Embedded and surface ultrasonic pulse velocity for in situ strength assessment of cast reinforced concrete during...

Reliable in-situ strength information is critical for construction-stage decisions, yet conventional UPV-UCS correlations are typically established on companion cylinders, which may overestimate the state of cast reinforced members. This study addresses this gap by developing an IoT-enabled embedded ultrasonic sensing system that tracks age-dependent UPV along a fixed internal path (200 mm) in cast reinforced concrete from casting to 28 days, and by quantifying the persistent discrepancy between embedded-path and cylinder-based surface UPV under identical mix designs. Across all mixes and ages, embedded-path UPV remained lower than surface UPV (ΔUPV = 118-415 m/s), suggesting that cylinder-based UPV may provide unconservative strength inference for cast members under the investigated configuration. By pooling embedded UPV with companion-cylinder UCS results, we establish a conservative empirical UCS-UPV model (UCS = 0.3846e0.0011V_p, R² = 0.82) with uncertainty metrics (RMSE and MAE). A cable-free LoRa-Wi-Fi architecture with gateway integrity checks and REST-based cloud upload demonstrates the feasibility of periodic near-real-time visualization for curing-stage monitoring, although full communication-performance benchmarking was beyond the scope of this study. Although direct member-strength verification of the cast specimens was not performed, the results support embedded-path UPV as a practical complementary indicator for construction-stage decision making.