At high Reynolds numbers the use of explicit in time compressible flow simulations with spectral/hp element discretization can become significantly limited by time step. To alleviate this limitation we extend the capability of the spectral/hp element open-source software framework, Nektar++, to include an implicit discontinuous Galerkin compressible flow solver. The integration in time is carried out by a singly diagonally implicit Runge-Kutta method. The non-linear system arising from the implicit time integration is iteratively solved by the Jacobian-free Newton Krylov (JFNK) method. A favorable feature of the JFNK approach is its extensive use of the explicit operators available from the previous explicit in time implementation. The functionalities of different building blocks of the implicit solver are analyzed from the point of view of software design and placed in appropriate hierarchical levels in the C++ libraries. In the detailed implementation, the contributions of different parts of the solver to computational cost, memory consumption and programming complexity are also analyzed. A combination of analytical and numerical methods is adopted to simplify the programming complexity in forming the preconditioning matrix. The solver is verified and tested using cases such as manufactured compressible tex, turbulent flow over a circular cylinder at Re = 3900 and shock wave boundary-layer interaction. The results show that the implicit solver can speed-up the simulations while maintaining good simulation accuracy.

Numerical simulations are employed to study hydrodynamic interactions between two-dimensional fish-like bodies under a traveling wavy lateral motion in high-density diamond-shaped fish schools. This study focuses on two different streamwise spacings, a dense school with 0.4 body length (BL) spacing and a sparse school with 2.0 BL spacing, respectively. An immersed-boundary-method-based incompressible Navier–Strokes flow solver is then employed to quantitatively simulate the resulting flow patterns and associated propulsive performance of the schools. The results suggest that a fish in the dense school achieves higher thrust production and higher propulsive efficiency than that in the sparse school due to a strong wall effect from neighboring fishes. In addition, results from changing the lateral spacing in the dense school have shown that the wall effect is enhanced as the lateral spacing decreases. Flow analyses have shown that the wake pattern of the fish swimming diagonally behind the leading fish in a dense diamond-shaped school transfers from 2S to 2P when the lateral spacing is smaller than 0.6 BL. As a result, an angled jet is produced behind the school and brings more momentum downstream. At the same time, the appearance of the trailing fish results in a stronger pressure region behind the leading fish and leads to a higher hydrodynamic performance of the leading fish in the dense school. The insights revealed from this study will contribute to understanding physical mechanisms in fish schools and providing a new swimming strategy for bio-inspired underwater swarm robots.

Hyperspectral image (HSI) provides both spatial structure and spectral information for classification, but many traditional methods simply concatenate spatial features and spectral features together that usually lead to the curse-of-dimensionality and unbalanced representation of different features. To address this issue, a new dimensionality reduction (DR) method, termed multi-feature manifold discriminant analysis (MFMDA), was proposed in this paper. At first, MFMDA explores local binary patterns (LBP) operator to extract textural features for encoding the spatial information in HSI. Then, under graph embedding framework, the intrinsic and penalty graphs of LBP and spectral features are constructed to explore the discriminant manifold structure in both spatial and spectral domains, respectively. After that, a new spatial-spectral DR model for multi-feature fusion is built to extract discriminant spatial-spectral combined features, and it not only preserves the similarity relationship between spectral features and LBP features but also possesses strong discriminating ability in the low-dimensional embedding space. Experiments on Indian Pines, Heihe and Pavia University (PaviaU) hyperspectral data sets demonstrate that the proposed MFMDA method performs significantly better than some state-of-the-art methods using only single feature or simply stacking spectral features and spatial features together, and the classification accuracies of it can reach 95.43%, 97.19% and 96.60%, respectively.

ABSTRACT:The problem of learning with both labeled and unlabeled examples arises frequently in Hyperspectral image (HSI) classification. While marginal Fisher analysis is a supervised method, which cannot be directly applied for Semi-supervised classification. In this paper, we proposed a novel method, called semi-supervised marginal Fisher analysis (SSMFA), to process HSI of natural scenes, which uses a combination of semi-supervised learning and manifold learning. In SSMFA, a new difference-based optimization objective function with unlabeled samples has been designed. SSMFA preserves the manifold structure of labeled and unlabeled samples in addition to separating labeled samples in different classes from each other. The semi-supervised method has an analytic form of the globally optimal solution, and it can be computed based on eigen decomposition. Classification experiments with a challenging HSI task demonstrate that this method outperforms current state-of-the-art HSI-classification methods.

Antarctica plays a central role in regulating global climatic and oceanographic patterns and is an integral part of global climate change discussions (Rogers et al., 2020). Warming and mass loss of outlet glaciers as described in the Sixth Assessment Report of the IPCC have been mainly observed in West Antarctica, whereas warming trends in East Antarctica have been seen as localized and inconsistent (Turner et al., 2009). Parts of East Antarctica are projected to experience greater-than-global warming in the 21st century (Meredith et al., 2019), especially in coastal areas due to relatively stronger Southern Ocean warming and effects of ozone recovery (Bracegirdle Abstract Against a changing climate, the development of evidence-based and progressive conservation policies depends on robust and quantitative baseline studies to resolve habitat natural variability and rate of change. Despite Antarctica's significant role in global climate regulation, climate trend estimates for continental Antarctica are ambiguous due to sparse long-term in situ records. Here, we present the longest, spatially explicit survey of Antarctic vegetation by harmonizing historic vegetation mapping with modern remote sensing techniques. In 1961, E. D. Rudolph established a permanent survey plot at Cape Hallett, one of the most botanically diverse areas along the Ross Sea coastline, harboring all known types of non-vascular Antarctic vegetation. Following a survey in 2004 using ground-based photography, we conducted the third survey of Rudolph's Plot in 2018 using near-ground remote sensing and methodologies closely mirroring the two historic surveys to identify long-term changes and trends. Our results revealed that the vegetation at Cape Hallett remained stable over the past six decades with no evidence of transformation related to a changing climate. Instead, the local vegetation shows strong seasonal phenology, distribution patterns that are driven by water availability, and steady perennial growth of moss. Given that East Antarctica is at the tipping point of drastic change in the near future, with biological change having been reported at certain locations, this record represents a unique and potentially the last opportunity to establish a meaningful biological sentinel that will allow us to track subtle yet impactful environmental change in terrestrial Antarctica in the 21st century. Plain Language SummaryIn early 2022, record-breaking high temperatures were recorded all over Antarctica, sparking concerns about the icy continent's future. Although the effects of climate change have been observed in West Antarctica, much less observation is available for East Antarctica, where almost 90% of the Antarctic ice mass is located. It is now, that East Antarctica is at a tipping point for change, and it is now, that we need to establish progressive conservation measures. What is at stake? The vegetation in East Antarctica is distinct. Any organism that managed to survive here has highly specialized traits, and we only find lichens, mosses, cy...