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Although the great challenge is to take in-place and real time measurements inside fuel rods within an NPP, the goal of the implementation plan is to develop a fully integrated wireless sensing and communication system to TRL-4. This system will be installed at HTTL, and the signal relay will be connected to INL's wireless link. The measurement data will then be transmitted to a cloud database housed in another building several blocks away. As part of the system testing, end-to-end performance, network delay, and the quality of the received data will be analyzed using INL's distributed antenna system test bed located in the Human System Simulation Laboratory. The RFID sensors will also be benchmarked against traditional wired sensors. v

To attain automation across different applications, industries are beginning to leverage advancements in wireless communication technologies. A "one-size-fits-all" solution cannot be applied since wireless technologies are selected according to application needs, quality of service requirements, and economic restrictions. To balance the trade-off between technical and economic requirements, a multi-band heterogeneous wireless network architecture is presented and discussed in this paper. Wireless local area network (WLAN) and distributed antenna system (DAS) with Long Term Evolution (LTE) are considered as the backbone for the multi-band heterogeneous network into which other wireless technologies can be integrated. The technical and economic feasibility of the network are evaluated through a techno-economic analysis (TEA). The economic feasibility of the proposed network is measured in terms of net present value while the technical feasibility is measured in terms of network throughput and latency. Finally, network performance for DAS with LTE and WLAN are verified using an NS3 simulator for machine-to-machine, real-time video, and high-definition video data transmissions. The TEA analysis showed that the number of DAS units required to achieve technical feasibility is less than WLAN units, but the overall cost of DAS units are higher compared to WLAN units, even without taking into consideration industrial, scientific, and medical band technologies.

The research and development reported here is part of the Technology Enabled Risk-Informed Maintenance Strategy project sponsored by the U.S. Department of Energy's Light Water Reactor Sustainability program. The primary objective of the research presented in this report is to produce a technical basis for developing explainable and trustable artificial intelligence (AI) and machine learning (ML) technologies. The technical basis will lay the foundation for addressing the technical and regulatory adoption challenges of AI/ML technologies across plant assets and the nuclear industry at scale and to achieve seamless cost-effective automation without compromising plant safety and reliability.The technical basis ensuring wider adoption of AI/ML technologies presented in this report was developed by Idaho National Laboratory (INL), in collaboration with Public Service Enterprise Group (PSEG) Nuclear, LLC. To develop the initial technical basis, the circulating water system (CWS) at the PSEG-owned plant sites was selected as the identified plant asset. Specifically, the issue of waterbox fouling diagnosis in the CWS using different types of CWS data is presented to address the said challenge. The approach presented in this report is based on the closed-loop forward-backward process that tries to capture the advancements in data science addressing the explainability of AI/ML outcomes, user-centric interpretability of those outcomes, and how user interpretation can be used as feedback to further simplify the process. A prototype interface is developed to present a focused component-level display of the ML model outputs in a usable and digestible form.