Hypereutectic Al-Si-Cu coatings were prepared by supersonic atmospheric plasma spraying to enhance the surface performance of lightweight alloys.To find out optimum process conditions and achieve desirable coatings,th...Hypereutectic Al-Si-Cu coatings were prepared by supersonic atmospheric plasma spraying to enhance the surface performance of lightweight alloys.To find out optimum process conditions and achieve desirable coatings,this work focuses on the influence of three important parameters(in-flight particle temperature,impact velocity,and substrate temperature)on the collected splats morphology coatings microstructure and microhardness.Results show that appropriate combinations of temperature and velocity of in-flight particles cannot only completely melt hypereutectic Al-Si-Cu particles especially the primary Si phase,but also provide the particles with sufficient kinetic energy.Thus,the optimized coating consists of 98.6%of fully-melted region with nanosized coupled eutectic and 0.9%of porosity.Increasing the substrate deposition temperature promotes the transition from inhomogeneous banded microstructure to homogeneous equiaxed microstructure with a lower porosity level.The observations are further interpreted by a newly developed phase-change heat transfer model on quantitatively revealing the solidification and remelting behaviors of several splats deposited on substrate Besides,phase evolutions including the formation of supersaturatedα-Al matrix solid solution,growth of Si and Al_(2)Cu phases at different process conditions are elaborated.An ideal microstructure(low fractions of unmelted/partially-melted regions and defects)together with solid solution,grain refinement and second phase strengthening effects contributes to the enhanced microhardness of coating.This integrated study not only provides a framework for optimizing Al-Si based coatings via thermal spraying but also gives valuable insights into the formation mechanisms of this class of coating materials.展开更多
To reduce the impact of potential strength outliers on parameter estimation,statistical methods based on the least median square and least absolute deviation have been proposed as alternatives to the traditional least...To reduce the impact of potential strength outliers on parameter estimation,statistical methods based on the least median square and least absolute deviation have been proposed as alternatives to the traditional least square method.However,little research has been conducted to compare the performance of these different statistical methods.This study introduces a novel procedure for evaluating the three statistical approaches across six selected rock failure criteria,constrained by various rock strength datasets.The consistency of the bestfitting failure criterion and the robustness of the strength parameter estimations serve as the primary benchmarks for evaluation.Based on the benchmark analysis,the following conclusions are drawn.First,both the least square and least absolute deviation methods perform equivalently in identifying the best-fitting failure criterion for a given rock strength dataset,whereas the least median square method does not.Second,when estimating the strength parameters in a two-dimensional failure criterion with the conventional test data of low complexity,the least absolute deviation method is recommended for obtaining robust parameter estimations.Third,as the complexity of conventional test data increases or when true triaxial test data are used to estimate strength parameters for a three-dimensional failure criterion,it is essential to evaluate the outlier-proneness by analyzing the prediction error.If the kurtosis of the prediction error is less than 3,the least square method is preferred.Otherwise,the least absolute deviation method should be used to mitigate the influence of potential strength outliers.This benchmark study offers valuable insights for the future application of different statistical methods in rock mechanics.展开更多
基金financially supported by the National Natural Science Foundation of China(Nos.51535011,51675531,52075542 and 52075543)the Pre-Research Program in National 13th FiveYear Plan(No.61409230603)+2 种基金the Joint Fund of Ministry of Education for Pre-research of Equipment(No.6141A02033120)the China Postdoctoral Science Foundation(No.2019M653598)the Natural Science Basic Research Plan in Shaanxi Province of China(No.2020JQ-911)。
文摘Hypereutectic Al-Si-Cu coatings were prepared by supersonic atmospheric plasma spraying to enhance the surface performance of lightweight alloys.To find out optimum process conditions and achieve desirable coatings,this work focuses on the influence of three important parameters(in-flight particle temperature,impact velocity,and substrate temperature)on the collected splats morphology coatings microstructure and microhardness.Results show that appropriate combinations of temperature and velocity of in-flight particles cannot only completely melt hypereutectic Al-Si-Cu particles especially the primary Si phase,but also provide the particles with sufficient kinetic energy.Thus,the optimized coating consists of 98.6%of fully-melted region with nanosized coupled eutectic and 0.9%of porosity.Increasing the substrate deposition temperature promotes the transition from inhomogeneous banded microstructure to homogeneous equiaxed microstructure with a lower porosity level.The observations are further interpreted by a newly developed phase-change heat transfer model on quantitatively revealing the solidification and remelting behaviors of several splats deposited on substrate Besides,phase evolutions including the formation of supersaturatedα-Al matrix solid solution,growth of Si and Al_(2)Cu phases at different process conditions are elaborated.An ideal microstructure(low fractions of unmelted/partially-melted regions and defects)together with solid solution,grain refinement and second phase strengthening effects contributes to the enhanced microhardness of coating.This integrated study not only provides a framework for optimizing Al-Si based coatings via thermal spraying but also gives valuable insights into the formation mechanisms of this class of coating materials.
基金supported by the National Natural Science Foundation of China(Grant No.42002278)the Open Foundation of Collaborative Innovation Center of Green Development and Ecological Restoration of Mineral Resources(Grant No.HLCX-2024-03)the Training Program of Innovation and Entrepreneurship for Undergraduates(Grant No.202415012).
文摘To reduce the impact of potential strength outliers on parameter estimation,statistical methods based on the least median square and least absolute deviation have been proposed as alternatives to the traditional least square method.However,little research has been conducted to compare the performance of these different statistical methods.This study introduces a novel procedure for evaluating the three statistical approaches across six selected rock failure criteria,constrained by various rock strength datasets.The consistency of the bestfitting failure criterion and the robustness of the strength parameter estimations serve as the primary benchmarks for evaluation.Based on the benchmark analysis,the following conclusions are drawn.First,both the least square and least absolute deviation methods perform equivalently in identifying the best-fitting failure criterion for a given rock strength dataset,whereas the least median square method does not.Second,when estimating the strength parameters in a two-dimensional failure criterion with the conventional test data of low complexity,the least absolute deviation method is recommended for obtaining robust parameter estimations.Third,as the complexity of conventional test data increases or when true triaxial test data are used to estimate strength parameters for a three-dimensional failure criterion,it is essential to evaluate the outlier-proneness by analyzing the prediction error.If the kurtosis of the prediction error is less than 3,the least square method is preferred.Otherwise,the least absolute deviation method should be used to mitigate the influence of potential strength outliers.This benchmark study offers valuable insights for the future application of different statistical methods in rock mechanics.
