Effects of grain morphology on critical state: a computational analysis

We introduce a new DEM scheme (LS-DEM) that takes advantage of level sets to enable the inclusion of real grain shapes into a classical discrete element method. Then, LS-DEM is validated and calibrated with respect to real experimental results. Finally, we exploit part of LS-DEM potentiality by using it to study the dependency of critical state (CS) parameters such as critical state line (CSL) slope \(\lambda \), CSL intercept \(\varGamma \), and CS friction angle \(\varPhi _{\mathrm{CS}}\) on the grain’s morphology, i.e., sphericity, roundness, and regularity. This study is carried out in three steps. First, LS-DEM is used to capture and simulate the shape of five different two-dimensional cross sections of real grains, which have been previously classified according to the aforementioned morphological features. Second, the same LS-DEM simulations are carried out for idealized/simplified grains, which are morphologically equivalent to their real counterparts. Third, the results of real and idealized grains are compared, so the effect of “imperfections” on real particles is isolated. Finally, trends for the CS parameters (CSP) dependency on sphericity, roundness, and regularity are obtained as well as analyzed. The main observations and remarks connecting particle’s morphology, particle’s idealization, and CSP are summarized in a table that is attempted to help in keeping a general picture of the analysis, results, and corresponding implications.     

Rice crop phenology mapping at high spatial and temporal resolution using downscaled MODIS time-series

Satellite data holds considerable potential as a source of information on rice crop growth which can be used to inform agronomy. However, given the typical field sizes in many rice-growing countries such as China, data from coarse spatial resolution satellite systems such as the Moderate Resolution Imaging Spectroradiometer (MODIS) are inadequate for resolving crop growth variability at the field scale. Nevertheless, systems such as MODIS do provide images with sufficient frequency to be able to capture the detail of rice crop growth trajectories throughout a growing season. In order to generate high spatial and temporal resolution data suitable for mapping rice crop phenology, this study fused MODIS data with lower frequency, higher spatial resolution Landsat data. An overall workflow was developed which began with image preprocessing, calculation of multi-temporal normalized difference vegetation index (NDVI) images, and spatiotemporal fusion of data from the two sensors. The Spatial and Temporal Adaptive Reflectance Fusion Model was used to effectively downscale the MODIS data to deliver a time-series of 30 m spatial resolution NDVI data at 8-day intervals throughout the rice-growing season. Zonal statistical analysis was used to extract NDVI time-series for individual fields and signal filtering was applied to the time-series to generate rice phenology curves. The downscaled MODIS NDVI products were able to characterize the development of paddy rice at fine spatial and temporal resolutions, across wide spatial extents over multiple growing seasons. These data permitted the extraction of key crop seasonality parameters that quantified inter-annual growth variability for a whole agricultural region and enabled mapping of the variability in crop performance between and within fields. Hence, this approach can provide rice crop growth data that is suitable for informing agronomic policy and practice across a wide range of scales.     

Mesoscale and microscale shock effects in the LL6 S4 chondrites Saint‐Séverin and Elbert: A tale of two breccias

Saint‐Séverin and Elbert, two LL6 chondrite breccias, were systematically studied to evaluate multiple deformation effects on spatial scales ranging from thin section (mesoscale) to micron‐submicron (microscale) using optical microscopy, electron backscatter diffraction (EBSD), and transmission electron microscopy (TEM). The different techniques provide consistent results but have complementary strengths, together providing a powerful approach to unravel even complex impact histories. Both meteorites have an S4 conventional shock stage, but interclast areas are more deformed, and clasts are more deformed in Elbert than in Saint‐Séverin. TEM and EBSD data provide compelling evidence that Saint‐Séverin experienced significant shock deformation while already hot, and cooled rapidly afterward, as a result of a major, possibly disruptive impact on the LL chondrite parent body ~4.4 Ga ago. In contrast, Elbert was shocked from a cold initial state but was heated significantly during shock, and cooled in a localized hot impact deposit on the LL asteroid. Both meteorites probably were shocked at least twice; data for Saint‐Séverin are best reconciled with a three‐impact model.     

