, 109373.

2. Chen, Q. S., Yu, B., & Li, B. (2022). Probabilistic calibration of compressive stress–strain models for FRP-confined concrete in square cross section members. Journal of Composites for Construction, 26(3), 04022015.

3. Shah, A., Sun, H., Qiao, Z., Khan, M. U., Ali, N., Gao, C., ... & Kashif, M. (2024). Synthesis of iron oxide nanoparticles and its antimicrobial, anticancer, anti-inflammatory, wound healing, and immunomodulatory activities-A Review. Phytopharmacology Research Journal, 3(3), 1-28.

4. Zeng, G., Maylott, S. E., Leung, T. S., Messinger, D. S., Wang, J., & Simpson, E. A. (2022). Infant temperamental fear, pupil dilation, and gaze aversion from smiling strangers. Developmental psychobiology, 64(7), e22324.

5. Li, C., Xu, J., & Xing, J. (2023). A frequency feature extraction method based on convolutional neural network for recognition of incipient fault. IEEE Sensors Journal, 24(1), 564-572.

6. Xing, J., & Xu, J. (2022). An improved incipient fault diagnosis method of bearing damage based on hierarchical multi-scale reverse dispersion entropy. Entropy, 24(6), 770.

7. Gu, D., Xu, H., Huang, Y., Zhu, Y., Pan, J., & Luković, M. (2024). Shear crack kinematics in reinforced engineered cementitious composite (ECC) beams. Case Studies in Construction Materials, 21, e03587.

8. Liu, T. (2022, December). Financial Constraint’Impact on Firms’ ESG Rating Based on Chinese Stock Market. In 2022 4th International Conference on Economic Management and Cultural Industry (ICEMCI 2022) (pp. 1085-1095). Atlantis Press.

9. Zhou, X., Wang, P., Al-Dhaifallah, M., Rawa, M., & Khadimallah, M. A. (2022). A machine learning-based model for the estimation of the critical thermo-electrical responses of the sandwich structure with magneto-electro-elastic face sheet. Advances in nano research, 12(1), 81-99.

10. Wang, Y., Khan, M., Uy, B., Lim, L., Thai, H. T., & Ngo, T. (2025). Behaviour, design and performance of steel-concrete composite walls in fire. Journal of Constructional Steel Research, 227, 109408.

11. Li, K., Ren, Y., Fan, D., Liu, L., Wang, Z., & Ma, Z. (2018). Enhance GO methodology for reliability analysis of the closed-loop system using Cyclic Bayesian Networks. Mechanical Systems and Signal Processing, 113, 237-252.

12. Zhang, W., Luo, M., & Chen, Z. (2024, October). Hybrid Forecasting: ML Predictions of Lake-Effect Regional Extreme Precipitations. In 2024 7th International Conference on Universal Village (UV) (pp. 1-11). IEEE.

13. Yao, Z., Hawi, P., Aitharaju, V., Mahishi, J., & Ghanem, R. (2024, October). Transfer Learning for Multiscale Analysis: Delamination of Carbon-Reinforced Composite Material Exploration. In American Society for Composites (ASC) Annual Technical Conference (pp. 95-112). Cham: Springer Nature Switzerland.

14. Pan, J., Lu, B., Gu, D., Xia, Z., & Xia, T. (2015). Mechanical behavior of rectangular steel-reinforced ECC/concrete composite column under eccentric compression. Transactions of Tianjin University, 21(3), 269-277.

15. Wei, G., Yang, Y., Li, R., Liu, Y., & He, B. J. (2024). Digital economy exhibits varying degrees of mitigation of air pollution in China: Total cities-economic subdivisions-urban agglomerations. Iscience, 27(6).

16. Wang, S., Sun, P., Sun, F., Jiang, S., Zhang, Z., & Wei, G. (2021). The direct and spillover effect of multi-dimensional urbanization on PM2. 5 concentrations: A case study from the Chengdu-Chongqing urban agglomeration in China. International Journal of Environmental Research and Public Health, 18(20), 10609.

17. Fan, J., Liang, W., & Zhang, W. Q. (2025). SARNet: A Spike-Aware consecutive validation Framework for Accurate Remaining Useful Life Prediction. arXiv preprint arXiv:2510.22955.

