Optimization of Grouting Material Mixture Ratio Based on Multi-Objective Optimization and Multi-Attribute Decision-Making

被引:4
|
作者
Xiong, Luchang [1 ,2 ]
Zhang, Zhaoyang [1 ,2 ]
Wan, Zhijun [1 ,2 ]
Zhang, Yuan [1 ,2 ]
Wang, Ziqi [1 ,2 ]
Lv, Jiakun [1 ,2 ]
机构
[1] China Univ Min & Technol, Sch Mines, Xuzhou 221116, Jiangsu, Peoples R China
[2] China Univ Min & Technol, Key Lab Deep Coal Resource Min, Minist Educ China, Xuzhou 221116, Jiangsu, Peoples R China
基金
中国国家自然科学基金;
关键词
grouting materials; ratio design; multi-objective optimization; multi-objective decision-making; DEEP; CONCRETE;
D O I
10.3390/su14010399
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
As a solid waste produced by coal combustion, fly ash will cause serious environmental pollution. However, it can be considered as a sustainable and renewable resource to replace partial cement in grouting materials. Fly ash grouting materials re-cement the broken rock mass and improve the mechanical properties of the original structure. It can reinforce the broken surrounding rock of mine roadway. The utilization of fly ash also reduces environmental pollution. Therefore, this paper establishes a new material mixture ratio optimization model to meet the requirement of material property through combining the methods of experimental design and numerical analysis. Based on the Box-Behnken design with 3 factors and 3 levels, a mathematical model is constructed to fit the nonlinear multiple regression functions between material properties and raw materials ratios. The influence of raw materials is analyzed on material properties (the material's 7-day uniaxial compressive strength, initial setting time, and slurry viscosity). Then, 80 Pareto solutions are obtained through NASG-II algorithm which takes the regression functions as the objective functions for multi-objective optimization of the grouting material ratio. Finally, the best ratio solution of water-cement ratio-0.71, silica fume content-1.73%, and sodium silicate content-2.61% is obtained through the NNRP-TOPSIS method.
引用
收藏
页数:14
相关论文
共 50 条
  • [31] Multi-Objective Parameter Calibration and Multi-Attribute Decision-Making: An Application to Conceptual Hydrological Model Calibration
    Zhou, Jianzhong
    Ouyang, Shuo
    Wang, Xuemin
    Ye, Lei
    Wang, Hao
    [J]. WATER RESOURCES MANAGEMENT, 2014, 28 (03) : 767 - 783
  • [32] DECISION-MAKING SUPPORT IN HUMAN RESOURCE MANAGEMENT BASED ON MULTI-OBJECTIVE OPTIMIZATION
    Mammadova, M. H.
    Jabrayilova, Z. G.
    [J]. TWMS JOURNAL OF PURE AND APPLIED MATHEMATICS, 2018, 9 (01): : 52 - 72
  • [33] Multi-objective optimization of wire electrical discharge machining process using multi-attribute decision making techniques and regression analysis
    Seidi, Masoud
    Yaghoubi, Saeed
    Rabiei, Farshad
    [J]. SCIENTIFIC REPORTS, 2024, 14 (01):
  • [34] Multi-objective decision-making on emergency material distribution under uncertain demand based on robust optimization
    Long, Hai-Bo
    Yang, Jia-Qi
    Yin, Liang
    Zhao, Xue-Yu
    Xiang, Zi-Quan
    [J]. Jilin Daxue Xuebao (Gongxueban)/Journal of Jilin University (Engineering and Technology Edition), 2023, 53 (04): : 1078 - 1084
  • [35] Multi-Objective Optimization in Multi-Attribute and Multi-Unit Combinatorial Reverse Auctions
    Shil, Shubhashis Kumar
    Sadaoui, Samira
    [J]. INTERNATIONAL JOURNAL ON ARTIFICIAL INTELLIGENCE TOOLS, 2017, 26 (05)
  • [36] Ensemble multi-attribute decision-making for material selection problems
    Sahin, Mehmet
    [J]. SOFT COMPUTING, 2024, 28 (06) : 5437 - 5460
  • [37] Ensemble multi-attribute decision-making for material selection problems
    Mehmet Şahin
    [J]. Soft Computing, 2024, 28 : 5437 - 5460
  • [38] Multi-Objective Optimization Algorithm and Preference Multi-Objective Decision-Making Based on Artificial Intelligence Biological Immune System
    Bao, Juan
    Liu, Xiangyang
    Xiang, Zhengtao
    Wei, Gang
    [J]. IEEE ACCESS, 2020, 8 : 160221 - 160230
  • [39] Multi-attribute decision-making based on the SPIFGIA operators
    Wang C.
    Fu X.
    Meng S.
    He Y.
    [J]. Granular Computing, 2017, 2 (4) : 321 - 331
  • [40] Fuzzy multi-objective optimization decision-making of reliability of series system
    Huang, HZ
    [J]. MICROELECTRONICS AND RELIABILITY, 1997, 37 (03): : 447 - 449