Abstract
Abstract Although there are many proposed relations for different rock types to predict the uniaxial compressive strength (UCS) as a function of P-wave velocity (V P) and point load index (Is), only a few of them are focused on marlstones. However, these studies have limitations in applicability since they are mainly based on local studies. In this paper, an attempt is therefore made to present updated relations for two previous proposed correlations for marlstones in Iran. The modification process is executed through multivariate regression analysis techniques using a provided comprehensive database for marlstones in Iran, including UCS, V P and Is from publications and validated relevant sources comprising 119 datasets. The accuracy, appropriateness and applicability of the obtained modifications were tested by means of different statistical criteria and graph analyses. The conducted comparison between updated and previous proposed relations highlighted better applicability in the prediction of UCS using the updated correlations introduced in this study. However, the derived updated predictive models are dependent on rock types and test conditions, as they are in this study.
Highlights
Marlstones are calcium carbonate or lime-rich mudstones with variable amounts of clays and silt [35]
Abstract there are many proposed relations for different rock types to predict the uniaxial compressive strength (UCS) as a function of P-wave velocity (VP) and point load index (Is), only a few of them are focused on marlstones
The derived updated predictive models are dependent on rock types and test conditions, as they are in this study
Summary
Marlstones are calcium carbonate or lime-rich mudstones with variable amounts of clays and silt [35] They are recognized by their inherent weak strength in rock engineering related projects Introducing and developing alternative nondestructive indirect methods can play a significant role in providing UCS predictive models [47]. Such nondestructive measurements (e.g. Schmidt hammer, Shore hardness, Los Angeles abrasion, slake durability, petrographical and structural property analyses, block punch strength index, core strangle test, point load index test, P-wave velocity and impact strength) with simpler and quicker procedures can be carried out both in field and laboratory conditions Various modeling methods such as statistical techniques and in particular multivariate
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