Salvato in:
| Autore principale: | |
|---|---|
| Natura: | Preprint |
| Pubblicazione: |
2025
|
| Soggetti: | |
| Accesso online: | https://arxiv.org/abs/2507.04555 |
| Tags: |
Aggiungi Tag
Nessun Tag, puoi essere il primo ad aggiungerne!!
|
Sommario:
- Digital twins have emerged as a powerful technology for modeling and simulating complex systems across various domains (Fuller et al., 2020; Tao et al., 2019). As virtual representations of physical assets, processes, or systems, digital twins enable real-time monitoring, predictive analysis, and optimization. However, as digital twins become more sophisticated and integral to decision-making processes, ensuring their accuracy, reliability, and ethical implementation is essential. This paper presents a comprehensive framework for the Testing, Evaluation, Verification and Validation (TEVV) of digital twins to address the unique challenges posed by these dynamic and complex virtual models.