- Three-dimensional mesoscopic investigation on the dynamic compressive behavior of coral sand concrete with reinforced granite coarse aggregate (GCA). In: Composite Structures, v. 352 (Januar 2025). (2025):
- Interpretation of dual time-dependent chloride diffusion in concrete based on physical information neural networks. In: Case Studies in Construction Materials, v. 21 (Dezember 2024). (2024):
- Study on dynamic mechanical properties and microstructure of basalt fiber reinforced coral sand cement composite *. In: Construction and Building Materials, v. 425 (April 2024). (2024):
- Machine learning-based prediction of outdoor thermal comfort: Combining Bayesian optimization and the SHAP model. In: Building and Environment, v. 254 (April 2024). (2024):
- Hybrid prediction model for reinforcements' corrosion stage by multiple nondestructive electrochemical indices. In: Journal of Building Engineering, v. 82 (April 2024). (2024):
- Bayesian probabilistic model for reinforcement corrosion ratio of reinforcement in concrete prediction based on modified half-cell potential. In: Journal of Civil Structural Health Monitoring, v. 14, n. 2 (Oktober 2023). (2023):
- Experimental study on high temperatures performance of rubberized geopolymer mortar. In: Journal of Building Engineering, v. 76 (Oktober 2023). (2023):
- Preparation and dynamic mechanical properties of fiber-reinforced high-strength all-coral-sand seawater concrete. In: Structures, v. 54 (August 2023). (2023):
- Multi-factor fuzzy prediction model of concrete surface chloride concentration with trained samples expanded by random forest algorithm. In: Marine Structures, v. 86 (November 2022). (2022):
- Experimental study on preparation and properties of low content rubberized geopolymer mortar. In: Construction and Building Materials, v. 352 (Oktober 2022). (2022):
- Multi-factor model to predict surface chloride concentration of concrete based on fuzzy logic system. In: Case Studies in Construction Materials, v. 17 (Dezember 2022). (2022):
- Comparison of models for predicting winter individual thermal comfort based on machine learning algorithms. In: Building and Environment, v. 215 (Mai 2022). (2022):
- Probabilistic Prediction Model for the Chloride Diffusion Coefficient of Concrete under Tensile and Compressive Stresses. In: KSCE Journal of Civil Engineering, v. 26, n. 2 (Dezember 2021). (2021):