Computational models of the cardiovascular system are increasingly used for the diagnosis,
treatment, and prevention of cardiovascular disease. Before being used for translational …

Machine learning (ML) methods, which fit to data the parameters of a given parameterized
model class, have garnered significant interest as potential methods for learning surrogate …

The aerospace sector is evolving due to reduced launch costs and standardization of small
satellite platforms. This research, aligned with European Guidelines for Thermo-Elastic …

This study addresses two primary challenges in spacecraft thermal analysis: the need for
onboard computation to support autonomous operations, and the requirement for real-time …

The dynamical behavior of opto-mechanical systems is crucial for ensuring the performance
in noisy environments. In particular, vibration mitigation is one of the design drivers for …

Machine learning (ML) methods, which fit data to the parameters of a given parameterized
model class, have garnered significant interest as potential methods for learning surrogate …

Computational models of the cardiovascular system are increasingly used for the diagnosis,
treatment, and prevention of cardiovascular disease. Before being used for translational …

Uncertainty analysis is of great use both for calculating outputs that are more akin to real
flight, and for optimization to more robust shapes. However, implementation of uncertainty …

The computational complexity of integrated structural-thermal-optical performance models,
particularly for one-of-a-kind telescope missions, often limits the maximum feasible number …

A Bayesian Validation Framework for Computationally Expensive Models Page 1 A Bayesian
Validation Framework for Computationally Expensive Models Dr. Giuseppe Cataldo NASA …