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09/18/2023
Enhancing Elasticity Models: A Novel Corrective Source Term Approach for Accurate Predictions
With the recent wave of digitalization, specifically in the context of s...
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09/18/2023
Machine Learning for enhancing Wind Field Resolution in Complex Terrain
Atmospheric flows are governed by a broad variety of spatio-temporal sca...
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04/16/2023
Digital Twins in Wind Energy: Emerging Technologies and Industry-Informed Future Directions
This article presents a comprehensive overview of the digital twin techn...
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12/14/2022
Artificial intelligence-driven digital twin of a modern house demonstrated in virtual reality
A digital twin is a powerful tool that can help monitor and optimize phy...
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11/08/2022
An Energy-Based Lengthscale for Reduced Order Models of Turbulent Flows
In this paper, we propose a novel reduced order model (ROM) lengthscale ...
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08/15/2022
Prospects of federated machine learning in fluid dynamics
Physics-based models have been mainstream in fluid dynamics for developi...
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06/17/2022
Digital Twin Data Modelling by Randomized Orthogonal Decomposition and Deep Learning
A digital twin is a surrogate model that has the main feature to mirror ...
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06/07/2022
Combining physics-based and data-driven techniques for reliable hybrid analysis and modeling using the corrective source term approach
Upcoming technologies like digital twins, autonomous, and artificial int...
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05/25/2022
Physics Guided Machine Learning for Variational Multiscale Reduced Order Modeling
We propose a new physics guided machine learning (PGML) paradigm that le...
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05/13/2022
Physics guided neural networks for modelling of non-linear dynamics
The success of the current wave of artificial intelligence can be partly...
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02/28/2022
Reduced Order Model Closures: A Brief Tutorial
In this paper, we present a brief tutorial on reduced order model (ROM) ...
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01/11/2022
Sketching Methods for Dynamic Mode Decomposition in Spherical Shallow Water Equations
Dynamic mode decomposition (DMD) is an emerging methodology that has rec...
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11/30/2021
Risk-based implementation of COLREGs for autonomous surface vehicles using deep reinforcement learning
Autonomous systems are becoming ubiquitous and gaining momentum within t...
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10/15/2021
Nonlinear proper orthogonal decomposition for convection-dominated flows
Autoencoder techniques find increasingly common use in reduced order mod...
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08/04/2021
A Numerical Investigation of the Lengthscale in the Mixing-Length Reduced Order Model of the Turbulent Channel Flow
In this paper, we propose a novel reduced order model (ROM) lengthscale ...
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05/24/2021
Deep neural network enabled corrective source term approach to hybrid analysis and modeling
Hybrid Analysis and Modeling (HAM) is an emerging modeling paradigm whic...
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03/26/2021
Hybrid analysis and modeling, eclecticism, and multifidelity computing toward digital twin revolution
Most modeling approaches lie in either of the two categories: physics-ba...
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03/15/2021
Geometric Change Detection in Digital Twins using 3D Machine Learning
Digital twins are meant to bridge the gap between real-world physical sy...
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12/22/2020
On the effectiveness of signal decomposition, feature extraction and selection on lung sound classification
Lung sounds refer to the sound generated by air moving through the respi...
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08/05/2020
A nudged hybrid analysis and modeling approach for realtime wake-vortex transport and decay prediction
We put forth a long short-term memory (LSTM) nudging framework for the e...
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06/17/2020
Interface learning of multiphysics and multiscale systems
Complex natural or engineered systems comprise multiple characteristic s...
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06/17/2020
Deep Reinforcement Learning Controller for 3D Path-following and Collision Avoidance by Autonomous Underwater Vehicles
Control theory provides engineers with a multitude of tools to design co...
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06/16/2020
COLREG-Compliant Collision Avoidance for Unmanned Surface Vehicle using Deep Reinforcement Learning
Path Following and Collision Avoidance, be it for unmanned surface vesse...
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02/15/2020
Data-Driven Variational Multiscale Reduced Order Models
We propose a new data-driven reduced order model (ROM) framework that ce...
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02/03/2020
Proportional integral derivative controller assisted reinforcement learning for path following by autonomous underwater vehicles
Control theory provides engineers with a multitude of tools to design co...
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12/18/2019
Taming an autonomous surface vehicle for path following and collision avoidance using deep reinforcement learning
In this article, we explore the feasibility of applying proximal policy ...
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10/09/2019
Dissecting Deep Neural Networks
In exchange for large quantities of data and processing power, deep neur...
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06/24/2019
A non-intrusive reduced order modeling framework for quasi-geostrophic turbulence
In this study, we present a non-intrusive reduced order modeling (ROM) f...
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07/28/2017