4 papers
A Comparative Analysis of Robust and Reliable Designs Using the Compromise Decision Support Problem: A Case Study in Hot Rod Rolling Processes
Maryam Ghasemzadeh, H M Dilshad Alam Digonta, Anand Balu Nellippallil +1
Design under uncertainty is a challenging problem, as a systems performance can be highly sensitive to variations in input parameters and model uncertainty. A conventional approach…
NOSTRA: A noise-resilient and sparse data framework for trust region based multi objective Bayesian optimization
Maryam Ghasemzadeh, Anton van Beek
Multi-objective Bayesian optimization (MOBO) struggles with sparse (non-space-filling), scarce (limited observations) datasets affected by experimental uncertainty, where identical…
Flow Battery Manifold Design with Heterogeneous Inputs Through Generative Adversarial Neural Networks
Eric Seng, Hugh O'Connor, Adam Boyce +2
Generative machine learning has emerged as a powerful tool for design representation and exploration. However, its application is often constrained by the need for large datasets o…
Bayesian Optimization for Intrinsically Noisy Response Surfaces
Anton van Beek
While many advanced statistical methods for the design of experiments exist, it is still typical for physical experiments to be performed adaptively based on human intuition. As a…