- Interpretable ensemble machine learning for the prediction of the expansion of cementitious materials under external sulfate attack. In: Journal of Building Engineering, v. 80 (December 2023). (2023):
- Coupled effects of simultaneous autogenous self-healing and sustained flexural loading in cementitious materials. In: Journal of Building Engineering, v. 79 (November 2023). (2023):
- Interpretable machine learning model for autogenous shrinkage prediction of low-carbon cementitious materials. In: Construction and Building Materials, v. 396 (September 2023). (2023):
- Creep analysis of cementitious materials in seawater using a poro-chemo-mechanical model. In: Marine Structures, v. 90 (July 2023). (2023):
- Imaging concrete cracks using Nonlinear Coda Wave Interferometry (INCWI). In: Construction and Building Materials, v. 391 (August 2023). (2023):
- Mechanical regains due to self-healing in cementitious materials: Experimental measurements and micro-mechanical model. In: Cement and Concrete Research, v. 80 (February 2016). (2016):
- Modular deep learning segmentation algorithm for concrete microscopic images. In: Construction and Building Materials, v. 349 (September 2022). (2022):
- Using machine learning techniques for predicting autogenous shrinkage of concrete incorporating superabsorbent polymers and supplementary cementitious materials. In: Journal of Building Engineering, v. 49 (May 2022). (2022):
- Determination of the origin of the strength regain after self-healing of binary and ternary cementitious materials including slag and metakaolin. In: Journal of Building Engineering, v. 41 (September 2021). (2021):
- Temperature effects on chloride binding capacity of cementitious materials. In: Magazine of Concrete Research, v. 73, n. 15 (August 2021). (2021):
- Monitoring of autogenous crack healing in cementitious materials by the nonlinear modulation of ultrasonic coda waves, 3D microscopy and X-ray microtomography. In: Construction and Building Materials, v. 123 (October 2016). (2016):