Comparison of various machine learning algorithms used for compressive strength prediction of steel fiber-reinforced concrete. [PDF]
Sci Rep, 2023 Adding hooked industrial steel fibers (ISF) to concrete boosts its tensile and flexural strength. However, the understanding of ISF’s influence on the compressive strength (CS) behavior of concrete is still questioned by the scientific society.
Pakzad SS, Roshan N, Ghalehnovi M.
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Residual Compressive Strength Prediction Model for Concrete Subject to High Temperatures Using Ultrasonic Pulse Velocity. [PDF]
Materials (Basel), 2023 This study measured and analyzed the mechanical properties of normal aggregate concrete (NC) and lightweight aggregate concrete (LC) subjected to high temperatures. The target temperature was set to 100, 200, 300, 500, and 700 °C, and W/C was set to 0.41,
Kim W, Choi H, Lee T.
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Compressive strength prediction model of lightweight high-strength concrete
Magazine of Civil Engineering, 2022 A reasonable prediction of the compressive strength of lightweight high-strength concrete is an important basis for determining concrete strength. Through cluster analysis, the key factors affecting the compressive strength of lightweight high-strength ...
Zhang Lina +4 more
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Machine learning and interactive GUI for concrete compressive strength prediction. [PDF]
Sci RepConcrete compressive strength (CS) is a crucial performance parameter in concrete structure design. Reliable strength prediction reduces costs and time in design and prevents material waste from extensive mixture trials. Machine learning techniques solve
Elshaarawy MK, Alsaadawi MM, Hamed AK.
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Performance Comparison of Machine Learning Models for Concrete Compressive Strength Prediction. [PDF]
Materials (Basel)This study explores the prediction of concrete compressive strength using machine learning models, aiming to overcome the time-consuming and complex nature of conventional methods.
Sah AK, Hong YM.
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Compressive strength prediction and low-carbon optimization of fly ash geopolymer concrete based on big data and ensemble learning. [PDF]
PLoS OnePortland cement concrete (PCC) is a major contributor to human-made CO2 emissions. To address this environmental impact, fly ash geopolymer concrete (FAGC) has emerged as a promising low-carbon alternative.
Jiang P +5 more
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Supervised Learning Methods for Modeling Concrete Compressive Strength Prediction at High Temperature. [PDF]
Materials (Basel), 2021 Supervised learning algorithms are a recent trend for the prediction of mechanical properties of concrete. This paper presents AdaBoost, random forest (RF), and decision tree (DT) models for predicting the compressive strength of concrete at high ...
Ahmad M +7 more
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Concrete compressive strength prediction using an explainable boosting machine model
Case Studies in Construction Materials, 2023 The mixing ratio of the raw materials has a significant impact on concrete compressive strength. Although the compressive strength of concrete can be inferred from the mix ratio, it is frequently challenging to determine how each mix ratio parameter ...
Gaoyang Liu, Bochao Sun
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Prediction of Lightweight Aggregate Concrete Compressive Strength [PDF]
Journal of Rehabilitation in Civil Engineering, 2018 Nowadays, the better performance of lightweight structures during earthquake has resulted in using lightweight concrete more than ever. However, determining the compressive strength of concrete used in these structures during their service through a none-
Omid Fatahi, Saeed Jafari
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Automatic Modeling for Concrete Compressive Strength Prediction Using Auto-Sklearn
Buildings, 2022 Machine learning is widely used for predicting the compressive strength of concrete. However, the machine learning modeling process relies on expert experience.
M. Shi, Weigang Shen
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