Assessment of airborne transmitted infection risk in classrooms using computational fluid dynamics and machine learning-based surrogate modeling

Keyphrases

• Computational Fluid Dynamics 100%
• Infection Risk 100%
• Surrogate Model 100%
• Machine Learning Based 100%
• Transmitted Infection 100%
• Dynamic Learning 100%
• Fluid Machine 100%
• Airborne Infection 75%
• Computational Fluid Dynamics Simulation 75%
• Air Change Rate 75%
• Artificial Neural Network 50%
• Ventilation Strategy 50%
• Particle Size 25%
• Risk Reduction 25%
• Swift 25%
• Computational Demand 25%
• Computation Time 25%
• Operation Strategy 25%
• Design Strategy 25%
• Risk Prediction 25%
• Neural Network 25%
• Supervised Learning 25%
• Dynamic Environment 25%
• Classroom Environment 25%
• R2 Value 25%
• Model Performance 25%
• Prediction Accuracy 25%
• Particle Concentration 25%
• Indoor Environment 25%
• Source Location 25%
• Disease Transmission 25%
• Health Intervention 25%
• Local Infection 25%
• System Operation 25%
• COVID-19 Pandemic 25%
• Unconventional Wells 25%
• Concentration Prediction 25%
• Long Short-term Memory Neural Network 25%
• Inhalable Particles 25%
• Physical Distancing 25%
• Wells-Riley Model 25%

Engineering

• Computational Fluid Dynamics 100%
• Change Rate 75%
• Air Change 75%
• Surrogate Model 50%
• Artificial Neural Network 50%
• Particle Concentration 25%
• Long Short-Term Memory 25%
• Risk Prediction 25%