Computational design and manufacturing of sustainable materials through first-principles and materiomics

SC Shen, E Khare, NA Lee, MK Saad… - Chemical …, 2023 - ACS Publications
Engineered materials are ubiquitous throughout society and are critical to the development
of modern technology, yet many current material systems are inexorably tied to widespread …

A systematic review of machine learning techniques and applications in soil improvement using green materials

AH Saad, H Nahazanan, B Yusuf, SF Toha, A Alnuaim… - Sustainability, 2023 - mdpi.com
According to an extensive evaluation of published studies, there is a shortage of research on
systematic literature reviews related to machine learning prediction techniques and …

[HTML][HTML] Data-driven multicollinearity-aware multi-objective optimisation of green concrete mixes

EA Shamsabadi, M Salehpour, P Zandifaez… - Journal of Cleaner …, 2023 - Elsevier
A multicollinearity-aware multi-objective optimisation (MA-MOO) framework was developed
to minimise the main environmental issues and the cost of production of green concrete …

Mapping the strength of agro-ecological lightweight concrete containing oil palm by-product using artificial intelligence techniques

A Ashrafian, E Panahi, S Salehi, M Karoglou… - Structures, 2023 - Elsevier
The critical challenge for the cement production industry is the high emission of greenhouse
gases. For the sustainability in a cycling economy context civil and environmental engineers …

Predicting carbonation depth of concrete using a hybrid ensemble model

Z Huo, L Wang, Y Huang - Journal of Building Engineering, 2023 - Elsevier
This study aims to develop a robust and accurate machine learning-based model to improve
the prediction accuracy of carbonation depth in complex concrete structures. Two hybrid …

Machine learning approach for predicting concrete compressive, splitting tensile, and flexural strength with waste foundry sand

V Mehta - Journal of Building Engineering, 2023 - Elsevier
The scarcity of landfilling and the growing expense of disposal, recycling, and reusing
industrial byproducts have become attractive alternatives to removal. There are several sorts …

Forensic-based investigation-optimized extreme gradient boosting system for predicting compressive strength of ready-mixed concrete

JS Chou, LY Chen, CY Liu - Journal of Computational Design …, 2023 - academic.oup.com
Regulations mandate testing concrete's compressive strength after the concrete has cured
for 28 days. In the ideal situation, cured strength equals the target strength. Advanced …

Artificial Intelligence in the Construction Industry: A Systematic Review of the Entire Construction Value Chain Lifecycle

CN Egwim, H Alaka, E Demir, H Balogun, R Olu-Ajayi… - Energies, 2023 - mdpi.com
In recent years, there has been a surge in the global digitization of corporate processes and
concepts such as digital technology development which is growing at such a quick pace that …

Application of predictive analytics in built environment research: A comprehensive bibliometric study to explore knowledge domains and future research agenda

A Halder, S Batra - Archives of Computational Methods in Engineering, 2023 - Springer
The built environment (BE) sector has seen a significant digital transformation in the past few
decades. While predictive analytics (PA) plays a critical role in such a transition. Applications …

Artificial intelligence for the prediction of the physical and mechanical properties of a compressed earth reinforced by fibers

B Houcine, R Mohamed, K Samir… - The Journal of …, 2023 - beta.periodicos.ufv.br
The use of natural fibers as a reinforcing product in the production of compressed earth
blocks can be considered as an effective means for the environment and savings. This study …