| Issue |
E3S Web Conf.
Volume 730, 2026
International Conference on Advances and Innovations in Soft Soil Engineering (Soft Soils 2026)
|
|
|---|---|---|
| Article Number | 05010 | |
| Number of page(s) | 6 | |
| Section | Infrastructure Performance and Monitoring | |
| DOI | https://doi.org/10.1051/e3sconf/202673005010 | |
| Published online | 03 August 2026 | |
Preloading effect on highly organic soft soil
Department of Civil Engineering, College of Science & Technology, Nihon University, Tokyo, Japan
* Corresponding author: This email address is being protected from spambots. You need JavaScript enabled to view it.
Abstract
The preloading method is a technique used to reduce residual settlement in soft clay soils. It is particularly effective in highly organic soils and has been widely used in the design and construction of embankment works. However, when highly organic soft ground that had been improved using the preloading method was subjected to preloading and subsequent unloading in order to artificially induce an overconsolidated state, long-term secondary consolidation settlement occurred. This settlement damaged both above- and below-ground structures, becoming a significant construction issue. Laboratory experiments revealed that, unless the overconsolidation ratio — defined as the ratio of the consolidation pressure before to after preload removal — is set correctly, soil expansion during preload removal will subsequently result in resettlement. Consequently, when using the preloading method to improve highly organic soft ground, setting the overconsolidation ratio correctly is critical. This paper presents model experiments that simulate the preloading method implemented in the laboratory on several types of highly organic soils and silts sampled in Japan. The optimal overconsolidation ratio for reducing resettlement was determined for each soil type. Subsequently, a prediction method based on soil properties was employed and compared with field-measured data. The results showed a strong correlation between the predictions and the measured values.
© The Authors, published by EDP Sciences, 2026
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.

