Metamodel-Based Slope Reliability Analysis—Case of Spatially Variable Soils Considering a Rotated Anisotropy

A rotation of the anisotropic soil fabric pattern is commonly observed in natural slopes with a tilted stratification. This study investigates the rotated anisotropy effects on slope reliability considering spatially varied soils. Karhunen–Loève expansion is used to generate the random fields of the soil shear strength properties (i.e., cohesion and friction angle). The presented probabilistic analyses are based on a meta-model combining Sparse Polynomial Chaos Expansion (SPCE) and Global Sensitivity Analysis (GSA). This method allows the number of involved random variables to be reduced and then the computational efficiency to be improved. Two kinds of deterministic models, namely a discretization kinematic approach and a finite element limit analysis, are considered. A variety of valuable results (i.e., failure probability, probability density function, statistical moments of model response, and sensitivity indices of input variables) can be effectively provided. Moreover, the influences of the rotated anisotropy, autocorrelation length, coefficient of variation and cross-correlation between the cohesion and friction angle on the probabilistic analysis results are discussed. The rotation of the anisotropic soil stratification has a significant effect on the slope stability, particularly for the cases with large values of autocorrelation length, coefficient of variation, and cross-correlation coefficient.

Effect of surface roughness topography on percolation characteristic of contact interface

The contact geometry of rough surfaces markedly affects the functional properties such as sealing and lubrication. The effect of surface roughness on the percolation characteristic of elastic contact was studied. The elastic contact of randomly rough surfaces with a glass plate was performed using four different surface roughnesses of silicone rubber blocks as specimens. The results illustrate that the percolation threshold was significantly affected by the valley morphology of a surface. The increase in depth and void volume of valleys improved the connectivity between valleys, but impeded the coalescence of contact clusters, resulting in the extinction of the spanning void cluster allowing fluid flow when the relative contact area was large. Furthermore, the critical pressure and connectivity at the percolation threshold were related to the maximum peak height and autocorrelation length of a surface, respectively.

Superclusters from velocity divergence fields

ABSTRACT Superclusters are a convenient way to partition and characterize the large-scale structure of the Universe. In this Letter, we explore the advantages of defining superclusters as watershed basins in the divergence velocity field. We apply this definition on diverse data sets generated from linear theory and N-body simulations, with different grid sizes, smoothing scales, and types of tracers. From this framework emerges a linear scaling relation between the average supercluster size and the autocorrelation length in the divergence field, a result that holds for one order of magnitude from 10 up to 100 Mpc h−1. These results suggest that the divergence-based definition provides a robust context to quantitatively compare results across different observational or computational frameworks. Through its connection with linear theory, it can also facilitate the exploration of how supercluster properties depend on cosmological parameters, paving the way to use superclusters as cosmological probes.

The influence of metagalactic ultraviolet background fluctuations on the high-redshift Lyα forest

ABSTRACT Under the assumption that galaxies and quasi-stellar objects (QSOs) dominate the metagalactic ultraviolet (UV) background, it is shown that at high redshifts, fluctuations in the UV background are dominated by QSO shot noise and have an autocorrelation length of a few to several comoving Mpcs, depending on the bright end of the QSO luminosity function. The correlations create long-range spatial coherence in the neutral hydrogen fraction. Using a semi-analytic model, it is demonstrated that the coherence may account for the broad distribution in effective optical depths measured in the Lyα forest spectra of background QSOs, for line-of-sight segments of comoving length $50\, h^{-1}$ Mpc at redshifts 5 < z < 6. Capturing the fluctuations in a numerical simulation requires a comoving box size of ∼1 Gpc, although a box half this size may be adequate if sufficient random realizations of the QSO population are performed.

Effect of the finite size of generated rough surfaces on the percolation threshold

Percolation threshold is a very important parameter to estimate the sealing performance. Thus, it is crucial to determine the correct value of the percolation threshold for contact sealing surfaces. In this paper, we applied a numerical generation method, in which the autocorrelation length can be easily controlled, to obtain different Gaussian isotropic rough surfaces. Then, the contact status between a rigid flat half-space and numerically generated rough surfaces were calculated using the conjugate gradient-fast Fourier transform method. Based on the contact status, the percolation threshold was obtained using a search method. The calculated results established that the percolation threshold of [Formula: see text] is determined for Gaussian isotropic contacting rough surfaces. To obtain an exact value of the percolation threshold, the finite size of the generated rough surfaces should be six times greater than the autocorrelation length, and the autocorrelation length should not be smaller than 20 times the sampling interval.

Tissue spatial correlation as cancer marker

We propose a new intrinsic cancer marker in fixed tissue biopsy slides, which is based on the local spatial autocorrelation length obtained from quantitative phase images. The spatial autocorrelation length in a small region of the tissue phase image is sensitive to the nanoscale cellular morphological alterations and can hence inform on carcinogenesis. Therefore, this metric can potentially be used as an intrinsic cancer marker in histopathology. Typically, these correlation length maps are calculated by computing 2D Fourier transforms over image sub-regions – requiring long computational times. In this paper, we propose a more time efficient method of computing the correlation map and demonstrate its value for diagnosis of benign and malignant breast tissues. Our methodology is based on highly sensitive quantitative phase imaging data obtained by spatial light interference microscopy (SLIM).

Development of a Size Effect Law for RC Structures

The work presented is a part of the french ANR (Agence Nationale pour la Recherche) project MACENA (Maitrise du Confinement en Accident), its main objective is to better present the role of concrete heterogeneities in RC structures in the cracking process. This paper aims to develop and use the size effect method (WL2) applicable to RC structures proposed by Sellier and Millard 2014 [1]. The originality of the method lies on introducing a weighting function defined in the direction of the maximum principal stress using a scale length. In this work, an inverse analysis of the method allows to identify this scale length using experimental test series of concrete specimens under tensile load and 3 point bending beams. The approach is then applied to predict the sensitivity of the mechanical behavior of a reinforced concrete tie under tensile load. The method is applied in the elastic phase and allows providing the structural tensile strength corresponding to the first crack which is affected by size effect and plays a key role because cracked and uncracked structures behave in severe environment in a very different way. In FE model, correlated random fields on the tensile strength of the concrete can be generated using the identified scale length to characterize the autocorrelation length.