We are pleased to participate in the 13th International Conference of the Croatian Nuclear Society (HND) taking place in Zadar, Croatia from June 5th to 8th. Three of our colleagues will present their papers and contribute to this year’s conference with the topic “Nuclear Option for CO2 Free Energy Generation”.
TARGET – Development of Submersible ROV System for BMN Inspection - Josip Arland
INETEC has developed a new remotely controlled TARGET system for bottom mounted nozzle (BMN) inspection. Its ease of navigating and operating helps it to move quickly on a designated BMN. Once submerged, TARGET becomes independent from polar crane or refueling bridge, thus reducing unnecessary time loss for maintenance operations. Review by the Electric Power Research Institute (EPRI) has shown that INETEC demonstrated system capabilities that satisfied demands for proper flaw detection and characterization.
Development of Conforming Ultrasonic Probe for Inspection of ITER Experimental Reactor - Josipa Delaš
The paper presents the development of an ultrasonic probe for inspection of welded joints between two, 60 mm thick, sector plates of the ITER Vacuum Vessel. Limited usage of couplant, specific type of austenitic stainless steel and large weld thickness all put additional constraints on the development process. Even though the probe is intended for usage in ITER, the solution can be applied in various environments. Especially the ones that require little to no couplant and have complex surfaces.
Improvement Possibilities for Nuclear Power Plants Inspections by Adding Deep Learning-based Assistance Algorithms Into a Classic Ultrasound NDE Acquisition and Analysis Software - Hrvoje Pavlović
The work presented in this paper shows a part of the project that aims to develop a modular ultrasound diagnostic NDE system (consisting of exchangeable transducers, electronics, and acquisition/analysis software algorithms), for applications in hazardous environments within nuclear power plants. The paper will show how the software part of this system can reach near-total automation by implementing various deep learning algorithms as its features and, then, testing those algorithms on laboratory samples, showing encouraging results and promises of online monitoring applications.
We are looking forward to exchanging knowledge and experience as well as to presenting our work.