Diffuse instabilities with transition to localization in loose granular materials

This paper is concerned with diffuse and other ensuing failure modes in geomaterials when tested under homogeneous states of shearing in various loading programs and drainage conditions. Material instability is indeed the basic property that accounts for the instability of an initially homogeneous deformation field leading to diffuse failure and strain localization in geomaterials. The former is normally characterized by a runaway type of failure accompanied with a sudden and violent collapse of the material in the absence of any localization phenomena. Against this backdrop, we present a brief overview of material instability in elastoplastic solids where one finds a rich source of theoretical concepts including bifurcation, strain localization, diffuse failure and second‐order work, as well as a considerable body of experiments. Some compelling laboratory experimental studies of material instability with focus to diffuse failure are then presented and interpreted based on the second‐order work. Finally, various material instability analyses using an elastoplastic constitutive and a general finite element analysis of the above‐mentioned laboratory experimental tests are presented as a boundary value problem. It is shown that instability can be captured from otherwise uniform stress, density and hydraulic states, whereas uniform deviatoric loads are being applied on the external boundaries of a specimen. Although the numerical simulations reproduce well the laboratory experimental results, they also highlight the hierarchy of failure modes where localization phenomena emerge in the post‐bifurcation regime as a result of a degradation of homogeneity starting from a diffuse mode signalled by a zero second‐order work. Copyright © 2012 John Wiley & Sons, Ltd.     

Seasonal cycle of N2O vertical distribution and air-sea fluxes over the continental shelf waters off central Chile (∼36°S)

The continental shelf off central Chile is subject to strong seasonal coastal upwelling and has been recognized as an important outgassing area for, amongst others, N₂O, an important greenhouse gas. Several physical and biogeochemical variables, including N₂O, were measured in the water column from August 2002 to January 2007 at a time series station in order to characterize its temporal variability and elucidate the physical and biogeochemical mechanisms affecting N₂O levels. This 4-year time series of N₂O levels reveals seasonal variability associated basically with hydrographic and oceanographic regimes (i.e., upwelling and non-upwelling). However, a noteworthy temporal evolution of both the vertical distribution and N₂O levels was observed repeatedly throughout the entire study period, allowing us to distinguish three stages: winter/early spring (Stage I), mid-spring/mid-summer (Stage II), and late summer/early autumn (Stage III).Stage I presents low N₂O, the lowest surface saturation ever registered (from 64% saturation) in a period of high O₂, and a homogeneous column driven by strong wind; this distribution is explained by physical and thermodynamic mechanisms. Stage II, with increasing N₂O concentrations, agrees with the appearance of upwelling-favourable wind stress and a strong influence of oxygen-poor, nutrient-rich equatorial subsurface waters (ESSW). The N₂O build-up creates a “hotspot” (up to 2426% N₂O saturation) and enhanced concentrations of (up to 3.97 μM) and (up to 4.6 μM) at the oxycline (4-28 μM) (∼20-40 m depth). Although the dominant N₂O sources could not be determined, denitrification (mainly below the oxycline) appears to be the dominant process in N₂O accumulation. Stage III, with diminishing N₂O concentrations from mid-summer to early autumn, was accompanied by low N/P ratios. During this stage, strong bottom N₂O consumption (from 40% saturation) was suggested to be mainly driven by benthic denitrification.Consistent with the evolution of N₂O in the water column over time, the estimated air-sea N₂O fluxes were low or negative in winter (−9.8 to 20 μmol m⁻² d⁻¹, Stage I) and higher in spring and summer (up to 195 μmol m⁻² d⁻¹, Stage II), after which they declined (Stage III). In spite of the occurrence of ESSW and upwelling events throughout stages II and III, N₂O behaviour should be a response of the biogeochemical evolution associated with biological productivity and concomitant O₂ levels in the water and even in the sediments. The results presented herein confirm that the study area is an important source of N₂O to the atmosphere, with a mean annual N₂O flux of 30.2 μmol m⁻² d⁻¹; however, interannual variability could not yet be properly characterized.     

