Results 191 to 200 of about 21,203 (255)

Machine learning prediction and explainability analysis of high strength glass powder concrete using SHAP PDP and ICE. [PDF]

Sci Rep
Mahmood MS, Ali T, Inam I, Qureshi MZ, Zaidi SSA, Alqurashi M, Ahmed H, Adnan M, Hotak AH.   +8 more
europepmc   +1 more source

THE EFFECT OF POLYCARBOXYLATE-TYPE SUPERPLASTICIZER CONTROLLED ITS ADSORPTION RATE ONTO THE CEMENT PARTICLES BY CHANGING THE POLYMER STRUCTURE

, 2009
Tsuyoshi Hirata, Toyoharu NAWA
openalex   +2 more sources

Optimizing nanomaterial dosages in concrete for structural applications using experimental design techniques. [PDF]

Sci Rep
Dhairiyasamy R, Gabiriel D, Varshney D, Singh S.   +3 more
europepmc   +1 more source

Suppression Mechanism of Early-Age Autogenous Shrinkage Cracking in Low Water-to-Binder Ratio Cement-Based Materials Incorporating Ground Granulated Blast-Furnace Slag and Silica Fume. [PDF]

Materials (Basel)
Li S, You G, Yu G, Jiang C, Xia X, Yu D.
europepmc   +1 more source

A digital twin approach for sustainable construction: predictive optimization of concrete strength using industry 4.0 principles. [PDF]

Sci Rep
Xin P, Isleem HF, Khishe M.
europepmc   +1 more source

Mechanical performance of sustainable concrete containing industrial waste admixtures of SF, FA, CCI, and crushed quartz at different water-binder ratios. [PDF]

Sci Rep
Ahmad SSE, Graf AAA, Bneni MK.
europepmc   +1 more source

Synthesis and Performance of Polycarboxylate Superplasticizer Based on a Novel Redox System of Manganese Dioxide/Acid

Shaoan Cheng, Xinghui Wang, Si Wu, Luyan Wang   +3 more
openalex   +2 more sources

Machine Learning-Assisted Development of Injectable, Mechanically Robust, and Energy Metabolism-Modulating Brushite Cements. [PDF]

Research (Wash D C)
Liu D, Shi J, Ni Y, Dong L, Cui C, Wang L, Zhang Y, Xu J, Chen W, Lu K, Lukic MJ, Xia W, Chen S, Li B.   +13 more
europepmc   +1 more source

Predicting the compressive strength of concrete incorporating waste powders exposed to elevated temperatures utilizing machine learning. [PDF]

Sci Rep
Fathy IN, Dahish HA, Alkharisi MK, Mahmoud AA, Fouad HEE.   +4 more
europepmc   +1 more source