Our group, CoMSAIL, will be delivering 6 presentations at APS DFD 2023. If you are also attending the conference in DC, please stop by and check out our talks (focusing on differentiable physics, GPU computing, and hybrid neural modeling for fluid flow)
J29.00003, Fan et al. Differentiable vectorized JAX solver for turbulent flow and fluid-structure interactions (4:35 PM–6:32 PM, Sunday, November 19, 2023, Session J 29, Room: 152B)
L17.00003 Sun et al. Unifying Predictions of Deterministic and Stochastic Physics in Mesh-reduced Space with Sequential Flow Generative Model (8:00 AM–10:36 AM, Monday, November 20,
Room: 145B)
L17.00005, Pan et al. Neural field based sequence model for generating spatial-temporal turbulence (8:00 AM–10:36 AM, Monday, November 20, 2023, Room: 145B)
X29.00001, Akhare et al. Implicit Neural Solver for Stable Surrogate Simulation of Fluid Dynamics (8:00 AM–10:36 AM, Tuesday, November 21, 2023, Room: 152B)
X29.00006, Liu et al. MuRFiV-Net: A Multi-Resolution Finite-Volume Inspired Neural Network for Predicting Spatiotemporal Dynamics (8:00 AM–10:36 AM, Tuesday, November 21, 2023, Room: 152B)
X29.00011, Zhang et al. A Differentiable Hybrid Neural Solver for Efficient Simulation of Cavitating Flows (8:00 AM–10:36 AM, Tuesday, November 21, 2023, Room: 152B)
Also one collaborative work with Prof. X. Zheng from RIT — R14.00007, Zheng et al. A hybrid physics informed neural network model for patient specific phonation simulation (1:50 PM–3:21 PM, Monday, November 20, 2023, Room: 144AB)