Simulation of polycrystalline aluminum tensile test with crystal plasticity finite element method

The crystal plasticity was implemented in the finite element method（FEM） software ABAQUS through the user subroutine UMAT. By means of discretizing the space at the grain level with the Voronoi diagram method, a polycrystal model was built and used in the FEM analysis. The initial orientation of each grain was generated based on the orientation distribution function（ODF）. The developed model was successfully applied in simulation of polycrystalline aluminium samples deformed by the tensile tests. The theoretical strain--stress relation was in good agreement with the experimental result. The simulation results show that the grain size has significant effect on the deformation behavior. The initial plastic deformation usually occurs at grain boundaries, and multiple slip often results in an enhanced local hardening at grain boundaries.     

面心纯铝单向拉伸的晶体塑性学有限元模拟

基于率相关晶体塑性本构模型,实现了晶体塑性学有限元模拟过程。直接将电子背散射衍射(EBSD)获取的晶粒初始取向输入晶体塑性有限元模型,分别预测了单向拉伸面心1050纯铝过程中的力学响应与织构演化。应力应变响应数值模拟结果与实验结果有较好的一致性,同时也存在一定的偏差。两种多晶模型(Taylor模型和有限单元模型)分别模拟了单向拉伸真应变0.25和0.37时的织构演化。随着真应变的增加,两种丝织构(〈111〉织构和〈100〉织构)变得更加锋锐,模拟结果与EBSD实验测得的织构演化结果有较好的一致性。     

Stock-Price Forecasting Based on XGBoost and LSTM

Using time-series data analysis for stock-price forecasting (SPF) is complex and challenging because many factors can influence stock prices (e.g., inflation, seasonality, economic policy, societal behaviors). Such factors can be analyzed over time for SPF. Machine learning and deep learning have been shown to obtain better forecasts of stock prices than traditional approaches. This study, therefore, proposed a method to enhance the performance of an SPF system based on advanced machine learning and deep learning approaches. First, we applied extreme gradient boosting as a feature-selection technique to extract important features from high-dimensional time-series data and remove redundant features. Then, we fed selected features into a deep long short-term memory (LSTM) network to forecast stock prices. The deep LSTM network was used to reflect the temporal nature of the input time series and fully exploit future contextual information. The complex structure enables this network to capture more stochasticity within the stock price. The method does not change when applied to stock data or Forex data. Experimental results based on a Forex dataset covering 2008–2018 showed that our approach outperformed the baseline autoregressive integrated moving average approach with regard to mean absolute error, mean squared error, and root-mean-square error.     

Chromium(III) compounds as catalysts for Hydrocarbon Oxidation and hydroperoxide decomposition

Chromium stearate and chromium acetylacetonate are very active catalysts both for the oxidation of hydrocarbons by molecular oxygen and for the decomposition of organic hydroperoxides. During these reactions they also catalyze the oxidation of secondary alcohols to the corresponding ketones by organic hydroperoxides. From organic hydroperoxides and chromium(III)compounds chromium (VI) compounds are formed which are probably the effective agents oxidizing secondary alcohols to ketones.     

Using an APK-051 analyzer in a chemical engineering monitoring system

The capabilities of an APK-051 automatic analyzer for directly measuring the standardized indicators used for automatic chemical monitoring and indirectly determining the concentration of ammonia in water coolant are described.     

Analysis of tribological feature of the oxide scale in hot strip rolling

In this paper, the effects of the flow stress of the scale and steel, and the friction coefficients at the scale-steel and the roll-scale interfaces on the final surface roughness have been studied. The surface roughness increases for both oxide scale and steel with an increasing friction coefficient at the roll-scale interface. However, the roughness increment is limited. The calculated roughness is close to the measured value. The temperature affects the scale roughness transfer, and the maximum difference is about 25% when the temperature is 850-1025 °C for rolling speeds 0.12-0.72 m/s. The developed model is applicable in hot strip mills.     

A Mixed Integer Stochastic Optimization Model for Settlement Risk in Retail Electric Power Markets

Recent changes in the U.S. electric power markets have contributed to volatility in hourly prices and loads. In this paper we consider the position of the electric power retailer who typically contracts with suppliers and end-users and must provide future load requirements to the suppliers. As part of this energy supply chain, the retailer is faced with great uncertainty in both market prices as well as end-user loads. Based on actual data for the PJM market covering Pennsylvania, New Jersey, and Maryland, we develop a probabilistic optimization model to optimize the net profits for the retailer for a forecast time horizon (typically one or more hours) given the cumulative performance in previous time periods (hours). The resulting model is formulated as a mixed integer linear program with binary variables due to the disjunctive nature of certain forward load estimation bandwidth tolerance constraints. In addition, we also provide an existence result to this optimization model. Lastly, we present a numerical example of the optimization model to validate its workings and provide some insight into model sensitivities.     

Crystal plasticity investigation of friction effect on texture evolution of Al single crystal during ECAP

A crystal plasticity finite element model has been developed to study the effect of friction between the die wall and the billet on texture evolution during equal channel angular pressing of an aluminum single crystal. Four cases with different coefficients of friction μ = 0, 0.05, 0.1, and 0.15 have been simulated. It has been found that the friction of μ = 0.05 and 0.1 can capture the major texture features shown in the experimental results, and μ = 0.05 predicts a slightly better texture than μ = 0.1. The frictional condition significantly affects texture evolution in the region between 1/2 and 3/4 of the billet thickness from the top surface. It can be attributed to the effect of friction on the corner gap and the distribution of stresses in the die corner.     

Computer simulation of the effect of post annealing parameters on the microstructure inhomogeneity of the non-uniformly deformed copper

A computer simulation on the basis of the Finite Element Method and Monte Carlo Model is developed to simulate the microstructure of the non-uniformly deformed copper workpiece after annealing. Using the computer simulation, the effects of annealing time and temperature on the microstructure inhomogeneity of the workpiece are simulated and investigated quantitatively, by defining an Inhomogeneity Factor, to design an annealing program for reducing the microstructure inhomogeneity. The results show that with increasing the parameters of annealing time and temperature, the inhomogeneity is decreased when one of the parameters is constant. Also, at high annealing temperature, the annealing time changes the inhomogeneity slowly compared with which occurs at low annealing temperature. The simulation results agree well with the experimental values.