Modelling alkali-silica reaction effects for condition assessment and capacity evaluation of reinforced concrete structures

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Alkali-silica reaction (ASR) is one of the most harmful distress mechanisms affecting concrete infrastructure worldwide. ASR is a chemical reaction that generates a secondary product, which induces expansive pressure within the reacting aggregate particles and adjacent cement paste upon moisture uptake. This in turn leads to cracking, loss of material integrity, and consequently compromises serviceability and capacity of the structure. In Australia, several concrete structures of various types such as dams, bridges and railway sleepers have been identified as affected by the reaction to varying extents. To date, the majority of experts agree that new concrete structures can be constructed in such a way to avoid ASR-induced effects by using either non-reactive aggregates classified by national and international standards, or supplementary cementitious materials to mitigate the reaction. However, there is currently a lack of a comprehensive plan for diagnosis and prognosis of existing concrete structures affected by ASR. This is despite its importance in providing efficient rehabilitation methods and management strategies for the infrastructure. When investigating existing structures affected by ASR, two crucial questions need to be answered prior to specifying management strategies, i.e., (i) the current state of damage and its effects on structural capacity and serviceability; and (ii) the prediction of damage progress and its impact on the structure in the coming months or years. In this regard, two main effects of the deleterious ASR - expansion and mechanical properties degradation of the concrete - need to be evaluated prior to assessing the condition and capacity of the affected structures suffering from ASR. This study aimed to provide different modelling approaches for evaluating alkali-silica reaction (ASR) induced effects for condition assessment and capacity evaluation of reinforced concrete structures suffering from ASR. First, degradation of mechanical properties due to ASR was evaluated using artificial neural network and computational homogenization. Then, a novel semi-empirical model was proposed for accurately correlating expansion from the laboratory tests to the expansion of concrete in the field. Finally, a finite element model was developed for effectively modelling expansion and load-carrying capacity of reinforced concrete members. The proposed models are successful to forecast the expansion of concrete in the field based on laboratory measurements and evaluating mechanical properties degradation prior to assessing the structural capacity.
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