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Polyaniline (PANI) has long been explored as a promising organic cathode for Li-ion batteries. However, its poor electrochemical utilization and cycling instability cast doubt on its potential for practical applications. In this work, we revisit the electrochemical performance of PANI in nonaqueous electrolytes, and reveal an unprecedented reversible capacity of 197.2 mAh g−1 (244.8 F g−1) when cycled in a wide potential range of 1.5 to 4.4 V vs. Li+/Li. This ultra-high capacity derives from 70% -NH- transformed to =NH+- during deep charging/discharging process. This material also demonstrates a high average coulombic efficiency of 98%, an excellent rate performance with 73.5 mAh g−1 at 1800 mA g−1, and retains 76% of initial value after 100 cycles, which are among the best reported values for PANI electrodes in battery applications. [ABSTRACT FROM AUTHOR]

Downstream hydraulic geometry (DHG) for multiple discharge frequencies remains poorly investigated. This paper seeks to clarify the DHG relations of different discharge frequencies and proposes the definition, mathematical expression, and geomorphological interpretation of multifrequency DHG (MFDHG). It also verifies the existence of DHG and MFDHG in the six major exoreic rivers located in the Qinghai–Tibet Plateau. MFDHG can be depicted with (1) log-linear plots between DHG coefficients and exponents for multiple discharge frequencies and (2) independent DHG curves intersecting near congruent discharge, width, depth, or velocity. The results show that rivers in the study area exhibit strong DHG relations. The variations in the DHG coefficients and exponents usually exhibit opposite trends with increasing discharge frequency. The MFDHG of a river reach is generally stronger than that of a river basin. Congruent hydraulics, as indices of geometric variability and hydraulic self-similarity, reflect consistent changes in hydraulic variables downstream. MFDHG is a novel geomorphic phenomenon that bridges spatiotemporal dimensions in HG systems and provides a basis for establishing an overall HG relationship. [ABSTRACT FROM AUTHOR]

The extraction of high-resolution geomorphic information from remote sensing images is a key technology for supporting mountain river research. Extracting small rivers (width < 90 m) from complex backgrounds based on satellite images remains a challenging issue. In this research, we propose an improved random forest (RF) algorithm, RF-ANN (artificial neural network), by using neural networks and thermal infrared data for the extraction of river surfaces. We also develop an automated river width extraction (ARWE) method based on the central axis transformation algorithm and centerline automatic correction algorithm for the automatic extraction of the river widths across the whole basin. We chose the Huangfuchuan River Basin on the Loess Plateau, China, as a case study area. Chinese GF-1 and ZY-3 satellite images were implemented as the primary data source. We extracted the bankfull river surface and river widths of the Huangfuchuan River by using these two improved methods. The results show that the RF-ANN method has a total river surface extraction accuracy of 94.7%, and the extracted river surfaces cover more than 85% of the order 3 DEM river network. By implementing high-resolution DEM and thermal infrared data, RF-ANN effectively eliminates the disturbance of shadows of mountains and other features, which ensures the high accuracy of the extracted widths. It was verified that the maximum and minimum river widths that can be extracted in the Huangfuchuan River Basin are 297.4 m and 6.1 m, respectively. The overall error of river width extraction is 0.97 m, which is less than half of the pixel length of remote sensing images. The R2 and root mean square error (RMSE) of the estimated river width values are 0.99 and 1.49, respectively. For tiny rivers with widths narrower than 10 m, the error of river width extraction is 10.9%. The error of thin rivers whose widths range from 10 to 30 m is 4.9%. For small rivers ranging from 30 to 90 and rivers wider than 90 m, the error is 1.1% and 0.6%, respectively. The new approach provides an effective method for extracting the surface and width of mountain rivers in topographically complex regions by using high-resolution satellite images, which may provide a database for estimating river carbon emissions and related research in fluvial morphology and water resource management. [ABSTRACT FROM AUTHOR]

