Multi-Objective Optimization Design of Hybrid Fiber-Reinforced ECC Based on Box–Behnken and NSGA-II

To enhance the effectiveness and precision of design and to produce more low-carbon and high-performance Engineered Cementitious Composites (ECCs), novel hybrid fiber-reinforced high-ductility cementitious composites developed by incorporating a combination of ultra-high-molecular-weight polyethylene fibers (UHMWPE) and basalt fibers (BFs) into the cementitious matrix. Building upon the Box-Behnken design model from Response Surface Methodology (RSM), this study investigates the effects of different water-to-binder ratios and fiber contents on the mechanical properties of hybrid fiber-reinforced ECC. Analysis of variance (ANOVA) was used to validate the regression models. Furthermore, multi-objective optimization of the ECC mix proportion was achieved by employing the NSGA-II algorithm in conjunction with the TOPSIS comprehensive evaluation method. The results indicate that UHMWPE and BFs exhibited a significant positive hybrid effect. The order of factor significance was as follows: The content of ultra-high-molecular-weight polyethylene is greater than that of basalt fiber, and the content of basalt fiber is greater than that of the water-binder ratio. The results of variance analysis show that the regression model has high fitting accuracy. Furthermore, the algorithmic optimization yielded an optimal mix proportion: a water-to-binder ratio of 0.21, UHMWPE fiber content of 1.51%, and BF content of 0.85%. This study provides a valuable reference for the multi-objective optimization design of ECC mix proportions targeting diverse strength and toughness requirements.

Authors

Institutions

Publication Details

Journal
Materials
Published
2025-10-27
DOI
https://doi.org/10.3390/ma18214914
Primary Topic
Innovative concrete reinforcement materials
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Multi-Objective Optimization Design of Hybrid Fiber-Reinforced ECC Based on Box–Behnken and NSGA-II

Jinggan Shao, Xiao Wang, H. F. Chen, Fei Yang et al.
Materials
Innovative concrete reinforcement materials
article

Multi-Objective Optimization Design of Hybrid Fiber-Reinforced ECC Based on Box–Behnken and NSGA-II

Jinggan Shao, Xiao Wang, H. F. Chen, Fei Yang, Sen Zheng, Hongyang Jing
article en

Abstract

To enhance the effectiveness and precision of design and to produce more low-carbon and high-performance Engineered Cementitious Composites (ECCs), novel hybrid fiber-reinforced high-ductility cementitious composites developed by incorporating a combination of ultra-high-molecular-weight polyethylene fibers (UHMWPE) and basalt fibers (BFs) into the cementitious matrix. Building upon the Box-Behnken design model from Response Surface Methodology (RSM), this study investigates the effects of different water-to-binder ratios and fiber contents on the mechanical properties of hybrid fiber-reinforced ECC. Analysis of variance (ANOVA) was used to validate the regression models. Furthermore, multi-objective optimization of the ECC mix proportion was achieved by employing the NSGA-II algorithm in conjunction with the TOPSIS comprehensive evaluation method. The results indicate that UHMWPE and BFs exhibited a significant positive hybrid effect. The order of factor significance was as follows: The content of ultra-high-molecular-weight polyethylene is greater than that of basalt fiber, and the content of basalt fiber is greater than that of the water-binder ratio. The results of variance analysis show that the regression model has high fitting accuracy. Furthermore, the algorithmic optimization yielded an optimal mix proportion: a water-to-binder ratio of 0.21, UHMWPE fiber content of 1.51%, and BF content of 0.85%. This study provides a valuable reference for the multi-objective optimization design of ECC mix proportions targeting diverse strength and toughness requirements.

MaterialsVol. 18(21)
Zhongyuan University of Technology (CN), North China University of Water Resources and Electric Power (CN), Henan Energy & Chemical Industry Group (China) (CN)
Openalex Percentile: Top 67%
Innovative concrete reinforcement materials
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.