@misc{f29ac826bdd14349bf8434a60cc4311a,
title = "Adaptive Computing and Multi-Fidelity Strategies for Control, Design and Scale-Up of Renewable Energy Applications",
abstract = "We describe our ongoing research in adaptive computing and multi-fidelity modeling strategies. Our goal is to use a combination of low- and high-fidelity simulation models to enable computationally efficient optimization and uncertainty quantification. We develop optimization formulations that take into account the compute resources currently available, which act as a constraint with regards to the fidelity level simulation we can run while maximizing information gain. These strategies are being implemented into a software framework with a generalized API allowing its application to a broad range of applications, from power grid stability and buildings control to material synthesis and biofuels processing. We will discuss a few examples from these applications that can benefit from this approach, especially when considering challenges arising in scaling up experiments and simulations.",
keywords = "adaptive computing, multi-fidelity, optimization, uncertainty",
author = "Marc Day and Deepthi Vaidhynathan",
year = "2023",
language = "American English",
series = "Presented at the International Conference for High Performance Computing, Networking, Storage, and Analysis (SC23), 12-17 November 2023, Denver, Colorado",
type = "Other",
}