Future Mars landing missions will require the capability of precise landing at certain sites for
specific scientific interests to gather more valuable scientific information. Autonomous …

The parameters to be identified are described as random variables, the randomness
reflecting the uncertainty about the true values, allowing the incorporation of new information …

Bayesian analysis provides a framework for the inverse uncertainty quantification (UQ) of
combustion kinetic models. As the workhorse of the Bayesian approach, the Markov chain …

In a Bayesian setting, inverse problems and uncertainty quantification (UQ)—the
propagation of uncertainty through a computational (forward) model—are strongly …

The proof of convergence of the standard ensemble Kalman filter (EnKF) from Le Gland,
Monbet, and Tran Large sample asymptotics for the ensemble Kalman filter, in The Oxford …

In this paper we deal with a probability-based scale bridging for concrete material when
passing the detailed information at the meso-scale (the scale where the aggregate vs …

In the current work we examine the application of the stochastic finite element method
(SFEM) to the modeling of representative volume elements for heterogeneous materials …

The paper deals with the propagation of uncertainty in input parameters through the aircraft
model in clean cruise configuration triggered by the elevator pulse. Assuming aerodynamic …

In a Bayesian setting, inverse problems and uncertainty quantification (UQ)-the propagation
of uncertainty through a computational (forward) model-are strongly connected. In the form …

In order to compute the sequential state estimation of Mars entry dynamic system from noisy
observations, a deterministic square-root Kalman filter is developed with the implementation …