Applied Sciences (Aug 2020)

Establishment of the Controlled Low-Strength Desulfurization Slag Prediction Model for Compressive Strength and Surface Resistivity

  • Chang-Chi Hung,
  • Chien-Chih Wang,
  • Her-Yung Wang

DOI
https://doi.org/10.3390/app10165674
Journal volume & issue
Vol. 10, no. 16
p. 5674

Abstract

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In this study, the desulfurization slag used the volume method to replace fine natural aggregates in controllable low-strength materials (CLSM); the desulfurization slag content (DS) and curing time (t) were used as variables to test the compressive strength and surface resistivity of CLSM and simulated a prediction model on the results. The test results showed during that the compressive strength on the 28th day, the average desulfurization slag replacement amount increased by 10%, and the compressive strength decreased by 0.9 MPa. The surface resistivity increases with age, and each ratio increases from seven days to 28 days, and the surface resistivity value increases from 9.3% to 20.6%. After that, a hyperbolic function and exponential function with multiple variables were used to establish a simulation model of the effects of the DS content and curing time on the compressive strength and surface resistivity of CLSM. Compared with the test results, the statistical analysis shows that the average absolute percentage error (MAPE) of the compressive strength is 9.17%, and the surface resistivity is 10.67%. From the results, the predictive analysis model developed in this paper provides good predictive results in terms of compressive strength and surface resistivity.

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