Photocatalytic performance and its internal relationship with hydration and carbonation of photocatalytic concrete: A review

H Fei, J Wu, J Zhang, T Zhao, W Guo, X Wang… - Journal of Building …, 2024 - Elsevier
Photocatalytic concrete technology has attracted much attention in the field of sustainable
construction and infrastructure by photocatalytic decomposition of harmful air and water …

On the use of machine learning and data-transformation methods to predict hydration kinetics and strength of alkali-activated mine tailings-based binders

S Surehali, T Han, J Huang, A Kumar… - Construction and Building …, 2024 - Elsevier
The escalating production of mine tailings (MT), a byproduct of the mining industry,
constitutes significant environmental and health hazards, thereby requiring a cost-effective …

Understanding and predicting micro-characteristics of ultra-high performance concrete (UHPC) with green porous lightweight aggregates: Insights from machine …

L Zhang, W Xu, D Fan, E Dong, K Liu, L Xu… - Construction and Building …, 2024 - Elsevier
Ultra-high performance concrete (UHPC) is an advanced material in construction. Porous
lightweight aggregates (PLWA) could reduce the self-shrinkage risk of UHPC by maintaining …

Optimization of mix proportion and strength prediction of magnesium phosphate cement-based composites based on machine learning

J Zhang, T Li, Y Yao, X Hu, Y Zuo, H Du… - Construction and Building …, 2024 - Elsevier
In order to optimize the mix ratio design of magnesium phosphate cementitious composites
(MPCC) to obtain excellent workability and strength, this study investigated the effects of …

Modeling hydration kinetics of sustainable cementitious binders using an advanced nucleation and growth approach

T Han, J Huang, G Sant, N Neithalath, A Goel… - … and Building Materials, 2023 - Elsevier
Supplementary cementitious materials (SCMs) are utilized to partially substitute Portland
cement (PC) in binders, reducing carbon-footprint and maintaining excellent performance …

Microstructure-informed deep learning model for accurate prediction of multiple concrete properties

Y Li, Y Ma, KH Tan, H Qian, T Liu - Journal of Building Engineering, 2024 - Elsevier
Predicting multiple properties of concrete using empirical models has become increasingly
challenging due to the complexity of modern concrete formulations and the nonlinear …

Development of chemistry-informed interpretable model for predicting compressive strength of recycled aggregate concrete containing supplementary cementitious …

Y Gao, Z Li, Y Li, Z Zhu, J Zhu - Journal of Cleaner Production, 2023 - Elsevier
Accurate prediction of compressive strength of recycled aggregate concrete (RAC) has great
value for promoting the sustainable development of concrete field. The study aims to …

Evolution of the microporous structure in cement hydration: A deep learning-based image translation method

X Yao, H Fang, M Du, H Feng, K Zhai, J Lin… - Journal of Building …, 2024 - Elsevier
Investigating the evolution of the microporous structure is essential for gaining insights into
the hydration process of the cementitious materials. However, conventional methods for …

Designing low-carbon fly ash based geopolymer with red mud and blast furnace slag wastes: Performance, microstructure and mechanism

Z Li, J Zhang, Z Lei, M Gao, J Sun, L Tong… - Journal of …, 2024 - Elsevier
In order to tackle the environmental problems induced by Portland cement production and
industrial solid wastes landfilling, this study aims to develop novel ternary cementless fly ash …

[HTML][HTML] Prediction of time-dependent concrete mechanical properties based on advanced deep learning models considering complex variables

Y Jiang, J Zhang, W Zuo, G Xu, C Yuan, L Wang… - Case Studies in …, 2024 - Elsevier
Evaluating the mechanical properties such as compressive strength, tensile strength, and
modulus of elasticity (MOE) of concrete is crucial for the design, construction, and quality …