|Abstract:||Early-age cracking and spalling in concrete pavements reduces slab capacity, joint load transfer, ride quality, and its long-term performance. These premature distresses lead to increased maintenance costs for sealing, patching, and grinding. Proper timing of sawcutting and curing are two construction activities that can minimize early-age distress development. In order to better time sawcutting and curing activities, an improved method to spatially monitor the setting time of concrete is required. Likewise, rapid evaluation of the joint quality after sawing is also necessary to provide feedback to adjust the timing. While previous methods for sawcutting and curing are experiential and subjective, this research aims to develop contactless sensing and computer vision techniques to significantly improve the timing of certain early-age concrete construction activity decisions through quantitative indicators.
A non-contact, ultrasonic testing system (UTS) to monitor concrete set time has been developed by monitoring the evolution of leaky Rayleigh (LR-wave) wave signals over time and space (surface of the concrete). The non-contact UTS integrates a 50 kHz non-contact ultrasonic transmitter and an array of five microelectromechanical systems (MEMS) sensors as non-contact receivers. The UTS technique was first implemented in the laboratory at incident angles of 12^° for mortar mixtures in order to determine the final setting times. The UTS technique was also applied at different incident angles (12^° to 60^° ) on a mortar mixture to evaluate its influence of the angle on the UTS measurement. The final setting times for mortars were consistent with the ASTM C403 penetration resistance standard when an incident angle of 12^° was used. Additionally, this UTS was successfully field validated on three concrete pavement test sections in Illinois that had different casting times during the day. Final setting times in the field greatly varied (287 to 210 minutes) given the higher ambient temperatures and surrounding concrete mass. In order to improve decision-making on sawcut timing, the final set times measured by the UTS were linked with the earliest time to initiate sawcutting within an acceptable level of raveling. A computer vision-based (CV) process was developed that employed multiple joint images, 2D segmentation for joint raveling/spalling extraction, 3D point cloud reconstruction and meshing of the joint damage, and a 3D damage quantification analysis for assessing the joint damage. The proposed CV-based joint damage analysis quantified joint damage through two newly defined indices: (i) raveling damage index (RDI) for raveling and (ii) joint damage index (JDI) for spalling. The proposed CV-based method had an accuracy of 76% with an error of 10%. With this CV-based process, it was determined that RDI of 3% or less is an acceptable quality level for contraction joints in the field.
A one-sided multi-sensor ultrasonic array device with a support vector machine algorithm was developed that detects the existence of a concealed, vertical crack beneath a notched contraction joint. This algorithm supports the field assessment of the effectiveness of sawcut timing, sawcut depth, and whether premature slab cracking was related to poor sawing procedures. The multi-sensor ultrasonic array device generated and received ultrasonic shear waves (S-wave) across the inspected joint. The acquired time domain signals were used to calculate normalized transmission energy (NTE) across the joint. The NTE algorithm defined the ratio of the energy of diffracted and reflected S-waves received behind the joint with respect to the energy of direct, diffracted, and reflected S-waves received in front of the joint. Laboratory results demonstrated that the NTE technique could successfully identify the existence or non-existence of a crack beneath the sawcut. Finally, the NTE technique coupled with a 2D decision boundary equation was field validated on 152 concrete pavement contraction joints from multiple projects with similar slab thicknesses and sawcut notch depths in Illinois and Iowa.
Finally, the non-contact UTS was coupled with a 2D wavefield analysis to rapidly evaluate the effectiveness, spatially and with time, of curing methods through monitoring of the near-surface damage in hydrating paste at early-ages. The new technique monitored the energy of the LR-waves signal over time with the non-contact UTS and then, analyzed the frequency-wave number (f-k) domain to characterize the quantity of near-surface damage in the cement paste specimens. An ultrasonic surface damage index (USDI) was defined from the f-k wavefield domain based on the ratio of the non-propagating and forwarding LR-wave energy. The non-contact sensing and 2D wavefield analysis easily distinguished the differences in surface damage between the different curing methods (no curing surface, the plastic sheet cover cure, and the wax-based curing). Surfaces with low surface damage had negligible non-propagating wave energy, which was seen in the wax-based curing specimens and the unexposed bottom surfaces of all cast specimens.