DEM modeling of aging or creep in sand based on the effects of microfracturing of asperities and evolution of microstructural anisotropy during triaxial creep

Aging- or creep-related phenomena in sand have been widely studied, and the discrete element method (DEM) has been frequently used to model the associated soil behavior and then to explore the associated underlying mechanisms. However, several difficulties involved in modeling still remain unsolved. To resolve these difficulties, a new approach based on the effect of the microfracturing of asperities is proposed in this study for the DEM modeling of the sand aging or creep process through several aging cycles of associated reduction in the mobilized friction resistance at particle contacts and subsequent particle rearrangement to reach a new equilibrium state. This approach can be easily incorporated into different contact models and DEM simulations of the loading, unloading, and/or reloading processes, in either drained or undrained conditions, before and/or after aging. This new approach is proven effective because the DEM simulations incorporated with this new approach can satisfactorily reproduce the experimental observations in the triaxial creep process, drained and undrained recompression after aging, and 1D secondary compression and rebound. The simulation results also indicate that, based on the stress–force–fabric relationship, the contribution from the contact normal anisotropy to the deviatoric stress q gradually increases, whereas the contribution from the tangential force anisotropy becomes less during triaxial creep under a constant q. Moreover, the contacts between particles are gradually away from the state where the frictional resistance is fully mobilized, and then become more stable. During the subsequent triaxial recompression after creep, the aged samples exhibit enhanced soil stiffness, which is also found to be associated with the evolution of the invariants of the anisotropy tensors. It is worthwhile noting that the aging or creep effects on the microstructural changes, e.g., the invariants of the anisotropy tensors, can be gradually erased upon further recompression. This explains why the stress–strain responses of the aged samples during recompression gradually rejoin the original stress–strain response obtained from the sample without being subjected to aging or creep.     

Simulating train moving loads in physical model testing of railway infrastructure and its numerical calibration

Ballastless high-speed railways have dynamic performances that are quite different from those of conventional ballasted railways. The essential dynamic characteristics of high-speed railways due to passing train wheels, such as the cyclic effect, moving effect, and speed effect, were put forward and discussed. A full-scale accelerated railway testing platform for ballastless high-speed railways was proposed in this study. The feasibility of the sequential loading method in simulating train moving loads, and the boundary effect of the proposed physical model of ballastless railways, was investigated using three-dimensional finite element models. A full-scale physical model, 5 m long, 15 m wide, and 6 m high, was then established according to practical engineering design methods. Using a sequential loading system composed of eight high-performance hydraulic actuators, loads of a moving train with highest speed of 360 km/h were simulated. Preliminary experimental results of vibration velocities were presented and compared with field measurements of the Wuguang high-speed railway in China. Results showed that the experimental results coincided with the field measurements, demonstrating that the full-scale accelerated railway testing platform can simulate the process of a moving train and realistically reproduce the dynamic behaviors of ballastless high-speed railways.     

Monitoring and analysis of changes in a wetland landscape in Xingzi county

Wetlands play an important role in water conservation, environmental protection, and biodiversity conservation. Remote sensing is an economical and efficient technique for wetland monitoring which can limit disturbance in sensitive areas and support wetland conservation. In this paper, we used three phases of Thematic Mapper/Enhanced Thematic Mapper plus (TM/ETM+) remote sensing images from October 1989, October 1999, and October 2009 to study wetlands in Xingzi County. The images were segmented using the object-oriented remote sensing image interpretation software eCognition Developer 8.64, then segmented images were classified by slope, digital elevation model (DEM) data, Normalized Difference Vegetation Index (NDVI), Specific Leaf Area Vegetation Index (SLAVI), and Land and Water Masks (LWM) index to produce land type classification maps. Land use change information was obtained by analyzing the superposition of two classification maps of the wetland area from different years. The results showed that landscape patches in Xingzi County displayed fragmentation in their spatial distribution over time. Based on an index of changes in landscape patches, the fastest growing landscape type is grassland, while the fastest decreasing type is irrigated land. Dominant driving factors of changes in Xingzi County’s wetland landscape are population growth and policy changes.     

