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