Nonlinear Propagation of Orbit Uncertainty Using Non-Intrusive Polynomial Chaos

By Brandon A. Jones, Alireza Doostan, George H. Born. 2013

193 citations recorded by the source corpus.

Subfields: Computational Mechanics, Environmental Engineering, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/56d18f36e6ed4964c39b06f41a99dae4e20ca2fe

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Computational Mechanics

1. Jerrad Hampton
2. Prasanth B. Nair
3. Alireza Doostan

In Environmental Engineering

1. Jerrad Hampton
2. Alireza Doostan
3. Anthony Nouy

In Statistics and Probability

1. Jerrad Hampton
2. Alireza Doostan
3. Prasanth B. Nair
4. Anthony Nouy
5. Mohammad Hadigol
6. Bruno Sudret
7. Albert Cohen
8. Ahmed H. Elsheikh

Citations in the corpus

• Coherence motivated sampling and convergence analysis of least squares polynomial Chaos regression (2014, methodology): “ions of model or measurement errors. The least squares regression problem (4) is among major techniques used to generate PC expansions for uncertainty quantification of engineering systems, see, e.g., [7, 8, 2, 9, 10, 11, 12, 13, 14, 15, 16, 17]. There has been a growing recent interest in understand”
• Aircraft Robust Trajectory Optimization Using Nonintrusive Polynomial Chaos (2014, methodology): “In contrast, in studies of stochastic dynamic systems considering uncertainties, the primary focus has been on efficient algorithms for uncertainty propagation [14–17,21].”