Recycling aerated concrete waste as aggregate to produce eco‐friendly foamed mortar (EFM)

Structural Concrete, Год журнала: 2025, Номер unknown

Опубликована: Янв. 7, 2025

Abstract Non‐structural components are difficult to recycle into fresh concrete due their high porosity, water absorption, and low strength. This study uses aerated waste (ACW) as a case investigate the effect of recycled aggregate on performance eco‐friendly foamed mortar (EFM). The results show that while incorporating ACW reduces fluidity mechanical properties its porous structure, it enhances lightweight thermal insulation capabilities EFM, making suitable for non‐structural applications. When 25% is applied, 28‐day compressive strength (CS) plain EFM decreases by 64.82%, hardened unit weight conductivity decrease 17.49% 30.85%, respectively. addition PPF compensates loss from ACW, with bridging inhibiting crack formation interlocking aggregates cement paste, though further fluidity. 0.5% 7‐ flexural increased 77.35% 30.54%, but this resulted in 22.22% reduction presents feasible approach recycling low‐grade construction production, contributing development sustainable materials.

Язык: Английский

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Enhancing bending performance of cemented lithium feldspar tailings backfill with 3D printing polymer lattices: effects of unit shapes and materials

Case Studies in Construction Materials, Год журнала: 2025, Номер unknown, С. e04463 - e04463

Опубликована: Март 1, 2025

Язык: Английский

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Study on the mechanics performance and deformation characteristics of polypropylene fiber-reinforced solid waste-based fill material

Journal of Materials Science, Год журнала: 2025, Номер 60(6), С. 3178 - 3199

Опубликована: Янв. 23, 2025

Язык: Английский

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Exploration of silica fume effect on solid waste based backfilling material: mechanical properties, hydration mechanism and economic benefits

Process Safety and Environmental Protection, Год журнала: 2025, Номер unknown, С. 107042 - 107042

Опубликована: Март 1, 2025

Язык: Английский

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Machine Learning Algorithm-Based Prediction Model and Software Implementation for Strength Efficiency of Cemented Tailings Fills

Minerals, Год журнала: 2025, Номер 15(4), С. 405 - 405

Опубликована: Апрель 11, 2025

A novel artificial intelligence (AI) application was proposed in the current study to predict CTF’s compressive strength (CS). The database contained six input parameters: age of curing for specimens (AS), cement–sand ratio (C/S), maintenance temperature (T), additives (EA), additive type (AT), concentration (AC), and one output parameter: CS. Then, adaptive boosting (AdaBoost) applied existing AI soft computing techniques, using AdaBoost, random forest (RF), SVM, ANN. Data were arbitrarily separated into training (70%) test (30%) sets. Results confirm that AdaBoost RF have best prediction accuracy, with a correlation coefficient (R2) 0.957 between these sets AdaBoost. Using Python 3.9 (64-bit), IDLE (Python 64-bit), PyQt5 achieve machine learning model computation software function interface development, this can quickly property CTF specimens, which saves time costs efficiently backfill researchers developing new eco-efficient components.

Язык: Английский

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Study on mechanical properties and toughness characteristics of fiber reinforced storage backfill after carbonation curing

Structures, Год журнала: 2025, Номер 77, С. 108996 - 108996

Опубликована: Май 2, 2025

Язык: Английский

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Mechanical characteristics and constitutive model of cemented tailings backfill under temperature-time effects

Journal of Building Engineering, Год журнала: 2024, Номер 96, С. 110630 - 110630

Опубликована: Сен. 1, 2024

Язык: Английский

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Experimental Investigation on the Mechanical and Microstructural Properties of Cemented Coal Ash Based Paste Backfill Reinforced with Polypropylene Fibre

Indian geotechnical journal, Год журнала: 2024, Номер unknown

Опубликована: Окт. 5, 2024

Язык: Английский

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Dynamic constitutive modeling and numerical validation of composite toughened oil well cement for well cementing applications

Construction and Building Materials, Год журнала: 2024, Номер 456, С. 139193 - 139193

Опубликована: Ноя. 20, 2024

Язык: Английский

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