With the use of the particle flow code in two dimensions, a fractal model is established with the number of particles of different particle fractions used as the statistics to study the fractal characteristics of particle size distribution. Numerically simulated specimens obtained by four scale methods are subjected to the relative density test and the biaxial compression test to explore the influences of fractal dimension D on the macroscopic and mesomechanical properties of specimens, as well as to study the relationship between fractal dimension D and different mechanical performance indexes. Results show that the particle size distribution of each of the four groups after scale exhibits fractal characteristics, with the fractal dimension D ranging from 1.27 to 2.03. The number of fine particles in the specimen increases with the fractal dimension D, the particle aggregates become more compact, the macroscopic mechanical properties of the specimens are improved, and a linear relationship exists between the fractal dimension D and different mechanical performance indexes. A large fractal dimension D corresponds to a great mesoparticle coordination number. [ABSTRACT FROM AUTHOR]

Rainfall stations of a certain number and spatial distribution supply sampling records of rainfall processes in a river basin. Uncertainty may be introduced when the station records are spatially interpolated for the purpose of hydrological simulations. This study adopts a bootstrap method to quantitatively estimate the uncertainty of areal rainfall estimates and its effects on hydrological simulations. The observed rainfall records are first analyzed using clustering and correlation methods and possible average basin rainfall amounts are calculated with a bootstrap method using various combinations of rainfall station subsets. Then, the uncertainty of simulated runoff, which is propagated through a hydrological model from the spatial uncertainty of rainfall estimates, is analyzed with the bootstrapped rainfall inputs. By comparing the uncertainties of rainfall and runoff, the responses of the hydrological simulation to the rainfall spatial uncertainty are discussed. Analyses are primarily performed for three rainfall events in the upstream of the Qingjian River basin, a sub-basin of the middle Yellow River; moreover, one rainfall event in the Longxi River basin is selected for the analysis of the areal representation of rainfall stations. Using the Digital Yellow River Integrated Model, the results show that the uncertainty of rainfall estimates derived from rainfall station network has a direct influence on model simulation, which can be conducive to better understand of rainfall spatial characteristic. The proposed method can be a guide to quantify an approximate range of simulated error caused by the spatial uncertainty of rainfall input and the quantified relationship between rainfall input and simulation performance can provide useful information about rainfall station network management in river basins. [ABSTRACT FROM AUTHOR]

Suffusion constitutes a major threat to the foundation of a dam, and the likelihood of suffusion is always determined by the internal stability of soils. It has been verified that internal stability is closely related to the grain size distribution (GSD) of soils. In this study, a numerical model is developed to simulate the suffusion process. The model takes the combined effects of GSD and porosity (n) into account, as well as Wilcock and Crowe's theory, which is also adopted to quantify the inception and transport of soils. This proposed model is validated with the experimental data and shows satisfactory performance in simulating the process of suffusion. By analyzing the simulation results of the model, the mechanism is disclosed on how soils with specific GSD behaving internally unstable. Moreover, the internal stability of soils can be evaluated through the model. Results show that it is able to distinguish the internal stability of 30 runs out of 36, indicating a 83.33% of accuracy, which is higher than the traditional GSD-based approaches. [ABSTRACT FROM AUTHOR]

In this study, the coupled effects of sediment inertia and stratification on the pattern of secondary currents in bend-flows are evaluated using a 3D numerical model. The sediment inertia effect, as well as the stratification effect induced by the non-uniform distribution of suspended sediment, is accounted for by adopting the hydrodynamic equations without the Boussinesq approximation. The 3D model is validated by existing laboratory experimental results. Simulation results of a simplified meandering channel indicate that sediment stratification effect enhances the intensity of secondary flow via reducing eddy viscosity, while sediment inertia effect suppresses it. The integrated effects result in an increase and a reduction in the secondary flow, respectively, at lower and higher concentrations (near-bed volumetric concentrations of 0.015 and 0.1 are, respectively, considered in this study). This suggests that the dominance of the suspended sediment effect depends on the sediment concentration profile. With the increase of concentration under a specific sediment size, the secondary flow rises to reach a maximum, and then decreases. Moreover, as the sediment concentration increases, an exponentially decaying rate has been found for the secondary flow. It is concluded that in the numerical simulation of flow in meandering channels, when concentration is high, the variable-density hydrodynamic equations without the Boussinesq approximation should be considered. [ABSTRACT FROM AUTHOR]