Advanced Digital Twin of a Industrial Robotic System for Measuring Pipe Wall Thickness in Nuclear Power Plants

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Guest Editors: Prof. Paul Andrew
Deadline: 30 Novermber 2025

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Guest Editors: Prof. Paul Andrew
Deadline: 30 April 2025

Advanced Digital Twin of a Industrial Robotic System for Measuring Pipe Wall Thickness in Nuclear Power Plants

by Rogério Adas Pereira Vitalli 1 and João Manoel Losada Moreira

1 Rogério Adas Pereira Vitalli, Federal University of ABC (UFABC), Interdisciplinary Laboratory of Nuclear Energy (NUC-LAB), Santo André, São Paulo, 09210-580, Brazil
2 João Manoel Losada Moreira, Federal University of ABC (UFABC), Interdisciplinary Laboratory of Nuclear Energy (NUC-LAB), Santo André, São Paulo, 09210-580, Brazil

* Author to whom correspondence should be addressed.

Journal of Engineering Research and Sciences, Volume 3, Issue 12, Page # 14-23, 2024; DOI: 10.55708/js0312002

Keywords: Digital Twin, Ultrasound Measurement, Pipe Wall Thickness, Virtual Commissioning, Process Simulate

Received: 15 September 2023, Revised: 30 October, 2024,  Accepted: 23 November, 2024, Published Online: 22 December, 2024

(This article belongs to the Special Issue Special Issue on Multidisciplinary Sciences and Advanced Technology 2024 & Section Biochemical Research Methods (BRM))

APA Style

Adas, R., Vitalli, P., Manoel, J., & Moreira, L. (2024). Advanced digital twin of an industrial robotic system for measuring pipe wall thickness in nuclear power plants. Journal of Engineering Research and Sciences, 3(12), 14–23. https://doi.org/10.55708/js0312002

Chicago/Turabian Style

Adas, Rogério, Pereira Vitalli, João Manoel, and Losada Moreira. “Advanced Digital Twin of an Industrial Robotic System for Measuring Pipe Wall Thickness in Nuclear Power Plants.” Journal of Engineering Research and Sciences 3, no. 12 (2024): 14–23. https://doi.org/10.55708/js0312002.

IEEE Style

R. Adas, P. Vitalli, J. Manoel, and L. Moreira, “Advanced digital twin of an industrial robotic system for measuring pipe wall thickness in nuclear power plants,” Journal of Engineering Research and Sciences, vol. 3, no. 12, pp. 14–23, 2024, doi: 10.55708/js0312002.

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