Tushar Bansal 
- : Sustainable construction: unveiling the potential of hempcrete in the modern era. In: Asian Journal of Civil Engineering.
- (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 February 2024).
- (2024): RILEM recommendation from TC 289-DCM: guideline for designing and operating long-term marine exposure sites. In: Materials and Structures, v. 57, n. 3 (5 March 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 (October 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 June 2023).
- (2023): Mechanical properties of concrete made with calcined clay: a review by RILEM TC-282 CCL. In: Materials and Structures, v. 56, n. 4 (13 April 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): Report of RILEM TC 281-CCC: outcomes of a round robin on the resistance to accelerated carbonation of Portland, Portland-fly ash and blast-furnace blended cements. In: Materials and Structures, v. 55, n. 3 (19 March 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).
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