The strength properties of marble and their intercorrelations: Insights into specimen size effect
BULLETIN OF ENGINEERING GEOLOGY AND THE ENVIRONMENT, cilt.85, sa.9, 2026 (SCI-Expanded, Scopus)
- Yayın Türü: Makale / Tam Makale
- Cilt numarası: 85 Sayı: 9
- Basım Tarihi: 2026
- Doi Numarası: 10.1007/s10064-026-05288-1
- Dergi Adı: BULLETIN OF ENGINEERING GEOLOGY AND THE ENVIRONMENT
- Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, IBZ Online, Compendex, Environment Index, Geobase, INSPEC, Academic Search Ultimate (EBSCO), Natural Science Collection (ProQuest), Earth, Atmospheric, & Aquatic Science Collection (ProQuest), Engineering Source (EBSCO), Materials Science & Engineering Collection (ProQuest), Technology Collection (ProQuest)
- Çanakkale Onsekiz Mart Üniversitesi Adresli: Evet
Özet
Specimen size is a critical factor influencing the mechanical strength behavior of building stones. In this study, the effect of specimen size on the uniaxial compressive strength (UCS), Brazilian tensile strength (BTS), and point load index (PLI) of different marbles was investigated. Furthermore, correlation equations for predicting UCS using BTS and PLI were developed, explicitly accounting for the effect of specimen size. To this end, UCS specimens with length-to-diameter (L/D) ratios of 2.0, 2.2, 2.4, 2.6, 2.8, and 3.0 were prepared from the marble samples. For BTS tests, specimens with thickness-to-diameter (T/D) ratios of 0.5, 0.6, 0.7, 0.8, 0.9, and 1.0 were extracted. Similarly, PLI specimens were prepared with T/D ratios of 0.30, 0.44, 0.58, 0.72, 0.86, and 1.00. The findings revealed a noticeable decrease in UCS, BTS, and PLI values as the L/D and T/D ratios increased. Based on scanning electron microscopy (SEM) observations, this trend was attributed to the higher probability of microcracks and internal flaws in larger-sized specimens. The results indicated that specimen size has a minor effect on the accuracy of the BTS and PLI-based correlation equations for predicting UCS. Additionally, it was observed that BTS is a more reliable parameter than PLI for predicting UCS.