A machine learning model for predicting the mechanical strength of cement-based materials filled with waste rubber modified by PVA DOI Creative Commons

Zhengfeng He,

Zhuofan Wu,

Wen‐Jun Niu

et al.

Frontiers in Materials, Journal Year: 2024, Volume and Issue: 11

Published: Oct. 8, 2024

As demand for sustainable building materials rises, the use of waste rubber in civil engineering is gaining attention. This study proposes a method to modify using polyvinyl alcohol (PVA) enhance its material properties and expand applications. A dataset was created focusing on mechanical strength cementitious incorporating PVA-modified rubber, multiple machine learning methods were used develop regression prediction models, particularly evaluating support vector (SVR) model. Results show that SVR model outperforms others, achieving mean squared errors 1.21 0.33, absolute 2.06 0.15. Analysis indicates negative correlation between content water-to-cohesive ratio (w/c) with indexes, while positive exists curing age PVA. Notably, significantly affects strength. The notably enhanced by likely due PVA's dispersion bridging effects. presents novel approach sustainably recycle highlighting potential construction materials.

Language: Английский

Development of hybrid gradient boosting models for predicting the compressive strength of high-volume fly ash self-compacting concrete with silica fume DOI
Rakesh Kumar, Shashikant Kumar,

Baboo Rai

et al.

Structures, Journal Year: 2024, Volume and Issue: 66, P. 106850 - 106850

Published: July 8, 2024

Language: Английский

Citations

18

Machine learning approach for predicting the compressive strength of biomedical waste ash in concrete: a sustainability approach DOI Creative Commons
Rakesh Kumar,

Shishir Karthik,

Abhishek Kumar

et al.

Discover Materials, Journal Year: 2025, Volume and Issue: 5(1)

Published: Feb. 21, 2025

Language: Английский

Citations

2

Development of a prediction tool for the compressive strength of ternary blended ultra-high performance concrete using machine learning techniques DOI
Rakesh Kumar,

Shubhum Prakash,

Baboo Rai

et al.

Journal of Structural Integrity and Maintenance, Journal Year: 2024, Volume and Issue: 9(3)

Published: July 2, 2024

Language: Английский

Citations

16

Assessing the seismic sensitivity of bridge structures by developing fragility curves with ANN and LSTM integration DOI

Ashwini Satyanarayana,

V. Babu R. Dushyanth,

Khaja Asim Riyan

et al.

Asian Journal of Civil Engineering, Journal Year: 2024, Volume and Issue: 25(8), P. 5865 - 5888

Published: Aug. 29, 2024

Language: Английский

Citations

9

Comparison of experimental and analytical studies in light gauge steel sections on CFST using SFRC in beams subjected to high temperatures DOI

Christo George,

Rakesh Kumar,

H. K. Ramaraju

et al.

Asian Journal of Civil Engineering, Journal Year: 2024, Volume and Issue: unknown

Published: Nov. 6, 2024

Language: Английский

Citations

9

Experimental Study of Carbonation and Chloride Resistance of Self-Compacting Concretes with a High Content of Fly Ash and Metakaolin, with and Without Hydrated Lime DOI Open Access
Marcos Alyssandro Soares dos Anjos, Aires Camões, Raphaele Malheiro

et al.

Materials, Journal Year: 2025, Volume and Issue: 18(2), P. 422 - 422

Published: Jan. 17, 2025

The durability of reinforced concrete is associated with several factors that can trigger the corrosion reinforcement bars. Among these factors, most significant are chloride-ion attack and carbonation. This study evaluated, through accelerated testing, self-compacting concretes (SCCs) reduced cement content in binary, ternary, quaternary mixtures using high-early-strength Portland cement, fly ash (FA), metakaolin (MK), hydrated lime (HL). These systems proposed to address slow compressive strength gains at 28 days high minimise effects carbonation levels mineral additives. Laboratory tests were conducted measure migration a non-steady-state system, controlled chamber, electrical resistivity, void indices, strength. Based on results obtained, it was found combined use MK, FA, HL effective reducing consumption extreme levels, such as 120 150 kg/m3, while still achieving indices superior those SCCs 500 kg/m3.

Language: Английский

Citations

1

Research on the prediction of mechanical properties of magnesium-silicon-based cement and the mechanism of element interaction based on machine learning DOI
Xiao Luo, Yue Li,

Yunze Liu

et al.

Construction and Building Materials, Journal Year: 2025, Volume and Issue: 463, P. 140062 - 140062

Published: Jan. 24, 2025

Language: Английский

Citations

1

Optimized machine learning models for predicting the tensile strength of high-performance concrete DOI

Divesh Ranjan Kumar,

Pramod Kumar, Pradeep Thangavel

et al.

Journal of Structural Integrity and Maintenance, Journal Year: 2025, Volume and Issue: 10(1)

Published: Jan. 2, 2025

Language: Английский

Citations

1

Machine learning based prediction models for the compressive strength of high-volume fly ash concrete reinforced with silica fume DOI
Anish Kumar, Sujit Sen, Sanjeev Sinha

et al.

Asian Journal of Civil Engineering, Journal Year: 2025, Volume and Issue: unknown

Published: March 14, 2025

Language: Английский

Citations

1

Enhancing urban sustainability: a study on lightweight and pervious concrete incorporating recycled plastic DOI Creative Commons
S. Sathvik,

Pathapati Rohithkumar,

Pshtiwan Shakor

et al.

Discover Sustainability, Journal Year: 2024, Volume and Issue: 5(1)

Published: Nov. 20, 2024

Abstract Increasing of plastic waste threatening ecosystems globally, this experimental work investigates recycled plastics as sustainable aggregate replacements in pervious concrete. Pervious concrete allows water passage but has installation/maintenance difficulty due to high weight. This research addresses the lack eco-friendly lightweight solutions by assessing physical and mechanical performance mixes with 100% traditional percentages. Density reduced 12% using a mix, achieving 1358 kg/m 3 compressive strength 3.92 MPa, adequate for non-structural applications. A 7.8% decrease absorption versus conventional signifies retained porosity permeability despite aggregates. Though early material limitations increase costs over 199.32%, show viability effective, substitutes natural aggregates With further availability affordability improvements, these recyclable can enable significantly greener construction practices. Findings provide key insights on balancing structural requirements, eco-friendliness infiltration capacity plastic-based broader adoption. The examines durability characteristics Light-Weight Concrete (LWPC) composed entirely aggregate. It also economic potential urban cost assessment reveals long-term environmental advantages, even though initial expenses are higher. Additionally, study considers an approach that combines plant growth promote greater sustainability.

Language: Английский

Citations

4