Grey model study on strength and pore structure of self-compacting concrete with different aggregates based on NMR. (1st April 2023)

• Record Type: Journal Article
• Authors: Zhang, Shuyun; Zheng, Suqin; Wang, En; Dai, Huijuan
• Is Part Of: Journal of building engineering. Volume 64(2023)
• Publication Date: 2023-04-01
• Subjects: Self-compacting concrete -- Shale ceramsite -- Machine-made sand -- Pore structure characteristic parameter -- NMR technology Grey relational entropy analysis; Building -- Periodicals; 690.05
• DOI: 10.1016/j.jobe.2022.105560
• Languages: English
• ISSNs: 2352-7102

Abstract

Abstract: To promote the application of machine-made sand and shale ceramsite in self-compacting concrete (SCC), this paper takes four kinds of SCC with different aggregates as the research object. The working performance and mechanical properties of four kinds of SCC are tested when gravel and shale ceramsite are used as coarse aggregate and machine-made sand and river sand are used as fine aggregates. The T2 spectrum of self-compacting concrete with different aggregates at different ages is obtained by NMR technology, and the pore size distribution curve is obtained. Then, the grey relation entropy theory is used to analyze the influence of pore structure on the mechanical properties of SCC. Finally, based on the pore structure parameters, a GM (1, 3) prediction model for the compressive strength of SCC is established. The results show that: shale ceramsite and machine-made sand can be used as substitutes for gravel and river sand; The working performance of shale ceramsite SCC and river sand SCC is better than that of gravel SCC and machine-made sand SCC; The mechanical properties of gravel SCC and machine-made sand SCC are better than shale ceramsite SCC and river sand SCC, respectively. Small pores and porosity less than 0.02 μm have little effect on the mechanical properties of SCC, while spectral area and larger pores have a greater impact on it; GM（1, 3）model can achieve a more accurate prediction of the mechanical properties of shale ceramsite concrete, and the prediction error of gravel concrete is relatively large, reflecting that compared with shale ceramsite, gravel has a great influence on the mechanical properties of concrete. Highlights: SCCs are prepared using different aggregates such as crushed stone, shale ceramite, river sand and machine-made sand. SCCs are tested to evaluate workability properties and mechanical properties. A Grey model (GM (3, 1)) is constructed to predict the compressive strength of the SCC. Four SCCs are suitable for construction but MS-SCLC and SCC have better performance. GM (3, 1) model predictions agree with experiment.