The particle-size distribution of concrete and mortar aggregates by image analysis

被引:0
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作者
Sitzia F. [1 ,2 ]
Beltrame M. [1 ,3 ]
Mirão J. [1 ,2 ]
机构
[1] Institute for Advanced Studies and Research, HERCULES Laboratory, University of Évora, Largo Marquês de Marialva 8, Évora
[2] Geosciences Department, School of Sciences and Technology, University of Évora, Rua Romão Ramalho 59, Évora
[3] CIDEHUS, UNESCO Chair of Intangible Heritage and Traditional Know-How: Linking Heritage, University of Évora, Palacío do Vimioso, Largo Marquês de Marialva, 8, Évora
关键词
Ancient and modern mortars and concrete; Cultural heritage; Image analysis; Non-destructive testing; Particle-size distribution;
D O I
10.1007/s41024-022-00214-w
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摘要
Particle-size analysis on ancient mortars and concretes aggregate is today a common practice in Cultural Heritage and civil engineering. Normally, a particle-size distribution of mortar aggregates on in situ materials is carried out using sieves, following the dissolution of the carbonate binder. This technique needs about 200 g of material per sample and produces a large volume of liquid wastes. Sampling is generally supervised by local authorities especially in the field of cultural heritage. Over the years it has therefore become necessary to devise analytical solutions for collecting the smallest volume of material to preserve the buildings. In this research a non-destructive testing to define the aggregate distribution and their percentage in the mortars and/or concretes is presented. It consists of 2D particle size image analysis performed in thin sections. To evaluate the reliability and limitations of this method, already operated in other research, 20 particle-size distributions, characterized by aggregates with Roundness 0.5 < R < 0.95 and Circularity 0.4 < C < 0.75 were created and analyzed using real sieves. Afterwards, the same particle-distributions were mixed with resin to reproduce a “fake” concrete/mortar. A thin section of this latter was analyzed by appropriate software. The method shows a good prediction of the Resin/Aggregate ratio with uniformity coefficient of 0.88 together with variable reliability of the particle-size distribution. © 2022, The Author(s), under exclusive licence to Springer Nature Switzerland AG.
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