5 papers
Latent Generative Modeling of Random Fields from Limited Training Data
James E. Warner, Tristan A. Shah, Patrick E. Leser +3
The ability to accurately model random fields plays a critical role in science and engineering for problems involving uncertain, spatially-varying quantities such as heterogeneous…
Polynomial Chaos-based Input Shaper Design under Time-Varying Uncertainty
Johannes Güttler, Karan Baker, Premjit Saha +2
The work presented here investigates the application of polynomial chaos expansion toward input shaper design in order to maintain robustness in dynamical systems subject to uncert…
Bond strength uncertainty quantification via confidence intervals for nondestructive evaluation of bonded composites
Michael C. Stanley, Peter W. Spaeth, James E. Warner +1
As bonded composite materials are used more frequently for aerospace applications, it is necessary to certify that parts achieve desired levels of certain physical characteristics…
BISTRO -- A Bi-Fidelity Stochastic Gradient Framework using Trust-Regions for Optimization Under Uncertainty
Thomas O. Dixon, Geoffrey F. Bomarito, James E. Warner +1
Stochastic optimization of engineering systems is often infeasible due to repeated evaluations of a computationally expensive, high-fidelity simulation. Bi-fidelity methods mitigat…
Generative Modeling of Microweather Wind Velocities for Urban Air Mobility
Tristan A. Shah, Michael C. Stanley, James E. Warner
Motivated by the pursuit of safe, reliable, and weather-tolerant urban air mobility (UAM) solutions, this work proposes a generative modeling approach for characterizing microweath…