Modelling of ground improvement by vertical drains in highly variable soils
The research presented in this thesis focuses on the probabilistic modelling of soil consolidation via prefabricated vertical drains (PVDs) considering soil spatial variability. Soils are highly variable from one point to another in the ground and yet this is often coupled with inadequate site data,...
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| Format: | Thesis |
| Language: | English |
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Curtin University
2012
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| Online Access: | http://hdl.handle.net/20.500.11937/2593 |
| _version_ | 1848743996756590592 |
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| author | Bari, Md. Wasiul |
| author_facet | Bari, Md. Wasiul |
| author_sort | Bari, Md. Wasiul |
| building | Curtin Institutional Repository |
| collection | Online Access |
| description | The research presented in this thesis focuses on the probabilistic modelling of soil consolidation via prefabricated vertical drains (PVDs) considering soil spatial variability. Soils are highly variable from one point to another in the ground and yet this is often coupled with inadequate site data, probabilistic analysis is a more rational approach to assess the behaviour of soil consolidation by PVDs. Although the fact that spatial variation of soil properties can affect soil consolidation has long been realized, the design of soil consolidation via PVDs has been traditionally carried out deterministically and thus can be misleading due to the ignorance of the uncertainty associated with the inherent spatial variation of soil properties. One of the major advantages of probabilistic modelling over deterministic approach is that it can explicitly incorporate soil spatial variability in the analysis and design of a geotechnical problem and subsequently provides much physical insight into the impact of soil spatial variability on the behaviour of the problem under consideration.However, owing to the complexity of the stochastic problem, available research into consolidation of highly variable soils has been limited. The review of relevant literature has indicated that soil spatial variability in relation to ground improvement by PVDs has never been previously considered in a systematic, scientific manner in design and little research has been done in this area. Therefore, to obtain a more realistic measure of the degree of consolidation at any specified time, the effect of soil spatial variability needs to be taken into account by employing probabilistic modelling approach.Among several available methods of stochastic modelling, the random finite element method (RFEM) using random variable soil input properties in a Monte Carlo framework has gained much popularity in recent years. The same approach is adopted in the present research for modelling soil spatial variability in soil consolidation by PVDs. The soil permeability, k, and volume compressibility, mv, are considered as random variables and the variability of both k and mv is characterised statistically in terms of the mean, standard deviation, lognormal probability distribution and scale of fluctuation (SOF).The random fields of k and mv are generated using 2D local average subdivision (LAS) method developed by Fenton and Vanmarcke (1990). The generated random fields are then used as inputs in a stochastic finite element modelling of soil consolidation by PVDs. In this research, all numerical analyses are carried out using the 2D finite element computer program AFENA (Carter and Balaam 1995), in which the consolidation process of soil is treated as a coupled transient problem governed by the Biot’s consolidation theory (Biot 1941). |
| first_indexed | 2025-11-14T05:54:27Z |
| format | Thesis |
| id | curtin-20.500.11937-2593 |
| institution | Curtin University Malaysia |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-14T05:54:27Z |
| publishDate | 2012 |
| publisher | Curtin University |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | curtin-20.500.11937-25932017-02-20T06:38:21Z Modelling of ground improvement by vertical drains in highly variable soils Bari, Md. Wasiul volume compressibility Vertical drains reliability-based semi-analytical model (RBSA) ramdon finite element method (RFEM) highly variable soils stochastic consolidation analyses soil permeability The research presented in this thesis focuses on the probabilistic modelling of soil consolidation via prefabricated vertical drains (PVDs) considering soil spatial variability. Soils are highly variable from one point to another in the ground and yet this is often coupled with inadequate site data, probabilistic analysis is a more rational approach to assess the behaviour of soil consolidation by PVDs. Although the fact that spatial variation of soil properties can affect soil consolidation has long been realized, the design of soil consolidation via PVDs has been traditionally carried out deterministically and thus can be misleading due to the ignorance of the uncertainty associated with the inherent spatial variation of soil properties. One of the major advantages of probabilistic modelling over deterministic approach is that it can explicitly incorporate soil spatial variability in the analysis and design of a geotechnical problem and subsequently provides much physical insight into the impact of soil spatial variability on the behaviour of the problem under consideration.However, owing to the complexity of the stochastic problem, available research into consolidation of highly variable soils has been limited. The review of relevant literature has indicated that soil spatial variability in relation to ground improvement by PVDs has never been previously considered in a systematic, scientific manner in design and little research has been done in this area. Therefore, to obtain a more realistic measure of the degree of consolidation at any specified time, the effect of soil spatial variability needs to be taken into account by employing probabilistic modelling approach.Among several available methods of stochastic modelling, the random finite element method (RFEM) using random variable soil input properties in a Monte Carlo framework has gained much popularity in recent years. The same approach is adopted in the present research for modelling soil spatial variability in soil consolidation by PVDs. The soil permeability, k, and volume compressibility, mv, are considered as random variables and the variability of both k and mv is characterised statistically in terms of the mean, standard deviation, lognormal probability distribution and scale of fluctuation (SOF).The random fields of k and mv are generated using 2D local average subdivision (LAS) method developed by Fenton and Vanmarcke (1990). The generated random fields are then used as inputs in a stochastic finite element modelling of soil consolidation by PVDs. In this research, all numerical analyses are carried out using the 2D finite element computer program AFENA (Carter and Balaam 1995), in which the consolidation process of soil is treated as a coupled transient problem governed by the Biot’s consolidation theory (Biot 1941). 2012 Thesis http://hdl.handle.net/20.500.11937/2593 en Curtin University fulltext |
| spellingShingle | volume compressibility Vertical drains reliability-based semi-analytical model (RBSA) ramdon finite element method (RFEM) highly variable soils stochastic consolidation analyses soil permeability Bari, Md. Wasiul Modelling of ground improvement by vertical drains in highly variable soils |
| title | Modelling of ground improvement by vertical drains in highly variable soils |
| title_full | Modelling of ground improvement by vertical drains in highly variable soils |
| title_fullStr | Modelling of ground improvement by vertical drains in highly variable soils |
| title_full_unstemmed | Modelling of ground improvement by vertical drains in highly variable soils |
| title_short | Modelling of ground improvement by vertical drains in highly variable soils |
| title_sort | modelling of ground improvement by vertical drains in highly variable soils |
| topic | volume compressibility Vertical drains reliability-based semi-analytical model (RBSA) ramdon finite element method (RFEM) highly variable soils stochastic consolidation analyses soil permeability |
| url | http://hdl.handle.net/20.500.11937/2593 |