Acceleration strategies for elastic full waveform inversion workflows in 2D and 3D

Full waveform inversion (FWI) is one of the most challenging procedures to obtain quantitative information of the subsurface. For elastic inversions, when both compressional and shear velocities have to be inverted, the algorithmic issue becomes also a computational challenge due to the high cost related to modelling elastic rather than acoustic waves. This shortcoming has been moderately mitigated by using high-performance computing to accelerate 3D elastic FWI kernels. Nevertheless, there is room in the FWI workflows for obtaining large speedups at the cost of proper grid pre-processing and data decimation techniques. In the present work, we show how by making full use of frequency-adapted grids, composite shot lists and a novel dynamic offset control strategy, we can reduce by several orders of magnitude the compute time while improving the convergence of the method in the studied cases, regardless of the forward and adjoint compute kernels used.     

Estuarine flooding in urban areas: enhancing vulnerability assessment

The assessment of vulnerability provides valuable knowledge in the risk assessment steps of a risk governance process. Given the multiscale, multilevel, and multisectorial aspects of flood risk, the diversified entities that directly and indirectly intervene in risk management require specific outputs from the assessment studies. Urban areas in estuarine margins are particularly exposed and vulnerable to flooding. Such interface conditions are found in the Old City Centre of the Seixal, located in the Tagus estuary, Portugal. Here, two distinct methodologies were applied for the assessment of territorial vulnerability. A regional, lower-scale, methodology explores the application of the statistical procedure based on the SoVI^® at the statistical block level. A second, local and higher-scale, methodology is based in data collected through field matrices at the building and statistical sub-block level. Comparison of results revealed that the lower-scale assessment provides information on the vulnerability drivers at the regional and municipal level. Nevertheless, only at a higher-scale, it is possible to characterize and differentiate the smaller geographical units of analysis that compose the Old City Centre of Seixal. The lower-scale vulnerability assessment allows a strategic response, based on adaptation measures such as spatial planning, institutional capacity building and public awareness. The local level assessment provides more accurate knowledge to support local emergency planning and the allocation of operational and material resources at the urban level. Nevertheless, rather than antagonistic, both models can be considered as complementary, having in mind the requirements of an holistic flood risk governance model.

     

Minimum weighted norm wavefield reconstruction for AVA imaging

Seismic wavefield reconstruction is posed as an inversion problem where, from inadequate and incomplete data, we attempt to recover the data we would have acquired with a denser distribution of sources and receivers. A minimum weighted norm interpolation method is proposed to interpolate prestack volumes before wave-equation amplitude versus angle imaging. Synthetic and real data were used to investigate the effectiveness of our wavefield reconstruction scheme when preconditioning seismic data for wave-equation amplitude versus angle imaging.     

Non-minimum phase wavelet estimation by non-linear optimization of all-pass operators

Convolution of a minimum‐phase wavelet with an all‐pass wavelet provides a means of varying the phase of the minimum‐phase wavelet without affecting its amplitude spectrum. This observation leads to a parametrization of a mixed‐phase wavelet being obtained in terms of a minimum‐phase wavelet and an all‐pass operator. The Wiener–Levinson algorithm allows the minimum‐phase wavelet to be estimated from the data. It is known that the fourth‐order cumulant preserves the phase information of the wavelet, provided that the underlying reflectivity sequence is a non‐Gaussian, independent and identically distributed process. This property is used to estimate the all‐pass operator from the data that have been whitened by the deconvolution of the estimated minimum‐phase wavelet. Wavelet estimation based on a cumulant‐matching technique is dependent on the bandwidth‐to‐central‐frequency ratio of the data. For the cumulants to be sensitive to the phase signatures, it is imperative that the ratio of bandwidth to central frequency is at least greater than one, and preferably close to two. Pre‐whitening of the data with the estimated minimum‐phase wavelet helps to increase the bandwidth, resulting in a more favourable bandwidth‐to‐central‐frequency ratio. The proposed technique makes use of this property to estimate the all‐pass wavelet from the prewhitened data. The paper also compares the results obtained from both prewhitened and non‐whitened data. The results show that the use of prewhitened data leads to a significant improvement in the estimation of the mixed‐phase wavelet when the data are severely band‐limited. The proposed algorithm was further tested on real data, followed by a test involving the introduction of a 90°‐phase‐rotated wavelet and then recovery of the wavelet. The test was successful.     

