Theoretical and practical fusion investigation for the intelligent real-time control technology of pavement fracturing recycling

Abstract

Conventional methods for evaluating pavement fracturing afford limited spatial coverage and provide little support for process control. This study develops a real-time, full-coverage assessment by extracting per-blow impact indices from falling-weight acceleration during free-fall impacts and embedding them in an integrated, closed-loop workflow. The methodology derives impact indices from the measured acceleration waveform, establishes their mechanics via a Hertz impact model, employs a DEM–FDM representation that accounts for layered pavement characteristics to simulate falling weight–pavement interaction, and uses an instrumented falling weight with wireless cloud telemetry for on-site threshold calibration, per-blow classification into under-fractured, acceptable, and over-fractured states, and immediate targeted secondary treatments. The results show that the Hertz formulation links impact acceleration to structural response and that the influence of Poisson’s ratio is negligible, yielding a single-valued mapping from impact acceleration to composite modulus. Simulations demonstrate the theoretical feasibility of using the impact indices to evaluate fracturing effectiveness, with R² not less than 0.86 relative to mechanical response. In field application on a control section of China National Highway G329, identification accuracies reached 69.2 %-92.3 %; target-deflection compliance increased from 85 % after initial microcracking to 99 % after secondary remediation through supplemental impacts or grouting, and modulus uniformity improved by 14 % under closed-loop operation. In conclusion, real-time impact indices effectively evaluate fracturing quality. Furthermore, they lay the foundation for the automation and intelligent upgrading of fracturing equipment and on-site process control.