Scholarlink

<p>OPC production emits ~ 0.8–1.0 t of CO<sub>2</sub> per tonne, making concrete a major contributor to greenhouse gas emissions. Alkali-activated concrete (AAC) offers a low-carbon alternative via by-product valorisation, but lacks standardised multi-objective design protocols. This study presents an integrated framework using Taguchi L16 design, regression modelling, and desirability function analysis (DFA) to optimise six AAC performance responses simultaneously. Three variables: glass waste powder (GWP: 5, 10, 15, 20%), recycled coarse aggregate (RCA: 25, 50, 75, 100%), and NaOH concentration (8, 10, 12, 14&#xa0;M), were evaluated within a GGBS-GWP hybrid binder matrix across compressive strength (CS), split tensile strength (STS), flexural strength (FS), ultrasonic pulse velocity (UPV), electrical resistivity (ER), and water absorption (WA). Regression models achieved high predictive reliability (R<sup>2</sup> ≥ 0.95), as confirmed by validation tests. ANOVA identified GWP as the dominant factor, contributing 50–81% of total response variance, underscoring its importance in polymerisation kinetics and matrix densification. The DFA optimised mix (M17: GWP 20%, RCA 75%, NaOH 12&#xa0;M) attained a composite desirability index of 0.9918, surpassing the mix M15 (CD = 0.9816) by 1.04% achieving CS = 47.05&#xa0;MPa, STS = 4.25&#xa0;MPa, FS = 12.17&#xa0;MPa, UPV = 4.751&#xa0;km/s, ER = 32.7 kΩ·cm, and WA = 1.50%. SEM-EDS confirmed a dense matrix with C(N)-A-S-H gel; XRD validated a predominantly amorphous aluminosilicate network interspersed with quartz and calcite. These findings establish the DFA-regression framework as a robust, resource-efficient method for performance-based AAC mix design aligned with circular construction principles. Future work should integrate long-term durability indicators and entropy or AHP-based response weighting strategies.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Multi-objective optimisation of sustainable alkali-activated concrete with industrial byproducts and recycled aggregates

  • 期刊论文

  • 发表日期：

    2026年5月26日

查看全文
  • Sajan Sharma,
  • Shailja Bawa,
  • Hariom Singare,
  • Sidarth Bhatt

摘要

OPC production emits ~ 0.8–1.0 t of CO2 per tonne, making concrete a major contributor to greenhouse gas emissions. Alkali-activated concrete (AAC) offers a low-carbon alternative via by-product valorisation, but lacks standardised multi-objective design protocols. This study presents an integrated framework using Taguchi L16 design, regression modelling, and desirability function analysis (DFA) to optimise six AAC performance responses simultaneously. Three variables: glass waste powder (GWP: 5, 10, 15, 20%), recycled coarse aggregate (RCA: 25, 50, 75, 100%), and NaOH concentration (8, 10, 12, 14 M), were evaluated within a GGBS-GWP hybrid binder matrix across compressive strength (CS), split tensile strength (STS), flexural strength (FS), ultrasonic pulse velocity (UPV), electrical resistivity (ER), and water absorption (WA). Regression models achieved high predictive reliability (R2 ≥ 0.95), as confirmed by validation tests. ANOVA identified GWP as the dominant factor, contributing 50–81% of total response variance, underscoring its importance in polymerisation kinetics and matrix densification. The DFA optimised mix (M17: GWP 20%, RCA 75%, NaOH 12 M) attained a composite desirability index of 0.9918, surpassing the mix M15 (CD = 0.9816) by 1.04% achieving CS = 47.05 MPa, STS = 4.25 MPa, FS = 12.17 MPa, UPV = 4.751 km/s, ER = 32.7 kΩ·cm, and WA = 1.50%. SEM-EDS confirmed a dense matrix with C(N)-A-S-H gel; XRD validated a predominantly amorphous aluminosilicate network interspersed with quartz and calcite. These findings establish the DFA-regression framework as a robust, resource-efficient method for performance-based AAC mix design aligned with circular construction principles. Future work should integrate long-term durability indicators and entropy or AHP-based response weighting strategies.