In this work,a novel computational framework for establishment of atomic mobility database directly from the experimental composition profiles and its uncertainty quantification was developed by merging the Bayesian i...In this work,a novel computational framework for establishment of atomic mobility database directly from the experimental composition profiles and its uncertainty quantification was developed by merging the Bayesian inference with the Markov chain Monte Carlo algorithm into the latest version of the Hit DIC software.By treating the simulation of composition profiles with the composition-dependent coefficients as the forward problem,the inverse coefficient problem that provides the potential way to compute the atomic mobilities directly from composition profiles can be postulated.The values and uncertainties of the atomic mobility parameters of interest were assessed by means of Bayesian inference,where the composition profiles were consumed directly.Benchmark tests that consider the number of diffusion couples and the noise levels were conducted.Practical application of the current framework in determination of atomic mobility descriptions of fcc Ni-Ta and Ni-Al-Ta alloys was performed.Further discussion about the results of the benchmark tests and practical study case indicated that the present computational framework together with numbers of composition profiles from the multiple diffusion couples can help to establish the high-quality atomic mobility database of the target multicomponent alloys.展开更多
基金financially supported by the National Key Research and Development Program of China(No.2016YFB0301101)the Hunan Provincial Science and Technology Program of China(No.2017RS3002)-Huxiang Youth Talent Plan+1 种基金the Youth Talent Project of Innovation-driven Plan at Central South University(No.2019XZ027)the support from the Fundamental Research Funds for the Central Universities of Central South University(No.2018zzts129)。
文摘In this work,a novel computational framework for establishment of atomic mobility database directly from the experimental composition profiles and its uncertainty quantification was developed by merging the Bayesian inference with the Markov chain Monte Carlo algorithm into the latest version of the Hit DIC software.By treating the simulation of composition profiles with the composition-dependent coefficients as the forward problem,the inverse coefficient problem that provides the potential way to compute the atomic mobilities directly from composition profiles can be postulated.The values and uncertainties of the atomic mobility parameters of interest were assessed by means of Bayesian inference,where the composition profiles were consumed directly.Benchmark tests that consider the number of diffusion couples and the noise levels were conducted.Practical application of the current framework in determination of atomic mobility descriptions of fcc Ni-Ta and Ni-Al-Ta alloys was performed.Further discussion about the results of the benchmark tests and practical study case indicated that the present computational framework together with numbers of composition profiles from the multiple diffusion couples can help to establish the high-quality atomic mobility database of the target multicomponent alloys.
