{"title":"在 Bifrost 太阳大气 MHD 代码中实施热传导能量传递模型","authors":"George Cherry, Boris Gudiksen, Mikolaj Szydlarski","doi":"arxiv-2409.07074","DOIUrl":null,"url":null,"abstract":"Context: Thermal conductivity provides important contributions to the energy\nevolution of the upper solar atmosphere, behaving as a non-linear\nconcentration-dependent diffusion equation. Recently, different methods have\nbeen offered as best-fit solutions to these problems in specific situations,\nbut their effectiveness and limitations are rarely discussed. Aims. We\nrigorously test the different implementations of solving the conductivity flux,\nin the massively-parallel magnetohydrodynamics code, Bifrost, with the aim of\nspecifying the best scenarios for the use of each method. Methods: We compare\nthe differences and limitations of explicit versus implicit methods, and\nanalyse the convergence of a hyperbolic approximation. Among the tests, we use\na newly derived 1st-order self-similar approximation to compare the efficacy of\neach method analytically in a 1D pure-thermal test scenario. Results: We find\nthat although the hyperbolic approximation proves the most accurate and the\nfastest to compute in long-running simulations, there is no optimal method to\ncalculate the mid-term conductivity with both accuracy and efficiency. We also\nfind that the solution of this approximation is sensitive to the initial\nconditions, and can lead to faster convergence if used correctly.\nHyper-diffusivity is particularly useful in aiding the methods to perform\noptimally. Conclusions: We discuss recommendations for the use of each method\nwithin more complex simulations, whilst acknowledging the areas of opportunity\nfor new methods to be developed.","PeriodicalId":501312,"journal":{"name":"arXiv - MATH - Mathematical Physics","volume":"50 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Implementation of thermal conduction energy transfer models in the Bifrost Solar atmosphere MHD code\",\"authors\":\"George Cherry, Boris Gudiksen, Mikolaj Szydlarski\",\"doi\":\"arxiv-2409.07074\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Context: Thermal conductivity provides important contributions to the energy\\nevolution of the upper solar atmosphere, behaving as a non-linear\\nconcentration-dependent diffusion equation. Recently, different methods have\\nbeen offered as best-fit solutions to these problems in specific situations,\\nbut their effectiveness and limitations are rarely discussed. Aims. We\\nrigorously test the different implementations of solving the conductivity flux,\\nin the massively-parallel magnetohydrodynamics code, Bifrost, with the aim of\\nspecifying the best scenarios for the use of each method. Methods: We compare\\nthe differences and limitations of explicit versus implicit methods, and\\nanalyse the convergence of a hyperbolic approximation. Among the tests, we use\\na newly derived 1st-order self-similar approximation to compare the efficacy of\\neach method analytically in a 1D pure-thermal test scenario. Results: We find\\nthat although the hyperbolic approximation proves the most accurate and the\\nfastest to compute in long-running simulations, there is no optimal method to\\ncalculate the mid-term conductivity with both accuracy and efficiency. We also\\nfind that the solution of this approximation is sensitive to the initial\\nconditions, and can lead to faster convergence if used correctly.\\nHyper-diffusivity is particularly useful in aiding the methods to perform\\noptimally. Conclusions: We discuss recommendations for the use of each method\\nwithin more complex simulations, whilst acknowledging the areas of opportunity\\nfor new methods to be developed.\",\"PeriodicalId\":501312,\"journal\":{\"name\":\"arXiv - MATH - Mathematical Physics\",\"volume\":\"50 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-09-11\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"arXiv - MATH - Mathematical Physics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/arxiv-2409.07074\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"arXiv - MATH - Mathematical Physics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/arxiv-2409.07074","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Implementation of thermal conduction energy transfer models in the Bifrost Solar atmosphere MHD code
Context: Thermal conductivity provides important contributions to the energy
evolution of the upper solar atmosphere, behaving as a non-linear
concentration-dependent diffusion equation. Recently, different methods have
been offered as best-fit solutions to these problems in specific situations,
but their effectiveness and limitations are rarely discussed. Aims. We
rigorously test the different implementations of solving the conductivity flux,
in the massively-parallel magnetohydrodynamics code, Bifrost, with the aim of
specifying the best scenarios for the use of each method. Methods: We compare
the differences and limitations of explicit versus implicit methods, and
analyse the convergence of a hyperbolic approximation. Among the tests, we use
a newly derived 1st-order self-similar approximation to compare the efficacy of
each method analytically in a 1D pure-thermal test scenario. Results: We find
that although the hyperbolic approximation proves the most accurate and the
fastest to compute in long-running simulations, there is no optimal method to
calculate the mid-term conductivity with both accuracy and efficiency. We also
find that the solution of this approximation is sensitive to the initial
conditions, and can lead to faster convergence if used correctly.
Hyper-diffusivity is particularly useful in aiding the methods to perform
optimally. Conclusions: We discuss recommendations for the use of each method
within more complex simulations, whilst acknowledging the areas of opportunity
for new methods to be developed.