Applying computational fluid dynamics to optimize adjustments on oral appliance used for the treatment of snoring and obstructive sleep apnea

Wang, C.-C.; Chuang, H.-C.; Hsiao, Hsin-Huang Michael; Wang, Y.-M.; Shih, Hsi-Chin

doi:10.1016/j.sleep.2017.11.397

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2018

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“…CFD is a branch of fluid mechanics dealing with the modeling of fluid flows using the Navier-Stokes equations [1] and has many applications in engineering design (e.g. [2]- [6]). However, a well-known disadvantage of CFD is the computation time: high-fidelity simulations often take many hours or even days of CPU-time to complete.…”

Section: Introductionmentioning

confidence: 99%

Neural Networks for Predicting the Output of wind flow Simulations Over Complex Topographies

Mayo¹,

Wakes²,

Anderson³

2018

2018 IEEE International Conference on Big Knowledge (ICBK)

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We use deep learning techniques to model computational fluid dynamics (CFD) simulations of wind flow over a complex topography. Our motivation is to "speed up" the optimisation of CFD-based simulations (such as the 3D wind farm layout optimisation problem) by developing surrogate models capable of predicting the output of a simulation at any given point in 3D space, given output from a set of training simulations that have already been run. Our promising results using TensorFlow show that deep neural networks can be learned to model CFD outputs with an error of as low as 2.5 meters per second.

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Section: Introductionmentioning

confidence: 99%