Effective stress

About: Effective stress is a research topic. Over the lifetime, 3922 publications have been published within this topic receiving 97256 citations.

Driven piles in clay - the effects of installation and subsequent consolidation

Abstract: This paper describes the results of numerical analysis of the effects of installing a driven pile. The geometry of the problem has been simplified by the assumption of plane strain conditions in addition to axial symmetry. Pile installation has been modelled as the undrained expansion of a cylindrical cavity. The excess pore pressures generated in this process have subsequently been assumed to dissipate by means of outward radial flow of pore water. The consolidation of the soil has been studied using a work-hardening elasto–plastic soil model which has the unique feature of allowing the strength of the soil to change as the water content changes. Thus it is possible to calculate the new intrinsic soil strength at any stage during consolidation. In particular the long-term shaft capacity of a driven pile may be estimated from the final effective stress state and intrinsic strength of the soil adjacent to the pile. A parametric study has been made of the effect of the past consolidation history of the soil...

How Permeability Depends on Stress and Pore Pressure in Coalbeds: A New Model

Abstract: In naturally fractured formations, such as coal, permeability is sensitive to changes in stress or pore pressure (i.e., effective stress). This paper presents a new theoretical model for calculating pore volume compressibility and permeability in coals as a function of effective stress and matrix shrinkage, using a single equation. The equation is appropriate for uniaxial strain conditions, as expected in a reservoir. The model predicts how permeability changes as pressure is decreased (i.e., drawdown). Pore volume compressibility is derived in this theory from fundamental reservoir parameters. It is not constant, as often assumed. Pore volume compressibility is high in coals because porosity is so small. A rebound in permeability can occur at lower drawdown pressures for the highest modulus and matrix shrinkage values. We have also history matched rates from a {open_quotes}boomer{close_quotes} well in the fairway of the San Juan basin using various stress-dependent permeability functions. The best fit stress-permeability function is then compared with the new theory.

Frictional characteristics of granite under high confining pressure

Abstract: At high confining pressure the coefficient of friction, μ, for granite depends on the relative displacement of the surfaces. For ground surfaces, μ reaches a maximum after about 0.1 cm and then decreases to nearly a constant value after 0.5 cm of sliding has occurred. Features on the surfaces after sliding suggest that the maximum is reached when intimate contact is first established. Also, this maximum value is the same as the initial μ for perfectly mated rough surfaces. The decrease in μ from the maximum is probably caused by rolling on wear particles between the surfaces, μ decreases with an increase in normal stress, owing to a finite shear strength at zero pressure of interlocking irregularities on the surfaces. Water reduces the frictional shear strength of granite by about 400 bars, independent of the normal stress across the sliding surfaces. Brittle fracture of surface asperities may be the controlling mechanism during the frictional sliding of brittle materials such as granite. Up to the highest pressures investigated, sliding movement between the surfaces occurred with violent stick-slip. Stick-slip along a pre-existing fault may be a source of crustal earthquakes. The ‘brittle-ductile’ transition pressure in silicate rocks may simply be the pressure at which the frictional shear strength is equal to the fracture shear strength. In the Coulomb theory it is assumed that the strength of a rock is determined by μ and the cohesive strength. The theory does not hold for westerly granite. According to the effective stress theory, the stress required for one block of rock to slide on another in the presence of pore fluid of pressure p is given by τ = μ(σn - p). The theory holds for granite if μ is the coefficient of friction for sliding on water-saturated surfaces and if allowances are made for the fact that μ may be a function of the effective stress across the surfaces.

Diffusion Models for Hot Pressing with Surface Energy and Pressure Effects as Driving Forces

Abstract: Models for initial‐, intermediate‐, and final‐stage densification under pressure have been developed, which explicitly include both the surface energy and applied pressure as driving forces. For the initial stage, the time dependences and size effects given by the integrated equations are identical to those reported earlier for surface energy (alone) as the driving force. The only modification is that the surface energy (γ) is expanded into (γ+PaR/π), where Pa is the applied pressure and R is the particle radius. For the intermediate stage of the process, the Nabarro‐Herring and Coble creep models may be adapted to give approximate (∼4×) densification rates for lattice and boundary diffusion models, respectively. In these cases the complex driving force is written as: (Pa/D+γk), where D is the relative density, and k is the pore surface curvature. At the final stage of the process those models are invalid; an alternate model is developed based on diffusive transport between concentric spherical shells which will give a better assessment of the time dependence of densification high density (>95%); the driving force is (Pa/D+γk) in this case also. Because of the fact that the pore size is some unknown function of density, the rate equations cannot be integrated without further information. It is shown that of the various relations which have been assumed in development of models for hot pressing, for the effective stress in relationship to the applied stress and the porosity, (Pa/D) is the only form which satifies the criteria demanded by self‐consistency in generation of steady‐state diffusion models.