Assessment of mechanical properties with machine learning modeling and durability, and microstructural characteristics of a biochar-cement mortar composite

MHR Sobuz, MH Khan, MKI Kabbo… - … and Building Materials, 2024‏ - Elsevier
Rising CO 2 emissions have become one of the biggest environmental challenges in recent
years. Due to the rising carbon footprint of the building industry, CO 2 emission regulation …

Modelling the mechanical properties of concrete produced with polycarbonate waste ash by machine learning

S Sathvik, R Kumar, N Ulloa, P Shakor, MS Ujwal… - Scientific Reports, 2024‏ - nature.com
India's cement industry is the second largest in the world, generating 6.9% of the global
cement output. Polycarbonate waste ash is a major problem in India and around the globe …

Soft computing techniques for predicting the properties of raw rice husk concrete bricks using regression-based machine learning approaches

N Ganasen, L Krishnaraj, KC Onyelowe… - Scientific Reports, 2023‏ - nature.com
In this study, the replacement of raw rice husk, fly ash, and hydrated lime for fine aggregate
and cement was evaluated in making raw rice husk-concrete brick. This study optimizes …

[HTML][HTML] Nonlinear finite element and machine learning modeling of tubed reinforced concrete columns under eccentric axial compression loading

HF Isleem, NDKR Chukka, A Bahrami, R Kumar… - Alexandria Engineering …, 2024‏ - Elsevier
There is still insufficient data on the behavior of tubed-reinforced concrete columns (TRCCs)
under the eccentric compression. Thus, this research work comprehensively examines the …

Assessment of short and long-term pozzolanic activity of natural pozzolans using machine learning approaches

J Khatti, BY Polat - Structures, 2024‏ - Elsevier
This investigation introduces the optimal performance models for predicting the compressive
strength (CS) and pozzolanic activity index (PAI) by comparing the machine learning …

Optimization and prediction of paver block properties with ceramic waste as fine aggregate using response surface methodology

GU Kiran, D Roy, GU Alaneme - Scientific Reports, 2024‏ - nature.com
The ceramic industry produces a significant volume of ceramic waste (CW), representing
around 20–30% of its the entire output. The waste mostly comes from challenges noticed in …

Prediction of steel plate-based damper for improving the behavior of concentrically braced frames based on RSM and ML approaches for sustainable structures

KC Onyelowe, JL Yaulema Castañeda, AFH Adam… - Scientific Reports, 2024‏ - nature.com
The stiffness (K) and slenderness factor (λ) of a steel plate-based damper has been studied
on the basis of elastic-inelastic-plastic buckling (EIP) modes and flexural/shear/flexural …

Effect of rice husk ash silicon nitride on mechanical, wear, thermal conductivity, and flammability behavior of aluminized glass-kenaf fiber-reinforced polyester …

NR Prakash, C Gnanavel - Biomass Conversion and Biorefinery, 2024‏ - Springer
The main goal of this present research was to find out how combining hybridized fiber
(aluminized glass and kenaf fiber) and biomass-derived bioceramic silicon nitride (Si3N4) …

Machine learning optimization of bio-sandcrete brick modelling using response surface methodology

N Ganasen, L Krishnaraj, KC Onyelowe… - Scientific Reports, 2024‏ - nature.com
In this study, raw grinded groundnut shell (RGGNS) was used as a fine aggregate in the
brick industry to reuse agricultural waste in building materials. In this study, an experimental …

Predicting an energy use intensity and cost of residential energy-efficient buildings using various parameters: ANN analysis

M Jayakeerti, G Nakkeeran, MD Aravindh… - Asian Journal of Civil …, 2023‏ - Springer
During their operational phase, the buildings consume significant amounts of energy. It is
one of the most significant sources of carbon emissions throughout their service life, which …