270 citations · 947 across the 25 of their papers we have counts for
26 papers
Global sensitivity analysis with limited data via sparsity-promoting D-MORPH regression: Application to char combustion
Dongjin Lee, Elle Lavichant, Boris Kramer
In uncertainty quantification, variance-based global sensitivity analysis quantitatively determines the effect of each input random variable on the output by partitioning the total…
Symplectic model reduction of Hamiltonian systems using data-driven quadratic manifolds
Harsh Sharma, Hongliang Mu, Patrick Buchfink +3
This work presents two novel approaches for the symplectic model reduction of high-dimensional Hamiltonian systems using data-driven quadratic manifolds. Classical symplectic model…
Bayesian Inference and Global Sensitivity Analysis for Ambient Solar Wind Prediction
Opal Issan, Pete Riley, Enrico Camporeale +1
The ambient solar wind plays a significant role in propagating interplanetary coronal mass ejections and is an important driver of space weather geomagnetic storms. A computational…
Exact and optimal quadratization of nonlinear finite-dimensional non-autonomous dynamical systems
Andrey Bychkov, Opal Issan, Gleb Pogudin +1
Quadratization of polynomial and nonpolynomial systems of ordinary differential equations is advantageous in a variety of disciplines, such as systems theory, fluid mechanics, chem…
Nonlinear Balanced Truncation: Part 2 -- Model Reduction on Manifolds
Boris Kramer, Serkan Gugercin, Jeff Borggaard
Nonlinear balanced truncation is a model order reduction technique that reduces the dimension of nonlinear systems in a manner that accounts for either open- or closed-loop observa…
Multifidelity conditional value-at-risk estimation by dimensionally decomposed generalized polynomial chaos-Kriging
Dongjin Lee, Boris Kramer
We propose novel methods for Conditional Value-at-Risk (CVaR) estimation for nonlinear systems under high-dimensional dependent random inputs. We develop a novel DD-GPCE-Kriging su…