Visalakshi Talakokula 
- (2024): Integrating electro-mechanical impedance data with machine learning for damage detection and classification of blended concrete systems. In: Construction and Building Materials, v. 445 (September 2024).
- (2024): Exploring chloride-induced corrosion in reinforced concrete structures through embedded piezo sensor technology: an experimental and numerical study. In: Smart Materials and Structures, v. 33, n. 3 (2 Februar 2024).
- (2023): A review on health monitoring of concrete structures using embedded piezoelectric sensor. In: Construction and Building Materials, v. 405 (November 2023).
- (2023): Comparative study of machine learning methods to predict compressive strength of high-performance concrete and model validation on experimental data. In: Asian Journal of Civil Engineering, v. 25, n. 2 (Oktober 2023).
- (2023): Recommendation of RILEM TC 281-CCC: Test method to determine the effect of uniaxial compression load and uniaxial tension load on concrete carbonation depth. In: Materials and Structures, v. 56, n. 7 (10 August 2023).
- (2023): Report of RILEM TC 281-CCC: effect of loading on the carbonation performance of concrete with supplementary cementitious materials — an interlaboratory comparison of different test methods and related observations. In: Materials and Structures, v. 56, n. 6 (19 Juni 2023).
- (2022): Durability aspects of blended concrete systems subjected to combined mechanical and environmental loading using piezo sensor. In: Construction and Building Materials, v. 348 (September 2022).
- (2022): Durability performance of binary and ternary blended cementitious systems with calcined clay: a RILEM TC 282 CCL review. In: Materials and Structures, v. 55, n. 5 (Juni 2022).
- (2021): A Machine Learning Approach for Predicting the Electro-mechanical Impedance Data of Blended Rc Structures Subjected to Chloride Laden Environment. In: Smart Materials and Structures, v. 31, n. 1 (23 November 2021).
Structurae kooperiert mit
