Abstract
Estimating the early-age strength of 3D printed concrete is more challenging than that of conventional concrete due to the absence of formwork and increased variability in curing conditions. The common maturity method is ineffective for 3D printed structures since it fails to account for moisture content variations. This paper introduces a new approach using embedded sensors to continuously collect data on the electrical properties and temperature of 3D printed concrete, enabling accurate strength estimation under varying curing conditions. Empirical models based on electrical resistivity, internal temperature, and relative permittivity are developed and evaluated. The permittivity-based model can estimate the flexural strength of 3D printed specimens with at least 83% accuracy and a maximum root mean square error of 0.27 MPa under different curing conditions across three concrete grades. Additionally, an innovative curing technique involving the automated application of curing compounds is proposed and proven effective for 3D printed concrete.
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