most citedReal-Time Asphalt Pavement Layer Thickness Prediction Using Ground-Penetrating Radar Based on a Modified Extended Common Mid-Point (XCMP) Approach

43 citations · 89 across the 6 of their papers we have counts for

collaborators

6 papers

eess.SY20246 cited

Development of a full-Scale approach to predict overlay reflective crack

Zehui Zhu, Imad L. Al-Qadi

Resurfacing a moderately deteriorated Portland cement concrete (PCC) pavement with asphalt concrete (AC) layers is considered an efficient rehabilitation practice. However, reflect…

cs.CV20243 cited

SIFT-Aided Rectified 2D-DIC for Displacement and Strain Measurements in Asphalt Concrete Testing

Zehui Zhu, Imad L. Al-Qadi

Two-dimensional digital image correlation (2D-DIC) is a widely used optical technique to measure displacement and strain during asphalt concrete (AC) testing. An accurate 2-D DIC m…

cs.CV202410 cited

Asphalt Concrete Characterization Using Digital Image Correlation: A Systematic Review of Best Practices, Applications, and Future Vision

Siqi Wang, Zehui Zhu, Tao Ma +1

Digital Image Correlation (DIC) is an optical technique that measures displacement and strain by tracking pattern movement in a sequence of captured images during testing. DIC has…

eess.SP202443 cited

Real-Time Asphalt Pavement Layer Thickness Prediction Using Ground-Penetrating Radar Based on a Modified Extended Common Mid-Point (XCMP) Approach

Siqi Wang, Zhen Leng, Xin Sui +3

The conventional surface reflection method has been widely used to measure the asphalt pavement layer dielectric constant using ground-penetrating radar (GPR). This method may be i…

cs.CV202318 cited

Crack Detection of Asphalt Concrete Using Combined Fracture Mechanics and Digital Image Correlation

Zehui Zhu, Imad L. Al-Qadi

Cracking is a common failure mode in asphalt concrete (AC) pavements. Many tests have been developed to characterize the fracture behavior of AC. Accurate crack detection during te…

cs.CV20239 cited

Automated crack propagation measurement on asphalt concrete specimens using an optical flow-based deep neural network

Zehui Zhu, Imad L. Al-Qadi

This article proposes a deep neural network, namely CrackPropNet, to measure crack propagation on asphalt concrete (AC) specimens. It offers an accurate, flexible, efficient, and l…