294 citations · 2.9k across the 83 of their papers we have counts for
11 papers · 1 filter
Risk-based implementation of COLREGs for autonomous surface vehicles using deep reinforcement learning
Thomas Nakken Larsen, Amalie Heiberg, Eivind Meyer +3
Autonomous systems are becoming ubiquitous and gaining momentum within the marine sector. Since the electrification of transport is happening simultaneously, autonomous marine vess…
Nonlinear proper orthogonal decomposition for convection-dominated flows
Shady E. Ahmed, Omer San, Adil Rasheed +1
Autoencoder techniques find increasingly common use in reduced order modeling as a means to create a latent space. This reduced order representation offers a modular data-driven mo…
Multi-fidelity information fusion with concatenated neural networks
Suraj Pawar, Omer San, Prakash Vedula +2
Recently, computational modeling has shifted towards the use of deep learning, and other data-driven modeling frameworks. Although this shift in modeling holds promise in many appl…
A Numerical Investigation of the Lengthscale in the Mixing-Length Reduced Order Model of the Turbulent Channel Flow
Changhong Mou, Elia Merzari, Omer San +1
In this paper, we propose a novel reduced order model (ROM) lengthscale definition that is based on energy distribution arguments. This novel ROM lengthscale is fundamentally diffe…
On closures for reduced order models A spectrum of first-principle to machine-learned avenues
Shady E. Ahmed, Suraj Pawar, Omer San +3
For over a century, reduced order models (ROMs) have been a fundamental discipline of theoretical fluid mechanics. Early examples include Galerkin models inspired by the Orr-Sommer…
Deep neural network enabled corrective source term approach to hybrid analysis and modeling
Sindre Stenen Blakseth, Adil Rasheed, Trond Kvamsdal +1
In this work, we introduce, justify and demonstrate the Corrective Source Term Approach (CoSTA) -- a novel approach to Hybrid Analysis and Modeling (HAM). The objective of HAM is t…