Undersampling Strategy for Machine-learned Deterioration Regression Model in Concrete Bridges

Okazaki, Yuriko; Okazaki, Shinichiro; Asamoto, Shingo; Chun, Pang‐jo

doi:10.3151/jact.18.753

Cited by 3 publications

(1 citation statement)

References 27 publications

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“…Getah tersebut belum menggumpal dengan bahan tambahan seperti serum lateks atau tanpa bahan penstabil (zat antikoagulan). Didalam lateks terdapat 90-95% karet murni, 2-3% protein, 1-2% asam lemak, 0,2% gula, dan 0,5% jenis garam [15] [16]. Lateks memiliki elastisitas atau ketahanan yang sempurna, plastisitas yang baik, kekenyalan yang tinggi, yang meningkatkan kuat tarik saat diregangkan [17].…”

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Optimalisasi Kuat Tekan dan Kuat Lentur Beton Menggunakan Campuran Lateks

et al. 2021

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Concrete is a building construction material that has an important role. Concrete itself tends to have strong properties in resisting compressive forces, but weak in resisting tensile or flexural forces. The use of additives in concrete is an option to improve the basic properties of concrete. Latex or rubber latex is one of the natural materials that can be used in concrete mixtures. Its adhesive properties can be utilized in improving the quality of concrete. This study aims to determine the compressive strength and flexural strength of concrete with the addition of latex. The research was conducted experimentally by making concrete specimens in the laboratory. The addition of latex by 10% and 30% with a planned concrete quality of fc' 29.5 MPa. The test object used is a cylinder measuring 15x30 cm and a beam measuring 15x15x30 cm. The tests carried out were testing the compressive strength and flexural strength at the age of 28 days. The results showed that the highest compressive strength was at the addition of 10% latex with a value of 9.96 MPa. While the highest flexural strength value obtained was 3.20 Mpa at the addition of 10% Latex or. From these results it can be seen that the addition of latex has not been able to improve the quality of concrete and has not been able to increase the compressive strength or flexural strength of concrete. So that these results can be used as research development or concrete production.

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Optimalisasi Kuat Tekan dan Kuat Lentur Beton Menggunakan Campuran Lateks

et al. 2021

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Data augmentation using conditional generative adversarial network (cGAN): Application for prediction of corrosion pit depth and testing using neural network

Woldesellasse

Tesfamariam²

2023

Journal of Pipeline Science and Engineering

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Machine learning in concrete science: applications, challenges, and best practices

Yoon

Zhang

et al. 2022

npj Comput Mater

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Concrete, as the most widely used construction material, is inextricably connected with human development. Despite conceptual and methodological progress in concrete science, concrete formulation for target properties remains a challenging task due to the ever-increasing complexity of cementitious systems. With the ability to tackle complex tasks autonomously, machine learning (ML) has demonstrated its transformative potential in concrete research. Given the rapid adoption of ML for concrete mixture design, there is a need to understand methodological limitations and formulate best practices in this emerging computational field. Here, we review the areas in which ML has positively impacted concrete science, followed by a comprehensive discussion of the implementation, application, and interpretation of ML algorithms. We conclude by outlining future directions for the concrete community to fully exploit the capabilities of ML models.

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Undersampling Strategy for Machine-learned Deterioration Regression Model in Concrete Bridges

Cited by 3 publications

References 27 publications

Optimalisasi Kuat Tekan dan Kuat Lentur Beton Menggunakan Campuran Lateks

Optimalisasi Kuat Tekan dan Kuat Lentur Beton Menggunakan Campuran Lateks

Data augmentation using conditional generative adversarial network (cGAN): Application for prediction of corrosion pit depth and testing using neural network

Machine learning in concrete science: applications, challenges, and best practices

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