JOURNAL OF YANGTZE RIVER SCIENTIFIC RESEARCH INSTI ›› 2016, Vol. 33 ›› Issue (7): 126-131.DOI: 10.11988/ckyyb.20150354

• HYDRAULIC STRUCTURE AND MATERIAL • Previous Articles     Next Articles

Regularity of Compressive Strength Deterioration and Grey Prediction of Concrete Corrosion in Ammonium Sulfate Solution

DENG Tong-fa1,2, PENG Jian1,2, OUYANG Bin3, ZHU Pei-dong1, LIN Huang1   

  1. 1.School of Architectural and Surveying & Mapping Engineering, Jiangxi University of Science and Technology, Ganzhou 341000,China;
    2.Jiangxi Provincial Key Laboratory of Environmental Geotechnical Engineering and Disaster Control, , Jiangxi University of Science and Technology, Ganzhou 341000,China;
    3. Jiangxi Wufang Architectural Design Co.Ltd.,Ganzhou 341000,China
  • Received:2015-04-26 Online:2016-07-01 Published:2016-07-11

Abstract: Corrosion tests were carried out by immersing concretes in ammonium sulfate solution of 5% concentration. The concretes are of different material compositions of water cement ratio, paste aggregate ratio and content of fly ash. The regularity of deterioration of compressive strength of immersed concretes during 0-120 d corrosion age were obtained. The grey correlation analysis method was used to research the influence of different factors on the compressive strength of concrete, and the GM (1,1) prediction model was established to forecast the service life and strength deterioration of the concretes in ammonium sulfate solution. Results show that the concretes with water cement ratio of 0.4, paste aggregate ratio of 0.28 and fly ash content of 10% have better anti-erosion performance. Moreover, the compressive strength of concretes declines significantly with the increases in water cement ratio, paste aggregate ratio and fly ash dosage. The prediction results by the GM(1,1) model indicate that the lifetimes of concretes with water cement ratio of 0.4, paste aggregate ratio of 0.28 and fly ash content of 10% increase by 247%, 125% and 74% than those of concretes with the same influence factors, respectively.

Key words: ammonium sulfate, concrete, water cement ratio, paste aggregate ratio, fly ash content, GM (1,1) prediction model

CLC Number: 

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