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Research Article

The optimal combination form of vacuum pre-loading combined with electro-osmosis and with dynamic compaction method on the improvement of dredged slurry

, , , , , , & show all
Pages 1192-1204 | Received 27 May 2020, Accepted 27 Jul 2020, Published online: 23 Sep 2020
 

Abstract

Aiming at the problems of soil column forming near the plastic vertical drains and soil cracking during electro-osmosis stage in the treatment of dredged slurry by vacuum pre-loading combined with electro-osmosis method, this paper proposed a new method, i.e. vacuum pre-loading combined with electro-osmosis and with dynamic compaction method. Through the laboratory model tests in self-made glass bucket, the optimal combination form of vacuum pre-loading, electro-osmosis and dynamic compaction was obtained by studying the drainage of soil, soil surface settlement, current intensity and the reinforcement effect of dredged slurry under different combination forms. The test results show that under the condition that the total dynamic compaction energy is fixed, when dynamic compaction was combined both in the vacuum pre-loading stage and the electro-osmosis stage, which not only promoted the drainage of soil to the greatest extent; but also effectively enhanced the circuit current and slowed down the attenuation of the circuit current. Moreover, compared with other combination forms in this test, the energy consumption was reduced to the greatest extent. In addition, in this test, when dynamic compaction was combined both in the vacuum pre-loading stage and the electro-osmosis stage, the optimal reinforcement effect of dredged slurry was obtained.

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

This research was supported by the National Key R&D Program of China (2016YFC0800200), the National Natural Science Foundation Projects of China (Grant Nos. 51878402, 51678352, 51878512, 51778501 and 51778500), the National Nature Science Foundation Projects of Zhejiang Province (Grant No. LY17E080010), the Key Research and Development Program of Zhejiang Province (Grant No. 2018C03038), and the Programs of Science and Technology of Wenzhou (Grant Nos. S20160001 and S20170005), which collectively funded this project.

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