5 papers
Robust Sparse Identification of Nonlinear Dynamics via Least Trimmed Squares
Fabio Amaral, Geovani N. Grapiglia, Cassio M. Oishi
In this work, we propose a robust Sparse Identification of Nonlinear Dynamics (SINDy) pipeline for handling datasets corrupted by noise and outliers. The method decouples outlier f…
Prediction of Viscoelastic Droplet Impact Dynamics Using a Vision Transformer-Based Approach
Diego A. de Aguiar, Cassio M. Oishi
Droplet impact on solid surfaces is a complex fluid dynamics problem with applications in spray cooling, inkjet printing, and pharmaceutical processing. Although numerical simulati…
From STLS to Projection-based Dictionary Selection in Sparse Regression for System Identification
Hangjun Cho, Fabio V. G. Amaral, Andrei A. Klishin +2
In this work, we revisit dictionary-based sparse regression, in particular, Sequential Threshold Least Squares (STLS), and propose a score-guided library selection to provide pract…
CS-SHRED: Enhancing SHRED for Robust Recovery of Spatiotemporal Dynamics
Romulo B. da Silva, Diego Passos, Cássio M. Oishi +1
We present CS-SHRED, a novel deep learning architecture that integrates Compressed Sensing (CS) into a Shallow Recurrent Decoder (SHRED) to reconstruct spatiotemporal dynamics from…
Predicting Energy Budgets in Droplet Dynamics: A Recurrent Neural Network Approach
Diego A. de Aguiar, Hugo L. França, Cassio M. Oishi
Neural networks in fluid mechanics offer an efficient approach for exploring complex flows, including multiphase and free surface flows. The recurrent neural network, particularly…