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  5. Determining the Macrostructural Stability of Compacted Wyoming Bentonites by a Disaggregation Method

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Article
en
2023

Determining the Macrostructural Stability of Compacted Wyoming Bentonites by a Disaggregation Method

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0 Files

en
2023
Vol 13 (20)
Vol. 13
DOI: 10.3390/app132011159

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Mark Tyrer
Mark Tyrer

Imperial College London

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José Manuel Moreno-Maroto
Óscar Merlo
Joel Torres-Serra
+3 more

Abstract

The use of compacted bentonites in radioactive waste repository barriers is a relevant application of geoenvironmental engineering. The on-site structural characteristics of the bentonites determine the performance and integrity of the barrier. The present work addresses the adaptation of the standardized sand equivalent shaking method for the controlled disaggregation of Wyoming bentonite specimens prepared at low, medium, and high compaction. The evolution of the macrostructural units’ size distribution was determined by sieving at different shaking times. The stability of the compacted material increases with dry density. However, if enough energy is applied in the disaggregation process, the size distribution of the macrostructural units after disaggregation has the same characteristics as that of the uncompacted starting material, regardless of the applied degree of compaction. Since the disaggregation rate is a function of the aggregation level (compaction), it follows that compaction energy is not only spent on reducing porosity but also on generating more stable macrostructural units. These findings pave the way for future research with different materials and test conditions (compaction, moisture, etc.). In addition, the proposed shaking method is adaptable and could also be used in other sectors, such as agriculture, to determine the structural stability of natural soils.

How to cite this publication

José Manuel Moreno-Maroto, Óscar Merlo, Joel Torres-Serra, Jacinto Alonso‐Azcárate, Mark Tyrer, Vicente Navarro (2023). Determining the Macrostructural Stability of Compacted Wyoming Bentonites by a Disaggregation Method. , 13(20), DOI: https://doi.org/10.3390/app132011159.

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Publication Details

Type

Article

Year

2023

Authors

6

Datasets

0

Total Files

0

Language

en

DOI

https://doi.org/10.3390/app132011159

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