The effectiveness of surrogate models in predicting the long-term behavior of varying compressive strength ranges of recycled concrete aggregate for a variety of shapes and sizes of specimens

• Autorzy: Ibrahim Aisha Kamal , Dhahir Hyfaa Yasin , Mohammed Ahmed Salih , Omar Helen Ali , Sedo Ammar Hassan

Identyfikatory

DOI

10.1007/s43452-022-00595-2

• Języki publikacji: EN

Abstrakty

EN

One of the most fundamental developments in improving the mechanical properties of concrete is the introduction of recycled coarse aggregate, which offers an environmentally preferable substitute for traditional waste management techniques. Using recycled coarse aggregate and a small number of mix proportions for the concrete components, a few studies looked at the mechanical properties of concrete. To assess the impact of recycled coarse aggregate on the long-term compressive strength of concrete at various mix proportions and different compressive strength ranges, this study analyzed four models, including linear regression (LR), nonlinear regression (NLR), pure quadratic (PQ), and full quadratic (FQ). Three datasets training, testing, and validating, each containing 314 data points culled from various studies, were used to apply the models. The recycled coarse aggregate (RA) density ranged from 0 to 1240 kg/m³, and the curing time (t) varied from 1 to 90 days. While the predicted compressive strength of the models ranged between 5 and 75 MPa, the compressive strength of the data gathered from the experimental work of several studies ranged from 8 to 78 MPa. The models’ accuracy was assessed using several metrics, including the coefficient of determination (R²), the root-mean-square error (RMSE), the scatter index (SI), the objective (OBJ), and the mean absolute error (MAE).

Słowa kluczowe

EN

mix proportion; compressive strength; statistical analysis; assessment criteria

PL

wytrzymałość na ściskanie; analiza statystyczna; kryteria oceny

• Wydawca: Springer ; Wrocław University of Science and Technology
• Czasopismo: Archives of Civil and Mechanical Engineering
• Rocznik: 2023
• Tom: Vol. 23, no. 1
• Strony: art. no. e61, 2023
• Opis fizyczny: Bibliogr. 35 poz., rys., tab., wykr.

Twórcy

autor

Ibrahim Aisha Kamal

• Civil Engineering Department, College of Engineering, American University of Iraq Sulaimani, Kurdistan, Sulaimani, Iraq

autor

Dhahir Hyfaa Yasin

• Civil Engineering Department, College of Engineering, American University of Iraq Sulaimani, Kurdistan, Sulaimani, Iraq

autor

Mohammed Ahmed Salih

• Civil Engineering Department, College of Engineering, American University of Iraq Sulaimani, Kurdistan, Sulaimani, Iraq
• American University of Iraq, Sulaimani, Iraq
• ACI-Kurdistan Chapter (AUIS-Student Chapter), Sulaymaniyah, Iraq

• https://orcid.org/0000-0003-4306-3274

autor

Omar Helen Ali

• Civil Engineering Department, College of Engineering, American University of Iraq Sulaimani, Kurdistan, Sulaimani, Iraq

autor

Sedo Ammar Hassan

• Civil Engineering Department, College of Engineering, American University of Iraq Sulaimani, Kurdistan, Sulaimani, Iraq

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Uwagi

PL

Opracowanie rekordu ze środków MEiN, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2022-2023)