Glass fibre concrete: experimental investigation and predictive modeling using advanced machine learning with an interactive online interface

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Mohamed, Rabie and Shaaban, Ibrahim ORCID: https://orcid.org/0000-0003-4051-341X (2025) Glass fibre concrete: experimental investigation and predictive modeling using advanced machine learning with an interactive online interface. Construction and Building Materials, 472. pp. 1-21. ISSN 0950-0618

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Abstract

This study investigates the mechanical properties of glass fibre concrete (GFC) through experimental and predictive analysis using advanced machine learning (ML) techniques. The experimental work focuses on the mechanical and durability characteristics of GFC. The data obtained in the experimental testing were added to the dataset collected from the literature for the application of machine learning algorithms. The dataset contains 108 compressive strength and 87 split tensile strength data points that evaluated vital factors, including fly ash, cement, aggregates, water, fibre content, superplasticizer, fibre length, fibre diameter, and micro-silica. Optuna, a state-of-the-art hyperparameter optimization library utilizing deep learning, was employed to determine the optimal hyperparameters for each model. The best hyperparameters were selected based on the highest average performance from 5-fold cross-validation. Experimental results showed significant influences of fibre content on GFC mechanical and durability characteristics. The Gradient Tree Boosting Regression (GTBR) model was identified as the optimal model for predicting the compressive and split tensile strength of GFC. The model demonstrated high predictive accuracy for both compressive and split tensile strengths, with R2 values of 0.968 and 0.954, respectively. Shapley Additive exPlanations (SHAP) analysis emphasized the significant impact of fine aggregate, cement, and the amount of glass fibre on both compressive and split tensile strengths, providing valuable insights into the contribution of each feature and enhancing the explainability of the optimum ML model. Finally, a user-friendly online interface was developed, allowing users to predict GFC properties based on the trained GTBR model. This tool, featuring interactive sliders for input variables, ensures precise predictions within the collected data range.

Item Type:	Article
Identifier:	10.1016/j.conbuildmat.2025.140951
Keywords:	Glass fibre concrete, Machine learning, Hyperparameter optimization, Compressive strength, Split tensile strength, Durability, Online user-friendly interface
Subjects:	Construction and engineering
Depositing User:	Ibrahim Shaaban
Date Deposited:	25 Apr 2025 08:16
Last Modified:	25 Apr 2025 08:30
URI:	https://repository.uwl.ac.uk/id/eprint/13492

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References

S. Sbahieh, M. Rabie, U. Ebead, S.G. Al-Ghamdi, The mechanical and environmental performance of fiber-reinforced polymers in concrete structures: opportunities, challenges and future directions, Buildings 12 (2022) 1417.

M.S. Saif, A.S. Shanour, G.E. Abdelaziz, H.I. Elsayad, I.G. Shaaban, B.A. Tayeh, M. S. Hammad, Influence of blended powders on properties of ultra-high strength fibre reinforced self compacting concrete subjected to elevated temperatures, Case Stud. Constr. Mater. 18 (2023) e01793.

M.R. Irshidat, N. Al-Nuaimi, M. Rabie, Hybrid effect of carbon nanotubes and polypropylene microfibers on fire resistance, thermal characteristics and microstructure of cementitious composites, Constr. Build. Mater. 266 (2021) 121154.

A.S. Fayed, A.S. Sherbini, H.S.S. Abou El-Mal, Mixed mode fracture behavior of fiber reinforced concrete; experimental and numerical analysis adopting cracked Brazilian disc specimen, Ain Shams Eng. J. 14 (2023) 102132, https://doi.org/ 10.1016/j.asej.2023.102132.

A. Ulu, A.I. Tutar, A. Kurklu, F. Cakir, Effect of excessive fiber reinforcement on mechanical properties of chopped glass fiber reinforced polymer concretes, Constr. Build. Mater. 359 (2022) 129486, https://doi.org/10.1016/j. conbuildmat.2022.129486.

M.S. Khan, A. Fuzail Hashmi, M. Shariq, S.M. Ibrahim, Effects of incorporating fibres on mechanical properties of fibre-reinforced concrete: a review, Mater. Today Proc. (2023), https://doi.org/10.1016/j.matpr.2023.05.106.

Y. Ju, M. Zhu, X. Zhang, D. Wang, Influence of steel fiber and polyvinyl alcohol fiber on properties of high performance concrete, Struct. Concr. 23 (2022) 1687–1703, https://doi.org/10.1002/suco.202100775.

J. Yu, Y. Chen, C. Leung, Mechanical performance of Strain-Hardening Cementitious Composites (SHCC) with hybrid polyvinyl alcohol and steel fibers, Compos. Struct. (2019), https://doi.org/10.1016/J.COMPSTRUCT.2019.111198.