18. Sun, W., Dong, X. M., Cui, B., & Tang, J. (2025, April). Attentive eraser: Unleashing diffusion model’s object removal potential via self-attention redirection guidance. In Proceedings of the AAAI Conference on Artificial Intelligence (Vol. 39, No. 19, pp. 20734-20742).

19. Bao, Zerui, et al. "SLOFetch: Compressed-Hierarchical Instruction Prefetching for Cloud Microservices." arXiv preprint arXiv:2511.04774 (2025).

20. Kashif, M., Jawad, M., Khan, A. A., Sun, H., Ullah, K., Fakayode, O., & Azizi, S. (2024). Fe/Ti-codoped strontium oxide nanoparticles for enhanced photocatalytic degradation of methyl orange. Journal of Applied Research in Water and Wastewater, 11(1), 8-14.

21. Huang, H., Zhang, J., Yu, L., Zhang, J., Wu, Q., & Xu, C. (2021). TOAN: Target-oriented alignment network for fine-grained image categorization with few labeled samples. IEEE Transactions on Circuits and Systems for Video Technology, 32(2), 853-866.

22. Yan, J., Ma, H., Wang, X., Li, H., Li, B., Wei, Q., & Cao, Z. (2025). Direct Measurement of Transverse Compressive Properties of Polyacrylonitrile-Based Single Carbon Fibers. Materials, 18(13), 3018.

23. Huang, J., & Sandeep, H. (2025, October). RESEARCH ON REINFORCEMENT LEARNING FOR TRUSTWORTHY CLIMATE POLICY SIMULATION AND APPLICATION. In The 7th International scientific and practical conference “Development of modern scientific technologies in the era of globalization”(October 14-17, 2025) Berlin, Germany. International Science Group. 2025. 237 p. (p. 32).

24. Chen, Q., & Li, B. (2026, May). Probabilistic damage assessment of longitudinally reinforced concrete beams using explainable AI and image-based analysis for structural health monitoring. In Structures (Vol. 87, p. 111594). Elsevier.

25. Wei, G., Zhang, W., Bi, M., Sun, P., Li, S., Ouyang, X., ... & Tian, X. (2024). Trade-offs and synergies pattern evolution of ecosystem structure-resilience-activity-services (SRAS) in the Belt and Road Initiative region. Resources, Conservation and Recycling, 211, 107883.

26. Chen, Q., & Li, B. (2025). Explainable artificial intelligence (XAI)-driven probabilistic image-based structural health monitoring of reinforced concrete beams with shear reinforcements. Automation in Construction, 180, 106549.

27. Wang, J. (2023, July). A multi-task learning and transfer learning-based model for crop leaf disease identification. In 2023 3rd International Symposium on Computer Technology and Information Science (ISCTIS) (pp. 348-355). IEEE.

28. Gu, D., Jiang, B., Lin, J., Xu, L., & Pan, J. (2025). Shear behaviour of steel-headed stud connectors in engineered cementitious composite (ECC) bridge deck under positive and negative moments. Engineering Structures, 324, 119316.

29. Xing, J., & Xu, J. (2022). An improved convolutional neural network for recognition of incipient faults. IEEE Sensors Journal, 22(16), 16314-16322.

30. Qi, Z., Yuan, Y., Ruan, X., Wang, S., Zhang, W., & Huang, Q. (2024, March). Bias-conflict sample synthesis and adversarial removal debias strategy for temporal sentence grounding in video. In Proceedings of the AAAI Conference on Artificial Intelligence (Vol. 38, No. 5, pp. 4533-4541).

31. Hawi, P. H. I. L. I. P. P. E., Yao, Z., Aitharaju, V., Mahishi, J., & Ghanem, R. (2023). A framework for design allowables accounting for paucity of data and errors in complex models. In Proceedings of the American society for composites-thirty-eighth technical conference.

32. Gu, D., Sun, Y., Hu, J., Lu, R., & Pan, J. (2026). Rheology-and fracture-guided design of lightweight spray-applied engineered cementitious composites achieving structural-grade strength and high tensile ductility. Journal of Building Engineering, 116100.

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Published

2026-05-05

Issue

Vol. 6 No. 01 (2026): Journal of geospace science

Section

Articles

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Copyright (c) 2026 Dabin Yang, Allan Charles, Ben Daphne (Author)

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