Accurate prediction of the compression deformation coefficient of loess fillers is key for stability assessment of loess subgrade engineering. In this study, the effects of key influencing factors such as compaction, water content, vertical pressure ...
This research investigates the self-healing potential of Bacillus subtilis in concrete due to its high capacity for calcium carbonate precipitation. Mathematical modelling and machine learning methods, i.e., Random Forest Method (RFM) and Kuhn-Tucker...
Accurate analysis and prediction of axial compression are important for ensuring the construction quality and safety of desert sand recycled aggregate concrete confined by steel tubes. In this study, the axial compressive strength and elastic modulus...
3D printing has brought significant changes to manufacturing sectors, making it possible to produce intricate, multi-layered designs with greater ease. This study focuses on optimizing the compressive strength (CS) of functionally graded multi-materi...
International journal of biological macromolecules
Jul 29, 2025
The integration of sustainable biopolymers into concrete has emerged as a promising approach to enhance mechanical properties, environmental performance, and long-term structural reliability. Conventional concrete, while globally prevalent, faces sig...
High strength and lightweight are key trends in concrete development. Achieving a balance between these properties to produce high structural efficiency (strength-to-weight ratio) concrete is challenging due to the complex relationship between compre...
The occurrence of rockburst is closely related to the strength and stress conditions of rock mass. The Lalin Railway tunnel in China was taken as an example, the strength and stress parameters of rock mass at 22 rockburst locations were obtained by u...
Deep learning has significantly advanced in predicting stress-strain curves. However, due to the complex mechanical properties of rock materials, existing deep learning methods have the problem of insufficient accuracy in predicting the stress-strain...
Environmental science and pollution research international
Mar 8, 2025
This research investigates the application of machine learning techniques for predicting unconfined compressive strength (UCS) and contaminant leachability in dredged contaminated sediments (DCS) with implications for land reclamation projects. Tradi...
Environmental science and pollution research international
Mar 1, 2025
Investigations on the potential use of sustainable sugarcane bagasse ash (SCBA) as a supplementary cementitious material (SCM) in concrete production have been carried out. The paper employs model agnostic eXplainable Artificial Intelligence (XAI) to...
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