Journal of Applied Science and Engineering

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The Truyen Tran1, Thu Minh Tran1, Xuan Tung Nguyen2This email address is being protected from spambots. You need JavaScript enabled to view it., Ba Thanh Vu1, and Quang Vu Le1

1Faculty of Civil Engineering, University of Transport and Communications, Hanoi 100000, Vietnam

2Campus in Ho Chi Minh City, University of Transport and Communications, Ho Chi Minh City 700000, Vietnam


 

 

Received: January 12, 2024
Accepted: October 1, 2024
Publication Date: January 2, 2025

 Copyright The Author(s). This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are cited.


Download Citation: ||https://doi.org/10.6180/jase.202509_28(9).0017  


This study aims to present the results of anticipation of lightweight concrete durability when exposed to a chloride environment under pre-compressive load. The research employs Keramzit aggregate as the coarse aggregate for lightweight concrete. Following a 28-day curing period in water, the concrete specimens undergo varying levels of pre-compressive stress. Rapid Chloride Permeability Testing is then conducted to ascertain the chloride diffusion coefficient. The study posits a correlation between the chloride diffusion coefficient and precompressive stress levels, drawing from the experimental findings. Furthermore, Monte-Carlo simulation is employed to assess the influence of stochastic variables on the corrosion likelihood of concrete structures using lightweight aggregates. These stochastic variables encompass the chloride diffusion coefficient, surface chloride concentration, critical chloride concentration, concrete protection layer thickness, and a coefficient contingent on environmental conditions, to appraise the operational lifespan of lightweight concrete structures.


Keywords: Lightweight concrete, Service life, Pre-Compressive stress, Corrosion, Monte Carlo simulation, Probability.


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