Secondary Compression Index Equation for Soft Clays

2017 ◽  
Author(s):  
Matchala Suneel ◽  
G. R. Konni ◽  
Im Jong Chul ◽  
Nguyen Tien Dung
Keyword(s):  
Compression Index ◽  
Soft Clays ◽  
Secondary Compression

Time-dependent behaviour of the Bearpaw Shale in oedometric loading and unloading

2012 ◽  
Vol 49 (4) ◽  
pp. 427-441 ◽  
Author(s):  
J. Suzanne Powell ◽  
W. Andy Take ◽  
Greg Siemens ◽  
V.H. Remenda
Keyword(s):  
Time Dependent ◽  
Exact Nature ◽  
Compression Index ◽  
Soft Clays ◽  
Consolidation Pressure ◽  
Secondary Compression ◽  
Clay Shales ◽  
Time Dependent Behaviour ◽  
The Many ◽  
Dependent Behaviour

Time-dependent behaviour can have a significant influence on the compressibility characteristics of soils. However, most of the research on this topic has investigated the behaviour of soft soils. In this paper, the time-dependent behaviour of a hard clay shale (Bearpaw Shale) is investigated using both one-dimensional multi-staged loading (MSL) oedometer and constant rate of strain (CRS) oedometer consolidation tests conducted on 25.0 and 16.9 mm diameter specimens. The results show that soft clays and hard clay shales that share the same Cαe/[Formula: see text] ratio (where Cαe is the secondary compression index and [Formula: see text] is the incremental compression index) will show the same approximately 7% change in pre-consolidation pressure for an increase of one log cycle of strain rate despite the many orders of magnitude difference in pre-consolidation pressure. In the case of the Bearpaw Shale, this 7% change in pre-consolidation pressure corresponds to approximately 700 kPa. The time-dependent behaviour of the Bearpaw Shale during unloading (Cαe/[Formula: see text], where [Formula: see text] is the incremental swelling index) was observed to follow a similar ratio to that observed in compression (Cαe/[Formula: see text]). While the exact nature of the compression and swelling events that have occurred over the life of the Bearpaw Formation is not clear, the influence of secondary compression cannot be ignored for interpretation of the geological history of this deposit.

Modelling unanticipated pore-water pressures in soft clays

1994 ◽  
Vol 31 (5) ◽  
pp. 773-778 ◽  
Author(s):  
Jianhua Yin ◽  
James Graham ◽  
Jack I. Clark ◽  
Longjun Gao
Keyword(s):  
Pore Water ◽  
Pore Water Pressure ◽  
Water Pressure ◽  
Creep Behaviour ◽  
Soft Clay ◽  
Field Observations ◽  
Soft Clays ◽  
Secondary Compression ◽  
Pore Water Pressures ◽  
Clay Layers

Field observations in thin soft clay layers may show pore-water pressures that increase for some time after the loading is applied. Reasons for these observations are not well understood. The paper shows how an elastic viscoplastic constitutive model incorporated into the consolidation equation can predict these pore-water pressure increases in soils that exhibit significant creep behaviour (or secondary compression). The phenomenon has been related to relaxation in regions of the profile from which drainage has not yet begun. Key words : clay, consolidation, creep, secondary compression, viscous, relaxation, pore-water pressure, elastic–plastic.

Compressibility and Consolidation of Soils

2015 ◽  
pp. 476-527
Keyword(s):  
Time Dependent ◽  
Square Root ◽  
Compression Index ◽  
Coefficient Of Consolidation ◽  
Secondary Compression ◽  
Volume Compressibility ◽  
Fitting Method ◽  
Preconsolidation Pressure ◽  
Elastic Settlement ◽  
Overconsolidated Soils

