Repository logo
 

Digital twins for design in the presence of uncertainties

Published version
Peer-reviewed

Type

Article

Change log

Authors

Abstract

Successful application of digital twins in the design process requires a tailored approach to identify high value information from the uncertain data. We propose a non-intrusive sensitivity metric toolbox that integrates black-box digital twins in the design and decision process under uncertainties. The toolbox captures the evolving nature of the key design performance indicators (KPI) and provide both KPI-free and KPI-based metrics. The KPI-free metrics, which are based on entropy and Fisher information but independent of design KPIs, is shown to give good indication of the most influential data for KPI-based metrics. This suggests a consistent identification of high value data throughout the design process.

Description

Keywords

Design sensitivity toolbox, Design key performance indicator, Design entropy, Fisher information, Probability of acceptance, Likelihood ratio method

Journal Title

Mechanical Systems and Signal Processing

Conference Name

Journal ISSN

0888-3270
1096-1216

Volume Title

179

Publisher

Elsevier BV
Sponsorship
Engineering and Physical Sciences Research Council (EP/R006768/1)