MARATTO

article · AI in Civil Engineering

The effect of geotechnical soil properties on cbr value: review

Abstract

Abstract This review paper summarizes the current state of research on relationships between geotechnical soil’s properties and the California Bearing Ratio (CBR) value. Geotechnical elements are pivotal in preventing civil engineering projects from collapses and settlement failures, so understanding detailed soil properties is an important task. CBR tests are used to assess the stiffness modulus and shear strength and guide the overlaying layer’s thickness in pavement designs. Despite such tests’ high expense and complexity, researchers have explored correlations and machine learning for CBR prediction from soil properties. This paper would delve into the varying influence of such properties as compaction properties (OMC and MDD) and index properties (LL, PL, and PI). By measuring the relevance of these properties to CBR, this paper examines their significance and potential interactions. In sum, this review sheds light on soil properties’ multifaceted effects on CBR value and provides support for informed pavement engineering decisions.

Research topics

  • Landslides and related hazards
  • Geotechnical Engineering and Analysis
  • Rock Mechanics and Modeling

Read the original research

This page summarises published work. The authoritative version sits with the publisher.

DOI: 10.1007/s43503-024-00039-1

Is something wrong with this record? Report it or request removal.

Discussion

Discuss this research

Have you built on this work, tried to replicate it, or seen it applied in practice? Share what you know. Verified researchers and MARATTO™ domain experts can open a discussion, and any member can reply. Contributions are reviewed before they appear.

No discussion yet. Open the first thread.