Synthetic turbulent inflow generator using machine learning

Mathematics

• Machine Learning 100%
• Direct numerical Simulation 86%
• Turbulent Channel Flow 81%
• Generator 66%
• Driver 59%
• Flow Rate 39%
• Velocity Field 31%
• Statistics 31%
• Deviation 27%
• Output 22%
• Multilayer Perceptron 22%
• Model 19%
• Accumulate 19%
• Simulation 19%
• Turbulence 17%
• Instant 16%
• Instantaneous 16%
• Reynolds number 15%
• Friction 15%
• Computational Cost 15%
• Cross section 14%
• Periodicity 14%
• Neural Networks 14%
• Time series 13%
• Sufficient 11%
• Methodology 11%

Engineering & Materials Science

• Direct numerical simulation 92%
• Machine learning 66%
• Channel flow 62%
• Statistics 40%
• Flow rate 27%
• Multilayer neural networks 18%
• Convolutional neural networks 16%
• Turbulence 16%
• Time series 15%
• Reynolds number 15%
• Friction 12%
• Costs 6%

Chemical Compounds

• Simulation 57%
• Flow 29%
• Velocity 25%
• Flow Kinetics 23%
• Turbulence 21%
• Reynolds Number 20%
• Time 16%
• Multilayer 13%