3 citations · 3 across the 2 of their papers we have counts for
8 papers
Dimensionally Consistent Learning with Buckingham Pi
Joseph Bakarji, Jared Callaham, Steven L. Brunton +1
In the absence of governing equations, dimensional analysis is a robust technique for extracting insights and finding symmetries in physical systems. Given measurement variables an…
Modeling Thermodynamic Trends of Rotating Detonation Engines
James Koch, J. Nathan Kutz
The formation of a number of co- and counter-rotating coherent combustion wave fronts is the hallmark feature of the Rotating Detonation Engine (RDE). The engineering implications…
Multi-fidelity sensor selection: Greedy algorithms to place cheap and expensive sensors with cost constraints
Emily Clark, Steven L. Brunton, J. Nathan Kutz
We develop greedy algorithms to approximate the optimal solution to the multi-fidelity sensor selection problem, which is a cost constrained optimization problem prescribing the pl…
Sensor Selection With Cost Constraints for Dynamically Relevant Bases
Emily Clark, J. Nathan Kutz, Steven L. Brunton
We consider cost-constrained sparse sensor selection for full-state reconstruction, applying a well-known greedy algorithm to dynamical systems for which the usual singular value d…
Mode-Locked Rotating Detonation Waves: Experiments and a Model Equation
James Koch, Mitsuru Kurosaka, Carl Knowlen +1
Direct observation of a Rotating Detonation Engine combustion chamber has enabled the extraction of the kinematics of its detonation waves. These records exhibit a rich set of inst…
A unified sparse optimization framework to learn parsimonious physics-informed models from data
Kathleen Champion, Peng Zheng, Aleksandr Y. Aravkin +2
Machine learning (ML) is redefining what is possible in data-intensive fields of science and engineering. However, applying ML to problems in the physical sciences comes with a uni…