Zenon Medina-Cetina

The Social Vulnerability Index (SVI) developed by the Centers for Disease Control and Prevention (CDC), has been widely used as a benchmark to measure the state of vulnerability of counties across the United States. The SVI is integrated using a simple aggregation methodology on a set of variables reflecting the region’s socioeconomic status, household characteristics, racial & ethnic minority status, and housing type/transportation. Due to its simple construction and inclusion of significant variables publicly available, the SVI has grown exponentially in popularity among organizations and government officials as a tool for decision-making, especially for resource allocation and for regional risk assessment. Furthermore, the COVID-19 pandemic brought a set of unprecedented challenges in the bi-national health between the United States and Mexico, particularly on the state of risk of supply chains. Since the North American Free Trade Agreement (NAFTA) became effective in 1994 and then renewed in 2020 as USMCA, Mexico has grown to be the biggest trading partner of the U.S., fast approaching a trade value of more than a trillion USD a year. For which conducting regional risk assessment following the SVI formulation can be a significant impact for multiple stakeholders and organizations. In this work, the formulation of the SVI is analyzed using a risk framework as a reference, to corroborate its applicability for decision-making, and to expand it to account for variables and processes impacting supply chains during the COVID-19 pandemic. This analysis shows that vulnerability is only one of three factors required to conduct risk assessment (i.e., hazards vulnerability, and consequences), needed to produce a baseline of reference to make informed decisions. A case study is also developed based on the use of the SVI during the COVID-19 pandemic for supply chains between the U.S. and Mexico, by introducing the formulation of a risk index that is compatible with the proposed risk framework. The first step to expand the SVI into a risk index for supply chains between U.S. and Mexico, was to reproduce the CDC methodology, followed by using an Empirical Cumulative Density Function (ECDF) aggregation methodology to justify it statistically, and then to illustrate its benefits and limitations when extended into a new risk index (accounting for the three required risk components). As a result, a bi-national risk index map is produced after harmonizing publicly available variables in the U.S. and Mexico, illustrating the potential to quantify the state of regional risk for supply chains and other path-dependent systems, and setting a reference to further improve it.

Current practice to model the occurrence of submarine landslides is based on methods that assess the potential of site-specific failures, all with the objective of providing elements to identify and quantify regional features associated to geohazards, before a project development takes place. Also, survey data to estimate parameters required to model submarine landslides show typically limited availability, mainly because of the cost associated to offshore surveying campaigns. In this paper, a probabilistic calibration approach is introduced using Bayesian statistical inference to maximize the use of available site investigation data, and to best estimate the occurrence of a marine landslide. For this purpose, a landslide model thought for its simplicity is used to illustrate the applicability and potential of the calibration methodology. The aim is to introduce a systematic approach to produce prior probability distributions of the model parameters, based on an actual integrated marine site investigation including geological, geophysical, and geomatics data, to then compare it with a posterior probability distribution of the same model parameters, but estimated after collecting in situ soil samples and testing them in the laboratory to produce the corresponding soil strength properties. This comparison allows to explore (a) the influence of the number of in situ samples, (b) the influence of a landslide factor of safety, and (c) the influence of the soil heterogeneity, into the likelihood of the occurrence of a marine landslide. The model parameters that are considered for calibration include the initial state of the submerged and saturated soil unit weight, the thickness of the soils’ unit layers, the pseudo-static seismic coefficient, and the slope angle, while the soil undrained shear strength is considered as the reference parameter to conduct the calibration (i.e., to compare model predictions vs. actual observations). Results show the potential of the proposed methodology to produce landslide geohazard maps, which are needed for the planning and design of marine infrastructure.

Masonry systems have been used extensively in historical, commercial, and residential buildings. A large number of experimental and computational studies have been conducted to investigate the behavior of masonry components and systems, including mortar, units (e.g., blocks), and walls. The Discrete Element Method (DEM) has been used to analyze masonry systems with a macro modeling methodology (i.e., structural systems like walls). Masonry systems and their components have not been analyzed using a micro-modeling methodology with the DEM. The objective of this paper is the deterministic calibration of micro-parameters of the mortar cylinder model based on a computationally efficient DEM model. To achieve this objective, a parametric analysis is introduced through a series of models of a mortar specimen tested under simple compression to explore the impact of the model micro-parameters when trying to reproduce a set of experimental observations conducted at the Universidad Autonoma de Yucatan Mexico (UADY). A calibration process based on optimization is implemented to determine the best estimates of the model’s micro-parameters. This paper is divided into three analyses. First, the particle size distribution of the mortar’s aggregate is used as a reference (i.e., scale 1), and then up-scaled 1.5 and two times using four particle sizes; second, using the two-times scaled particle size, the influence of varying particle sizes within a reference particle size distribution was explored (from one particle size to 4 particle sizes following the aggregate particle size distribution); and third, a parametric analysis is performed varying seven micro-parameters, one at the time, varying from 0.25 to 1.5, at 0.25 scale increments, on a model including four particle sizes. The results show micro-parameters and stress-strain curves of mortar for the different analyses, and a representation of the cross sections of the models, indicating the distributions of contact forces. All proposed models showed good agreement with the experimental observations (i.e., stress-strain curve). Also, it was observed from the proposed analyses that some micro-parameters vary as the particle size and the scaled particle size distributions change when using the same experimental stress-strain curve. Also, it was found that the proposed DEM must contain at least two particle sizes to significantly improve the particle interlocking to ensure that the mechanistic behavior reproduces the same experimental observations. Finally, from the results presented in this work, it is concluded that it is possible to produce a computationally efficient model that can later serve as a reference for future research accounting for other control variables such as particle shape, particle size distributions, the exploration of damage propagation effects, and most importantly their corresponding uncertainty quantification and propagation effects in masonry systems.

