5 citations · 5 across the 4 of their papers we have counts for
4 papers
Data-driven Balanced Truncation for Predictive Model Order Reduction of Aeroacoustic Response
Elnaz Rezaian, Karthik Duraisamy
Rapid prediction of the aeroacoustic response is a key component in the design of aircraft and turbomachinery. While it is possible to achieve accurate predictions using direct sol…
A Non-intrusive Approach for Physics-constrained Learning with Application to Fuel Cell Modeling
Vishal Srivastava, Valentin Sulzer, Peyman Mohtat +2
A data-driven model augmentation framework, referred to as Weakly-coupled Integrated Inference and Machine Learning (IIML), is presented to improve the predictive accuracy of physi…
Machine Learning-augmented Predictive Modeling of Turbulent Separated Flows over Airfoils
Anand Pratap Singh, Shivaji Medida, Karthik Duraisamy
A modeling paradigm is developed to augment predictive models of turbulence by effectively utilizing limited data generated from physical experiments. The key components of our app…
An Optimized Weighted Association Rule Mining On Dynamic Content
P. Velvadivu, K. Duraisamy
Association rule mining aims to explore large transaction databases for association rules. Classical Association Rule Mining (ARM) model assumes that all items have the same signif…