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OPTIMIZATION OF THE VOLUME OF LABORATORY TESTS IN ENGINEERING SURVEY

Viktor Gordeev, Dmitry Gura, Grittel Shevchenko, Ekaterina Panchenko, Saida Pshidatok

First published: 2021-12-20https://doi.org/10.5593/sgem2021/2.1/s09.50View metrics

Abstract

The objective of this research is to optimize the volume of laboratory tests of physical and mechanical properties of soil. Today, the solution to geomechanical and mining technological problems has the form of functional or statistical relationships, reasoned by the physical parameters of soils (density, moisture, strength properties, acoustic indicators, etc.). The calculations use the average values or estimates of these parameters obtained from statistical processing of multiple laboratory or field test data. The objectively existing natural variability of the physical and mechanical properties of soils does not allow for a limited number of tests to obtain absolutely accurate estimates of the design parameters. Instead of the true values of properties we should insert in the formulas the mathematical expectations of the centers of empirical distributions of these properties, established for specific fields or their areas. As a result, even deterministic expressions become functions of random arguments. The article deals with both simple and complex cases of optimization of single value measurements. We have derived formulas for calculating the required volume of tests for each argument of a random function, and proposed an approach to solve complex cases of optimizing the volumes of field and laboratory research on soil properties.

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Publication details

Title
OPTIMIZATION OF THE VOLUME OF LABORATORY TESTS IN ENGINEERING SURVEY
Authors
Viktor Gordeev, Dmitry Gura, Grittel Shevchenko, Ekaterina Panchenko, Saida Pshidatok
Proceedings
SGEM International Multidisciplinary Scientific GeoConference EXPO Proceedings; 21st SGEM International Multidisciplinary Scientific GeoConference Proceedings 2021, Informatics, Geoinformatics and Remote Sensing
Publisher
STEF92 Technology
Year
2021
Pages
401-410
SWS Citekey
Gordeev20219401409
ISSN
1314-2704
ISBN
978-619-7603-62-0
Language
en
Publication type
Conference Paper
Keywords
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