In recent years, an international consortium of research organizations conducted investigations at the Chicxulub Crater in Yucatan, Mexico, to better understand the crater’s formation mechanisms and the effects produced by the impact of the asteroid that is hypothesized to have caused one of the major life extinctions on Earth. This study aims to reproduce the asteroid’s impact mechanics by matching computer simulations obtained with the use of the distinct element method (DEM) against the latest topographic data observed across the crater footprint. A 2D model was formulated using ITASCA’s PFC2D software to reproduce the asteroid’s impact on Earth. The model ground conditions prior to impact were replicated based on available geological and geophysical field information. Also, the proposed DEM model configuration was designed to reproduce a far-field effect to ascertain the energy dissipation of the asteroid’s impact at the model’s boundaries. Impact conditions of the asteroid were defined based on previous asteroid impact investigations. A parametric analysis including the asteroid’s impact angle and the asteroid’s impact velocity was conducted to assess their influence on the crater formation process. Results of the simulations included the final crater topography and stratigraphy, stress profiles, contact force chains, and velocity fields. Numerical simulations showed that both the asteroid velocity and impact inclination play a major role in the crater formation process, and that the use of DEM provides interesting insights into impact crater formation.

This paper follows up on a series of reference papers that inspired MDPI’s Topic “Stochastic Geomechanics: From Experimentation to Forward Modeling”, where global and local deformation effects on sand specimens are fully described from high-resolution boundary displacement fields, as supported by a comprehensive experimental database (which includes varying degrees of specimen’s heterogeneity) that is available to the scientific community for further study. This paper presents an elasto-plastic comparative analysis of different finite element models reproducing different sand specimen heterogeneity configurations as follows: loose, dense, and half-dense half-loose specimens. The experimental conditions for these specimens’ heterogeneity configurations were simulated with an axisymmetric finite element model. To characterize the stress-strain response obtained from the experiments, an elasto-plastic constitutive model with strain-hardening and softening laws was adopted to reproduce the sand specimens’ mechanistic response. An expert-based calibration of the numerical models accounted for both global and local effects by making use of global observations captured by the triaxial point sensors (i.e., axial force and displacement) and by local observations captured by 3D digital image correlation analysis (i.e., 3D boundary displacement fields). Results show that predictions of the proposed numerical models are in good agreement with the experimental observations, both global and local responses. The combined use of global and local observations to calibrate sand triaxial specimens sets the basis for a more comprehensive parameterization process. For the first model set, three experiments were assumed with homogeneous materials. While both dense and loose models showed good agreement with the experiments, the displacement field prediction of the half-dense half-loose layered model identified limitations in reproducing heterogeneous configurations. Afterward, the second set compared and analyzed the half-dense half-loose layered models by implementing a heterogeneous model, showing significantly better model predictions (i.e., after the implementation of the heterogeneous model, which accounts for a transition zone between the upper and lower segments).

This paper follows up on a reference paper that inspired MDPI’s topic “Stochastic Geomechanics: From Experimentation to Forward Modeling”, in which the authors populated a spatio–temporal database of boundary displacement fields from a series of triaxial sand specimens using three-dimensional (3D) digital image correlation analysis. The database was curated and is currently available to the scientific community for further study. This paper uses a subset of this database, in which the experimental conditions were similar, to statistically investigate the dominant kinematic phenomena observed on the boundary of triaxial sand specimens under compression. The first-order 3D kinematic operators under the cylindrical coordinates, comprised of the divergence, curl, and gradient, were applied to the boundary displacement fields to illustrate the localization deformation patterns including the translational, rotational, shearing, and volumetric behaviors throughout the triaxial compression processes. Subsequently, the first-order statistics of the kinematic results are estimated, with the aim of revealing the evolution of associated localization effects as well as their corresponding uncertainties in space and time. The results of this research provide an innovative statistical interpretation of the localization effects on soil specimens under three-dimensional stress conditions. The proposed approach advances the interpretation of granular material’s responses under triaxial compression experimental conditions, while opening an opportunity to reproduce the material’s kinematic responses under the triaxial experimental conditions through constitutive modeling or machine learning techniques.