P. Zhang, Y. Zheng, K. Wang, K. Zhang, Combined influence of nano-CaCO3 and polyvinyl alcohol fibers on fresh and mechanical performance of concrete incorporating fly ash, Struct. Concr. 21 (2019) 724–734, https://doi.org/10.1002/ suco.201900134.

V. Sivakumar, O. Kavitha, G. Arulraj, V. Srisanthi, An experimental study on combined effects of glass fiber and Metakaolin on the rheological, mechanical, and durability properties of self-compacting concrete, Appl. Clay Sci. 147 (2017) 123–127, https://doi.org/10.1016/J.CLAY.2017.07.015.

M. Madhkhan, R. Katirai, Effect of pozzolanic materials on mechanical properties and aging of glass fiber reinforced concrete, Constr. Build. Mater. (2019), https:// doi.org/10.1016/J.CONBUILDMAT.2019.07.128.

Z. Yuan, Y. Jia, Mechanical properties and microstructure of glass fiber and polypropylene fiber reinforced concrete: an experimental study, Constr. Build. Mater. 266 (2021) 121048, https://doi.org/10.1016/J. CONBUILDMAT.2020.121048.

M. Anjum, K. Khan, W. Ahmad, A. Ahmad, M.N. Amin, A. Nafees, Application of ensemble machine learning methods to estimate the compressive strength of fiber reinforced nano-silica modified concrete, Polymers 14 (2022) 3906, https://doi. org/10.3390/polym14183906.

Q.-F. Li, Z.-M. Song, High-performance concrete strength prediction based on ensemble learning, Constr. Build. Mater. 324 (2022) 126694.

H. Thiagu, T.C. Madhavi, Optimization of fibre reinforced foam concrete for the mechanical behaviour by artificial neural network, Asian J. Civ. Eng. 24 (2023) 3175–3190.

C. Cs, B.U. Shankar, Effect of foundry sand and glass fibres in concrete using artificial neural network, J. Civ. Eng. 11 (2020).

G. Nakkeeran, L. Krishnaraj, A. Bahrami, H. Almujibah, H. Panchal, M.M.A. Zahra, Machine learning application to predict the mechanical properties of glass fiber mortar, Adv. Eng. Softw. 180 (2023) 103454, https://doi.org/10.1016/j. advengsoft.2023.103454.

Travis Perkins | Builders’ Merchant | Building Supplies, (n.d.). 〈https://www.travis perkins.co.uk/〉 (accessed June 20, 2024).

B. Ali, L.A. Qureshi, Influence of glass fibers on mechanical and durability performance of concrete with recycled aggregates, Constr. Build. Mater. 228 (2019) 116783, https://doi.org/10.1016/j.conbuildmat.2019.116783.

BS EN 12350–2:2019 - TC. Testing fresh concrete. Slump-test, British Standards Institution, London, UK, 2019..

BS 1881: Part 116:1983. Testing concrete. Method for determination of compressive strength of concrete cubes, British Standards Institution, London, UK, 1983..

ASTM C496/C496M-17, Standard Test Method for Splitting Tensile Strength of Cylindrical Concrete Specimens, ASTM International, West Conshohocken, PA, 2017.

J. Sanjeev, K.J.N. Sai Nitesh, Study on the effect of steel and glass fibers on fresh and hardened properties of vibrated concrete and self-compacting concrete, Mater. Today Proc. 27 (2020) 1559–1568, https://doi.org/10.1016/j.matpr.2020.03.208.

Y.R. Atewi, M.F. Hasan, E. Güneyisi, Fracture and permeability properties of glass fiber reinforced self-compacting concrete with and without nanosilica, Constr. Build. Mater. 226 (2019) 993–1005, https://doi.org/10.1016/j. conbuildmat.2019.08.029.

B. Ali, L.A. Qureshi, S.U. Khan, Flexural behavior of glass fiber-reinforced recycled aggregate concrete and its impact on the cost and carbon footprint of concrete pavement, Constr. Build. Mater. 262 (2020) 120820, https://doi.org/10.1016/j. conbuildmat.2020.120820.

V.R. Sivakumar, O.R. Kavitha, G. Prince Arulraj, V.G. Srisanthi, An experimental study on combined effects of glass fiber and Metakaolin on the rheological, mechanical, and durability properties of self-compacting concrete, Appl. Clay Sci. 147 (2017) 123–127, https://doi.org/10.1016/j.clay.2017.07.015.

P. Asokan, M. Osmani, A. Price, Improvement of the mechanical properties of glass fibre reinforced plastic waste powder filled concrete, Constr. Build. Mater. 24 (2010) 448–460, https://doi.org/10.1016/j.conbuildmat.2009.10.017.

