Reducing uncertainties and improving sand soil-water retention curve (SWRC) predictions for hazard screening analyses

Abstract

<jats:p> An energy-based laboratory-testing program was undertaken to investigate the effects of different testing methods, numerical model fits, and soil fabrics and densities on the soil-water retention curve (SWRC) using a poorly graded sand. Four different reconstitution energies and three saturation levels were used to generate different soil fabrics and structure within a narrow band of possible densities, as limited by the mechanical properties of the soil particles. Tests were performed using a “transient retention imbibition method” and a Fredlund device to develop a statistically representative laboratory SWRC. Testing results for the poorly graded sand indicate little aleatory variability in SWRC from the soil structure. The dominant source of data variability is a function of the epistemic uncertainty associated with the testing methods and fitting models but can be accounted for by a bounded mean SWRC. This bounding allows for the development of a laboratory “proxy” soil, representative of generalized sand SWRC behavior, for use as a hazard screening tool for modeling unsaturated sand behavior. The proxy soil SWRC is compared with other generalized SWRC models and independent SWRC field and laboratory tests, wherein the proxy soil SWRC yields significant increases in accuracy between the estimated and field SWRC behavior. </jats:p>

To fall or not to fall: the physics of sandcastles

“…( 7). The results were validated against bounded laboratory SWRC studies of the SP [6] and SM [40] materials, Table 1.…”

“…The SWRC method is the accepted standard for constrained soil testing in geotechnical engineering and was used to calculate parameters associated with pore fluid influence under confined conditions [6,[37][38][39] with no additional laboratory SWRC testing conducted for this analysis. For translation between saturated sigmoid model (Model B) and the SWRC, the phenomenological model-fitting parameters replaced the non-unique a, n, and m Fredlund and Xing SWRC curvefitting parameters [2-4, 6, 37-39], Eq.…”

“…where θ s is the saturated volumetric water content, θ is the volumetric water content, and is matric suction. The coefficient C( ) is a correction factor that forces the model to zero at a matric suction of 10 6 kPa and is defined as where is matric suction and r is the residual suction, assumed to be 3.0 MPa [6].…”

“…Analyzing the 487 data sets individually will yield a set of non-unique fitting parameters [6,43]. Physically, all ICP are interdependent, irrespective of test apparatus or protocol and therefore Γ , , and must yield a unique solution.…”

“…Conventional geotechnical theory holds that suction (interstitial fluid) and granular material parameters can be treated as independent, not intrinsically linked, state variables. Measurements have traditionally reflected particular conditions that are extrapolated to an idealized picture founded on continuum mechanics, with strength (resistance to additional load) and stability directly proportional [1] and fitting parameters for macroscopic characteristic properties that have little or no physical meaning [2][3][4][5][6][7]. In classical physics, granular media is not understood as a dynamic continuum of fluid saturation levels in a porous media [8][9][10], but rather as a bimodal system of saturated and unsaturated end members where the stable structure of the jammed state [11,12] is constrained in a phase space of energy (granular temperature), density, and load.…”