<p>Quantitative correlations between mechanical degradation, expansion, and crack size distribution have not been identified in previous research on concrete degradation caused by alkali-silica reaction (ASR), limiting the accuracy of numerical modeling for ASR-induced damage. To fill this gap, this study introduces an experimental framework to concurrently monitor mechanical properties, expansion, and crack patterns in four groups of specimens with varying reactive aggregate sizes, during ASR progression. Following continuous expansion measurement under ASR acceleration, each specimen was sliced at different expansion levels. Compression tests and crack observations were conducted on separate portions of the same specimen. To enhance crack pattern visualization, fluorescent resin was applied, and images were captured under ultraviolet light. Utilizing image analysis, the length and width distributions of cracks were quantified, and the size distributions were further converted into <InlineEquation ID="IEq1"> <InlineMediaObject> <ImageObject Color="BlackWhite" FileRef="11527_2025_2618_Article_IEq1.gif" Format="GIF" Height="15" Rendition="HTML" Resolution="72" Type="Linedraw" Width="178" /> </InlineMediaObject> <EquationSource Format="TEX">$MACRO-crack\ ratio$</EquationSource> <EquationSource Format="MATHML"><math> <mrow> <mi>M</mi> <mi>A</mi> <mi>C</mi> <mi>R</mi> <mi>O</mi> <mo>-</mo> <mi>c</mi> <mi>r</mi> <mi>a</mi> <mi>c</mi> <mi>k</mi> <mspace width="4pt" /> <mi>r</mi> <mi>a</mi> <mi>t</mi> <mi>i</mi> <mi>o</mi> </mrow> </math></EquationSource> </InlineEquation> for each specimen. Correlating this ratio with expansion revealed a more consistent decline in compressive strength across groups than evaluation based solely on expansion. The integration of <InlineEquation ID="IEq2"> <InlineMediaObject> <ImageObject Color="BlackWhite" FileRef="11527_2025_2618_Article_IEq2.gif" Format="GIF" Height="15" Rendition="HTML" Resolution="72" Type="Linedraw" Width="178" /> </InlineMediaObject> <EquationSource Format="TEX">$MACRO-crack\ ratio$</EquationSource> <EquationSource Format="MATHML"><math> <mrow> <mi>M</mi> <mi>A</mi> <mi>C</mi> <mi>R</mi> <mi>O</mi> <mo>-</mo> <mi>c</mi> <mi>r</mi> <mi>a</mi> <mi>c</mi> <mi>k</mi> <mspace width="4pt" /> <mi>r</mi> <mi>a</mi> <mi>t</mi> <mi>i</mi> <mi>o</mi> </mrow> </math></EquationSource> </InlineEquation> into an ASR simulation model significantly enhanced the accuracy of compressive strength prediction. This study proposes a quantitative evaluation method integrating crack pattern analysis with numerical simulation, promising for improved ASR assessment in engineering practices.</p>

Quantitative evaluation of crack size effect on concrete deterioration induced by alkali-silica reaction: an experimental and numerical study

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2025年3月29日

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Xi Ji,
Hyo Eun Joo,
Yuya Takahashi

摘要

Quantitative correlations between mechanical degradation, expansion, and crack size distribution have not been identified in previous research on concrete degradation caused by alkali-silica reaction (ASR), limiting the accuracy of numerical modeling for ASR-induced damage. To fill this gap, this study introduces an experimental framework to concurrently monitor mechanical properties, expansion, and crack patterns in four groups of specimens with varying reactive aggregate sizes, during ASR progression. Following continuous expansion measurement under ASR acceleration, each specimen was sliced at different expansion levels. Compression tests and crack observations were conducted on separate portions of the same specimen. To enhance crack pattern visualization, fluorescent resin was applied, and images were captured under ultraviolet light. Utilizing image analysis, the length and width distributions of cracks were quantified, and the size distributions were further converted into $MACRO-crack\ ratio$ $M A C R O - c r a c k r a t i o$ for each specimen. Correlating this ratio with expansion revealed a more consistent decline in compressive strength across groups than evaluation based solely on expansion. The integration of $MACRO-crack\ ratio$ $M A C R O - c r a c k r a t i o$ into an ASR simulation model significantly enhanced the accuracy of compressive strength prediction. This study proposes a quantitative evaluation method integrating crack pattern analysis with numerical simulation, promising for improved ASR assessment in engineering practices.