The total compression of soil under load is composed of three components (i.e. elastic settlement, primary consolidation settlement, and secondary compression). The consolidation component is time-dependent and its analysis is usually based on Terzaghi's theory. The chapter considers the consolidation characteristics of a soil and their experimental determination. The coefficient of consolidation can be determined by the Casagrande Logarithm-of-Time Fitting Method or the Taylor Square-Root of Time Method. The concepts of preconsolidation and overconsolidation are discussed while ways of determining the preconsolidation pressure, compression index, precompression index, and the coefficient of volume compressibility are explained. Ways to compute the settlement using coefficient of volume compressibility and e-logs methods for both normally consolidated and overconsolidated soils are provided. The chapter also explains Schmertmann (1955) graphical procedure for approximating the field compression index from the laboratory curve. It includes the derivation of Terzaghi's 1-D theory of consolidation and its solution using both analytical and graphical methods. Finally, the phenomenon and way of computing the secondary compression index are treated.

scholarly journals Method of removing secondary compression on clay using preloading

2018 ◽  
Vol 195 ◽  
pp. 03006
Author(s):  
Ega Dhianty ◽  
Indrasurya B. Mochtar
Keyword(s):  
Void Ratio ◽  
Soft Soil ◽  
Soil Improvement ◽  
Compression Index ◽  
Secondary Compression ◽  
Initial Void Ratio ◽  
Prefabricated Vertical Drain ◽  
Primary Consolidation ◽  
Short Time ◽  
External Loads

Due to external loads, the soft soil will undergo a large compression of both primary and secondary compression. With soil improvement using prefabricated vertical drain (PVD), the time of primary compression becomes shorter so that secondary compression occurs in short time. There has been little research on how to remove secondary compression. Therefore, further investigation of behaviour and method of removing secondary compression is necessary. This research was conducted based on an experimental study of clay consolidation test with a variation of loading time in the laboratory. The results show that there is an empirical correlation among the secondary compression index (Cα’), the initial void ratio (e0), the void ratio at the end of primary consolidation (ep), and the effective consolidation stress (P’). The correlations obtained from this study are Cα’ = (0.0072e0 - 0.0067)P’ and Cα’ = (0.0077ep - 0.006)P’. The greater the effective consolidation stress is, the greater the secondary compression index will become. Therefore, in soil improvement secondary compression can be removed by giving an extra load (Δq) that causes additional compression to the primary consolidation where the magnitude equals to the expected secondary compression. Then, this Δq could be removed at the end of the primary consolidation.

scholarly journals Geotechnical properties of a municipal water treatment sludge incorporating a coagulant

2008 ◽  
Vol 45 (5) ◽  
pp. 715-725 ◽  
Author(s):  
Brendan C. O’Kelly
Keyword(s):  
Shear Strength ◽  
Water Treatment ◽  
Water Content ◽  
Geotechnical Properties ◽  
Strength Parameter ◽  
Compression Index ◽  
Water Treatment Sludge ◽  
Secondary Compression ◽  
Municipal Water ◽  
Density Values

The geotechnical properties of a municipal water treatment sludge from an upland catchment are presented. The gelatinous sludge comprised flocs of mainly quartz, manganoan calcite, and clay-sized organic solids, and incorporated an alum coagulant and an anionic polyelectrolyte. Standard Proctor compaction yielded low bulk density values of 0.95–1.10 t/m3 and dry density values of 0.12–0.36 t/m3 (water content is 160%–780%) in line with the low specific gravity of solids value of 1.86. The undrained shear strength and the water content were inversely related on a semi-log plot. The effective stress shear strength parameter values were c' = 0 and ϕ' = 39°. The consolidation properties were studied using the oedometer, consolidometer, and triaxial apparatus. The material was highly compressible with primary compression index (Cc) values of 2.5–3.7, and primary compression ratio (C*c) values of 0.20–0.28. The majority of the strain response occurred due to primary consolidation although the material had a very low permeability (coefficient of permeability values decreasing from 2 × 10−9 to 5 × 10−11 m/s for an effective vertical stress of σ'v = 3–800 kPa). Secondary compression was minor, with a mean secondary compression index (Cαe) value of 0.15, and Cαe/Cc = 0.04–0.06.

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