In this section
@inbook{Kucherenko:2024:10.1007/978-3-031-56208-2_42,
author = {Kucherenko, S and Shah, N and Zaccheus, O},
booktitle = {Large-Scale Scientific Computations},
doi = {10.1007/978-3-031-56208-2_42},
editor = {Lirkov and Margenov},
pages = {412--418},
publisher = {Springer Nature Switzerland AG},
title = {Application of active subspaces for model reduction and identification of design space},
url = {http://dx.doi.org/10.1007/978-3-031-56208-2_42},
year = {2024}
}
TY - CHAP
AB - The design space is defined as the combination of materials and process conditions which provides assurance of quality. Identification of the design space is a computationally demanding task especially in high dimensional settings. The active subspaces method is a technique that identifies the most important directions in the parameter space, enabling significant dimension reduction. We show how to apply the active subspaces method for model reductions and identification of design space. The results of constraint global sensitivity analysis match those obtained with the active subspaces method for the considered test case.
AU - Kucherenko,S
AU - Shah,N
AU - Zaccheus,O
DO - 10.1007/978-3-031-56208-2_42
EP - 418
PB - Springer Nature Switzerland AG
PY - 2024///
SN - 978-3-031-56207-5
SP - 412
TI - Application of active subspaces for model reduction and identification of design space
T1 - Large-Scale Scientific Computations
UR - http://dx.doi.org/10.1007/978-3-031-56208-2_42
ER -