Long‐term temporal and spatial patterns in bioeroding sponge distribution at the Abrolhos Bank,Brazil, Southwestern Atlantic

Bioeroding sponges belong to the most dominant bioeroders, significantly contributing to the erosion of coral reefs. Some species are tolerant or even benefit from environmental conditions such as ocean warming, acidification, and eutrophication. In consequence, increases in sponge bioerosion have been observed on some coral reefs over the last decades. The Abrolhos Bank is the largest coral reef system in the South Atlantic. It has been affected by sedimentation, eutrophication, overfishing, and climate change, mainly affecting coastal reefs, and at lesser intensity outer ones as well. This study aimed to describe spatial and temporal patterns in bioeroding sponge distribution in carbonate substrates in the Abrolhos Bank. Photo‐quadrats were used to compare bioeroding sponge abundance between two shallow reefs: a coastal, Pedra de Leste (PL), and an outer reef, Parcel dos Abrolhos (PAB). Each individual was delimitated over the substrate by determining the sponge surface through a line connecting the outermost papillae. The study was conducted over 6 years in 2008–2009 and 2013–2016. Four species of bioeroding sponges were identified: Cliona carteri Ridley, 1881, C. delitrix Pang, 1973, C. cf. schmidtii Ridley, 1881, and Siphonodictyon coralliphagum Rützler, 1971. The distribution and abundance of species varied between the inner and outer reefs and across the years, and displayed certain selectivity for the calcareous substrates recorded. Crustose coralline algae (CCA) were the main substrate excavated by the most abundant bioeroding species, C. carteri, and represented 70% of the substrate types occupied by this sponge (CCA, coral overgrown by CCA and plain coral). The highest abundance of bioeroding sponges observed in photo‐quadrats was 21.3 individuals/m² at the outer reefs (PAB) in 2014. The abundances or areal extents of bioeroding sponges were up to 10 times greater on the outer reefs than on the coastal ones, where sedimentation is higher and more strongly influenced by siliciclastic material. Moreover, a higher herbivorous fish biomass has been reported on outer reefs which could also influence the higher abundance of bioeroding sponges in outer reefs. During the study period of 6 years, an increase in bioeroding sponge abundance was observed at the outer reefs (PAB), with the sea surface temperature increase. As CCA have an important role in reefal cementation and carbonate production in the Abrolhos reefs, a bioerosion impact might be expected, in particular, on the outer reefs.     

Evaluation of Inference Adequacy in Cumulative Logistic Regression Models: An Empirical Validation of ISWRidge Relationships

Internal solitary wave propagation over a submarine ridge results in energy dissipation, in which the hydrodynamic interaction between a wave and ridge affects marine environment. This study analyzes the effects of ridge height and potential energy during wave-ridge interaction with a binary and cumulative logistic regression model. In testing the Global Null Hypothesis, all values are p 〈0.001, with three statistical methods, such as Likelihood Ratio, Score, and Wald. While comparing with two kinds of models, tests values obtained by cumulative logistic regression models are better than those by binary logistic regression models. Although this study employed cumulative logistic regression model, three probability functions p^1, p^2 and p^3, are utilized for investigating the weighted influence of factors on wave reflection. Deviance and Pearson tests are applied to cheek the goodness-of-fit of the proposed model. The analytical results demonstrated that both ridge height （X1 ） and potential energy （X2 ） significantly impact （p 〈 0. 0001 ） the amplitude-based refleeted rate; the P-values for the deviance and Pearson are all 〉 0.05 （0.2839, 0.3438, respectively）. That is, the goodness-of-fit between ridge height （ X1 ） and potential energy （X2） can further predict parameters under the scenario of the best parsimonious model. Investigation of 6 predictive powers （ R2, Max-rescaled R^2, Sorners＇ D, Gamma, Tau-a, and c, respectively） indicate that these predictive estimates of the proposed model have better predictive ability than ridge height alone, and are very similar to the interaction of ridge height and potential energy. It can be concluded that the goodness-of-fit and prediction ability of the cumulative logistic regression model are better than that of the binary logistic regression model.     

Evaluation of Inference Adequacy in Cumulative Logistic Regression Models： An Empirical Validation of ISW-Ridge Relationships

