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EP2 - Dr Florian Menter - Turbulence Modelling Pioneer

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Indhold leveret af Neil Ashton. Alt podcastindhold inklusive episoder, grafik og podcastbeskrivelser uploades og leveres direkte af Neil Ashton eller deres podcastplatformspartner. Hvis du mener, at nogen bruger dit ophavsretligt beskyttede værk uden din tilladelse, kan du følge processen beskrevet her https://da.player.fm/legal.

Florian Menter discusses his journey in the field of computational fluid dynamics (CFD) and the development of the K-Omega SST model. He shares his experiences working at NASA Ames and the collaborative environment in the CFD community. Florian also talks about his decision to return to Germany and his role in the early days of what would be become ANSYS. Florian Menter discusses the birth and development of the SST turbulence model, the challenges of transition modeling, and the future of RANS models. He also explores the potential of machine learning in CFD and shares advice for young researchers. The conversation highlights the importance of pursuing valuable ideas, keeping things simple, and envisioning the outcome of one's work.

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14 episoder

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Manage episode 416944208 series 3572969
Indhold leveret af Neil Ashton. Alt podcastindhold inklusive episoder, grafik og podcastbeskrivelser uploades og leveres direkte af Neil Ashton eller deres podcastplatformspartner. Hvis du mener, at nogen bruger dit ophavsretligt beskyttede værk uden din tilladelse, kan du følge processen beskrevet her https://da.player.fm/legal.

Florian Menter discusses his journey in the field of computational fluid dynamics (CFD) and the development of the K-Omega SST model. He shares his experiences working at NASA Ames and the collaborative environment in the CFD community. Florian also talks about his decision to return to Germany and his role in the early days of what would be become ANSYS. Florian Menter discusses the birth and development of the SST turbulence model, the challenges of transition modeling, and the future of RANS models. He also explores the potential of machine learning in CFD and shares advice for young researchers. The conversation highlights the importance of pursuing valuable ideas, keeping things simple, and envisioning the outcome of one's work.

  continue reading

14 episoder

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