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 …

Modeling strength characteristics of basalt fiber reinforced concrete using multiple explainable machine learning with a graphical user interface

W Kulasooriya, RSS Ranasinghe, US Perera… - Scientific Reports, 2023 - nature.com
This study investigated the importance of applying explainable artificial intelligence (XAI) on
different machine learning (ML) models developed to predict the strength characteristics of …

Map** 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 …

Improving the experience of machine learning in compressive strength prediction of industrial concrete considering mixing proportions, engineered ratios and …

MZ Akber - Construction and Building Materials, 2024 - Elsevier
In previous literature on predicting compressive strength (CS) using machine learning (ML),
the focus has primarily been on algorithm-specific improvements, with less emphasis on …

Compressive strength prediction of high-strength oil palm shell lightweight aggregate concrete using machine learning methods

S Ghanbari, AA Shahmansouri… - … Science and Pollution …, 2023 - Springer
Promoting the use of agricultural wastes/byproducts in concrete production can significantly
reduce environmental effects and contribute to sustainable development. Several …

[HTML][HTML] Prediction of pull-out behavior of timber glued-in glass fiber reinforced polymer and steel rods under various environmental conditions based on ANN and …

MM Taleshi, N Tajik, A Mahmoudian… - Case Studies in …, 2024 - Elsevier
This study employs soft computing techniques, including artificial neural network (ANN)
models and gene expression programming (GEP), to enhance the prediction of ultimate load …

Machine learning models for estimating the compressive strength of rubberized concrete subjected to elevated temperature: Optimization and hyper-tuning

TS Alahmari, I Ullah, F Farooq - Sustainable Chemistry and Pharmacy, 2024 - Elsevier
The incorporation of rubber fibers (RFs) brings about significant divergence in the
characteristics of rubberized concrete when contrasted with traditional varieties. Thus …

An evolutionary neuro-fuzzy-based approach to estimate the compressive strength of eco-friendly concrete containing recycled construction wastes

A Ashrafian, NS Hamzehkolaei, NKA Dwijendra… - Buildings, 2022 - mdpi.com
There has been a significant increase in construction and demolition (C&D) waste due to the
growth of cities and the need for new construction, raising concerns about the impact on the …

Gradient boosting hybridized with exponential natural evolution strategies for estimating the strength of geopolymer self-compacting concrete

SA Basilio, L Goliatt - Knowledge …, 2022 - … journals.publicknowledgeproject.org
The current global demand to minimize carbon dioxide (CO2 $) emissions from Portland
cement manufacturing processes has led to the use of environmentally friendly additives in …

[HTML][HTML] Compressive strength prediction models for concrete containing nano materials and exposed to elevated temperatures

HA Dahish, AD Almutairi - Results in Engineering, 2025 - Elsevier
The addition of nanomaterials to concrete is widely employed in modern construction to
improve its durability and mechanical properties. In the present study, two machine learning …