Reflectance spectroscopy and remote sensing data for finding sulfide-bearing alteration zones and mapping geology in Gilgit-Baltistan,Pakistan

Gilgit-Baltistan region is covering the northern most part of Pakistan where the rocks of the Kohistan-Ladakh island arc and Karakoram plate are exposed. The area has greater potential for precious and base metals deposits which are needed to be explored through spectroscopy and remote sensing techniques. Minerals and rocks can nowadays be identified through the measurement of their absorption and reflectance features by spectroscopic analysis. Spectral reflectance analysis is also very important in selecting the appropriate spectral bands for remote-sensing data analysis of unknown or inaccessible areas. In this study, reflectance spectra in the spectral range of 0.35–2.5 μm of different types of unaltered and altered rocks found in the Machulu and Astor areas of northern Pakistan were obtained using an ASD spectroradiometer. The fresh rock samples showed low spectral reflectance as compared to the altered rock samples. The minerals jarosite, goethite, and hematite showed depth of absorption minima in the range of 0.4–1.15 μm due to the presence of iron (Fe), while jarosite and limonite showed absorption depth at 2.2 μm due to the presence of hydroxyl ions (OH^¯). The clay minerals montmorillonite and illite showed absorption depth at 1.93 and 2.1 μm, respectively. Muscovite showed depth of absorption minima at 1.4 and 1.9 μm in some samples. Calcite showed deep absorption minima at 2.32 μm, while anorthite showed absorption features at 1.4, 1.9, 2.24, and 2.33 μm. Olivine showed a slight depressed absorption feature at 1.07 μm. The copper-bearing phases malachite, chrysocolla, and azurite showed, respectively, a broad absorption feature in the range of 0.6–0.9 μm, a small absorption at 1.4 μm, and a deep absorption at 1.93 μm. The unmineralized samples exhibited high reflectance in the wavelength ranges of 0.6–0.8, 1.6–1.9, 2.0–2.3, 2.1–2.25, and 2.4–2.5 μm, respectively, while the mineralized samples showed reflectance bands in the wavelength ranges of 0.4–0.6, 1.3–1.8, and 2.1–2.2 μm. On this basis, the band ratio combinations 7/5–4/3–6/3 and 7/5–6/3–4/3 of Landsat 8 and 4/7–4/3–2/1 for ASTER data were found to be very effective in the lithological differentiation of major rock units.     

A topical evaluation and discussion of data movement technologies for data-intensive scientific applications

Transferring large volumes of information from one location to potentially many others that are geographically distributed and across varying networks is still prevalent in modern scientific data systems. This is despite the movement to push computation to the data and to reduce data movement needed to compute answers to challenging scientific problems, to disseminate information to the scientific community, and to acquire data for curation and enrichment. Because of this, it is imperative that decisions made regarding data movement systems and architectures be backed by both analytical rigor, and also by empirical evidence and measurement. The purpose of this study is to expand on the work performed by our research team over the last decade and to take a fresh look at the evaluation of multiple topical data transfer technologies in use cases derived from data-intensive scientific systems and applications in the areas of Earth science. We report on the evaluation of a set of data movement technologies against a set of empirically derived comparison dimensions. Based on this evaluation, we make recommendations towards the selection of appropriate data movement technologies in scientific applications and scenarios.     

New variogram modeling method using MGGP and SVR

A critical step for kriging in geostatistics is estimation of the variogram. Traditional variogram modeling comprise of the experimental variogram calculation, appropriate variogram model selection and model parameter determination. Selecting of the variogram model and fitting of model parameters is the most controversial aspect of geostatistics. Shapes of valid variogram models are finite, and sometimes, the optimal shape of the model can not be fitted, leading to reduced estimation accuracy. In this paper, a new method is presented to automatically construct a model shape and fit model parameters to experimental variograms using Support Vector Regression (SVR) and Multi-Gene Genetic Programming (MGGP). The proposed method does not require the selection of a variogram model and can directly provide the model shape and parameters of the optimal variogram. The validity of the proposed method is demonstrated in a number of cases.