M. Mastali, A. Dalvand, A.R. Sattarifard, The impact resistance and mechanical properties of reinforced self-compacting concrete with recycled glass fibre reinforced polymers, J. Clean. Prod. 124 (2016) 312–324, https://doi.org/ 10.1016/j.jclepro.2016.02.148.

A.K. Parashar, A. Gupta, Investigation of the effect of bagasse ash, hooked steel fibers and glass fibers on the mechanical properties of concrete, Mater. Today Proc. 44 (2021) 801–807, https://doi.org/10.1016/j.matpr.2020.10.711

L. Qureshi, A. Raza, S. Rehman, M. Nawaz, M. Rashid, Influence of glass fibers on mechanical properties of concrete with recycled coarse aggregates, Civ. Eng. J. 5 (2019) 1007–1019, https://doi.org/10.28991/cej-2019-03091307.

J. Ahmad, R.A. Gonzalez-Lezcano, ´ A. Majdi, N. Ben Kahla, A.F. Deifalla, M.A. El Shorbagy, Glass fibers reinforced concrete: overview on mechanical, durability and microstructure analysis, Materials 15 (2022) 5111, https://doi.org/10.3390/ ma15155111.

J. Ahmad, O. Zaid, F. Aslam, M. Shahzaib, R. Ullah, H. Alabduljabbar, K. M. Khedher, A study on the mechanical characteristics of glass and nylon fiber reinforced peach shell lightweight concrete, Materials 14 (2021) 4488, https://doi. org/10.3390/ma14164488.

L. Hou, B. Wen, W. Huang, X. Zhang, X. Zhang, Mechanical properties and microstructure of polypropylene–glass-fiber-reinforced desert sand concrete, Polymers 15 (2023) 4675, https://doi.org/10.3390/polym15244675.

H. Tahir, M.B. Khan, N. Shafiq, D. Radu, M.H. Nyarko, A. Waqar, H.R. Almujibah, O. Benjeddou, Optimisation of mechanical characteristics of alkali-resistant glass fibre concrete towards sustainable construction, Sustainability 15 (2023), https:// doi.org/10.3390/su151411147.

A. Singh, A. Charak, K.P. Biligiri, V. Pandurangan, Glass and carbon fiber reinforced polymer composite wastes in pervious concrete: material characterization and lifecycle assessment, Resour. Conserv. Recycl 182 (2022) 106304, https://doi.org/10.1016/j.resconrec.2022.106304.

T. Jeevetha, S. VijayaShanthy, A. Sivakumar, N.B. Singh, Evaluation on strength parameters of self-compacting concrete incorporated with carbon and glass fibres,Mater. Today Proc. 45 (2021) 708–712, https://doi.org/10.1016/j. matpr.2020.02.743.
B. Ali, L.A. Qureshi, Influence of glass fibers on mechanical and durability performance of concrete with recycled aggregates, Constr. Build. Mater. 228 (2019) 116783, https://doi.org/10.1016/j.conbuildmat.2019.116783.

M. Madhkhan, R. Katirai, Effect of pozzolanic materials on mechanical properties and aging of glass fiber reinforced concrete, Constr. Build. Mater. 225 (2019) 146–158, https://doi.org/10.1016/j.conbuildmat.2019.07.128.

M. Abdi Moghadam, R.A. Izadifard, Effects of steel and glass fibers on mechanical and durability properties of concrete exposed to high temperatures, Fire Saf. J. 113 (2020) 102978, https://doi.org/10.1016/j.firesaf.2020.102978.

J.K. Ganta, M.V. Seshagiri Rao, S.S. Mousavi, V. Srinivasa Reddy, C. Bhojaraju, Hybrid steel/glass fiber-reinforced self-consolidating concrete considering packing factor: mechanical and durability characteristics, Structures 28 (2020) 956–972, https://doi.org/10.1016/j.istruc.2020.09.042.

S.T. Tassew, A.S. Lubell, Mechanical properties of glass fiber reinforced ceramic concrete, Constr. Build. Mater. 51 (2014) 215–224, https://doi.org/10.1016/j. conbuildmat.2013.10.046.

F. Cakir, Evaluation of mechanical properties of chopped glass/basalt fibers reinforced polymer mortars, Case Stud. Constr. Mater. 15 (2021) e00612, https:// doi.org/10.1016/j.cscm.2021.e00612.

M.E. Arslan, Effects of basalt and glass chopped fibers addition on fracture energy and mechanical properties of ordinary concrete: CMOD measurement, Constr. Build. Mater. 114 (2016) 383–391, https://doi.org/10.1016/j. conbuildmat.2016.03.176.

A. Tibebu, E. Mekonnen, L. Kumar, J. Chimdi, H. Hailu, N. Fikadu, Compression and workability behavior of chopped glass fiber reinforced concrete, Mater. Today Proc. 62 (2022) 5087–5094, https://doi.org/10.1016/j.matpr.2022.02.427.

