Xiaolong Liao
- Deep hybrid neural network-aided electromechanical impedance method for automated damage detection of lining concrete under freeze-thaw cycling. Dans: Structural Health Monitoring. :
- Automated estimation of early-age concrete compressive strength using EMI signature-driven deep learning technique. Dans: Construction and Building Materials, v. 426 (mai 2024). (2024):
- Nondestructive detection of fiber content in steel fiber reinforced concrete through percussion method coordinated with a hybrid deep learning network. Dans: Journal of Building Engineering, v. 86 (juin 2024). (2024):
- Automatic assessment of freeze-thaw damage in concrete structures using piezoelectric-based active sensing approach and deep learning technique. Dans: Engineering Structures, v. 302 (mars 2024). (2024):
- Dashijian Reservoir spillway physical shape optimisation design using model experiment. Dans: LHB: Hydroscience Journal, v. 109, n. 1 (8 mars 2023). (2023):
- Intelligent monitoring of concrete-rock interface debonding via ultrasonic measurement integrated with convolutional neural network. Dans: Construction and Building Materials, v. 400 (octobre 2023). (2023):
- The friction-weakening cause by localized wear-induced damage and its effect on liquefaction resistance of sandy soil using DEM. Dans: Soil Dynamics and Earthquake Engineering, v. 177 (février 2024). (2024):
- An innovative deep neural network coordinating with percussion-based technique for automatic detection of concrete cavity defects. Dans: Construction and Building Materials, v. 400 (octobre 2023). (2023):