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Optimization and Performance Study of Desert Sand Concrete Mix Proportion Based on Response Surface and NSGA-II Algorithm
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Lei GONG, Yong-jun QIN*, Yuan TIAN, Dong HUANG, Bei-sen FENG
Science Technology and Engineering | 2025, 25(13) : 5571 - 5578
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Science Technology and Engineering | 2025, 25(13): 5571-5578
Papers·Architectural Science
Optimization and Performance Study of Desert Sand Concrete Mix Proportion Based on Response Surface and NSGA-II Algorithm
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Lei GONG, Yong-jun QIN*, Yuan TIAN, Dong HUANG, Bei-sen FENG
Affiliations
  • School of Civil Engineering and Civil Engineering, Xinjiang University, Urumqi 830017, China
Published: 2025-05-08 doi: 10.12404/j.issn.1671-1815.2404472
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To explore the impacts of various factors on the performance of concrete, the response surface methodology was adopted to optimize the concrete mix proportion. In the experiment, the water-binder ratio, the dosage of steel slag, and the content of desert sand were taken as variables, with a focus on analyzing the main performance indicators such as the slump of concrete, compressive strength, and splitting tensile strength. The experimental results indicate that the content of desert sand has the most significant influence on the slump of concrete, while the compressive strength and splitting tensile strength are mainly affected by the variation of the water-binder ratio. With the increase of the content of desert sand, the slump, compressive strength, and splitting tensile strength of concrete exhibit a trend of initially increasing and then decreasing. When the content of desert sand reaches 30%, the performance is optimal. The addition of steel slag can enhance the fluidity of desert sand concrete (DSC). As the amount of steel slag increases, the compressive strength of DSC shows a decreasing trend, and the tensile strength increases initially and then decreases. The addition of steel slag interacts with desert sand, particularly on the tensile strength of DSC. Through response analysis, the optimal mix proportion was obtained as a water-binder ratio of 0.39, a dosage of steel slag of 10%, and a content of desert sand of 30%, at which the comprehensive performance of DSC is the best. Finally, non-dominated sorting genetic algorithm Ⅱ(NSGA-Ⅱ) was utilized for multi-objective optimization, which yielded a more complete solution set, thereby providing certain technical support for the application of DSC.

desert sand concrete  /  response surface method  /  NSGA-Ⅱ  /  multi-objective optimization
Lei GONG, Yong-jun QIN, Yuan TIAN, Dong HUANG, Bei-sen FENG. Optimization and Performance Study of Desert Sand Concrete Mix Proportion Based on Response Surface and NSGA-II Algorithm[J]. Science Technology and Engineering, 2025 , 25 (13) : 5571 -5578 . DOI: 10.12404/j.issn.1671-1815.2404472
Year 2025 volume 25 Issue 13
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doi: 10.12404/j.issn.1671-1815.2404472
  • Receive Date:2024-06-15
  • Online Date:2025-07-09
  • Published:2025-05-08
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  • Received:2024-06-15
  • Revised:2025-01-24
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    School of Civil Engineering and Civil Engineering, Xinjiang University, Urumqi 830017, China
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表12种不同金属材料的力学参数

Family
属数
Number of
genus
种数
Number of
species
占总种数比例
Percentage of
total species (%)

Genus
种数
Number of
species
占总种数比例
Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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