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Found 6 papers, 0 papers with code
Non-iterative generation of an optimal mesh for a blade passage using deep reinforcement learning
Despite automation in mesh generation using either an empirical approach or an optimization algorithm, repeated tuning of meshing parameters is still required for a new geometry.
Control of a fly-mimicking flyer in complex flow using deep reinforcement learning
For the deep-RL to successfully learn the control policy, accurate and ample data of the dynamics are required.
Multi-condition multi-objective optimization using deep reinforcement learning
A multi-condition multi-objective optimization method that can find Pareto front over a defined condition space is developed for the first time using deep reinforcement learning.
Prediction of typhoon tracks using a generative adversarial network with observational and meteorological data
Tracks of typhoons are predicted using a generative adversarial network (GAN) with observational data in form of satellite images and meteorological data from a reanalysis database.
Atmospheric and Oceanic Physics
Typhoon track prediction using satellite images in a Generative Adversarial Network
Tracks of typhoons are predicted using satellite images as input for a Generative Adversarial Network (GAN).
Prediction of laminar vortex shedding over a cylinder using deep learning
Unsteady flow fields in the future at a Reynolds number which is not in the training datasets are predicted using a GAN.
Fluid Dynamics
