Sergio Gutiérrez Sánchez, Jacqueline Yang, Andreas Kronenburg, Thorsten Zirwes
{"title":"拉格朗日滤波密度函数方法混合时间尺度建模的再探讨","authors":"Sergio Gutiérrez Sánchez, Jacqueline Yang, Andreas Kronenburg, Thorsten Zirwes","doi":"10.1007/s10494-024-00612-9","DOIUrl":null,"url":null,"abstract":"<div><p>Mixing models for multiple mapping conditioning (MMC) methods are revisited as some details of their implementation have not yet been assessed. We use simulations of scalar mixing in non-reacting homogeneous isotropic decaying turbulence (HIT) such that (1) key modelling parameters can be taken from the direct numerical simulations without incurring additional modelling uncertainties and (2) direct validation is possible. Variants of Curl’s model are studied and direct comparison is sought with the variants’ performances in the context of standard (intensive) and sparse (such as MMC) particle approaches for the modelling of the probability density function (PDF). The second aim is to show the relative importance of micro-mixing and spatial diffusion in the presence of differential diffusion. The results demonstrate that MMC approximates the correct relaxation towards Gaussian independent of the mixing model’s variant. This is different from the standard PDF approach that requires a clear spatial localization given by the computational mesh to achieve a similar outcome. This spatial localization is not needed in MMC as the MMC mixing model already employs a localization in reference space. Differential diffusion effects can, however, only be accurately predicted if not only mixing but also spatial transport accounts for the differences in the molecular diffusion term. It is insufficient to adjust the mixing time scales only and future MMC models may require adjustments for accurate prediction capabilities.</p></div>","PeriodicalId":559,"journal":{"name":"Flow, Turbulence and Combustion","volume":"114 2","pages":"585 - 615"},"PeriodicalIF":2.0000,"publicationDate":"2024-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s10494-024-00612-9.pdf","citationCount":"0","resultStr":"{\"title\":\"Revisiting the Modelling of Mixing Time Scales for Lagrangian Filtered Density Function Methods\",\"authors\":\"Sergio Gutiérrez Sánchez, Jacqueline Yang, Andreas Kronenburg, Thorsten Zirwes\",\"doi\":\"10.1007/s10494-024-00612-9\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>Mixing models for multiple mapping conditioning (MMC) methods are revisited as some details of their implementation have not yet been assessed. We use simulations of scalar mixing in non-reacting homogeneous isotropic decaying turbulence (HIT) such that (1) key modelling parameters can be taken from the direct numerical simulations without incurring additional modelling uncertainties and (2) direct validation is possible. Variants of Curl’s model are studied and direct comparison is sought with the variants’ performances in the context of standard (intensive) and sparse (such as MMC) particle approaches for the modelling of the probability density function (PDF). The second aim is to show the relative importance of micro-mixing and spatial diffusion in the presence of differential diffusion. The results demonstrate that MMC approximates the correct relaxation towards Gaussian independent of the mixing model’s variant. This is different from the standard PDF approach that requires a clear spatial localization given by the computational mesh to achieve a similar outcome. This spatial localization is not needed in MMC as the MMC mixing model already employs a localization in reference space. Differential diffusion effects can, however, only be accurately predicted if not only mixing but also spatial transport accounts for the differences in the molecular diffusion term. It is insufficient to adjust the mixing time scales only and future MMC models may require adjustments for accurate prediction capabilities.</p></div>\",\"PeriodicalId\":559,\"journal\":{\"name\":\"Flow, Turbulence and Combustion\",\"volume\":\"114 2\",\"pages\":\"585 - 615\"},\"PeriodicalIF\":2.0000,\"publicationDate\":\"2024-11-22\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://link.springer.com/content/pdf/10.1007/s10494-024-00612-9.pdf\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Flow, Turbulence and Combustion\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://link.springer.com/article/10.1007/s10494-024-00612-9\",\"RegionNum\":3,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"MECHANICS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Flow, Turbulence and Combustion","FirstCategoryId":"5","ListUrlMain":"https://link.springer.com/article/10.1007/s10494-024-00612-9","RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"MECHANICS","Score":null,"Total":0}
Revisiting the Modelling of Mixing Time Scales for Lagrangian Filtered Density Function Methods
Mixing models for multiple mapping conditioning (MMC) methods are revisited as some details of their implementation have not yet been assessed. We use simulations of scalar mixing in non-reacting homogeneous isotropic decaying turbulence (HIT) such that (1) key modelling parameters can be taken from the direct numerical simulations without incurring additional modelling uncertainties and (2) direct validation is possible. Variants of Curl’s model are studied and direct comparison is sought with the variants’ performances in the context of standard (intensive) and sparse (such as MMC) particle approaches for the modelling of the probability density function (PDF). The second aim is to show the relative importance of micro-mixing and spatial diffusion in the presence of differential diffusion. The results demonstrate that MMC approximates the correct relaxation towards Gaussian independent of the mixing model’s variant. This is different from the standard PDF approach that requires a clear spatial localization given by the computational mesh to achieve a similar outcome. This spatial localization is not needed in MMC as the MMC mixing model already employs a localization in reference space. Differential diffusion effects can, however, only be accurately predicted if not only mixing but also spatial transport accounts for the differences in the molecular diffusion term. It is insufficient to adjust the mixing time scales only and future MMC models may require adjustments for accurate prediction capabilities.
期刊介绍:
Flow, Turbulence and Combustion provides a global forum for the publication of original and innovative research results that contribute to the solution of fundamental and applied problems encountered in single-phase, multi-phase and reacting flows, in both idealized and real systems. The scope of coverage encompasses topics in fluid dynamics, scalar transport, multi-physics interactions and flow control. From time to time the journal publishes Special or Theme Issues featuring invited articles.
Contributions may report research that falls within the broad spectrum of analytical, computational and experimental methods. This includes research conducted in academia, industry and a variety of environmental and geophysical sectors. Turbulence, transition and associated phenomena are expected to play a significant role in the majority of studies reported, although non-turbulent flows, typical of those in micro-devices, would be regarded as falling within the scope covered. The emphasis is on originality, timeliness, quality and thematic fit, as exemplified by the title of the journal and the qualifications described above. Relevance to real-world problems and industrial applications are regarded as strengths.