T. Thaker, S.P. Dalal, R. Motiani, H. Contractor, Effect of electrical grade glass fibers and alkaline resistant glass fibers on high strength concrete, Mater. Today Proc. 62 (2022) 6998–7001, https://doi.org/10.1016/j.matpr.2021.12.542.

H. Alguhi, D. Tomlinson, Experimental and analytical study of steel and chopped glass fibre reinforced concrete under compression, Constr. Build. Mater. 418 (2024) 135421, https://doi.org/10.1016/j.conbuildmat.2024.135421.

M. Waskom, seaborn: statistical data visualization, J. Open Source Softw. 6 (2021) 3021, https://doi.org/10.21105/JOSS.03021.

M. Jalal, P. Arabali, Z. Grasley, J.W. Bullard, H. Jalal, Behavior assessment, regression analysis and support vector machine (SVM) modeling of waste tire rubberized concrete, J. Clean. Prod. 273 (2020) 122960, https://doi.org/10.1016/ j.jclepro.2020.122960.

M. Pal, S. Deswal, Support vector regression based shear strength modelling of deep beams, Comput. Struct. 89 (2011) 1430–1439, https://doi.org/10.1016/j. compstruc.2011.03.005.

C. Cortes, V. Vapnik, Support-vector networks, Mach. Learn 20 (1992) 273–297, https://doi.org/10.1109/64.163674.

C.C. Chang, C.J. Lin, LIBSVM: a library for support vector machines, ACM Trans. Intell. Syst. Technol. 2 (2011), https://doi.org/10.1145/1961189.1961199.
C.J.C. Burges, A tutorial on support vector machines for pattern recognition, Data Min. Knowl. Discov. 2 (1998), https://doi.org/10.1023/A:1009715923555. [55] H. Drucker, C.J. Burges, L. Kaufman, A. Smola, V. Vapnik, Support vector regression machines, Adv. Neural Inf. Process. Syst. 9 (1996).
L. Breiman, J. Friedman, C.J. Stone, R.A. Olshen, Classification and regression trees, CRC press, 1984. [57] Y. Freund, L. Mason, The alternating decision tree learning algorithm, Icml (1999) 124–133.

K. Fawagreh, M.M. Gaber, E. Elyan, Random forests: from early developments to recent advancements, Syst. Sci. Control Eng. Open Access J. 2 (2014) 602–609. [59] L. Breiman, Random forests, Mach. Learn 45 (2001) 5–32.

P. Geurts, D. Ernst, L. Wehenkel, Extremely randomized trees, Mach. Learn 63 (2006) 3–42.

J.H. Friedman, Stochastic gradient boosting, Comput. Stat. Data Anal. 38 (2002) 367–378, https://doi.org/10.1016/S0167-9473(01)00065-2.

M.A. Aladsani, H. Burton, S.A. Abdullah, J.W. Wallace, Explainable machine learning model for predicting drift capacity of reinforced concrete walls, Acids Struct. J. 119 (2022).

C. Cakiroglu, M. Shahjalal, K. Islam, S.M.F. Mahmood, A.H.M.M. Billah, M. L. Nehdi, Explainable ensemble learning data-driven modeling of mechanical properties of fiber-reinforced rubberized recycled aggregate concrete, J. Build. Eng. 76 (2023) 107279, https://doi.org/10.1016/J.JOBE.2023.107279.

T. Akiba, S. Sano, T. Yanase, T. Ohta, M. Koyama, Optuna: A Next-generation Hyperparameter Optimization Framework, in: Proc. 25th ACM SIGKDD Int. Conf. Knowl. Discov. Data Min., 2019.

N. Ruben, C. Venkatesh, C. Durga, M. Chand, Comprehensive study on performance of glass fibers-based concrete, Innov. Infrastruct. Solut. 6 (2021) 1–11, https://doi.org/10.1007/s41062-021-00490-4.

H. Othman, H. Marzouk, M. Sherif, Effects of variations in compressive strength and fibre content on dynamic properties of ultra-high performance fibre-reinforced concrete, Constr. Build. Mater. (2019), https://doi.org/10.1016/J. CONBUILDMAT.2018.11.093.

A. Abrishambaf, M. Pimentel, S. Nunes, Influence of fibre orientation on the tensile behaviour of ultra-high performance fibre reinforced cementitious composites, Cem. Concr. Res. 97 (2017) 28–40, https://doi.org/10.1016/J. CEMCONRES.2017.03.007.

S. Fu, B. Lauke, Effects of fiber length and fiber orientation distributions on the tensile strength of short-fiber-reinforced polymers, Compos. Sci. Technol. 56 (1996) 1179–1190, https://doi.org/10.1016/S0266-3538(96)00072-3.

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Glass fibre concrete: experimental investigation and predictive modeling using advanced machine learning with an interactive online interface

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