Random noise attenuation via the randomized canonical polyadic decomposition

Tensor algebra provides a robust framework for multi-dimensional seismic data processing. A low-rank tensor can represent a noise-free seismic data volume. Additive random noise will increase the rank of the tensor. Hence, tensor rank-reduction techniques can be used to filter random noise. Our filtering method adopts the Candecomp/Parafac decomposition to approximates a N-dimensional seismic data volume via the superposition of rank-one tensors. Similar to the singular value decomposition for matrices, a low-rank Candecomp/Parafac decomposition can capture the signal and exclude random noise in situations where a low-rank tensor can represent the ideal noise-free seismic volume. The alternating least squares method is adopted to compute the Candecomp/Parafac decomposition with a provided target rank. This method involves solving a series of highly over-determined linear least-squares subproblems. To improve the efficiency of the alternating least squares algorithm, we uniformly randomly sample equations of the linear least-squares subproblems to reduce the size of the problem significantly. The computational overhead is further reduced by avoiding unfolding and folding large dense tensors. We investigate the applicability of the randomized Candecomp/Parafac decomposition for incoherent noise attenuation via experiments conducted on a synthetic dataset and field data seismic volumes. We also compare the proposed algorithm (randomized Candecomp/Parafac decomposition) against multi-dimensional singular spectrum analysis and classical prediction filtering. We conclude the proposed approach can achieve slightly better denoising performance in terms of signal-to-noise ratio enhancement than traditional methods, but with a less computational cost.     

Reweighting strategies in seismic deconvolution

Reweighting strategies have been widely used to diminish the influence of outliers in inverse problems. In a similar fashion, they can be used to design the regularization term that must be incorporated to solve an inverse problem successfully. Zero-order quadratic regularization, or damped least squares (pre-whitening) is a common procedure used to regularize the deconvolution problem. This procedure entails the definition of a constant damping term which is used to control the roughness of the deconvolved trace. In this paper I examine two different regularization criteria that lead to an algorithm where the damping term is adapted to successfully retrieve a broad-band reflectivity.
Synthetic and field data examples are used to illustrate the ability of the algorithm to deconvolve seismic traces.     

Ordinary kriging and indicator kriging in the cartography of trace elements contamination in São Domingos mining site (Alentejo, Portugal)

The abandoned pyrite mine of São Domingos, in the southeast Portugal is still an acid mine drainage generator and a source for trace elements pollution. This study aims to evaluate and map the soils and sediments chemical pollution. With this purpose three test sites located in the vicinities of the mine were sampled for soils, sediments and mining waste materials. The samples were analysed for pH, organic carbon, iron oxides and total content of As, Cu, Cr, Hg, Pb, Sb, U, Zn, Mn, S, Fe Al, Ca, K, Mg and P. The hyperspectral image of the test sites was acquired using the aero transported sensor HymapTM. Chemical analysis and hyperspectral images data were processed to estimate the contamination maps by multivariate data analysis, ordinary kriging, cokriging and indicator kriging methodologies.The test sites located downstream the mine open pit, are highly contaminated mainly in As, Hg, Pb and Sb, but no contamination was found in the third test site, upstream the mining site. The acid mining drainage seems to be the main spreading agent of chemical contaminants mostly originating from the mine waste materials. Factorial analysis and the geostatistical methodologies allowed several approaches for the contamination cartography of mining areas.     

Erratum to: Climate change projections over three metropolitan regions in Southeast Brazil using the non-hydrostatic Eta regional climate model at 5-km resolution

Theoretical and Applied Climatology -