1 citations · 1 across the 4 of their papers we have counts for
4 papers
Towards Streaming Prediction of Oscillatory Flows: A Data Assimilation and Machine Learning Approach
Miguel M. Valero, Marcello Meldi
Data-driven methods have demonstrated strong predictive capabilities in fluid mechanics, yet most current applications still focus on simplified configurations, often characterised…
Enhanced State Estimation for turbulent flows combining Ensemble Data Assimilation and Machine Learning
Miguel M. Valero, Marcello Meldi
A novel strategy is proposed to improve the accuracy of state estimation and reconstruction from low-fidelity models and sparse data from sensors. This strategy combines ensemble D…
A physics-infused Immersed Boundary Method using online sequential Data Assimilation
Miguel M. Valero, Marcello Meldi
A physics-infused strategy relying on the Ensemble Kalman Filter (EnKF) is here used to augment the accuracy of a continuous Immersed Boundary Method (IBM). The latter is a classic…
Augmented state estimation of urban settings using intrusive sequential Data Assimilation
Lucas Villanueva, Miguel Martinez Valero, Anina Sarkic Glumac +1
A data-driven investigation of the flow around a high-rise building is performed combining heterogeneous experimental samples and RANS CFD. The coupling is performed using techniqu…