This paper follows up on a reference paper that inspired MDPI’s topic “Stochastic Geomechanics: From Experimentation to Forward Modeling”, in which global and local deformation effects on sand specimens were fully described from high-resolution boundary displacement fields. This paper is supported by that study’s experimental database, which is open to the scientific community for further study. This paper focuses on the analysis of this experimental study to investigate strain localization effects on a subset of tests included in this database. Strain localization is defined here as associated with the non-homogeneous deformation process occurring in elastoplastic materials, including sands. Many experimental and numerical studies have been conducted during the last two decades to explore the characteristics of localization effects on sand, and to determine how these contribute to the failure mechanisms of specific sands. Under a triaxial compression condition, localization effects have been studied mainly with regard to particle kinematics and translational strain of the specimen’s displacement fields. However, to the best of the authors’ knowledge, there has been no 3D experimental kinematic analysis performed on sands to study the localization phenomena that can directly relate the impact of a specimen’s initial and boundary conditions to a failure mechanism during a triaxial test. In this paper, we introduce a full set of 3D kinematic operators under cylindrical coordinates to assess the boundary localization effects of deforming sand specimens under triaxial loading conditions. Furthermore, a set of experiments were carried out under varying experimental conditions to study the impact of variability in these localization effects. Results show that patterns of kinematic effects are quantifiable and can be used to assess likely failure-influencing factors, such as confining pressure, initial density, sample geometry, and sample heterogeneity, in the development of specific failure mechanisms. Spatio-temporal interdependencies between localization effects, such as the interactions between shear, expansion, and compaction bands observed during the specimen’s shearing process, were also studied. We therefore hypothesize that the proposed framework will serve as the basis for quantifying the uncertainty associated with the development of localization effects over the boundary of sand-deforming specimens.

This paper follows up on a reference paper that inspired MDPI’s Topic “Stochastic Geomechanics: From Experimentation to Forward Modeling”, where global and local deformation effects on sand specimens are fully described from high resolution boundary displacement fields, and supported by its experimental database, which is open to the scientific community for further study. This paper introduces the use of spatio-temporal statistics from a subset of such an experimental database to characterize the specimens’ spatio-temporal displacement fields, populated by repeating a set of triaxial compression tests on drained, dry, vacuum-consolidated sand specimens, tested under similar experimentally controlled conditions. A three-dimensional digital image correlation (3D-DIC) technique was used to measure the specimens’ boundary displacement fields throughout the course of shearing under axial compression. Spatio-temporal first- and second-order statistics were computed for different data dimensionality conditions (0D, 0D-T, 1D-T, 3D-T) to identify and characterize the dominant failure mechanisms across different testing specimens. This allowed us to quantify localization phenomena’s spatio-temporal uncertainty. Results show that the uncertainty captured along the deformation process across different dimensionality conditions can be directly associated with different failure mechanisms, including localization patterns, such as the onset and evolution of shear, compression, and expansion bands. These spatio-temporal observations show the dependencies between locally distinctive displacement regions over a specimen’s surface, and across different times during a specimen’s shearing process. Results of this work provide boundary spatio-temporal statistics of experimental evidence in sands, which sets the basis for the development of research on the numerical simulation of sand’s constitutive behavior. Moreover, it allows to add a new understanding on the effect of uncertainty on the mechanistic interpretation of sands’ kinematic phenomena.

A comprehensive experimental database containing results of a series of dry vacuum-consolidated triaxial compression tests was populated. The tests were performed on sand specimens and conducted under similar experimental conditions, in which specimens’ boundary deformation was captured using a three-dimensional digital image correlation analysis (3D-DIC). The use of a standard triaxial device along with the 3D-DIC technology allowed the specimens’ global and local boundary displacement fields to be computed from start to end of the compression phase. By repeating each test under the same experimental conditions and building the specimens using the same type of sand, the boundary deformation patterns could be identified, and the statistics associated with both global and local displacement fields could be assessed. Making this experimental database available to others should serve to calibrate as well as develop new forward models to account for effects associated with the specimens’ local displacements and material heterogeneity and include statistics to represent a specimen’s random response. Moreover, this work will serve as a basis for the statistical characterization of spatio-temporal boundary localization effects used to develop stochastic models and machine-learning models, and simulate virtual triaxial tests.