Analysis of the influence of tropical soil classification methods on railway subgrades according to repeated load triaxial (RLT) and light weight deflectometer (LWD) tests
Source abstract
Abstract
Recently, non-destructive in-situ tests have emerged that can predict the resilient modulus (MR) of materials that make up railway sidewalk layers in an agile and low-cost manner. These are in contrast to laboratory tests that require more infrastructure and are more time-consuming to perform. However, few studies have been directed to the resilient behavior compared to in-situ and laboratory tests for soils classified as tropical. This paper aims to determine the relationship between the estimated modulus of elasticity (ELWD) and the estimated resilient modulus (MR) from the repeated load triaxial test (RLT) for use in tropical soil railway subsoils. The samples of subgrade soils belong to a railway stretch in Brazil, present in the states of São Paulo-SP and Minas Gerais-MG, which has large circulation of minerals and commodities. The soils are classified as lateritic and non-lateritic according to the Brazilian Miniature, Compacted, Tropical (MCT) methodology, in addition to grain size, compaction, LWD and RLT tests. It is noted that the modulus of elasticity (ELWD) tends to decrease according to the increase in strain obtained in LWD. For soils classified as lateritic, as the soil moisture increases the ratio between the moduli obtained by RLT and LWD tend to increase. However, non-lateritic soils have the opposite performance, i.e., the ratio between the modulus of the tests decreases with increasing moisture. In this study, the LWD test is a possible viable alternative with good accuracy and effectiveness for geotechnical investigations in tropical soils.
Source: openalex_inverted_index · Quality: baseline
Research context
OpenAlex topics: Geotechnical and construction materials studies · Geotechnical Engineering and Soil Stabilization · Geotechnical Engineering and Soil Mechanics
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
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