Predicting the compaction parameters of solidified dredged fine sediments with statistical approach - Archive ouverte HAL Accéder directement au contenu
Article Dans Une Revue Marine Georesources and Geotechnology Année : 2023

Predicting the compaction parameters of solidified dredged fine sediments with statistical approach

Résumé

The compaction behavior of solidified dredged fine sediments is an important parameter for recycling dredged fine sediments in road engineering. However, the Proctor compaction test is time-consuming, which could cause project delays. Thus, this study is aiming to develop simple models in order to correlate the compaction performance (Maximum Dry Density (MDD) and Optimum Moisture Content (OMC)) of solidified dredged fine sediments with the basic physical parameters of raw sediments and the types and quantities of binder. To create the models, a database of 94 measurements was established firstly from different literature studies. Then, a statistical approach was used to evaluate the effects of input parameters on the compaction parameters of solidified dredged sediments. In the third stage, four models were proposed as the optimum models to predict the MDD and the OMC of solidified dredged fine sediments. Further, the variance analysis (ANOVA test) and residual analysis proved that all the chosen four models meet the statistical requirements. In the end, the proposed four models were further validated using new experimental data, indicating that the proposed four models could be used to reasonably predict the compaction parameters of solidified dredged sediments with acceptable accuracy.
Fichier non déposé

Dates et versions

hal-04095787 , version 1 (12-05-2023)

Identifiants

Citer

Hongwei Wang, Rachid Zentar, Dongxing Wang. Predicting the compaction parameters of solidified dredged fine sediments with statistical approach. Marine Georesources and Geotechnology, 2023, 41 (2), pp.195-210. ⟨10.1080/1064119X.2021.2023827⟩. ⟨hal-04095787⟩
11 Consultations
0 Téléchargements

Altmetric

Partager

Gmail Facebook X LinkedIn More