Modulus of elasticity for grain-supported carbonates — determination and estimation for preliminary engineering purposes

Scientific paper - Original scientific paper

• Author: Zlatko Briševac https://orcid.org/0000-0001-7810-8255
• Author: Davor Pollak
• Author: Ana Maričić
• Author: Andreja Vlahek
• Author's institution: Croatian Geological Survey
• Author's institution: University of Zagreb; Faculty of Chemical Engineering and Technology
• Author's institution: University of Zagreb; Faculty of Mining, Geology and Petroleum Engineering; (Department of Mineralogy, Petrology and Mineral Resources)
• Author's institution: University of Zagreb; Faculty of Mining, Geology and Petroleum Engineering; (Department of Mining and Geotechnical Engineering)
• Scientific / art field, discipline and subdiscipline: NATURAL SCIENCES; Mathematics
• Scientific / art field, discipline and subdiscipline: NATURAL SCIENCES; Geology
• Scientific / art field, discipline and subdiscipline: TECHNICAL SCIENCES; Mining, Petroleum and Geology Engineering

Abstract (english)

The determination and estimation of elastic behaviour are essential in engineering practise, especially in quarrying, mining, construction, and all engineering professions that perform operations dealing with rock materials. Young’s modulus, or modulus of elasticity, is the most important property describing the deformability of rock material. In this paper, grain-supported carbonates from Croatia are described and their elastic modulus and significant physical and mechanical properties are determined. The analysis of the collected data was performed in the R statistical environment. Estimation models based on multiple linear regression and the regression tree model were created. The methodology of model development and evaluation in R environment is described in detail. According to the more stringent coefficients (RMSECV and adjusted R2) used to evaluate the success of the estimation, simple regression tree models were found to perform well for the preliminary estimation, while more complex models based on Bagging performed very well.

• Keywords (english): modulus of elasticity; grain-supported carbonates; estimate; regression tree; R statistical environment
• Language: english
• Publication type: Scientific paper - Original scientific paper
• Publication status: Published
• Peer review: Peer review - international
• Publication version: Published version
• Journal title: Applied Sciences
• Numbering: vol. 11, no. 13, 6148
• e-ISSN: 2076-3417
• DOI: https://doi.org/10.3390/app11136148
• URN:NBN: urn:nbn:hr:169:207622
• Publication: 2021-07-01
• Document URL: https://www.mdpi.com/2076-3417/11/13/6148
• Type of resource: Text
• Access conditions: Open access
• Created on: 2021-09-10 11:14:12