Simulation of the precipitation process of Ni_(75)Al_xV_(25-x) alloys incorporated in the microelasticity field

The microelasticity field was incorporated into the microscopic phase-field equation for the ternary alloy systems, the morphology evolution and coarsening behavior of the Ni75AixV25-x alloy were simulated. The γ phase precipitates initially for Ni75Al7aV17.9 and Ni75Al5.5V19.5 alloys and the two phases transform from the equiaxed or strip-like to the quadrate as the growth and coarsening processes. For the anisotropic elasticity interaction of the system, the orientation of γ is along the 〈001〉 directions and the θ phase is along the short axis direction of [10]. Analysis of the structure and the pair-correlation functions indicate that the average precipitate length scale of the particles increases at the late-stage coarsening, and the dynamical scaling behavior is obeyed.

High-quality reconstruction of China’s natural streamflow

Reconstruction of natural streamflow is fundamental to the sustainable management of water resources.In China,previous reconstructions from sparse and poor-quality gauge measurements have led to large biases in simulation of the interannual and seasonal variability of natural flows.Here we use a well-trained and tested land surface model coupled to a routing model with flow direction correction to reconstruct the first high-quality gauge-based natural streamflow dataset for China,covering all its330 catchments during the period from 1961 to 2018.A stronger positive linear relationship holds between upstream routing cells and drainage areas,after flow direction correction to 330 catchments.We also introduce a parameter-uncertainty analysis framework including sensitivity analysis,optimization,and regionalization,which further minimizes biases between modeled and inferred natural streamflow from natural or near-natural gauges.The resulting behavior of the natural hydrological system is represented properly by the model which achieves high skill metric values of the monthly streamflow,with about 83%of the 330 catchments having Nash-Sutcliffe efficiency coefficient(NSE)>0.7,and about56%of the 330 catchments having Kling-Gupta efficiency coefficient(KGE)>0.7.The proposed construction scheme has important implications for similar simulation studies in other regions,and the developed low bias long-term national datasets by statistical postprocessing should be useful in supporting river management activities in China.

A comprehensive framework for assessing the spatial drivers of flood disasters using an Optimal Parameter-based Geographical Detector-machine learning coupled model

Flood disasters pose serious threats to human life and property worldwide.Exploring the spatial drivers of flood disasters on a macroscopic scale is of great significance for mitigating their impacts.This study proposes a comprehensive framework for integrating driving-factor optimization and interpretability,while considering spatial heterogeneity.In this framework,the Optimal Parameter-based Geographic Detector(OPGD),Recursive Feature Estimation(RFE),and Light Gradient Boosting Machine(LGBM)models were utilized to construct the OPGD–RFE–LGBM coupled model to identify the essential driving factors and simulate the spatial distribution of flood disasters.The SHapley Additive ExPlanation(SHAP)interpreter was employed to quantitatively explain the driving mechanisms behind the spatial distribution of flood disasters.Yunnan Province,a typical mountainous and plateau area in Southwest China,was selected to implement the proposed framework and conduct a case study.For this purpose,a flood disaster inventory of 7332 historical events was prepared,and 22 potential driving factors related to precipitation,surface environment,and human activity were initially selected.Results revealed that flood disasters in Yunnan Province exhibit high spatial heterogeneity,with geomorphic zoning accounting for 66.1%of the spatial variation in historical flood disasters.The OPGD–RFE–LGBM coupled model offers clear advantages over a single LGBM in identifying essential driving factors and quantitatively analyzing their impacts.Moreover,the simulation performance shows a slight improvement(a 6%average decrease in RMSE and an average increase of 1%in R2)even with reduced factor data.Factor explanatory analysis indicated that the combination of the essential driving factor sets varied across different subregions;nevertheless,precipitation-related factors,such as precipitation intensity index(SDII),wet days(R10MM),and 5-day maximum precipitation(RX5day),were the main driving factors controlling flood disasters.This study provides a quantitative analytical framework for the spatial drivers of flood disasters at large scales with significant heterogeneity,offering a reference for disaster management authorities in developing macro-strategies for disaster prevention.

Electrochemical behavior of Cu in the (NaCl-KCl-CuCl) molten salt

The electrochemical reaction mechanism and electrocrystallization process of Cu on copper electrode in the eutectic NaC1-KC1-CuC1 molten salt were investigated by means of cyclic voltammetry, chronopotentiometry and chronoamperometry tech-nique at 710℃. The results show that the electrochemical reaction process of Cu is a quasi-reversible process mix-controlled by Cu＋ diffusion rate and electron transport rate;the electrochemical reduction mechanism is Cu＋e→Cu;the electrocrystallization process of copper is an instantaneous hemispheroid three-dimensional nucleation process; the Cu diffusino coefficient is 4.3×10^-4cm^2·s^-1 under the experimental conditions.