Development of flexible grouting material for cement-stabilized macadam base using response surface and genetic algorithm optimization methodologies

Lu, Haonan; Dong, Qiao; Yan, Shiao; Chen, Xueqin; Wang, Xiang

doi:10.1016/j.conbuildmat.2023.133823

Cited by 9 publications

(2 citation statements)

References 30 publications

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“…Response surface methodology is a collection of statistical and mathematical techniques, which achieves its goal by improving the settings of the factors, bringing the response closer and closer to the predetermined maximum or minimum value 36 – 38 . Response surface methodology can be used in the process of designing, developing, and building new products, as well as in improving existing products designs 39 – 43 . Meanwhile, the number of trials can be minimized by response surface methodology and identify the interactions between factors at-a-time 44 .…”

Section: Introductionmentioning

confidence: 99%

Research on mix design and mechanical performances of MK-GGBFS based geopolymer pastes using central composite design method

Yao,

Luo,

Qin

et al. 2024

Sci Rep

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In order to alleviate environmental problems and reduce CO2 emissions, geopolymers had drew attention as a kind of alkali-activated materials. Geopolymers are easier access to raw materials, green and environment friendly than traditional cement industry. Its special reaction mechanism and gel structure show excellent characteristics such as quick hardening, high strength, acid and alkali resistance. In this paper, geopolymer pastes were made with metakaolin (MK) and ground granulated blast furnace slag (GGBFS) as precursors. The effects of liquid–solid ratio (L/S) and modulus of sodium silicate (Ms) on the performances of MK-GGBFS based geopolymer paste (MSGP) were characterized by workability, strength and microstructural tests. The regression equations were obtained by central composite design method to optimize the mix design of MSGP. The goodness of fit of all the equations were more than 98%. Based on the results of experiments, the optimum mix design was found to have L/S of 0.75 and Ms of 1.55. The workability of MSGP was significantly improved while maintaining the strength under the optimum mix design. The initial setting time of MSGP decreased by 71.8%, while both of the fluidity and 28-d compressive strength increased by 15.3%, compared with ordinary Portland cement pastes. Therefore, geopolymers are promising alternative cementitious material, which can consume a large amount of MK and GGBFS and promote green and clean production.

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Section: Introductionmentioning

confidence: 99%

Research on mix design and mechanical performances of MK-GGBFS based geopolymer pastes using central composite design method

Yao,

Luo,

Qin

et al. 2024

Sci Rep

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“…At the same time, genetic algorithms are also popular in agriculture [32][33][34]. Researchers have also used genetic algorithms in materials science [35,36]. Genetic algorithms can also be used to solve sustainability issues and environmental engineering issues [37][38][39].…”

Section: Introductionmentioning

confidence: 99%

A Bibliometric Analysis of a Genetic Algorithm for Supply Chain Agility

Lam,

Lee

2024

Mathematics

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As a famous population-based metaheuristic algorithm, a genetic algorithm can be used to overcome optimization complexities. A genetic algorithm adopts probabilistic transition rules and is suitable for parallelism, which makes this algorithm attractive in many areas, including the logistics and supply chain sector. To obtain a comprehensive understanding of the development in this area, this paper presents a bibliometric analysis on the application of a genetic algorithm in logistics and supply chains using data from 1991 to 2024 from the Web of Science database. The authors found a growing trend in the number of publications and citations over the years. This paper serves as an important reference to researchers by highlighting important research areas, such as multi-objective optimization, metaheuristics, sustainability issues in logistics, and machine learning integration. This bibliometric analysis also underlines the importance of Non-Dominated Sorting Genetic Algorithm II (NSGA-II), sustainability, machine learning, and variable neighborhood search in the application of a genetic algorithm in logistics and supply chains in the near future. The integration of a genetic algorithm with machine learning is also a potential research gap to be filled to overcome the limitations of genetic algorithms, such as the long computational time, difficulties in obtaining optimal solutions, and convergence issues for application in logistics and supply chains.

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Performance and mechanism of dual-network cementitious material formed by acrylamide monomer in-situ polymerization and ultra-fine portland cement

Yan,

Shao,

Shu

et al. 2024

J Mater Sci

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Development of flexible grouting material for cement-stabilized macadam base using response surface and genetic algorithm optimization methodologies

Cited by 9 publications

References 30 publications

Research on mix design and mechanical performances of MK-GGBFS based geopolymer pastes using central composite design method

Research on mix design and mechanical performances of MK-GGBFS based geopolymer pastes using central composite design method

A Bibliometric Analysis of a Genetic Algorithm for Supply Chain Agility

Performance and mechanism of dual-network cementitious material formed by acrylamide monomer in-situ polymerization and ultra-fine portland cement

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