Efficient recovery of iron and alumina from red mud by alkali-enhanced magnetization reduction DOI

Yafei Qi,

Xiaolin Pan, Honghe Zheng

и другие.

Separation and Purification Technology, Год журнала: 2025, Номер unknown, С. 133146 - 133146

Опубликована: Апрель 1, 2025

Язык: Английский

Study on Purification of SiO2 by S-HGMS Coupling Technology with Fluorine-Free from Iron Ore Tailings and Mechanism DOI

Xuebao Tang,

Suqin Li, Cong Li

и другие.

JOM, Год журнала: 2025, Номер unknown

Опубликована: Фев. 10, 2025

Язык: Английский

Процитировано

0

Study on the forming method and subgrade performance of construction waste recycled material specimen DOI

Xiao Qian-hui,

Kaixuan Lv,

Shulin Liu

и другие.

Journal of Building Engineering, Год журнала: 2025, Номер unknown, С. 112114 - 112114

Опубликована: Фев. 1, 2025

Язык: Английский

Процитировано

0

Novel approaches in prediction of tensile strain capacity of engineered cementitious composites using interpretable approaches DOI Creative Commons
Turki S. Alahmari, Furqan Farooq

REVIEWS ON ADVANCED MATERIALS SCIENCE, Год журнала: 2025, Номер 64(1)

Опубликована: Янв. 1, 2025

Abstract The performance and durability of conventional concrete (CC) are significantly influenced by its weak tensile strength strain capacity (TSC). Thus, the intrusion fibers in cementitious matrix forms ductile engineered composites (ECCs) that can cater to this area CC. Moreover, ECCs have become a reasonable substitute for brittle plain due their increased flexibility, ductility, greater TSC. prediction ECC is crucial without need laborious experimental procedures. achieve this, machine learning approaches (MLAs), namely light gradient boosting (LGB) approach, extreme (XGB) artificial neural network (ANN), k -nearest neighbor (KNN), were developed. data gathered from literature comprise input parameters which fiber content, length, cement, diameter, water-to-binder ratio, fly ash (FA), age, sand, superplasticizer, TSC as output utilized. assessment models gauged with coefficient determination ( R 2 ), statistical measures, uncertainty analysis. In addition, an analysis feature importance carried out further refinement model. result demonstrates ANN XGB perform well train test sets > 0.96. Statistical measures show all give fewer errors higher , depict robust performance. Validation via K -fold confirms showing correlation determination. reveals FA major contribution ECC. graphical user interface also developed help users/researchers will facilitate them estimate practical applications.

Язык: Английский

Процитировано

0

Synergistic recycling of ground granulated blast furnace slag-red mud-phosphogypsum for developing low-carbon composite cementitious material: Performance characterization and process optimization DOI

Chuanbo Sun,

Xin Chen,

Longzhao Lu

и другие.

Construction and Building Materials, Год журнала: 2025, Номер 473, С. 141025 - 141025

Опубликована: Март 29, 2025

Язык: Английский

Процитировано

0

Efficient recovery of iron and alumina from red mud by alkali-enhanced magnetization reduction DOI

Yafei Qi,

Xiaolin Pan, Honghe Zheng

и другие.

Separation and Purification Technology, Год журнала: 2025, Номер unknown, С. 133146 - 133146

Опубликована: Апрель 1, 2025

Язык: Английский

Процитировано

0