期刊
INTERNATIONAL JOURNAL OF SUSTAINABLE ENGINEERING
卷 14, 期 4, 页码 835-851出版社
TAYLOR & FRANCIS LTD
DOI: 10.1080/19397038.2021.1929549
关键词
Fuzzy logic; concrete compressive strength; MATLAB; palm-bunch-ash; bentonite
This study demonstrates the modelling of green-concrete's mechanical properties using fuzzy logic and partial replacement of cementitious portion with PBA/BN. The evaluation of elemental oxides and strength responses shows improved performance in concrete with these admixtures. The fuzzy logic model outperforms in predicting setting time and mechanical properties of PBA/BN-concrete.
This study presents green-concrete's mechanical-properties modelling with cementitious portion replaced by PBA/BN ranging from 0-50% using fuzzy-logic. Incorporation of these admixtures in concrete encourages solid-waste derivatives utilization to achieve cost-effective and eco-efficient construction-materials which also mitigates environmental-degradation challenges due to CO(2-)emission during cement production and hydration. Assessment of the elemental-oxides inherent in the admixtures showed a good pozzolanic-activity with Al2O3+SiO2+Fe2O3 results of 74.75% and 72.03% for PBA and BN respectively. The maximum and minimum strength-responses were derived at 5%-replacement and 50%-replacement with experimental-results of 19.48-4.17MPa, 21.85-4.84MPa, 26.30-8.637MPa, 32.77-12.713MPa and 35.53-18.46MPa for 3-d,7-d,28-d,60-d and 90-d respectively. Fuzzy-logic technique was utilized to evaluate the strength development property of the green-concrete as it takes precisely into account the issue of vagueness of well-defined parameters to develop expert intelligent-model using Mamdani-FIS. The model's performance was evaluated by using MLR-models, MAPE and RMSE. R-2 of 84.905% and 99.1% was calculated for MLR-model and fuzzy-logic model respectively. RMSE and MAPE score of 2.406-2.14%, 6.5935-7.29%, 0.4183-4.62%, 0.2774-1.54%, 0.7544-2.06%, 0.4197-1.48% and 0.7912-1.66% were calculated for the initial and final setting-time, 3-d,7-d,28-d,60-d and 90-d concrete's compressive-strength target responses respectively. The results obtained from the indicates better performance for the fuzzy-logic model in predicting the setting-time and mechanical-properties of PBA/BN-concrete.
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