Internal solitary wave propagation over a submarine ridge results in energy dissipation, in which the hydrodynamic interaction between a wave and ridge affects marine environment. This study analyzes the effects of ridge height and potential energy during wave-ridge interaction with a binary and cumulative logistic regression model. In testing the Global Null Hypothesis, all values are p<0.001, with three statistical methods, such as Likelihood Ratio, Score, and Wald. While comparing with two kinds of models, tests values obtained by cumulative logistic regression models are better than those by binary logistic regression models. Although this study employed cumulative logistic regression model, three probability functions p^1, p^2 and p^3, are utilized for investigating the weighted influence of factors on wave reflection. Deviance and Pearson tests are applied to check the goodness-of-fit of the proposed model. The analytical results demonstrated that both ridge height (X1) and potential energy (X2) significantly impact (p<0.0001) the amplitude-based reflected rate; the P-values for the deviance and Pearson are all >0.05 (0.2839, 0.3438, respectively). That is, the goodness-of-fit between ridge height (X1) and potential energy (X2) can further predict parameters under the scenario of the best parsimonious model.Investigation of 6 predictive powers (R2, Max-rescaled R2, Somers'D, Gamma, Tau-a, and c, respectively) indicate that these predictive estimates of the proposed model have better predictive ability than ridge height alone, and are very similar to the interaction of ridge height and potential energy. It can be concluded that the goodness-of-fit and prediction ability of the cumulative logistic regression model are better than that of the binary logistic regression model.     

Combining pixel and object based image analysis of ultra-high resolution multibeam bathymetry and backscatter for habitat mapping in shallow marine waters

Habitat mapping data are increasingly being recognised for their importance in underpinning marine spatial planning. The ability to collect ultra-high resolution (cm) multibeam echosounder (MBES) data in shallow waters has facilitated understanding of the fine-scale distribution of benthic habitats in these areas that are often prone to human disturbance. Developing quantitative and objective approaches to integrate MBES data with ground observations for predictive modelling is essential for ensuring repeatability and providing confidence measures for habitat mapping products. Whilst supervised classification approaches are becoming more common, users are often faced with a decision whether to implement a pixel based (PB) or an object based (OB) image analysis approach, with often limited understanding of the potential influence of that decision on final map products and relative importance of data inputs to patterns observed. In this study, we apply an ensemble learning approach capable of integrating PB and OB Image Analysis from ultra-high resolution MBES bathymetry and backscatter data for mapping benthic habitats in Refuge Cove, a temperate coastal embayment in south-east Australia. We demonstrate the relative importance of PB and OB seafloor derivatives for the five broad benthic habitats that dominate the site. We found that OB and PB approaches performed well with differences in classification accuracy but not discernible statistically. However, a model incorporating elements of both approaches proved to be significantly more accurate than OB or PB methods alone and demonstrate the benefits of using MBES bathymetry and backscatter combined for class discrimination.     

Experimental impact cratering: A summary of the major results of the MEMIN research unit

This paper reviews major findings of the Multidisciplinary Experimental and Modeling Impact Crater Research Network (MEMIN). MEMIN is a consortium, funded from 2009 till 2017 by the German Research Foundation, and is aimed at investigating impact cratering processes by experimental and modeling approaches. The vision of this network has been to comprehensively quantify impact processes by conducting a strictly controlled experimental campaign at the laboratory scale, together with a multidisciplinary analytical approach. Central to MEMIN has been the use of powerful two-stage light-gas accelerators capable of producing impact craters in the decimeter size range in solid rocks that allowed detailed spatial analyses of petrophysical, structural, and geochemical changes in target rocks and ejecta. In addition, explosive setups, membrane-driven diamond anvil cells, as well as laser irradiation and split Hopkinson pressure bar technologies have been used to study the response of minerals and rocks to shock and dynamic loading as well as high-temperature conditions. We used Seeberger sandstone, Taunus quartzite, Carrara marble, and Weibern tuff as major target rock types. In concert with the experiments we conducted mesoscale numerical simulations of shock wave propagation in heterogeneous rocks resolving the complex response of grains and pores to compressive, shear, and tensile loading and macroscale modeling of crater formation and fracturing. Major results comprise (1) projectile–target interaction, (2) various aspects of shock metamorphism with special focus on low shock pressures and effects of target porosity and water saturation, (3) crater morphologies and cratering efficiencies in various nonporous and porous lithologies, (4) in situ target damage, (5) ejecta dynamics, and (6) geophysical survey of experimental craters.     

Hydraulic roughness over simple subaqueous dunes

Detailed studies of flow over subaqueous dunes in laboratory flumes were used to suggest a virtual near-bed layer of twice the dune height in which the mean velocity is accelerated towards the crest by contraction. The mean flow velocity in this layer above the crest, transformed into friction velocity by means of the surface skin roughness, is shown to give values consistent with measured values. The resulting dimensionless shear stress due to skin friction is depth-independent, in contrast to that derived by means of often cited traditional methods. As a result of the relationship between dune height and the thickness of the near-bed layer, an expression for the expansion loss behind dunes was formulated and used to relate form resistance directly to dune height.