Details
| Original language | English |
|---|---|
| Title of host publication | Proceedings of the 11th European Workshop on Structural Health Monitoring |
| Publication status | Published - Jul 2024 |
| Event | 11th European Workshop on Structural Health Monitoring, EWSHM 2024 - Potsdam, Germany Duration: 10 Jun 2024 → 13 Jun 2024 |
Abstract
Ensuring certainty in the rapidly evolving digital twin environments amidst inherent uncertainty is paramount in decision-making for critical engineering systems. This paper presents a novel approach for quantifying and tracking confidence levels within a network of sensors and structural models, specifically addressing uncertainty arising from faulty sensors. By leveraging known relations and implementing a trust discount mechanism, our methodology offers a fundamental framework for navigating in the presence of uncertainties. A quasi-real-time case study on a cantilever beam model is simulated to demonstrate the efficacy of the proposed approach. We showcase the ability of our method to accurately assess and adapt to varying levels of uncertainty introduced by faulty sensors. Our findings highlight the importance of incorporating trust dynamics and established relationships within digital twin environments to achieve improved certainty despite imperfect data. This research contributes to the theoretical underpinnings of digital twin technology and offers practical insights for its application across diverse domains.
Keywords
- Confidence, Digital Twins, Trust, Uncertainty Quantification
ASJC Scopus subject areas
- Computer Science(all)
- Computer Science Applications
- Health Professions(all)
- Health Information Management
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Proceedings of the 11th European Workshop on Structural Health Monitoring . 2024.
Research output: Chapter in book/report/conference proceeding › Conference contribution › Research › peer review
}
TY - GEN
T1 - How to Be Certain
T2 - 11th European Workshop on Structural Health Monitoring, EWSHM 2024
AU - Winnewisser, Niklas R.
AU - Potthast, Thomas
AU - Mett, Felix
AU - Perin, Andrea
AU - Broggi, Matteo
AU - Beer, Michael
N1 - Publisher Copyright: © 2024 11th European Workshop on Structural Health Monitoring, EWSHM 2024. All rights reserved.
PY - 2024/7
Y1 - 2024/7
N2 - Ensuring certainty in the rapidly evolving digital twin environments amidst inherent uncertainty is paramount in decision-making for critical engineering systems. This paper presents a novel approach for quantifying and tracking confidence levels within a network of sensors and structural models, specifically addressing uncertainty arising from faulty sensors. By leveraging known relations and implementing a trust discount mechanism, our methodology offers a fundamental framework for navigating in the presence of uncertainties. A quasi-real-time case study on a cantilever beam model is simulated to demonstrate the efficacy of the proposed approach. We showcase the ability of our method to accurately assess and adapt to varying levels of uncertainty introduced by faulty sensors. Our findings highlight the importance of incorporating trust dynamics and established relationships within digital twin environments to achieve improved certainty despite imperfect data. This research contributes to the theoretical underpinnings of digital twin technology and offers practical insights for its application across diverse domains.
AB - Ensuring certainty in the rapidly evolving digital twin environments amidst inherent uncertainty is paramount in decision-making for critical engineering systems. This paper presents a novel approach for quantifying and tracking confidence levels within a network of sensors and structural models, specifically addressing uncertainty arising from faulty sensors. By leveraging known relations and implementing a trust discount mechanism, our methodology offers a fundamental framework for navigating in the presence of uncertainties. A quasi-real-time case study on a cantilever beam model is simulated to demonstrate the efficacy of the proposed approach. We showcase the ability of our method to accurately assess and adapt to varying levels of uncertainty introduced by faulty sensors. Our findings highlight the importance of incorporating trust dynamics and established relationships within digital twin environments to achieve improved certainty despite imperfect data. This research contributes to the theoretical underpinnings of digital twin technology and offers practical insights for its application across diverse domains.
KW - Confidence
KW - Digital Twins
KW - Trust
KW - Uncertainty Quantification
UR - http://www.scopus.com/inward/record.url?scp=85202623862&partnerID=8YFLogxK
U2 - 10.58286/29669
DO - 10.58286/29669
M3 - Conference contribution
AN - SCOPUS:85202623862
BT - Proceedings of the 11th European Workshop on Structural Health Monitoring
Y2 - 10 June 2024 through 13 June 2024
ER -