C56-40n-272712 The limiting factor in previous imaging approaches to material, control, and accounting of pebbles going through pebble bed reactors was the ability to reliably identify hundreds of thousands of unique pebbles in a short time. Moreover, the secondary approach of identifying types of pebbles does support fresh fuel loading by distinguishing fuel pebbles from moderator pebbles, but still fails to identify individual pebbles as such. The company provides a unique solution for pebble bed reactors material, control, and accounting via its patented, optical-AI-based software system, which can uniquely characterize and identify pebbles from their initial insertion in the reactor vessel to their discharge, to ensure that those exiting are the same as those entering. This could potentially enable Continuity of Knowledge on a statistically significant percentage of individual pebbles traversing through the reactors. PHASE I - Objective 1: Test the companys solutions ability to remain valid from pebble insertion to extraction to reinsertion and so forth. Objective 2: Test different cameras to determine those optimal for pebble image capture. Objective 3: Identify appropriate settings and thresholds for the system to achieve the target of 99.85% accuracy. Objective 4: Consult with current utilities to ensure that design choices for implementation could be optimized in ways that would best fit current structures. Final Deliverable: Achieve successful authentication and identification levels at both entry and exit points in the nuclear reactor vessel. From a technical perspective, the use of computer vision software would significantly improve the accuracy and efficiency of pebble identification and tracking in their reactors. This information would be valuable for research and development in the field of nuclear energy, enabling further improvements in the technology. From an economic perspective, the use of computer vision software would increase the efficiency of pebble bed reactors operations, reducing the need for manual inspection and increasing the overall capacity of the reactors. From a social perspective, the use of computer vision software in pebble bed reactors would contribute to a safer and more reliable energy supply, reducing the risk of accidents and increasing the overall public confidence in nuclear power, which is a critical factor in its continued development.
